WO2012099970A1 - Brand index evaluation apparatuses, methods and systems - Google Patents

Brand index evaluation apparatuses, methods and systems Download PDF

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Publication number
WO2012099970A1
WO2012099970A1 PCT/US2012/021735 US2012021735W WO2012099970A1 WO 2012099970 A1 WO2012099970 A1 WO 2012099970A1 US 2012021735 W US2012021735 W US 2012021735W WO 2012099970 A1 WO2012099970 A1 WO 2012099970A1
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Prior art keywords
data
brand
index
comprises
competitor
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PCT/US2012/021735
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French (fr)
Inventor
John BEJNAROWICZ
Jason Harper
Stephen F. Kerho
Jonathan PRANTNER
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Organic, Inc.
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Priority to US201161433901P priority Critical
Priority to US61/433,901 priority
Application filed by Organic, Inc. filed Critical Organic, Inc.
Publication of WO2012099970A1 publication Critical patent/WO2012099970A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management

Abstract

The BRAND INDEX EVALUATION APPARATUSES, METHODS AND SYSTEMS (hereinafter "B-INDEX") transforms social media mentions, web visits, Google Insights search analytics inputs data via B-INDEX components into brand index value and comparative graphic plots/charts outputs. In one embodiment, a method is disclosed, including: receiving a brand index evaluation request from a user interface; obtaining consumer activity data batch related to a brand product; transforming the obtained consumer activity data batch associated the brand product into a single brand index data indicator based on a statistical procedure; calculating a brand index score of the brand product based on the single brand index data indicator; comparing a plurality of the calculated brand index scores of the brand product over a period of time; and providing a data presentation output including the brand index score comparison via a user interface.

Description

I BRAND INDEX EVALUATION APPARATUSES, METHODS AND

SYSTEMS

3 [ooo i] This patent application disclosure document (hereinafter "description"

4 and/or "descriptions") describes inventive aspects directed at various novel innovations

5 (hereinafter "innovation," "innovations," and/or "innovation(s)") and contains material

6 that is subject to copyright, mask work, and/or other intellectual property protection.

7 The respective owners of such intellectual property have no objection to the facsimile

8 reproduction of the patent disclosure document by anyone as it appears in published

9 Patent Office file/records, but otherwise reserve all rights.

RELATED APPLICATION

I I [0002] Applicant hereby claims priority under Paris Convention and Patent

12 Cooperation Treaty to United States provisional application serial no. 61/433,901

13 (attorney docket no. 19392-007PV), filed January 18, 2011, entitled "Apparatuses,

14 Methods and Systems for a Brand Index Evaluator," which is herein expressly

15 incorporated by reference.

FIELD

17 [0003] The present innovations are directed generally to marketing planning is platforms, and more particularly, to BRAND INDEX EVALUATION APPARATUSES, 19 METHODS AND SYSTEMS. BACKGROUND

[0004 ] Business owners, service providers, and consumer products manufacturers may associate a brand with the offered service, products, and/or business. The brand may be a combination of graphics and texts, a logo, and a slogan, which facilitate consumers to identify the service, products, and/or the business.

BRIEF DESCRIPTION OF THE DRAWINGS

[0005 ] The accompanying appendices and/or drawings illustrate various non- limiting, example, innovative aspects in accordance with the present descriptions: [0006 ] FIGURES 1A-1B provide block diagrams illustrating examples of clients desires to know consumer impressions of their brands/products within embodiments of the B-INDEX; [0007] FIGURE lC shows a block diagram illustrating data flows between a B- INDEX server and affiliated entities within embodiments of the B-INDEX; [0008 ] FIGURE lD provides a block diagram illustrating example system structure of B-INDEX within embodiments of the B-INDEX; [0009 ] FIGURE 2A-2D provide logic flow diagrams illustrating index score calculation within embodiments of the B-INDEX; [0010 ] FIGURES 3A-3E provide exemplary user interfaces illustrating index score calculation within embodiments of the B-INDEX; [0011 ] FIGURES 4A-5H show exemplar screen shots illustrating B-INDEX data presentation outputs within embodiments of the B-INDEX; and [0012] FIGURE 6 shows a block diagram illustrating embodiments of a B-INDEX controller; [0013] The leading number of each reference number within the drawings indicates the figure in which that reference number is introduced and/or detailed. As such, a detailed discussion of reference number 101 would be found and/or introduced in Figure 1. Reference number 201 is introduced in Figure 2, etc.

DETAILED DESCRIPTION

[0014 ] The BRAND INDEX EVALUATION APPARATUSES, METHODS AND SYSTEMS (hereinafter "B-INDEX") provides a brand index evaluating platform, which generate a brand value index associated with a commercial product based on sale data and web visits statistics. In one embodiment, the B-INDEX may obtain web visits statistics of a brand name product over a period of time, and measure the brand value by calculating a consideration score of the brand name. In one implementation, the B- INDEX may compare the consideration score of that of a competitor to analyze the consumer's preference over the brand names. [0015 ] For example, for a client "Ella Electronics" who may want to know user consideration and market performance of their products, such performance may be reflected by social media reaches (e.g., number of followers, comments on "Ella Electronics" Facebook page, Tweets, etc.), social media sentiments, search volume (e.g., number of searches of "Ella Electronics" via Google), site traffic of websites. The B- INDEX may combine the various data into a single trackable index score (e.g., a numeric value between 0-100). In one implementation, the client may track market performance of their competitors and themselves by tracking and comparing their index scores over a period of time. [0016] In further implementations, the B-INDEX may provide a client measures from a range of "virtual" touch-points which may give a better measure of overall brand share-of-mind than any single measure. For example, the B-INDEX may compare time dependent plots of the generated index scores, and various metrics, e.g., direct 1 consumer brand interaction (website visits, page views), indirect consumer brand

2 interaction (natural Google searches), active consumer participation in brand reputation

3 (social media mentions)), etc., so that the B-INDEX may facilitate to discover a more

4 determinative data factor that drives the overall consumer brand impression.

5 B-INDEX

6 [0017] FIGURES 1A-1B provide block diagrams illustrating examples of B-INDEX

7 client services within embodiments of the B-INDEX. Within implementations, a B-

8 INDEX client 104 may comprise a variety of brand products vendors, retailers, service

9 providers, and/or the like. For example, as shown in FIGURE lA, the client 104, "Ella

10 Electronics," may have invested in a market campaign 165 of their products, by putting

11 advertisement in a variety of media channels, such as, but not limited to social media

12 180a (e.g., a Facebook page of "Ella Electronics" which may populate news feeds of

13 products news, new product promotions, coupon distributions, etc.), websites 180b (e.g.,

14 advertisement on the client's homepage, banner advertisements on a news page, etc.),

15 Google advertisement 180c, TV advertisements i8od, mobile advertisements i8oe (e.g.,

16 mobile pop-ups, etc.), and/or the like. The client "Ella Electronics" may want to know

17 the effects of their advertisement campaign 103a.

18 [0018 ] Continuing on with FIGURE lB, the client "Ella Electronics" 104 may want

19 to know consumer impressions about their product and brand 103a, as one exemplary

20 indicator of their advertisement campaign effects. The client 104 may submit an

21 evaluation request to a B-INDEX platform 120 via a user interface, e.g., a web based

22 application, a mobile application, etc., which may in turn return an evaluation result to

23 the client. For example, as shown in FIGURE lB, the B-INDEX platform may return a 1 numeric index score as "76.5/100" 103c to the client 104, which may be accompanied by

2 a list of index scores of the client's competitors so that the client may interpret their

3 campaign effects and market shares via index score comparisons.

4 [0019] In one implementations, the B-INDEX platform 120 may consider a

5 variety of indicators of a brand value, such as social media mentions 185 (e.g., whether

6 the consumers are talking about "Ella Electronics" on Facebook, Twitter, etc.), home

7 pages visits 182 (e.g., whether and how many consumers are visiting the homepage of

8 "Ella Electronics" and/or clicking on an advertisement placed on a news page, etc.),

9 search engine index 183 (e.g., whether and/or how many consumers are searching for

10 "Ella Electronics" brand name or related products, etc.), and/or the like. Such data may

11 be obtained by the B-INDEX platform and analyzed via a statistical engine to generate a

12 B-INDEX score as "76.5/100" for the client "Ella Electronics" 104.

13 [0020 ] FIGURE lC shows a block diagram illustrating data flows between a B-

14 INDEX server and affiliated entities within embodiments of the B-INDEX. Within

15 various embodiments, one or more consumers user(s) 102 and client(s) 104, B-INDEX

16 server 120, B-INDEX database(s) 119, social media 140, other third party data source

17 145 are shown to interact via various communication network 113.

18 [0021 ] In one embodiment, the user 102, who may be a B-INDEX service provider,

19 or the client 104, who may be a brand name business entity, may submit a request for B-

20 INDEX evaluation 106, which may include a list of the client's competitor names. For

21 example, in one implementation, the client 104 may enter a B-INDEX evaluation

22 request via a user interface of a B-INDEX client component instantiated on a client

23 device (e.g., a desktop computer, a laptop computer, a mobile device, etc.), e.g., a web based application (see FIGURES 3A-3B), etc. The client device may generate a Hypertext Transfer Protocol Secure (HTTPS) POST message including information of the client's B-INDEX evaluation request 106 in the form of data formatted according to the extensible Markup Language (XML). Below is an example HTTP(S) POST message including an XML-formatted B-INDEX evaluation request message 106 for the B- INDEX server: POST /EvaluationRequst .php HTTP/1.1

Host: 216.15.16.00

Content-Type: Application/XML

Content-Length: 718

<?XML version = "1.0" encoding = "UTF-8"?>

<EvaluationRequest>

<Time> 15:30:30 </Time>

<Date> 09-09-20XX </Date>

<User>

<UserID> ellae </UserID>

<Password> 123456789 </Password>

<PasswordQ>

<Q1> "What is your mother's maiden name? </Ql>

<A1> Johnson </Al>

</PasswordQ>

<UserName> Ella Electornics </UserName>

<UserType> Corporations </UserType>

<UserCategory> Retail </UserCategory>

<BusinessKeyTerms> Electronics, Retail </BusinessKeyTerms>

<URL> www . el La-electronics■ com </URL>

<Address>

<linel> 800 Dream Street, Garden Plaza </linel>

<City> Big City </City>

<State> CA </State>

<Zipcode> 90000 </Zipcode>

</Address>

</User>

<EvaluationType> Competitor-based </EvaluationType>

<EvaluationTarget> brand name </EvaluationTarget>

<Competitors>

<Competitorl> JS Electronics </Competitorl>

<CompetitorTarget> Brand Name </CompetitorlTarget>

<Competitor2> Supermart Electronics </Competitor2>

<Competitor2Target> Brand Name </Competitor2Target>

</Competitors>

<TimeFrame>

<from> Mar-01-20XX </from>

<to> Mar-31-20XX </to>

</TimeFrame>

</EvaluationRequest> [0022 ] In the above example, the client "Ella Electronics" may submit user profile information, such as a type of the business (e.g., "electronics," "retail", etc.) so that the B-INDEX may determine a related industry of the client and recommend a list of competitors for the client. The client may also indicate a desired evaluation index type is "competitor-based," and may submit a list of interested competitor names. For example, the client may elect to obtain a competitor-based index evaluation, which may return comparative brand scores of the client and the competitors so that the client may compare market performance of the competitors against themselves, as further illustrated in FIGURES 2B. In an alternative implementation, the client may elect to request a competitor-independent index score, e.g., the returned index score is not related, or comparative to that of a competitor's, etc., wherein the client may obtain such index scores over a time frame to track consumer impression and market performance changes over a period of time. In one implementation, the client may elect to submit an evaluation target for itself and for each competitor. In this example, the client elect the evaluation target as the brand name, e.g., "Ella Electronics." For another example, the client may select a product name, a service name, etc. for evaluation, e.g., "Ella Electronics Home Office Promotion," etc. The client may also select a specific product name, service names for a selected competitor for competitor-based index score evaluation. [0023 ] In further implementations, the B-INDEX evaluation request may include historical sales data 106a of the client's featured brand name product, and/or the campaign strategy 106b to the B-INDEX server 120 for campaign strategy recommendation plan. 1 [0024 ] Within implementations, upon receiving the evaluation request 106, the B-

2 INDEX server 120 may obtain various consumer impression data from a variety of data

3 sources, such as, but not limited to social media mentions 108 from social media 140,

4 web visits data 105a, competitor visits data 105b, search engine analytics 105c from

5 various third party data sources 145. In further implementations, the third party data

6 sources may comprise various website hosts such as, but not limited to Google Insights,

7 Wikipedia, Yahoo.com, ask.com, fast.com, and/or the like.

8 [0025 ] In one implementation, the B-INDEX server may monitor consumer

9 discussions of "Ella Electronics" related topics and its competitors on the social media

10 140, such as but not limited to Facebook, Linkedln, eBlogger, Twitter, Meltwater,

11 Sysomos, BlogPulse, and/or the like. In another implementation, the B-INDEX server

12 120 may obtain website traffic from the brand name product's website, Google searches

13 on brand terms, mentions of brands in blogs and news media, positive sentiment of

14 those blog posts, and/or the like. For another example, the B-INDEX server 120 may

15 obtain campaign visits data from other third party data source 145, such as an online

16 database, statistics of the products homepage, and/or the like. Example third party data

17 sources 145 may include, but not limited to Google Insights, web visits monitoring data

18 service analytics from Alexa, Comscore, Quantcast, Hitwise, and/or the like.

19 [0026 ] In one implementation, the third party data sources 145 may provide a

20 data file in the format of XML, CSV, etc., to the B-INDEX server 120. For example,

21 exemplary data files from Google Insights may take a form similar to the following Table

22 1 and Table 2. Table 1 shows Google Insight analytics rules (e.g., selected in US,

23 "electronics retailer" under "electronics filter") and analyzed data sources, including exemplary Google search terms related to the client and its competitors, web visits via Google search links, Sysomos page visits, key words mentions, and/or the like; and Table 2 shows daily Google search times of the client name and a list competitors.

Table 1 Exemplary Google Insights Table

Figure imgf000011_0001

Table 2 Exemplary Daily Google Search Times

Figure imgf000011_0002
[0027] For another example, a data file of web visits summary may take a form similar to Table 3. Table 3 shows daily web visit times (e.g., a user click, etc.) and page views (e.g., the duration of staying on the page is greater than 30 seconds, etc.). In further implementations, as shown in Table 3, the web visits summary may separate unique visitors of the page (e.g., by tracking a visitor's IP address, etc.), and show daily growth of the visits.

Table 3 Exemplary Web Visits Summary

Figure imgf000012_0001
[0028] For another example, a data file of blog mention summary may take a form similar to Table 4, which shows daily blog mentions (e.g., a consumer mentions the name of the client or the competitor's in his blog, etc.) of the client "Ella Electronics" and a list of its competitors.

Table 4 Exemplary Blog Mentions Brand 4/2 4/3 4/4 4/5 4/6 4/7 4/8 4/9 4/10

Ella Elec 38 34 21 17 40 37 38 51 37

JS Elec 37 32 24 25 37 35 39 36 21

Supermart 187 155 140 121 192 166 144 172 163

Fancy E 43 30 33 29 30 42 38 49 28

Wall E 57 78 45 52 72 116 99 73 68

Best Buy 50 32 23 24 39 28 36 50 42

Amazon 21 15 8 9 26 17 20 15 18 [0029] For another example, a data file of news mention summary may take a form similar to Table 5, which shows daily news/press mentions (e.g., a news article that mentions the name of the client or the competitor's in his blog, etc.) of the client "Ella Electronics" and a list of its competitors.

Table 5 Exemplary News Mentions

Figure imgf000013_0001
[0030] For another example, a data file of Twitter mentions summary may take a form similar to Table 6, which shows daily Twitter mentions (e.g., a consumer mentions the name of the client or the competitor's in his Tweet, etc.) of the client "Ella Electronics" and a list of its competitors. Such social media mentions may be obtained from various social media platforms such as Facebook, Linkedln, eBlogger, Meltwater, Sysomos, BlogPulse, and/or the like. Table 6 Exemplary Twitter Mentions Brand 4/26 4/27 4/28 4/29 4/30 5/1 5/2 5/3 5/4

Ella Elec 350 221 449 504 365 259 172 371 390

JS Elec 229 348 320 271 222 271 184 299 252

Supermart 1054 1041 1099 1077 1239 985 884 1422 1154

Fancy E 272 214 208 242 254 196 155 235 218

Wall E 894 613 973 606 682 528 850 1120 1167

Best Buy 319 284 351 390 295 123 155 294 172

Amazon 60 90 92 87 106 75 116 138 94 [0031 ] For another example, a data file of sentiment data summary may take a form similar to Table 7, which may analyze and summary sentiment mentions of the client "Ella Electronics" and a list of its competitors in the data summaries Table 2-6. For example, a news article that introduces new discounts and promotions of "Ella Electronics" may constitute a positive mention for "Ella Electronics," while a consumer complains about poor quality of "Ella Electronics" products (e.g., see 185 in FIGURE lB, etc.) may constitute a negative mention. As shown in Table 7, positive and/or negative mentions may be summarized and listed separately for each brand (the client and its competitors). Table 7 Exemplary Sentiment Data

Figure imgf000014_0001
[0032 ] Within implementation, the B-INDEX server 120 may perform statistical analysis 109 based on the received data files (e.g., see Tables 1-7) to generate a brand index score 135a indicating a consumer impression level of the brand name "Ella Electronics" of the client, and return the index score 135a to the client, wherein higher scores may indicate more consumer awareness for the brand. In one implementation, the index score 135a may comprise a numeric value, a list of values over time, a graphic presentation including any charts, tables, plots, etc., as further illustrated in FIUGRE 3E. In one implementation, the B-INDEX server may send the evaluation results (e.g., the index score 135b) to the database 119 for storage. [0033 ] For example, in one implementation, the B-INDEX may generate a Hypertext Transfer Protocol Secure (HTTPS) POST message including the generated index score 135 in the form of data formatted according to the extensible Markup Language (XML). Below is an example HTTP(S) POST message including an XML- formatted index score message 135 to the client 104: POST /IndexScoreResult .php HTTP/1.1

Host: www.brand-index.com

Content-Type: Application/XML

Content-Length: 718

<?XML version = "1.0" encoding = "UTF-8"?>

<IndexScoreResult>

<Time> 15:33.56 </Time>

<Date> 09-09-20XX </Date>

<User>

<UserID> ellae </UserID>

<Password> 123456789 </Password>

<PasswordQ>

<Q1> "What is your mother's maiden name? </Ql>

<A1> Johnson </Al>

</PasswordQ>

<UserName> Ella Electornics </UserName>

<UserType> Corporations </UserType>

<UserCategory> Retail </UserCategory>

<BusinessKeyTerms> Electronics, Retail </BusinessKeyTerms>

<URL> www . ella-electronics . com </URL>

</User>

<IndexType> Competitor-based </IndexType>

<DataSource>

<Sourcel> Google Insights </Sourcel>

<Source2> Hitwise </Source2> </DataSource>

<IndexValue>

<Min> 0 </Min>

<Max> 100 </Max>

<Date> March-1 </Date>

<Valuel> 76.8 <Valuel>

<Userl> Ella Electronics </Userl>

<Value2> 82.2 </Value2>

<User2> JS Electronics </User2>

</IndexValue>

</IndexScoreResult>

[0034] In one implementation, the B-INDEX server may generate heuristics and marketing strategy recommendations 155 based on the brand index 135 for the client, and the client may then implement the revised marketing strategy 150 based on recommendations. For example, the B-INDEX server may invest more in social media campaign when the index score shows a larger growth when there is a social media campaign carried on. In further implementations, the B-INDEX index scores 135 may serve as an objective for marketing optimization, which may determine and optimize campaign spends distribution over a variety of media channels. Further embodiments of marketing optimization are discussed in Patent Cooperation Treaty Application serial no. PCT/US2010/42167 and U.S. Application serial no. 13/383,867, both entitled "Apparatuses, Methods and Systems for a Media Marketing Panning and Optimization Tool," both of which are herein expressly incorporated by reference. [0035] FIGURE lD provides a block diagram illustrating example system structure of B-INDEX within embodiments of the B-INDEX. Within implementations, the B-INDEX system 151 may contain a number of functional components and/or data stores. A B-INDEX controller 160 may serve a central role in some embodiments of B- INDEX operation, serving to orchestrate the reception, generation, modification, and distribution of data and/or instructions, to, from, and between B-INDEX components 1 and/or mediate communications with external entities and systems. Further example

2 details with regard to the B-INDEX controller 160 is provided in Figure 6.

3 [0036] In one embodiment, the B-INDEX controller 160 may be housed

4 separately from other components and/or databases within the B-INDEX system, while

5 in another embodiment, some or all of the other components and/or databases may be

6 housed within and/or configured as part of the B-INDEX controller. Further detail

7 regarding implementations of B-INDEX controller operations, components, and

8 databases are provided below.

9 [0037] In the implementation illustrated in Fig. lD, the B-INDEX controller 160

10 may be configured to couple to external entities via a maintenance interface 154, a

11 power interface 156, a user interface 158 and a network interface 155. The user interface

12 158 may, for example, receive and configure inputs/ outputs between a user and the B-

13 INDEX, e.g., secured user account information, user submitted configuration data, user

14 provided client data, a client index evaluation request, client identified competitor

15 information, B-INDEX generated evaluation scores, B-INDEX generated

16 plots/tables/graphs, and/or the like. In various implementations, the network interface

17 155 may, be configured for receipt and/or transmission of data to an external and/or

18 network database, e.g. a third party data source providing web visits summary, social

19 media mentions, etc. In one embodiment, the maintenance interface 154 may, for

20 example, configure regular inspection and repairs, receive system upgrade data, report

21 system behaviors, and/or the like. In one embodiment, the power interface 156 may, for

22 example, connect the B-INDEX system to an external power source.

23 [0038 ] In one implementation, the B-INDEX controller 160 may further be 1 coupled to a plurality of components configured to implement B-INDEX functionality

2 and/or services. The plurality of components may, in one embodiment, be configurable

3 to instantiate an online or offline application for B-INDEX index evaluation. In one

4 embodiment, the B-INDEX may comprise components such as, but not limited to a data

5 loading component 170, a data reduction component 171, a competitor-based index

6 generation component 172, a competitor- independent index generation 173, a data

7 presentation component 174, and/or the like.

8 [0039 ] In one embodiment, the data loading component 170 may obtain various

9 data indicative of consumer impression of a client's brand name and/or products from

10 third party data sources via the network interface 155. For example, the data loading

11 component 170 may load data such as web visits, social media mentions, page views,

12 blog mentions, press mentions, search engine index, and/or the like from a variety of

13 data analytics sources (e.g., Alexa, Comscore, Quantcast, Hitwise, Google Insights, etc.).

14 Such data may be loaded in CSV data files, e.g., see Tables 1-7, etc.

15 [0040 ] In one implementation, the data reduction component 171 may determine

16 whether every data factor obtained by the data loading component 170 may be directly

17 combined into index calculation. For example, in one implementation, the data

18 reduction component 171 may scrub the received raw data via multicolinearity testing to

19 eliminate unviable data indicators, and combine the remaining viable indicator into one

20 factor based on their correlations, as further illustrated in Figure 2C.

21 [0041 ] In one embodiment, the competitor-based index generation component

22 172 and the competitor-independent index generation component 173 may generate two

23 types of index scores based on the processed data factors from data reduction component 171. In one implementation, the competitor-based index score generation component 172 may return comparative brand scores of the client and the competitors so that the client may compare market performance of the competitors against themselves, as further illustrated in FIGURES 2B. In an alternative implementation, the competitor-independent index score generation component may generate an index score that is not related, or comparative to that of a competitor's, etc., wherein the client may obtain such index scores over a time frame to track consumer impression and market performance changes over a period of time, as further illustrated in FIGURE 2D. [0042] Within implementations, the competitor-based index generation component 172 and the competitor-independent index generation component 173 may operate in a similar procedure except that the component 172 may load competitor data while the 173 component may not load competitor data. For example, the index generation components 172/173 may take the obtained multivariate factors and determine whether an unobservable, hypothetical variable (e.g., the index score, etc.) that contributes to the variance of at least two of the observed variables may be obtained via combining two or more variables so that the number of data factors for analysis may be reduced. As further illustrated in FIGURE 2B, factor analysis may be adopted to determine the linear combination that accounts for the maximum variance of the variables, then removes this variance and finds the next linear combination that explains the remaining variance, to obtain a group of orthogonal (uncorrelated) factors. The index generation components 172/173 may eventually obtain one final factor as the index score. [0043] In one embodiment, the data presentation component 174 may output the obtained client/competitor data by data loading component 170, index scores generated by the competitor-based index generation component 172 and the competitor- independent index generation component 173, and/or the like, to a client via a user interface, in a variety of formats. For example, the data presentation component 174 may generate reports with charts/graphs such as, but not limited to tables, pie charts, bar charts, statistical graphs, and/or the like comparing the client's index scores versus the competitors' index scores, plots showing the client's index score changes over a period of time, and/or the like. Further examples of data presentations generated by the data presentation component 174 are illustrated in FIGURES 4A-5H. [0044 ] In one implementation, the B-INDEX controller 160 may further be coupled to one or more databases configured to store and/or maintain B-INDEX data. A user database 119a may contain information pertaining to account information, contact information, profile information, identities of hardware devices, Customer Premise Equipments (CPEs), and/or the like associated with users, reminder preferences, reminder configurations, system settings, and/or the like. A hardware database 119b may contain information pertaining to hardware devices with which the B-INDEX system may communicate, such as but not limited to Email servers, user telephony devices, CPEs, gateways, routers, user terminals, and/or the like. The hardware database 119b may specify transmission protocols, data formats, and/or the like suitable for communicating with hardware devices employed by any of a variety of B-INDEX affiliated entities. A web visits database 119c may contain data pertaining to loaded web visits data, such as, but not limited to client/competitor name, data source(s), web URL, web type, web visits, time frame, and/or the like. A Google search database ii9d may contain data pertaining to Google Insights information, such as, but not limited to 1 client/competitor name, Google Insights report date, search indices, search times, click

2 times on the search results, and/or the like. A social media database ii9e may contain

3 data pertaining to social media mentions, such as, but not limited to client/ competitor

4 name, data source(s), social media platform name, social media URL, key terms, social

5 media mention times, observed time frame, and/or the like. A competitor database ii9f

6 may contain data pertaining to competitor profile, such as, but not limited to competitor

7 name, competitor business category, competitor key terms, homepage URL, competitor

8 historical index scores, and/or the like. An index database ii9g may contain data

9 pertaining to generated index scores, such as, but not limited to client/competitor name,

10 time and date, index score type, index score value, heuristics notes, and/or the like. The

11 B-INDEX database may be implemented using various standard data-structures, such

12 as an array, hash, (linked) list, struct, structured text file (e.g., XML), table, and/or the

13 like. Further examples of data table fields of databases H9a-ii9g are discussed in

14 FIGURE 6.

15 [0045 ] FIGURE 2A shows a logic flow diagram illustrating aspects of the B-

16 INDEX. In one embodiment, the B-INDEX may periodically (e.g., monthly) monitor

17 web visits data of an Internet campaign advertisement of a brand name product 201.

18 For example, the B-INDEX may obtain shares of website visits 202, shares of web page

19 visits 203, Google search index 204, shares of news media mentions 205, shares of blog

20 mentions 206, share of positive blog mentions 207, and/or the like.

21 [0046 ] In one implementation, the B-INDEX may determine a weighing factor

22 220 for each variable obtained at 210. For example, the B-INDEX may incorporate all of

23 the inputs wherein each share may contribute the same amount. In an alternative 1 implementation, the relative value of B-INDEX inputs may be determined by the model

2 based upon apriori variability. For example, Google searches and the brand

3 product website visits may contribute more than the percentage of positive blog posts.

4 [0047] In one embodiment, the B-INDEX may combine the different visits data

5 via multivariate factor analysis 225 to generate the brand index 230. For example, the

6 B-INDEX may generate a correlation matrix for the web visits data, and then determine

7 at least one principal component based on the correlation matrix. For example, in one

8 implementation, the principal component may be determined by calculating the

9 eigenvalues of the correlation matrix and the principal component indicator may be

10 determined as the one that corresponds to the greatest eigenvalue. For example, in one

11 implementation, the principal factor analysis may be implemented by SAS code similar

12 to the following form:

13 PROC FACTOR data = "C:\macro econ" corr scree residuals method = principal;

14 VAR indicatorl indicator2 indicator3 indicator4 indicator5 indicator6;

15 RUN;

16

17 [0048] In one implementation, the brand index may have a numeric value, e.g.,

18 ranging from 70 to 140. In another implementation, the brand index may be a relative

19 measure and have no absolute scale, and the B-INDEX may compare the measure with

20 the brand indices of other brand name products to evaluate consumer consideration.

21 [0049] In one implementation, the client may adjust the marketing investment

22 233 of a product based on the generated brand index, and implement the marketing

23 plan 235, e.g., via the social media platform. In one implementation, the client may

24 adopt B-INDEX to adjust the marketing plan, e.g., an advertisement post on a social

25 media platform, in a real-time manner, based on instant consumer responses via visits

26 data and blog mentions. [0050 ] FIGURE 2B provides a logic flow diagram illustrating the B-INDEX index score calculation within alternative embodiments of the B-INDEX. Within implementations, a client 104 may submit an index evaluation request 236, e.g., by logging into a web based B-INDEX application and launching a B-INDEX calculation project (e.g. see FIGURES 3A-3B, etc.). In one implementation, the B-INDEX may determine an index type 239, e.g., a competitor-based index score or a competitor- independent index score. For example, the client may elect to obtain competitor-based index evaluation (e.g., namely the "brand index" 312 in FIGURE 3B), and/or a competitor-independent index evaluation (e.g., namely the "connection index" 313 in FIGURE 3B). Figure 2D further illustrates processing flows when the client chooses a competitor-independent score. [0051 ] In one implementation, if a competitor-based index score is chosen, the client may identify and submit a list of competitor names 238 to the B-INDEX for a competitor-based index score calculation (e.g., see FIGURE 3B). Alternatively, if the client does not identify any competitors, the B-INDEX may retrieve a client profile and identify an industry, interested key terms of the client from its profile, and thus determine a set of competitors for the client 240. For example, for the client "Ella Electronics," the B-INDEX may identify it as "retail," "electronics," and may determine a set of electronics retailers such as "JS Electronics," "Supermart Electronics," "BestBuy," and/or the like as its competitors. For another example, for a client "Marriot," the B- INDEX may identify it as "hotel brand" and may determine a set of chain hotel brands such as "Ritz-Carlton," "Hilton," "Hyatt," "Best Western," and/or the like, as its competitors. [0052] In one implementation, the B-INDEX platform may collect data for the client and all the identified competitors 243. For example, B-INDEX may obtain data from third party data analytics sources 145, as illustrated in FIGURE iC, which may provide web traffic logs 243a, social media content 243b, Google Insights analytics 243c, and other third party data 243d, e.g., also see FIGURE 3C. For example, the third party data source may further provide new transactions, new sign-ups, and/or the like. For another example, if the client is related to real estate business, the third party data source may provide builder new orders, e.g., via SEC filings, etc. Within implementations, the data collection may be performed periodically (e.g., weekly, monthly, etc.), intermittently, and/or constantly, and updated data records may be stored at databases (e.g., ii9c-e in FIGURE lD). Within alternative implementations, the data collection may be performed upon demand, e.g., when an index score evaluation request is received, etc. [0053] Within implementations, the social media data 243b may be collected from the various sources, including: Sysomos, Google Insights, Radian6, Compete, and/or the like. Each of the data sources may export data in a standard csv format, e.g., as shown in Tables 1-7., wherein each such data file may be loaded into SAS and converted into a SAS data. For example, daily and weekly data is summed/converted into monthly data, and share of each brand for each month may be computed by monthly total of tweets, blog mentions, news mentions, web site views, web site visits, unique web site views, and/or the like. [0054] Within implementations, for each data sections 243a-243d, the B-INDEX may create monthly shares 247 among the client and its competitors for the obtained data. Each individual brand total may be divided by the computed monthly total to give each brands a monthly percentage, or share of the respective measurement, whererin all shares for each month, across brands, shall be summed up to 100%. For example, as shown in FIGURE 3D, the monthly share of visits of "Ella Electronics" as "7%" is calculated by dividing the site visits of "Ella Electronics" of "106,893" over the sum of all site visits of all the listed competitors in the data categorization overview 325 in FIGURE 3C. In further implementations, the B-INDEX may determine whether data reduction is necessary for each data section 245, e.g., when there are multiple data factors for one of the data types 243a-d, as further illustrated in FIGURE 2C.

[ 055] For example, in one implementation, an exemplary SAS procedure to load data sets and calculate monthly share may take a form similar to the following: ***Summary : Read CSV file into SAS datasets and calculate shares ***;

/ * * * *

Data in the "Input data. csv" file is collected from 3 sources: Sysomos, Compete, Google Insights for Search

* * * * /

Proc Import datafile= ' WFilsrvl- det . windows . organic . com\strategy\Modeling\input mentions . csv ' dbms=csv

out=mentions replace;

getnames=yes ;

format brand $9.;

run;

Proc Import datafile= ' WFilsrvl- det . windows . organic . com\strategy\Modeling\input compete. csv' dbms=csv

out=compete replace;

getnames=yes ;

format month date 9.;

format brand $9.;

run;

Proc Import datafile= ' WFilsrvl- det . windows . organic . com\strategy\Modeling\input google. csv' dbms=csv

out=google replace;

getnames=yes ;

format week date9.;

format brand $9.;

run;

Proc Import datafile= ' WFilsrvl- det . windows . organic . com\strategy\Modeling\input sentiment . csv ' dbms=csv

out=sentiment replace;

getnames=yes ;

format month date 9. ;

format brand $9.;

run; data mentions month; set mentions;

month=intnx ( 'month ', date, 0) ;

format month date 9. ;

format brand $9.;

run;

data google month; set google;

month=intnx ( 'month ', week, 0) ;

format month date 9.;

run;

proc sql;

create table mentionsl as

select brand, corporate, month, sum(blog) as blog, sum (news) as news, sum(twitter) as twitter

from mentions month

group by brand, month;

create table googlel as

select brand, corporate, month, mean (google) as google

from google month

group by brand, month;

quit;

proc sort data=compete nodupkey; by brand month;

proc sort data=mentionsl nodupkey; by brand month;

proc sort data=sentiment nodupkey; by brand month;

proc sort data=googlel nodupkey; by brand month;

run;

data inputs; merge compete googlel mentionsl sentiment; by brand month;

if google=. then google=0;

total social=blog+twitter+news ;

net_pos= (pos-neg) ;

absolute_net= total_social* (net_pos/100 ) ;

absolute_pos= total_social* (pos/100 ) ;

absolute_pos_blog = blog* (pos/100 ) ;

absolute_neg= total_social* (neg/100 ) ;

unique ratio= uniques/visits;

run;

proc sql;

create table inputs2 as

select *, sum (visits) as sum visits, sum (views) as sum views, sum (uniques) as sum uniques, sum (news) as sum news, sum (blog) as sum blogs, sum (twitter) as sum twitter, sum (total social) as sum social,

sum(absolute pos) as sum pos, sum(absolute neg) as sum neg, sum (absolute pos blog) as sum pos blog

from inputs

group by month;

create table inputs3 as

select month, corporate, brand, google, visits, views, uniques, blog, news, twitter, total_social, pos, neg, net_pos, absolute_pos , absolute_net,

absolute neg, unique ratio,

visits/sum visits as share visits, views/sum views as share views, uniques/sum uniques as share uniques,

total social/sum social as share social, blog/sum blogs as share blogs, news/sum news as share news, twitter/sum twitter as share twitter, absolute pos/sum pos as share pos, absolute neg/sum neg as share neg, absolute pos blog/sum pos blog as share pos blog

from inputs2

order by month, brand;

quit;

run;

proc sort data=inputs3 ; by month corporate; run;

proc sql;

create table inputs corporate as

select month, brand, corporate, sum (google) as google, sum (visits) as visits, sum(views) as views, sum (uniques ) as uniques,

sum(blog) as blog, sum(news) as news, sum (twitter) as twitter, sum (total_social) as total_social, mean(pos) as pos, mean(neg) as neg,

mean (net_pos ) as net_pos, sum (absolute_pos) as absolute_pos , sum(absolute net) as absolute net, sum(absolute neg) as absolute neg,

sum(share visits) as share visits, sum(share views) as

share views, sum (share blogs) as share blogs,

sum(share news) as share news, sum(share pos) as share pos, sum(share social) as share social, sum(share pos blog) as share pos blog,

sum(share pos blog) as share pos blog

from inputs3

group by month, corporate;

quit;

run;

proc sort data=inputs corporate nodupkey; by month corporate;

run;

[0056] Based upon the calculated monthly shares (e.g., see 328 in FIGURE 3D), the B-INDEX may consolidate the prepared data into a single SAS data set for principal factor analysis to generate scoring coefficients for a B-INDEX index score. In one implementation, factor analysis may be performed 250 done in SAS, e.g., via the "proc factor" command line (see the exemplary SAS code below), etc. A principal component analysis based procedure may be performed which may use an orthogonal transformation to convert the set of observations of possibly correlated variables (e.g., the shares of web visits, shares of page views, shares of social mentions, shares of Google searches, shares of new orders/sign-ups, and/or the like) into one single principal component (e.g., the B-INDEX index score). [0057] In one implementation, the B-INDEX may obtain coefficients from the principal factor analysis, and may utilize the obtained scoring coefficients to calculate a B-INDEX score 253, e.g., based on the following equation: B-INDEX Score = 27.7 + 81.5 * (Share of Visits) + 69.5 * (Share of Page

Views) +0.265 * (Google Search Index) + 44.8 * (Share of Total Social Mentions) +25.3 * (Share of Positive Social Mentions) + 47.2 * (Share of Net New Sign ups) Wherein the numeric values in the above equation are exemplary coefficients for each factor obtained from principal actor analysis. [0058] In one implementation, an exemplary SAS procedure for combining the calculated monthly shares into one single index factor may take a form similar to the following: ***Summary: Take SAS dataset and run it through Proc Factor to output ongoin***; libname pitch ' \\Filsrvl-det . windows . organic . com\strategy\Modeling ' ;

/************** Run Factor Analyses, output the factor scores *************/ data factor input share; set inputs3;

if pos ne . ;

if visits ne . ;

if month>=' 01jan2009 'd;

run;

proc factor data = factor input share priors=smc rotate=varimax nfactors=l score out=temp scores share outstat=pitch . Consideration Coeffs share;

var share visits share views google share blogs share news share pos;

run;

proc score data=inputs corporate (where= (month>= ' 01j an2009 ' d) )

score=pitch . Consideration Coeffs share out=Corp scores;

var share visits share views google share blogs share news share pos;

run;

/******* ange Qf raw Factor Scores (Factor 1 + 2* Factor2 ) from development set were -1. 7 to 6.9. So, assumed a max range of possible scores as -3.0 to 8.0, and scaled this to represent a range of 0-150. Thus, scores of <30 or >100 will be rare and difficult to achieve.*******/

proc sort data=temp scores share; by brand month;

proc sort data=corp scores nodupkey; by brand month;

data temp scores share; merge temp scores share corp scores; by brand month;

if factorl ne . ;

run;

data temp scores share (keep=month corporate brand Factorl Consideration Score Rolling 3mo Consideration Score visits views uniques pos neg net pos

absolute pos absolute neg absolute net google blog news twitter share visits share views share uniques share blogs share news share pos) ;

set temp scores share; by brand month;

if factorl ne . ;

Consideration Score= (Factorl+2) *25;

retain CS_lagI CS_lag2 CS_lag3;

CS lagl = lag (consideration score);

CS_lag2 = lag ( C S_lagl) ;

CS_lag3 = lag (CS_lag2) ;

if lag ( C S_lagl) =. then CS_lag2=.;

if first. brand then do;

CS_lagl = . ;

CS_lag2 = . ;

Rolling 3mo Consideration Score = (consideration score + CS lagl + CS_lag2)/3;

end;

Rolling 3mo Consideration Score = (consideration score + CS lagl + CS lag2)/3; run;

proc sort data=temp scores share; by month brand;

run;

symboll interpol^j oin value^circle cv=blue height^l;

symbol2 interpol^j oin value=square cv=black height^l;

symbol3 interpol=j oin value^diamond cv=orange height^l;

symbol4 interpol^j oin value^triangle cv=tan height=l;

symbol5 interpol^j oin value^cross cv=red height^l;

symbol6 interpol^j oin value=dot cv=green height^l;

axisl label= (' Month ' j ustify^center) ; * order=' 01jan2006 'd to Oldec2009'd by 1 month minor= (number=12 ) ;

2 axis2 labels (' Consideration Score' j ustify=center angle=90) ;

3 *axis3 labels ( 'Errors ' j ustify=center angle=-90) orders -50000 to 150000 by

4 25000;

5 *legendl valuer (' Predicted Sales' 'Actual Sales');

6 ods html;

7 ods graphics on;

8 proc gplot data=temp scores share;

9 plot Consideration Score*month=brand;

10 plot Rolling 3mo Consideration Score*month=brand;

11 plot chg visits*month=brand;

12 plot chg views*month=brand;

13 plot chg blog*month=brand;

14 plot chg google*month=brand;

15 plot chg news*month=brand;

16 plot absolute pos*month=brand;

17 plot absolute neg*month=brand;

18 plot absolute net*month=brand;

19 run;

20 ods graphics off;

21 ods html close;

22 run;

23 * * * * οϋΤΡϋΤ FILES FOR dashboard ****;

24 data output table; merge temp scores trended temp scores share; by month brand;

25 run;

26 proc sql;

27 create table output table as

28 select month, brand, google, visits, views, blog, news, absolute pos,

29 Consideration Score as share CS

30 from output table

31 where month>= ' 01j an2009 ' d;

32 run;

33 proc sort data=output table; by month brand;

34 proc export data=output table

35 outfile= ' WFilsrvldet .windows . organic. com\strategy\Pulte\output KC tr

36 ended. csv' dbms=csv replace;

37 run;

38 * /

39 [0059] In one implementation, the calculated score may be scaled range from o-

40 100, e.g., at 255. In alternative implementations, scaling may take place at data

41 collection, e.g., 247, so that the principal factor analysis may be performed with SAS

42 based on standardized data, e.g., all data values have been transformed so that their

43 means are zero and their standard deviations are one. To avoid confusion of negative

44 values, the data values may be rescaled so that the mean has a value of approximately 50,

45 and the largest value is approximately 100.

46 [0060] The generated index scores of the client and its competitors may be

47 provided to the client via a user interface, e.g., 258. In one implementation, the B- INDEX may generate a plot line of the calculated index score evolution over a time period, showing how the "brand index" of the client changes for each brand over time, e.g., see FIGURE 3E. Additional graphs for each of the factors that contributed to the creation of the index scores may also be included to show where changes in the individual components contributed to changes in the overall index score, e.g., see FIGURES 4A-5H. [0061] Within implementations, the B-INDEX index score may be generated in a multi-stage principal component analysis, e.g., the number of correlated variables may be reduced to more than one principal factors if necessary (e.g., as discussed in in one implementation in FIGURE 2C), and the generated principal factors may be then reduced to a less number of factors; the procedure may continue on until the factors are reduced into a single factor. In one implementation, the principal factor analysis component may generate a scree plot (e.g., a plot of the eigenvalues against the number of factors) to determine the optimal number of final factors of one data category, e.g., social media mentions, blog mentions, web visits, etc. The B-INDEX may look for breaks, or "elbows" in the generated scree plot curve to see how many factors to retain. In most cases, B-INDEX may determine one factor is sufficient to represent one data category, e.g., social media mentions, blog mentions, web visits, etc. In cases where the principal component analysis yields two factors eventually, the B-INDEX may combine the two factors into one final factor using a linear combination (e.g., based on a linear regression structure). [0062 ] FIGURE 2C shows a logic flow diagram illustrating aspects of data reduction within embodiments of the B-INDEX, e.g., in one embodiment, taking the form of a data reduction component 171 of the B-INDEX. In one implementation, data reduction may be taken by B-INDEX to take multiple variables and condense their information into a lesser number of variables while still capturing the monthly swings in the data. Within implementations, the B-INDEX may adopt statistical methodology such as principal factor analysis, multi-dimensional scaling, etc., to achieve data reduction.

[oo63] In one implementation, upon loading various data inputs, the B-INDEX may load the obtained data in one category (e.g., the categories 243a-243d). For example, the B-INDEX may data of the category "social media" including data from a variety of social media platforms, e.g., Meltwater, Facebook, Twitter, etc. [0064 ] The B-INDEX may determine whether data reduction is necessary 263. For example, not every data factor may be used in creating the index score as data factors that are too highly correlated to others, or factors that have a comparatively low variance, may be dropped from the final analysis. In one implementation, the B-INDEX may elect to proceed without data reduction, e.g., treating each data component (e.g., Facebook mentions, Twitter mentions, Meltwater mentions, etc.) as an individual component in the principal component analysis. In an alternative implementation, when there are multiple sources of social media mentions, the B-INDEX may elect to combine different data factors into one social media mention factor. Similarly, for the data category "blog mentions," B-INDEX may combine various blog mentions data from different blog sites (e.g., wordpress, tumblr, etc.) into one blog mentions factor. [0065 ] Within implementations, for each data factor 265, the B-INDEX may determine viability through multicolinearity testing 268, e.g., for each social media mentions indicator, the viability of Facebook mentions, Twitter mentions, etc. For example, in one implementation, multicolinearity diagnostic statistics may be implemented in SAS under "PROC REG" with options "VIF TOL," e.g., exemplary SAS code may take a form similar to: PROC REG DATA=Social_Media_mentions;

MODEL sc mentions = facebook mentions twitter mentions meltwater mentions eblogger mentions / p vif tol;

RUN;

[0066] In one implementation, the viability of each data factor may be defined as the tolerance and/or variance inflation factor (VIF) of the indicator, wherein the indicator may be eliminated if its tolerance (VIF resp.) is less (higher resp.) than a predetermined level, e.g. tolerance < o.i and/or VIF > io. In one embodiment, if the calculated viability is desirable 270, the B-INDEX may store the economic indicator as a significant economic indicator 275. Otherwise, the indicator may be eliminated 273. For example, the B-INDEX may obtain Facebook mentions, Twitter mentions, eBlogger mentions, Meltwater mentions, Sysomos mentions, Linkedln mentions and BlogPulse mentions at 260 as social media mentions. At 265-275, the B-INDEX may determine that all the six types of social media mentions have favorable viability and are significant factors except Linkedln mentions, which may have an undesirable tolerance level. In alternative implementations, the B-INDEX may proceed with index score generation via principal factor analysis using all the six social median mentions indicators. [0067] In one embodiment, the B-INDEX may generate a correlation matrix for the remaining significant data factors 278, and then determine at least one principal component based on the correlation matrix 280. For example, in one implementation, the principal component may be determined by calculating the eigenvalues of the correlation matrix and the principal component indicator may be determined as the one that corresponds to the greatest eigenvalue. The B-INDEX may then combine the significant social media indicators into the at least one principal component 283 based on the calculated correlation, as a single social media factor. For example, in one implementation, the principal factor analysis associated with 280 and 283 may be implemented by SAS in addition to many others. One non-limiting example of SAS code implementation may take a form similar to the following: PROC FACTOR data = "C:\social media mentions" corr scree residuals method = principal;

VAR Facebook mentions Twitter mentions Meltwater mentions eBloggers mentions Sysomos mentions;

RUN;

[0068 ] FIGURE 2D provides a logic flow diagram illustrating aspects of calculating a competitor-independent index score within embodiments of the B-INDEX. In one implementation, the calculation of a competitor-independent index score may take a similar procedure as that of calculating a competitor-based index score, as illustrated in FIGURE 2B, but the competitor-independent index score does not data related to competitors of the client. [0069 ] Within implementations, upon a client submitting an index evaluation request 236, the B-INDEX may collect data for the client over a time frame 286, e.g., over several months, etc. The obtained data may include web traffic logs 286a, social media contents 286b, Google insights 286c, and other third party data 286d, which may take a similar form to that of 243a-243d in FIGURE 2B. In further implementations, the B-INDEX may obtain client specific consumer engagement data 286e, if submitted by the client, such as client sales data, client new enrollment data, and/or the like. Such client specific data may facilitate the B-INDEX to generate an index value indicative of client engagement performance with their brand products. 1 [0070 ] The B-INDEX may then perform data reduction if necessary 288 for each

2 data section 287, in a similar procedure as shown in FIGURE 2C. In one

3 implementation, the B-INDEX may perform principal factor analysis to generate scoring

4 coefficients for each single factor of the data section 289 based on competitor-

5 independent data, and calculate a raw score as a weighted sum of all data factors 290

6 (e.g., via similar principal factor analysis procedure as discussed at 250 and 253 in

7 FIGURE 2B), and provide the generated index scores over the time period to the client

8 292. In one implementation, the generated index score may be scaled to 0-50, etc. In

9 one implementation, the generated competitor-independent scores may not be

10 compared with any of the competitors, but rather be compared with the client's own

11 index score at a different time instant. For example, in one implementation, if the client

12 has an index score of "46.8" in the first week of March, but has an index score of "37.9"

13 in the second week of March, the drop in the index score may suggest a decreased

14 market performance or consumer impression of the client. In one implementation, the

15 B-INDEX may generate performance heuristics of the index scores over a time frame

16 291, such as a plot of the client's index score over the selected time frame, which may

17 indicates the change of consumer impressions of the client's brand name/products over is time. Further details of example plots and performance heuristics are provided in

19 FIGURES 4A-5H.

20 [0071 ] In further implementations, the B-INDEX may generate plots to compare

21 a time-dependent curve of different data factors 286a-286f curve, and the generated

22 index score curve so that it may be determined which data factor may give a better

23 measure of overall performance as it is the closely correlated to the index score curve. 1 [0072 ] FIGURES 3 A-3 E provide exemplary user interfaces illustrating index score

2 calculation within embodiments of the B-INDEX. As shown in FIGURE 3A, a client may

3 access the B-INDEX platform via a web based application, which may request the client

4 to log in with a login user name 306a and a password 306b. Upon successful login, as

5 shown in FIGURE 3B, the client may elect to "view/edit user profile" 311, "start brand

6 index" 312 evaluation (e.g., the competitor-based index score), "start connection index"

7 313 evaluation (e.g., the competitor-independent index score), "view summary" 314,

8 and/or the like.

9 [0073 ] In one implementation, if the user clicks "start brand index" 312 to submit

10 an evaluation request (e.g., also see 236 in FIGURE 2B), as shown in FIGURE 3B, the

11 client "Ella Electronics" may view a brief summary of its user profile as "Ella Electronics,

12 Ltd." 315, including its address, telephone number, company website, key words of

13 business category, etc. In one implementation, the client may identify an interested

14 evaluation target, e.g., the brand name "Ella Electronics," 317. In another

15 implementation, the client may identify a specific product, promotion package, service

16 program, etc., of "Ella Electronics" for evaluation, e.g., "Ella Electronics Super March

17 Savings," "Ella Electronics Student Package," and/or the like. The client may also

18 identify itself by selecting interested industry category 318. For example, the client "Ella

19 Electronics" may select labels "Electronics" 318a and its subcategories including a

20 variety of electronics products, and "retail" 318b. In another implementation, the client

21 may review and select from a list of recommended competitors provided by B-INDEX

22 319 (e.g., also see 238 in FIGURE 2B), wherein the recommended list of competitors

23 may be generated based on the client's interested industry category 318. For example,

24 the client may elect to select a default option, e.g., "all recommended" 319a competitors. 1 The client may further review and select recommended data source 320, e.g., a default

2 option "all available data" 320a, and a time frame, e.g., "march," etc.

3 [0074] The client may further select a time frame including a frequency basis of

4 the evaluation "weekly" (e.g., or daily, monthly, etc.), from a start date of "Mar 01" to an

5 end date of "Aug 31," e.g., at 321 in FIGURE 3B. In one implementation, such time

6 frame selection may result in a B-INDEX index score curve including weekly index

7 scores over a period of time from March to August.

8 [0075 ] FIGURE 3C provides an exemplary user interface screenshot illustrating

9 data collection of the client and its competitors (e.g., 243 in FIGURE 2B) within

10 embodiments of the B-INDEX. For example, in one implementation, the client "Ella

11 Electronics" may view a data table 325 of different data categories, including site visits,

12 page view, Google index, total social mentions, positive social mentions, net new sign-

13 ups, and/or the like, of "Ella Electronics" and its competitors.

14 [0076] FIGURE 3D provides an exemplary user interface screenshot illustrating

15 monthly share calculation (e.g., 247 in FIGURE 2B) within embodiments of the file INDEX. For example, in one implementation, the client "Ella Electronics" may view a 17 data table 328 of calculated monthly shares among "Ella Electronics" and its is competitors under different data categories, including site visits, page view, Google

19 index, total social mentions, positive social mentions, net new sign-ups, and/or the like.

20 The monthly shares as shown in the table 328 are calculated based on the data overview

21 325 in FIGURE 3C.

22 [0077] FIGURE 3E provides an exemplary user interface screenshot illustrating

23 calculated index score dashboard within embodiments of the B-INDEX. For example, as shown in FIGURE 3E, a dashboard screen may be provided to the user, showing an index score 305 of the client "Ella Electronics," and compare "Ella Electronics" with its top competitors MS," "Supermart," "Fancy E," and "Wall E" in table 310. In one implementation, the B-INDEX may draw a "monthly consideration score trend" 340, comparing the calculated index scores of the client "Ella Electronics" and its competitors. [0078 ] FIGURES 4A-5H provide various exemplary user interface screenshots within embodiments of the B-INDEX. For example, the B-INDEX may calculate a evaluation score (either competitor-based, or competitor-independent) based on metrics such as, but not limited to site visits, average page visits, Google search index, mentions in blogs, mentions in news, and/or the like. In FIGURE 4A, the B-INDEX provides a graphic view comparing the client's (e.g., "Ella Electronics") competitor- based index score curve over a period of 5 months versus that of several top competitors. FIGURES 4B-4F provide various charts, curves, etc., comparing various consideration metrics that contribute to the index score between the client and its competitors. Compared consideration metrics may include mentions in News (e.g., see FIGURE 4B), site visits (e.g., see FIGURE 4C), average page views (e.g., see FIGURE 4D), Google search index (e.g., see FIGURE 4E), mentions in blogs (e.g., see FIGURE 4F), and/or the like. [0079 ] In another implementation, the B-INDEX may consider metrics such as site visits, average page visits, Google search index, shares of net new orders, positive social mentions, unique visits, bounce rates, and/or the like. FIGURES 5A-5H provide further examples of comparisons between a client and its competitors. [0080 ] As shown in FIGURES 4A-5H, B-INDEX may generate plots illustrating a comparison between the client and its competitors showing changes of the calculated index score and each data metric over a time frame, so that it may be determined that one or more data metrics (e.g., social media sentiment, etc.) may be more determinative in driving the overall brand index score. Such comparison among different data metrics may be applied for competitor-based and/or competitor-independent index scores, towards the client's own data metrics and/or the competitor's data metrics. [0081 ] For example, the client "Ella Electronics" may find its B-INDEX index score most closely track with its web site visits and page views. For another example, the client may learn competitors' market performance, e.g., whether a competitor's investment in social media presence improves its social media mentions, news mentions, web visits, and/or index scores. For another example, the client may analyze the impacts of news reporting on their own, or competitors' products, e.g., whether the positive and/or negative press comments affect the index scores. [0082 ] In further implementations, the B-INDEX may perform principle components based factor analysis to gauge consumers share of mind, and provide guidance for social and awareness content/messaging strategy in real-time. The B- INDEX may provide clients ability to monitor the online conversation across the digital ecosystem, transform reporting from brand centric to competitive intelligence.

B- INDEX Controller

[0083 ] FIGURE 6 shows a block diagram illustrating embodiments of a B-INDEX controller. In this embodiment, the B-INDEX controller 601 may serve to aggregate, process, store, search, serve, identify, instruct, generate, match, and/or facilitate interactions with a computer through data mining technologies, and/or other related data. [0084] Typically, users, which may be people and/or other systems, may engage information technology systems (e.g., computers) to facilitate information processing. In turn, computers employ processors to process information; such processors 603 may be referred to as central processing units (CPU). One form of processor is referred to as a microprocessor. CPUs use communicative circuits to pass binary encoded signals acting as instructions to enable various operations. These instructions may be operational and/or data instructions containing and/or referencing other instructions and data in various processor accessible and operable areas of memory 629 (e.g., registers, cache memory, random access memory, etc.). Such communicative instructions may be stored and/or transmitted in batches (e.g., batches of instructions) as programs and/or data components to facilitate desired operations. These stored instruction codes, e.g., programs, may engage the CPU circuit components and other motherboard and/or system components to perform desired operations. One type of program is a computer operating system, which, may be executed by CPU on a computer; the operating system enables and facilitates users to access and operate computer information technology and resources. Some resources that may be employed in information technology systems include: input and output mechanisms through which data may pass into and out of a computer; memory storage into which data may be saved; and processors by which information may be processed. These information technology systems may be used to collect data for later retrieval, analysis, and manipulation, which may be facilitated through a database program. These information technology systems provide interfaces that allow users to access and operate various system components. [0085] In one embodiment, the B-INDEX controller 601 may be connected to and/or communicate with entities such as, but not limited to: one or more users from user input devices 611; peripheral devices 612; an optional cryptographic processor device 628; and/or a communications network 613. [0086] Networks are commonly thought to comprise the interconnection and interoperation of clients, servers, and intermediary nodes in a graph topology. It should be noted that the term "server" as used throughout this application refers generally to a computer, other device, program, or combination thereof that processes and responds to the requests of remote users across a communications network. Servers serve their information to requesting "clients." The term "client" as used herein refers generally to a computer, program, other device, user and/or combination thereof that is capable of processing and making requests and obtaining and processing any responses from servers across a communications network. A computer, other device, program, or combination thereof that facilitates, processes information and requests, and/or furthers the passage of information from a source user to a destination user is commonly referred to as a "node." Networks are generally thought to facilitate the transfer of information from source points to destinations. A node specifically tasked with furthering the passage of information from a source to a destination is commonly called a "router." There are many forms of networks such as Local Area Networks (LANs), Pico networks, Wide Area Networks (WANs), Wireless Networks (WLANs), etc. For example, the Internet is generally accepted as being an interconnection of a multitude of networks whereby remote clients and servers may access and interoperate with one another. [0087] The B-INDEX controller 601 may be based on computer systems that may comprise, but are not limited to, components such as: a computer systemization 602 connected to memory 629. Computer Systemization

[0088] A computer systemization 602 may comprise a clock 630, central processing unit ("CPU(s)" and/or "processor(s)" (these terms are used interchangeable throughout the disclosure unless noted to the contrary)) 603, a memory 629 (e.g., a read only memory (ROM) 606, a random access memory (RAM) 605, etc.), and/or an interface bus 607, and most frequently, although not necessarily, are all interconnected and/or communicating through a system bus 604 on one or more (mother )board(s) 602 having conductive and/or otherwise transportive circuit pathways through which instructions (e.g., binary encoded signals) may travel to effectuate communications, operations, storage, etc. The computer systemization may be connected to a power source 686; e.g., optionally the power source may be internal. Optionally, a cryptographic processor 626 and/or transceivers (e.g., ICs) 674 may be connected to the system bus. In another embodiment, the cryptographic processor and/or transceivers may be connected as either internal and/or external peripheral devices 612 via the interface bus I/O. In turn, the transceivers may be connected to antenna(s) 675, thereby effectuating wireless transmission and reception of various communication and/or sensor protocols; for example the antenna(s) may connect to: a Texas Instruments WiLink WL1283 transceiver chip (e.g., providing 802.1m, Bluetooth 3.0, FM, global positioning system (GPS) (thereby allowing B-INDEX controller to determine its location)); Broadcom BCM4329FKUBG transceiver chip (e.g., providing 802.1m, Bluetooth 2.1 + EDR, FM, etc.); a Broadcom BCM4750IUB8 receiver chip (e.g., GPS); an Infineon Technologies X-Gold 618-PMB9800 (e.g., providing 2G/3G HSDPA/HSUPA communications); and/or the like. The system clock typically has a crystal oscillator and generates a base signal through the computer systemization's circuit pathways. The clock is typically coupled to the system bus and various clock multipliers that will increase or decrease the base operating frequency for other components interconnected in the computer systemization. The clock and various components in a computer systemization drive signals embodying information throughout the system. Such transmission and reception of instructions embodying information throughout a computer systemization may be commonly referred to as communications. These communicative instructions may further be transmitted, received, and the cause of return and/or reply communications beyond the instant computer systemization to: communications networks, input devices, other computer systemizations, peripheral devices, and/or the like. It should be understood that in alternative embodiments, any of the above components may be connected directly to one another, connected to the CPU, and/or organized in numerous variations employed as exemplified by various computer systems. [0089] The CPU comprises at least one high-speed data processor adequate to execute program components for executing user and/or system-generated requests. Often, the processors themselves will incorporate various specialized processing units, such as, but not limited to: integrated system (bus) controllers, memory management control units, floating point units, and even specialized processing sub-units like graphics processing units, digital signal processing units, and/or the like. Additionally, processors may include internal fast access addressable memory, and be capable of mapping and addressing memory 629 beyond the processor itself; internal memory may include, but is not limited to: fast registers, various levels of cache memory (e.g., level 1, 2, 3, etc.), RAM, etc. The processor may access this memory through the use of a memory address space that is accessible via instruction address, which the processor can construct and decode allowing it to access a circuit path to a specific memory address space having a memory state. The CPU may be a microprocessor such as: AMD's Athlon, Duron and/or Opteron; ARM's application, embedded and secure processors; IBM and/or Motorola's DragonBall and PowerPC; IBM's and Sony's Cell processor; Intel's Celeron, Core (2) Duo, Itanium, Pentium, Xeon, and/or XScale; and/or the like processor(s). The CPU interacts with memory through instruction passing through conductive and/or transportive conduits (e.g., (printed) electronic and/or optic circuits) to execute stored instructions (i.e., program code) according to conventional data processing techniques. Such instruction passing facilitates communication within the B-INDEX controller and beyond through various interfaces. Should processing requirements dictate a greater amount speed and/or capacity, distributed processors (e.g., Distributed B-INDEX), mainframe, multi-core, parallel, and/or super-computer architectures may similarly be employed. Alternatively, should deployment requirements dictate greater portability, smaller Personal Digital Assistants (PDAs) may be employed. [0090 ] Depending on the particular implementation, features of the B-INDEX may be achieved by implementing a microcontroller such as CAST's R8051XC2 microcontroller; Intel's MCS 51 (i.e., 8051 microcontroller); and/or the like. Also, to implement certain features of the B-INDEX, some feature implementations may rely on embedded components, such as: Application-Specific Integrated Circuit ("ASIC"), Digital Signal Processing ("DSP"), Field Programmable Gate Array ("FPGA"), and/or the like embedded technology. For example, any of the B-INDEX component collection (distributed or otherwise) and/or features may be implemented via the microprocessor and/or via embedded components; e.g., via ASIC, coprocessor, DSP, FPGA, and/or the like. Alternately, some implementations of the B-INDEX may be implemented with embedded components that are configured and used to achieve a variety of features or signal processing. [0091] Depending on the particular implementation, the embedded components may include software solutions, hardware solutions, and/or some combination of both hardware/software solutions. For example, B-INDEX features discussed herein may be achieved through implementing FPGAs, which are a semiconductor devices containing programmable logic components called "logic blocks", and programmable interconnects, such as the high performance FPGA Virtex series and/or the low cost Spartan series manufactured by Xilinx. Logic blocks and interconnects can be programmed by the customer or designer, after the FPGA is manufactured, to implement any of the B- INDEX features. A hierarchy of programmable interconnects allow logic blocks to be interconnected as needed by the B-INDEX system designer/administrator, somewhat like a one-chip programmable breadboard. An FPGA's logic blocks can be programmed to perform the operation of basic logic gates such as AND, and XOR, or more complex combinational operators such as decoders or mathematical operations. In most FPGAs, the logic blocks also include memory elements, which may be circuit flip-flops or more complete blocks of memory. In some circumstances, the B-INDEX may be developed on regular FPGAs and then migrated into a fixed version that more resembles ASIC implementations. Alternate or coordinating implementations may migrate B-INDEX controller features to a final ASIC instead of or in addition to FPGAs. Depending on the implementation all of the aforementioned embedded components and microprocessors may be considered the "CPU" and/or "processor" for the B-INDEX. Power Source

[0092] The power source 686 may be of any standard form for powering small electronic circuit board devices such as the following power cells: alkaline, lithium hydride, lithium ion, lithium polymer, nickel cadmium, solar cells, and/or the like. Other types of AC or DC power sources may be used as well. In the case of solar cells, in one embodiment, the case provides an aperture through which the solar cell may capture photonic energy. The power cell 686 is connected to at least one of the interconnected subsequent components of the B-INDEX thereby providing an electric current to all subsequent components. In one example, the power source 686 is connected to the system bus component 604. In an alternative embodiment, an outside power source 686 is provided through a connection across the I/O 608 interface. For example, a USB and/or IEEE 1394 connection carries both data and power across the connection and is therefore a suitable source of power. Interface Adapters

[0093] Interface bus(ses) 607 may accept, connect, and/or communicate to a number of interface adapters, conventionally although not necessarily in the form of adapter cards, such as but not limited to: input output interfaces (I/O) 608, storage interfaces 609, network interfaces 610, and/or the like. Optionally, cryptographic processor interfaces 627 similarly may be connected to the interface bus. The interface bus provides for the communications of interface adapters with one another as well as with other components of the computer systemization. Interface adapters are adapted for a compatible interface bus. Interface adapters conventionally connect to the interface bus via a slot architecture. Conventional slot architectures may be employed, such as, but not limited to: Accelerated Graphics Port (AGP), Card Bus, (Extended) Industry Standard Architecture ((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral Component Interconnect (Extended) (PCI(X)), PCI Express, Personal Computer Memory Card International Association (PCMCIA), and/or the like. [0094 ] Storage interfaces 609 may accept, communicate, and/or connect to a number of storage devices such as, but not limited to: storage devices 614, removable disc devices, and/or the like. Storage interfaces may employ connection protocols such as, but not limited to: (Ultra) (Serial) Advanced Technology Attachment (Packet Interface) ((Ultra) (Serial) ATA(PI)), (Enhanced) Integrated Drive Electronics ((E)IDE), Institute of Electrical and Electronics Engineers (IEEE) 1394, fiber channel, Small Computer Systems Interface (SCSI), Universal Serial Bus (USB), and/or the like. [0095 ] Network interfaces 610 may accept, communicate, and/or connect to a communications network 613. Through a communications network 613, the B-INDEX controller is accessible through remote clients 633b (e.g., computers with web browsers) by users 633a. Network interfaces may employ connection protocols such as, but not limited to: direct connect, Ethernet (thick, thin, twisted pair 10/100/1000 Base T, and/or the like), Token Ring, wireless connection such as IEEE 8o2.na-x, and/or the like. Should processing requirements dictate a greater amount speed and/or capacity, distributed network controllers (e.g., Distributed B-INDEX), architectures may similarly be employed to pool, load balance, and/or otherwise increase the communicative bandwidth required by the B-INDEX controller. A communications network may be any one and/or the combination of the following: a direct interconnection; the Internet; a Local Area Network (LAN); a Metropolitan Area Network (MAN); an Operating Missions as Nodes on the Internet (OMNI); a secured custom connection; a Wide Area Network (WAN); a wireless network (e.g., employing protocols such as, but not limited to a Wireless Application Protocol (WAP), I-mode, and/or the like); and/or the like. A network interface may be regarded as a specialized form of an input output interface. Further, multiple network interfaces 610 may be used to engage with various communications network types 613. For example, multiple network interfaces may be employed to allow for the communication over broadcast, multicast, and/or unicast networks. [0096 ] Input Output interfaces (I/O) 608 may accept, communicate, and/or connect to user input devices 611, peripheral devices 612, cryptographic processor devices 628, and/or the like. I/O may employ connection protocols such as, but not limited to: audio: analog, digital, monaural, RCA, stereo, and/or the like; data: Apple Desktop Bus (ADB), IEEE I394a-b, serial, universal serial bus (USB); infrared; joystick; keyboard; midi; optical; PC AT; PS/2; parallel; radio; video interface: Apple Desktop Connector (ADC), BNC, coaxial, component, composite, digital, Digital Visual Interface (DVI), high-definition multimedia interface (HDMI), RCA, RF antennae, S-Video, VGA, and/or the like; wireless transceivers: 802.na/b/g/n/x; Bluetooth; cellular (e.g., code division multiple access (CDMA), high speed packet access (HSPA(+)), high-speed downlink packet access (HSDPA), global system for mobile communications (GSM), long term evolution (LTE), WiMax, etc.); and/or the like. One typical output device may include a video display, which typically comprises a Cathode Ray Tube (CRT) or Liquid Crystal Display (LCD) based monitor with an interface (e.g., DVI circuitry and cable) that accepts signals from a video interface, may be used. The video interface composites information generated by a computer systemization and generates video signals based on the composited information in a video memory frame. Another output device is a television set, which accepts signals from a video interface. Typically, the video interface provides the composited video information through a video connection interface that accepts a video display interface (e.g., an RCA composite video connector accepting an RCA composite video cable; a DVI connector accepting a DVI display cable, etc.). [0097] User input devices 611 often are a type of peripheral device 512 (see below) and may include: card readers, dongles, finger print readers, gloves, graphics tablets, joysticks, keyboards, microphones, mouse (mice), remote controls, retina readers, touch screens (e.g., capacitive, resistive, etc.), trackballs, trackpads, sensors (e.g., accelerometers, ambient light, GPS, gyroscopes, proximity, etc.), styluses, and/or the like. [0098] Peripheral devices 612 may be connected and/or communicate to I/O and/or other facilities of the like such as network interfaces, storage interfaces, directly to the interface bus, system bus, the CPU, and/or the like. Peripheral devices may be external, internal and/or part of the B-INDEX controller. Peripheral devices may include: antenna, audio devices (e.g., line-in, line-out, microphone input, speakers, etc.), cameras (e.g., still, video, webcam, etc.), dongles (e.g., for copy protection, ensuring secure transactions with a digital signature, and/or the like), external processors (for 1 added capabilities; e.g., crypto devices 528), force-feedback devices (e.g., vibrating

2 motors), network interfaces, printers, scanners, storage devices, transceivers (e.g.,

3 cellular, GPS, etc.), video devices (e.g., goggles, monitors, etc.), video sources, visors,

4 and/or the like. Peripheral devices often include types of input devices (e.g., cameras).

5 [0099 ] It should be noted that although user input devices and peripheral devices

6 may be employed, the B-INDEX controller may be embodied as an embedded, dedicated,

7 and/or monitor-less (i.e., headless) device, wherein access would be provided over a

8 network interface connection.

9 [00100 ] Cryptographic units such as, but not limited to, microcontrollers,

10 processors 626, interfaces 627, and/or devices 628 may be attached, and/or

11 communicate with the B-INDEX controller. A MC68HC16 microcontroller,

12 manufactured by Motorola Inc., may be used for and/or within cryptographic units. The

13 MC68HC16 microcontroller utilizes a 16-bit multiply-and-accumulate instruction in the

14 16 MHz configuration and requires less than one second to perform a 512-bit RSA

15 private key operation. Cryptographic units support the authentication of

16 communications from interacting agents, as well as allowing for anonymous

17 transactions. Cryptographic units may also be configured as part of the CPU. Equivalent is microcontrollers and/or processors may also be used. Other commercially available

19 specialized cryptographic processors include: Broadcom's CryptoNetX and other

20 Security Processors; nCipher's nShield; SafeNet's Luna PCI (e.g., 7100) series;

21 Semaphore Communications' 40 MHz Roadrunner 184; Sun's Cryptographic

22 Accelerators (e.g., Accelerator 6000 PCIe Board, Accelerator 500 Daughtercard); Via

23 Nano Processor (e.g., L2100, L2200, U2400) line, which is capable of performing 500+ MB/s of cryptographic instructions; VLSI Technology's 33 MHz 6868; and/or the like. Memory

[00101] Generally, any mechanization and/or embodiment allowing a processor to affect the storage and/or retrieval of information is regarded as memory 629. However, memory is a fungible technology and resource, thus, any number of memory embodiments may be employed in lieu of or in concert with one another. It is to be understood that the B-INDEX controller and/or a computer systemization may employ various forms of memory 629. For example, a computer systemization may be configured wherein the operation of on-chip CPU memory (e.g., registers), RAM, ROM, and any other storage devices are provided by a paper punch tape or paper punch card mechanism; however, such an embodiment would result in an extremely slow rate of operation. In a typical configuration, memory 629 will include ROM 606, RAM 605, and a storage device 614. A storage device 614 may be any conventional computer system storage. Storage devices may include a drum; a (fixed and/or removable) magnetic disk drive; a magneto-optical drive; an optical drive (i.e., Blueray, CD ROM/RAM/Recordable (R)/ReWritable (RW), DVD R/RW, HD DVD R/RW etc.); an array of devices (e.g., Redundant Array of Independent Disks (RAID)); solid state memory devices (USB memory, solid state drives (SSD), etc.); other processor-readable storage mediums; and/or other devices of the like. Thus, a computer systemization generally requires and makes use of memory. Component Collection

[00102] The memory 629 may contain a collection of program and/or database components and/or data such as, but not limited to: operating system component(s) 615 1 (operating system); information server component(s) 616 (information server); user

2 interface component(s) 617 (user interface); Web browser component(s) 618 (Web

3 browser); database(s) 619; mail server component(s) 621; mail client component(s) 622;

4 cryptographic server component(s) 620 (cryptographic server); the B-INDEX

5 component(s) 635; and/or the like (i.e., collectively a component collection). These

6 components may be stored and accessed from the storage devices and/or from storage

7 devices accessible through an interface bus. Although non-conventional program

8 components such as those in the component collection, typically, are stored in a local

9 storage device 614, they may also be loaded and/or stored in memory such as:

10 peripheral devices, RAM, remote storage facilities through a communications network,

11 ROM, various forms of memory, and/or the like.

12 Operating System

13 [00103] The operating system component 615 is an executable program

14 component facilitating the operation of the B-INDEX controller. Typically, the operating

15 system facilitates access of I/O, network interfaces, peripheral devices, storage devices,

16 and/or the like. The operating system may be a highly fault tolerant, scalable, and

17 secure system such as: Apple Macintosh OS X (Server); AT&T Plan 9; Be OS; Unix and

18 Unix-like system distributions (such as AT&T's UNIX; Berkley Software Distribution

19 (BSD) variations such as FreeBSD, NetBSD, OpenBSD, and/or the like; Linux

20 distributions such as Red Hat, Ubuntu, and/or the like); and/or the like operating

21 systems. However, more limited and/or less secure operating systems also may be

22 employed such as Apple Macintosh OS, IBM OS/2, Microsoft DOS, Microsoft Windows

23 2000/2003/3. i/95/98/CE/Millenium/NT/Vista/XP (Server), Palm OS, and/or the like. An operating system may communicate to and/or with other components in a component collection, including itself, and/or the like. Most frequently, the operating system communicates with other program components, user interfaces, and/or the like. For example, the operating system may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, and/or responses. The operating system, once executed by the CPU, may enable the interaction with communications networks, data, I/O, peripheral devices, program components, memory, user input devices, and/or the like. The operating system may provide communications protocols that allow the B-INDEX controller to communicate with other entities through a communications network 613. Various communication protocols may be used by the B-INDEX controller as a subcarrier transport mechanism for interaction, such as, but not limited to: multicast, TCP/IP, UDP, unicast, and/or the like. Information Server

[00104] An information server component 616 is a stored program component that is executed by a CPU. The information server may be a conventional Internet information server such as, but not limited to Apache Software Foundation's Apache, Microsoft's Internet Information Server, and/or the like. The information server may allow for the execution of program components through facilities such as Active Server Page (ASP), ActiveX, (ANSI) (Objective-) C (++), C# and/or .NET, Common Gateway Interface (CGI) scripts, dynamic (D) hypertext markup language (HTML), FLASH, Java, JavaScript, Practical Extraction Report Language (PERL), Hypertext Pre-Processor (PHP), pipes, Python, wireless application protocol (WAP), WebObjects, and/or the like. The information server may support secure communications protocols such as, but not limited to, File Transfer Protocol (FTP); HyperText Transfer Protocol (HTTP); Secure Hypertext Transfer Protocol (HTTPS), Secure Socket Layer (SSL), messaging protocols (e.g., America Online (AOL) Instant Messenger (AIM), Application Exchange (APEX), ICQ, Internet Relay Chat (IRC), Microsoft Network (MSN) Messenger Service, Presence and Instant Messaging Protocol (PRIM), Internet Engineering Task Force's (IETF's) Session Initiation Protocol (SIP), SIP for Instant Messaging and Presence Leveraging Extensions (SIMPLE), open XML-based Extensible Messaging and Presence Protocol (XMPP) (i.e., Jabber or Open Mobile Alliance's (OMA's) Instant Messaging and Presence Service (IMPS)), Yahoo! Instant Messenger Service, and/or the like. The information server provides results in the form of Web pages to Web browsers, and allows for the manipulated generation of the Web pages through interaction with other program components. After a Domain Name System (DNS) resolution portion of an HTTP request is resolved to a particular information server, the information server resolves requests for information at specified locations on the B-INDEX controller based on the remainder of the HTTP request. For example, a request such as http://123.124.125.126/myInformation.html might have the IP portion of the request "123.124.125.126" resolved by a DNS server to an information server at that IP address; that information server might in turn further parse the http request for the "/mylnf ormation.html" portion of the request and resolve it to a location in memory containing the information "myInformation.html." Additionally, other information serving protocols may be employed across various ports, e.g., FTP communications across port 21, and/or the like. An information server may communicate to and/or with other components in a component collection, including itself, and/or facilities of the like. Most frequently, the information server communicates with the B-INDEX database 619, operating systems, other program components, user interfaces, Web browsers, and/or the like. [00105 ] Access to the B-INDEX database may be achieved through a number of database bridge mechanisms such as through scripting languages as enumerated below (e.g., CGI) and through inter-application communication channels as enumerated below (e.g., CORBA, WebObjects, etc.). Any data requests through a Web browser are parsed through the bridge mechanism into appropriate grammars as required by the B-INDEX. In one embodiment, the information server would provide a Web form accessible by a Web browser. Entries made into supplied fields in the Web form are tagged as having been entered into the particular fields, and parsed as such. The entered terms are then passed along with the field tags, which act to instruct the parser to generate queries directed to appropriate tables and/or fields. In one embodiment, the parser may generate queries in standard SQL by instantiating a search string with the proper join/select commands based on the tagged text entries, wherein the resulting command is provided over the bridge mechanism to the B-INDEX as a query. Upon generating query results from the query, the results are passed over the bridge mechanism, and may be parsed for formatting and generation of a new results Web page by the bridge mechanism. Such a new results Web page is then provided to the information server, which may supply it to the requesting Web browser. [00106 ] Also, an information server may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, and/or responses. 1 User Interface

2 [00107] Computer interfaces in some respects are similar to automobile operation

3 interfaces. Automobile operation interface elements such as steering wheels, gearshifts,

4 and speedometers facilitate the access, operation, and display of automobile resources,

5 and status. Computer interaction interface elements such as check boxes, cursors,

6 menus, scrollers, and windows (collectively and commonly referred to as widgets)

7 similarly facilitate the access, capabilities, operation, and display of data and computer

8 hardware and operating system resources, and status. Operation interfaces are

9 commonly called user interfaces. Graphical user interfaces (GUIs) such as the Apple

10 Macintosh Operating System's Aqua, IBM's OS/2, Microsoft's Windows

11 2000/2003/3. i/95/98/CE/Millenium/NT/XP/Vista/7 (i.e., Aero), Unix's X-Windows

12 (e.g., which may include additional Unix graphic interface libraries and layers such as K

13 Desktop Environment (KDE), mythTV and GNU Network Object Model Environment

14 (GNOME)), web interface libraries (e.g., ActiveX, AJAX, (D)HTML, FLASH, Java,

15 JavaScript, etc. interface libraries such as, but not limited to, Dojo, jQuery(UI),

16 MooTools, Prototype, script.aculo.us, SWFObject, Yahoo! User Interface, any of which

17 may be used and) provide a baseline and means of accessing and displaying information is graphically to users.

19 [00108] A user interface component 617 is a stored program component that is

20 executed by a CPU. The user interface may be a conventional graphic user interface as

21 provided by, with, and/or atop operating systems and/or operating environments such

22 as already discussed. The user interface may allow for the display, execution, interaction,

23 manipulation, and/or operation of program components and/or system facilities

24 through textual and/or graphical facilities. The user interface provides a facility through which users may affect, interact, and/or operate a computer system. A user interface may communicate to and/or with other components in a component collection, including itself, and/or facilities of the like. Most frequently, the user interface communicates with operating systems, other program components, and/or the like. The user interface may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, and/or responses. Web Browser

[00109] A Web browser component 618 is a stored program component that is executed by a CPU. The Web browser may be a conventional hypertext viewing application such as Microsoft Internet Explorer or Netscape Navigator. Secure Web browsing may be supplied with I28bit (or greater) encryption by way of HTTPS, SSL, and/or the like. Web browsers allowing for the execution of program components through facilities such as ActiveX, AJAX, (D)HTML, FLASH, Java, JavaScript, web browser plug-in APIs (e.g., FireFox, Safari Plug-in, and/or the like APIs), and/or the like. Web browsers and like information access tools may be integrated into PDAs, cellular telephones, and/or other mobile devices. A Web browser may communicate to and/or with other components in a component collection, including itself, and/or facilities of the like. Most frequently, the Web browser communicates with information servers, operating systems, integrated program components (e.g., plug-ins), and/or the like; e.g., it may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, and/or responses. Also, in place of a Web browser and information server, a combined application may be developed to perform similar operations of both. The combined application would similarly affect the obtaining and the provision of information to users, user agents, and/or the like from the B-INDEX enabled nodes. The combined application may be nugatory on systems employing standard Web browsers. Mail Server

[o o no ] A mail server component 621 is a stored program component that is executed by a CPU 603. The mail server may be a conventional Internet mail server such as, but not limited to sendmail, Microsoft Exchange, and/or the like. The mail server may allow for the execution of program components through facilities such as ASP, ActiveX, (ANSI) (Objective-) C (++), C# and/or .NET, CGI scripts, Java, JavaScript, PERL, PHP, pipes, Python, WebObjects, and/or the like. The mail server may support communications protocols such as, but not limited to: Internet message access protocol (IMAP), Messaging Application Programming Interface (MAPI)/Microsoft Exchange, post office protocol (POP3), simple mail transfer protocol (SMTP), and/or the like. The mail server can route, forward, and process incoming and outgoing mail messages that have been sent, relayed and/or otherwise traversing through and/or to the B-INDEX. [00111 ] Access to the B-INDEX mail may be achieved through a number of APIs offered by the individual Web server components and/or the operating system. [00112 ] Also, a mail server may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, information, and/or responses. Mail Client

[00113 ] A mail client component 622 is a stored program component that is executed by a CPU 603. The mail client may be a conventional mail viewing application such as Apple Mail, Microsoft Entourage, Microsoft Outlook, Microsoft Outlook Express, Mozilla, Thunderbird, and/or the like. Mail clients may support a number of transfer protocols, such as: IMAP, Microsoft Exchange, POP3, SMTP, and/or the like. A mail client may communicate to and/or with other components in a component collection, including itself, and/or facilities of the like. Most frequently, the mail client communicates with mail servers, operating systems, other mail clients, and/or the like; e.g., it may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, information, and/or responses. Generally, the mail client provides a facility to compose and transmit electronic mail messages. Cryptographic Server

[00114] A cryptographic server component 620 is a stored program component that is executed by a CPU 603, cryptographic processor 626, cryptographic processor interface 627, cryptographic processor device 628, and/or the like. Cryptographic processor interfaces will allow for expedition of encryption and/or decryption requests by the cryptographic component; however, the cryptographic component, alternatively, may run on a conventional CPU. The cryptographic component allows for the encryption and/or decryption of provided data. The cryptographic component allows for both symmetric and asymmetric (e.g., Pretty Good Protection (PGP)) encryption and/or decryption. The cryptographic component may employ cryptographic techniques such as, but not limited to: digital certificates (e.g., X.509 authentication framework), digital signatures, dual signatures, enveloping, password access protection, public key management, and/or the like. The cryptographic component will facilitate numerous (encryption and/or decryption) security protocols such as, but not limited to: checksum, Data Encryption Standard (DES), Elliptical Curve Encryption (ECC), International Data Encryption Algorithm (IDEA), Message Digest 5 (MD5, which is a one way hash operation), passwords, Rivest Cipher (RC5), Rijndael, RSA (which is an Internet encryption and authentication system that uses an algorithm developed in 1977 by Ron Rivest, Adi Shamir, and Leonard Adleman), Secure Hash Algorithm (SHA), Secure Socket Layer (SSL), Secure Hypertext Transfer Protocol (HTTPS), and/or the like. Employing such encryption security protocols, the B-INDEX may encrypt all incoming and/or outgoing communications and may serve as node within a virtual private network (VPN) with a wider communications network. The cryptographic component facilitates the process of "security authorization" whereby access to a resource is inhibited by a security protocol wherein the cryptographic component effects authorized access to the secured resource. In addition, the cryptographic component may provide unique identifiers of content, e.g., employing and MD5 hash to obtain a unique signature for an digital audio file. A cryptographic component may communicate to and/or with other components in a component collection, including itself, and/or facilities of the like. The cryptographic component supports encryption schemes allowing for the secure transmission of information across a communications network to enable the B-INDEX component to engage in secure transactions if so desired. The cryptographic component facilitates the secure accessing of resources on the B-INDEX and facilitates the access of secured resources on remote systems; i.e., it may act as a client and/or server of secured resources. Most frequently, the cryptographic component communicates with information servers, operating systems, other program components, and/or the like. The cryptographic component may contain, communicate, generate, obtain, and/or provide program component, system, user, and/or data communications, requests, and/or responses. The B- INDEX Database

[00115] The B-INDEX database component 619 may be embodied in a database and its stored data. The database is a stored program component, which is executed by the CPU; the stored program component portion configuring the CPU to process the stored data. The database may be a conventional, fault tolerant, relational, scalable, secure database such as Oracle or Sybase. Relational databases are an extension of a flat file. Relational databases consist of a series of related tables. The tables are interconnected via a key field. Use of the key field allows the combination of the tables by indexing against the key field; i.e., the key fields act as dimensional pivot points for combining information from various tables. Relationships generally identify links maintained between tables by matching primary keys. Primary keys represent fields that uniquely identify the rows of a table in a relational database. More precisely, they uniquely identify rows of a table on the "one" side of a one-to-many relationship. [00116] Alternatively, the B-INDEX database may be implemented using various standard data-structures, such as an array, hash, (linked) list, struct, structured text file (e.g., XML), table, and/or the like. Such data-structures may be stored in memory and/or in (structured) files. In another alternative, an object-oriented database may be used, such as Frontier, ObjectStore, Poet, Zope, and/or the like. Object databases can include a number of object collections that are grouped and/or linked together by common attributes; they may be related to other object collections by some common attributes. Object-oriented databases perform similarly to relational databases with the exception that objects are not just pieces of data but may have other types of capabilities encapsulated within a given object. If the B-INDEX database is implemented as a data- structure, the use of the B-INDEX database 619 may be integrated into another component such as the B-INDEX component 635. Also, the database may be implemented as a mix of data structures, objects, and relational structures. Databases may be consolidated and/or distributed in countless variations through standard data processing techniques. Portions of databases, e.g., tables, may be exported and/or imported and thus decentralized and/or integrated. [00117] In one embodiment, the database component 619 includes several tables 6i9a-l. A user (client) table 619a includes fields such as, but not limited to: a UserlD, UserName, UserAddress, UserPassword, UserProject, UserClientID, UserBrand, UserCategory, UserKeyWords, UserCompetitorlD, and/or the like. The user table may support and/or track multiple entity accounts on a B-INDEX. A hardware table 619b includes fields such as, but not limited to: HdID, HdName, HdProtocol, HdAddress, HdManufacture, HdPortID, HdComponentList, and/or the like. A web visits table 619c includes fields such as, but not limited to: WebVisitsID, WebVisitsType, Web Vistis Stat, WebVisitsClientID, WebVisitsTime, WebVisitsBrandlndex, and/or the like. A Google Insights table 6i9d includes fields such as, but not limited to: ReportID, ReportTime, UserlD, CompetitorlD, SearchTerm, RelatedTerm, SearchTimes, SearchSubsequentActivity, and/or the like. A social media table 6i9e includes fields such as, but not limited to: SocialMediaType, SocialMediaName, SocialMediaUserlD, SocialMediaPage, SocialMediaMentionTerm, SocialMediaMentionNames, SocialMediaMentionTimes, SocialMediaMentionSentiment, and/or the like. A competitor 6i9f includes fields such as, but not limited to: CompetitorlD, CompetitorName, CompetitorCategory, CompetitorKeyTerms, CompetitorURL, CompetitorAddress, and/or the like. A new mentions databases 6i9g includes fields such as, but not limited to: NewsID, NewsType, NewsStat, NewsClientID, NewsTime, NewsBrandlndex, and/or the like. A blog mentions databases 619I1 includes fields such as, but not limited to: blogID, blogType, blogStat, blogClientID, blogTime, blogBrandlndex, and/or the like. A new mentions databases 6i9g includes fields such as, but not limited to: BounceRatelD, BounceType, BounceStat, BounceClientID, BounceTime, BounceBrandlndex, and/or the like. A brand index table 6i9j includes fields such as, but not limited to: BrandlndexID, BrandlndexTime, BrandlndexType, BrandlndexPlot, BrandlndexClientID, BrandlndexAd, BrandlndexMedia, BrandlndexPlan, and/or the like. An activity table 619k includes fields such as, but not limited to: UserlD, CompetitorlD, ActivityType, ActivitySource, ActivityTime, ActivityCount, and/or the like. An analytics table 619I includes fields such as, but not limited to: UserlD, ActivitylD, AveragePageViews, ActivityShare, Activity GrowthRate, Activity Min, ActivityMax, and/or the like. [00118 ] In one embodiment, the B-INDEX database may interact with other database systems. For example, employing a distributed database system, queries and data access by search B-INDEX component may treat the combination of the B-INDEX database, an integrated data security layer database as a single database entity. [00119 ] In one embodiment, user programs may contain various user interface primitives, which may serve to update the B-INDEX. Also, various accounts may require custom database tables depending upon the environments and the types of clients the B- INDEX may need to serve. It should be noted that any unique fields may be designated as a key field throughout. In an alternative embodiment, these tables have been decentralized into their own databases and their respective database controllers (i.e., individual database controllers for each of the above tables). Employing standard data processing techniques, one may further distribute the databases over several computer systemizations and/or storage devices. Similarly, configurations of the decentralized database controllers may be varied by consolidating and/or distributing the various database components 6i9a-l. The B-INDEX may be configured to keep track of various settings, inputs, and parameters via database controllers. [00120] The B-INDEX database may communicate to and/or with other components in a component collection, including itself, and/or facilities of the like. Most frequently, the B-INDEX database communicates with the B-INDEX component, other program components, and/or the like. The database may contain, retain, and provide information regarding other nodes and data. The B- INDEXs

[00121] The B-INDEX component 635 is a stored program component that is executed by a CPU. In one embodiment, the B-INDEX component incorporates any and/or all combinations of the aspects of the B-INDEX that was discussed in the previous figures. As such, the B-INDEX affects accessing, obtaining and the provision of information, services, transactions, and/or the like across various communications networks. [00122] The B-INDEX transforms social media mentions, web visits, Google Insights search analytics inputs data via B-INDEX components data loading component 1 641, data reduction component 642, competitor-based index generation component 643,

2 competitor-independent index generation component 644, data presentation

3 component 645, and/or the like into brand index value and comparative graphic

4 plots/charts outputs.

5 [00123] The B-INDEX component enabling access of information between nodes

6 may be developed by employing standard development tools and languages such as, but

7 not limited to: Apache components, Assembly, ActiveX, binary executables, (ANSI)

8 (Objective-) C (++), C# and/or .NET, database adapters, CGI scripts, Java, JavaScript,

9 mapping tools, procedural and object oriented development tools, PERL, PHP, Python,0 shell scripts, SQL commands, web application server extensions, web development1 environments and libraries (e.g., Microsoft's ActiveX; Adobe AIR, FLEX & FLASH;2 AJAX; (D)HTML; Dojo, Java; JavaScript; jQuery(UI); MooTools; Prototype;3 script.aculo.us; Simple Object Access Protocol (SOAP); SWFObject; Yahoo! User4 Interface; and/or the like), WebObjects, and/or the like. In one embodiment, the B-5 INDEX server employs a cryptographic server to encrypt and decrypt communications.6 The B-INDEX component may communicate to and/or with other components in a7 component collection, including itself, and/or facilities of the like. Most frequently, the8 B-INDEX component communicates with the B-INDEX database, operating systems,9 other program components, and/or the like. The B-INDEX may contain, communicate,0 generate, obtain, and/or provide program component, system, user, and/or data1 communications, requests, and/or responses. 2 Distributed B- INDEXs

3 [00124] The structure and/or operation of any of the B-INDEX node controller components may be combined, consolidated, and/or distributed in any number of ways to facilitate development and/or deployment. Similarly, the component collection may be combined in any number of ways to facilitate deployment and/or development. To accomplish this, one may integrate the components into a common code base or in a facility that can dynamically load the components on demand in an integrated fashion. [00125] The component collection may be consolidated and/or distributed in countless variations through standard data processing and/or development techniques. Multiple instances of any one of the program components in the program component collection may be instantiated on a single node, and/or across numerous nodes to improve performance through load-balancing and/or data-processing techniques. Furthermore, single instances may also be distributed across multiple controllers and/or storage devices; e.g., databases. All program component instances and controllers working in concert may do so through standard data processing communication techniques. [00126] The configuration of the B-INDEX controller will depend on the context of system deployment. Factors such as, but not limited to, the budget, capacity, location, and/or use of the underlying hardware resources may affect deployment requirements and configuration. Regardless of if the configuration results in more consolidated and/or integrated program components, results in a more distributed series of program components, and/or results in some combination between a consolidated and distributed configuration, data may be communicated, obtained, and/or provided. Instances of components consolidated into a common code base from the program component collection may communicate, obtain, and/or provide data. This may be accomplished through intra-application data processing communication techniques such as, but not limited to: data referencing (e.g., pointers), internal messaging, object instance variable communication, shared memory space, variable passing, and/or the like. [00127] If component collection components are discrete, separate, and/or external to one another, then communicating, obtaining, and/or providing data with and/or to other component components may be accomplished through inter-application data processing communication techniques such as, but not limited to: Application Program Interfaces (API) information passage; (distributed) Component Object Model ((D)COM), (Distributed) Object Linking and Embedding ((D)OLE), and/or the like), Common Object Request Broker Architecture (CORBA), Jini local and remote application program interfaces, JavaScript Object Notation (JSON), Remote Method Invocation (RMI), SOAP, process pipes, shared files, and/or the like. Messages sent between discrete component components for inter-application communication or within memory spaces of a singular component for intra-application communication may be facilitated through the creation and parsing of a grammar. A grammar may be developed by using development tools such as lex, yacc, XML, and/or the like, which allow for grammar generation and parsing capabilities, which in turn may form the basis of communication messages within and between components. [00128] For example, a grammar may be arranged to recognize the tokens of an HTTP post command, e.g.: w3c -post http://... Valuel

[00129] where Valuei is discerned as being a parameter because "http://" is part of the grammar syntax, and what follows is considered part of the post value. Similarly, with such a grammar, a variable "Valuei" may be inserted into an "http://" post command and then sent. The grammar syntax itself may be presented as structured data that is interpreted and/or otherwise used to generate the parsing mechanism (e.g., a syntax description text file as processed by lex, yacc, etc.). Also, once the parsing mechanism is generated and/or instantiated, it itself may process and/or parse structured data such as, but not limited to: character (e.g., tab) delineated text, HTML, structured text streams, XML, and/or the like structured data. In another embodiment, inter-application data processing protocols themselves may have integrated and/or readily available parsers (e.g., JSON, SOAP, and/or like parsers) that may be employed to parse (e.g., communications) data. Further, the parsing grammar may be used beyond message parsing, but may also be used to parse: databases, data collections, data stores, structured data, and/or the like. Again, the desired configuration will depend upon the context, environment, and requirements of system deployment. [00130] For example, in some implementations, the B-INDEX controller may be executing a PHP script implementing a Secure Sockets Layer ("SSL") socket server via the information sherver, which listens to incoming communications on a server port to which a client may send data, e.g., data encoded in JSON format. Upon identifying an incoming communication, the PHP script may read the incoming message from the client device, parse the received JSON-encoded text data to extract information from the JSON-encoded text data into PHP script variables, and store the data (e.g., client identifying information, etc.) and/or extracted information in a relational database accessible using the Structured Query Language ("SQL"). An exemplary listing, written substantially in the form of PHP/SQL commands, to accept JSON-encoded input data from a client device via a SSL connection, parse the data to extract variables, and store the data to a database, is provided below: <?PHP

header (' Content-Type : text/plain');

// set ip address and port to listen to for incoming data

$address = Ί92.168.0.100' ;

$port = 255;

// create a server-side SSL socket, listen for/accept incoming communication $sock = socket_create (AF_INET, SOCK_STREAM, 0) ;

socket_bind ( $sock, $address, $port) or die ( 'Could not bind to address');

socket_listen ($sock) ;

$client = socket_accept ($sock) ;

// read input data from client device in 1024 byte blocks until end of message do {

$input = "";

$input = socket_read ($client, 1024);

$data . = $input;

} while($input ! = "");

// parse data to extract variables

$obj = j son_decode ( $data, true);

// store input data in a database

mysql connect ( "201.408.185.132 ", $DBserver, $password) ; // access database server mysql_select ( " CLIENT_DB . SQL" ) ; // select database to append

mysql_query ("INSERT INTO UserTable (transmission)

VALUES ($data)"); // add data to UserTable table in a CLIENT database

mysql close ( "CLIENT DB.SQL"); // close connection to database

? >

Also, the following resources may be used to provide example embodiments regarding SOAP parser implementation: http : //www . xav . com/perl/ site/lib/ SOAP/Parser . html

http : //publib .boulder . ibm. com/infocenter/tivihelp/v2rl/index . j sp?topic=/com. ibm . IBMDI . doc/referenceguide295. htm

and other parser implementations: http : //publib .boulder . ibm. com/infocenter/tivihelp/v2rl/index . j sp?topic=/com. ibm . IBMDI . doc/referenceguide259. htm

all of which are hereby expressly incorporated by reference. [00131] In order to address various issues and advance the art, the entirety of this application for BRAND INDEX EVALUATION APPARATUSES, METHODS AND SYSTEMS (including the Cover Page, Title, Headings, Field, Background, Summary, Brief Description of the Drawings, Detailed Description, Claims, Abstract, Figures, Appendices, and otherwise) shows, by way of illustration, various embodiments in which the claimed innovations may be practiced. The advantages and features of the application are of a representative sample of embodiments only, and are not exhaustive and/or exclusive. They are presented only to assist in understanding and teach the claimed principles. It should be understood that they are not representative of all claimed innovations. As such, certain aspects of the disclosure have not been discussed herein. That alternate embodiments may not have been presented for a specific portion of the innovations or that further undescribed alternate embodiments may be available for a portion is not to be considered a disclaimer of those alternate embodiments. It will be appreciated that many of those undescribed embodiments incorporate the same principles of the innovations and others are equivalent. Thus, it is to be understood that other embodiments may be utilized and functional, logical, operational, organizational, structural and/or topological modifications may be made without departing from the scope and/or spirit of the disclosure. As such, all examples and/or embodiments are deemed to be non-limiting throughout this disclosure. Also, no inference should be drawn regarding those embodiments discussed herein relative to those not discussed herein other than it is as such for purposes of reducing space and repetition. For instance, it is to be understood that the logical and/or topological structure of any combination of any program components (a component collection), other components and/or any present feature sets as described in the figures and/or throughout are not limited to a fixed operating order and/or arrangement, but rather, any disclosed order is exemplary and all equivalents, regardless of order, are contemplated by the disclosure. Furthermore, it is to be understood that such features are not limited to serial execution, but rather, any number of threads, processes, services, servers, and/or the like that may execute asynchronously, concurrently, in parallel, simultaneously, synchronously, and/or the like are contemplated by the disclosure. As such, some of these features may be mutually contradictory, in that they cannot be simultaneously present in a single embodiment. Similarly, some features are applicable to one aspect of the innovations, and inapplicable to others. In addition, the disclosure includes other innovations not presently claimed. Applicant reserves all rights in those presently unclaimed innovations including the right to claim such innovations, file additional applications, continuations, continuations in part, divisions, and/or the like thereof. As such, it should be understood that advantages, embodiments, examples, functional, features, logical, operational, organizational, structural, topological, and/or other aspects of the disclosure are not to be considered limitations on the disclosure as defined by the claims or limitations on equivalents to the claims. It is to be understood that, depending on the particular needs and/or characteristics of a B-INDEX individual and/or enterprise user, database configuration and/or relational model, data type, data transmission and/or network framework, syntax structure, and/or the like, various embodiments of the B- INDEX, may be implemented that enable a great deal of flexibility and customization, For example, aspects of the B-INDEX may be adapted for market campaign analysis. While various embodiments and discussions of the B-INDEX have been directed to evaluating brand value, however, it is to be understood that the embodiments described herein may be readily configured and/or customized for a wide variety of other applications and/or implementations.

Claims

What is claimed is:
l. A low-latency and data-transformative brand index evaluating processor- implemented method, comprising:
receiving a brand index evaluation request from a user interface;
obtaining a low-latency and low network transaction consumer activity data batch related to a brand product and a competitor brand at a low-latency data- processing server;
calculating shares of the brand product and the competitor brand in each data category of the obtained consumer activity data batch;
transforming the calculated shares associated the brand product into a single brand index data indicator based on a statistical procedure;
transforming the calculated shares associated with the competitor brand into a single competitor brand index data indicator based on the statistical procedure;
calculating brand index scores of each of the brand product and the competitor brand based on the single brand index data indicator and the single competitor brand index data indicator;
comparing the calculated brand index scores between the brand product and the competitor; and
providing a data presentation output including the brand index score comparison via a user interface. 2. The method of claim l, wherein the brand index evaluation request is submitted by a client.
3. The method of claim 1, wherein the user interface comprises a web based application instantiated on a client device. 4. The method of claim 1, wherein the brand index evaluation request comprises an identification of a client profile,
wherein the client profile comprises any of a client name, a client's business category, and a client's business key terms. 5. The method of claim 1, wherein the brand index evaluation request further comprises a list of client specified competitor names. 6. The method of claim 1, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's homepage. 7. The method of claim 1, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's advertising page. 8. The method of claim 1, wherein the consumer activity data batch comprises social media mentions. 9. The method of claim 1, wherein the consumer activity data batch comprises Google search times.
10. The method of claim l, wherein the consumer activity data batch comprises new sign-ups, new orders with the brand product. 11. The method of claim l, wherein the consumer activity data batch is obtained from a third party data vendor. 12. The method of claim l, wherein the consumer activity data batch is received in a CSV data file. 13. The method of claim 1, wherein the consumer activity data batch is loaded into a SAS compliant data format at the low-latency data-processing server. 14. The method of claim 1, wherein the competitor brand is automatically determined by the server via analysis of a brand product's category. 15. The method of claim 1, wherein the calculating shares of the brand product and the competitor brand comprises transforming a raw figure of a data category into a data percentage among the brand product and the competitor brand,
wherein the calculated shares of the brand product and the competitor brand of one data category sum up to 100%. 16. The method of claim 1, wherein the data category comprises any of web visits, social media mentions, google search times, and blog mentions.
17. The method of claim 1, wherein the statistical procedure comprises principal component analysis. 18. The method of claim 1, wherein the statistical procedure comprises principal component analysis comprises factor analysis. 19. The method of claim 1, wherein the calculated shares associated with the brand serve as correlated variables, and are combined into the single brand index data indicator as a principal component. 20. The method of claim 1, wherein calculating brand index scores of each of the brand product and the competitor brand comprises scaling the single brand index data indicator and the single competitor brand index data indicator into a 0-100 interval. 21. The method of claim 1, wherein the comparison of the calculated brand index scores between the brand product and the competitor provides heuristics of consumer impression and market performance of the brand product versus the competitor brand. 22. The method of claim 1, wherein the data presentation output comprises any of tables, charts, and plots. 23. The method of claim 1, wherein the data presentation output further comprises a comparison of a data category associated with the brand product and the I competitor brand over a period of time.
2
3 24. The method of claim 1, further comprising performing data reduction over
4 the calculated shares associated with the brand product and the competitor brand.
5
6 25. The method of claim 24, further comprising determining whether data
7 reduction is required for each data category.
8
9 26. The method of claim 24, further comprising:
10 performing multicolinearity testing to determine viability of each data variable
I I under each data category; and
12 removing the data variable when the viability of the data variable is undesirable.
13
14 27. The method of claim 24, further comprising:
15 generating a correlation matrix of the data variables under each data category.
16
17 28. The method of claim 27, further comprising:
18 determining at least one principal component based on the correlation matrix;
19 and
20 combining correlated data variables into the one principal component.
21
22 29. The method of claim 28, further comprising:
23 using the principal component associated with the data category for brand index
24 calculation.
30. The method of claim 1, further comprising:
determining a more determinative data factor that contributes to the brand index score based on a comparison of time-dependent changes of each data category and the brand index score associated with the brand product. 31. A low-latency and data-transformative brand index evaluating system, comprising:
a memory;
a processor disposed in communication with said memory, and configured to issue a plurality of processing instructions stored in the memory, wherein the processor issues instructions to:
receive a brand index evaluation request from a user interface; obtain a low-latency and low network transaction consumer activity data batch related to a brand product and a competitor brand at a low-latency data- processing server;
calculate shares of the brand product and the competitor brand in each data category of the obtained consumer activity data batch;
transform the calculated shares associated the brand product into a single brand index data indicator based on a statistical procedure;
transform the calculated shares associated with the competitor brand into a single competitor brand index data indicator based on the statistical procedure;
calculate brand index scores of each of the brand product and the competitor brand based on the single brand index data indicator and the single competitor brand index data indicator;
compare the calculated brand index scores between the brand product and the competitor; and
provide a data presentation output including the brand index score comparison via a user interface. 32. The system of claim 31, wherein the brand index evaluation request is submitted by a client. 33. The system of claim 31, wherein the user interface comprises a web based application instantiated on a client device. 34. The system of claim 31, wherein the brand index evaluation request comprises an identification of a client profile,
wherein the client profile comprises any of a client name, a client's business category, and a client's business key terms. 35. The system of claim 31, wherein the brand index evaluation request further comprises a list of client specified competitor names. 36. The system of claim 31, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's homepage. 37. The system of claim 31, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's advertising page. 38. The system of claim 31, wherein the consumer activity data batch comprises social media mentions. 39. The system of claim 31, wherein the consumer activity data batch comprises Google search times. 40. The system of claim 31, wherein the consumer activity data batch comprises new sign-ups, new orders with the brand product. 41. The system of claim 31, wherein the consumer activity data batch is obtained from a third party data vendor. 42. The system of claim 31, wherein the consumer activity data batch is received in a CSV data file. 43. The system of claim 31, wherein the consumer activity data batch is loaded into a SAS compliant data format at the low-latency data-processing server. 44. The system of claim 31, wherein the competitor brand is automatically determined by the server via analysis of a brand product's category. 45. The system of claim 31, wherein the calculating shares of the brand product and the competitor brand comprises transforming a raw figure of a data category into a data percentage among the brand product and the competitor brand, wherein the calculated shares of the brand product and the competitor brand of one data category sum up to ioo . 46. The system of claim 31, wherein the data category comprises any of web visits, social media mentions, Google search times, and blog mentions. 47. The system of claim 31, wherein the statistical procedure comprises principal component analysis. 48. The system of claim 31, wherein the statistical procedure comprises principal component analysis comprises factor analysis. 49. The system of claim 31, wherein the calculated shares associated with the brand serve as correlated variables, and are combined into the single brand index data indicator as a principal component. 50. The system of claim 31, wherein calculating brand index scores of each of the brand product and the competitor brand comprises scaling the single brand index data indicator and the single competitor brand index data indicator into a 0-100 interval. 51. The system of claim 31, wherein the comparison of the calculated brand index scores between the brand product and the competitor provides heuristics of consumer impression and market performance of the brand product versus the competitor brand. 52. The system of claim 31, wherein the data presentation output comprises any of tables, charts, and plots. 53. The system of claim 31, wherein the data presentation output further comprises a comparison of a data category associated with the brand product and the competitor brand over a period of time. 54. The system of claim 31, wherein the processor further issues instructions to perform data reduction over the calculated shares associated with the brand product and the competitor brand. 55. The system of claim 54, wherein the processor further issues instructions to determine whether data reduction is required for each data category. 56. The system of claim 54, wherein the processor further issues instructions to:
performing multicolinearity testing to determine viability of each data variable under each data category; and
removing the data variable when the viability of the data variable is undesirable. 57. The system of claim 54, wherein the processor further issues instructions to:
generating a correlation matrix of the data variables under each data category. 58. The system of claim 57, wherein the processor further issues instructions to:
determining at least one principal component based on the correlation matrix; and
combining correlated data variables into the one principal component. 59. The system of claim 58, wherein the processor further issues instructions to:
using the principal component associated with the data category for brand index calculation. 60. The system of claim 31, wherein the processor further issues instructions to:
determining a more determinative data factor that contributes to the brand index score based on a comparison of time-dependent changes of each data category and the brand index score associated with the brand product. 61. A low-latency and data-transformative brand index evaluating processor- readable storage medium storing processor-executable instructions to:
receive a brand index evaluation request from a user interface; obtain a low-latency and low network transaction consumer activity data batch related to a brand product and a competitor brand at a low-latency data- processing server;
calculate shares of the brand product and the competitor brand in each data category of the obtained consumer activity data batch;
transform the calculated shares associated the brand product into a single brand index data indicator based on a statistical procedure;
transform the calculated shares associated with the competitor brand into a single competitor brand index data indicator based on the statistical procedure;
calculate brand index scores of each of the brand product and the competitor brand based on the single brand index data indicator and the single competitor brand index data indicator;
compare the calculated brand index scores between the brand product and the competitor; and
provide a data presentation output including the brand index score comparison via a user interface. 62. The medium of claim 61, wherein the brand index evaluation request is submitted by a client. 63. The medium of claim 61, wherein the user interface comprises a web based application instantiated on a client device. 64. The medium of claim 61, wherein the brand index evaluation request comprises an identification of a client profile, wherein the client profile comprises any of a client name, a client's business category, and a client's business key terms. 65. The medium of claim 61, wherein the brand index evaluation request further comprises a list of client specified competitor names. 66. The medium of claim 61, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's homepage. 67. The medium of claim 61, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's advertising page. 68. The medium of claim 61, wherein the consumer activity data batch comprises social media mentions. 69. The medium of claim 61, wherein the consumer activity data batch comprises Google search times. 70. The medium of claim 61, wherein the consumer activity data batch comprises new sign-ups, new orders with the brand product. 71. The medium of claim 61, wherein the consumer activity data batch is obtained from a third party data vendor.
72. The medium of claim 61, wherein the consumer activity data batch is received in a CSV data file. 73. The medium of claim 61, wherein the consumer activity data batch is loaded into a SAS compliant data format at the low-latency data-processing server. 74. The medium of claim 61, wherein the competitor brand is automatically determined by the server via analysis of a brand product's category. 75. The medium of claim 61, wherein the calculating shares of the brand product and the competitor brand comprises transforming a raw figure of a data category into a data percentage among the brand product and the competitor brand, wherein the calculated shares of the brand product and the competitor brand of one data category sum up to 100%. 76. The medium of claim 61, wherein the data category comprises any of web visits, social media mentions, Google search times, and blog mentions. 77. The medium of claim 61, wherein the statistical procedure comprises principal component analysis. 78. The medium of claim 61, wherein the statistical procedure comprises principal component analysis comprises factor analysis.
79. The medium of claim 61, wherein the calculated shares associated with the brand serve as correlated variables, and are combined into the single brand index data indicator as a principal component. 80. The medium of claim 61, wherein calculating brand index scores of each of the brand product and the competitor brand comprises scaling the single brand index data indicator and the single competitor brand index data indicator into a 0-100 interval. 81. The medium of claim 61, wherein the comparison of the calculated brand index scores between the brand product and the competitor provides heuristics of consumer impression and market performance of the brand product versus the competitor brand. 82. The medium of claim 61, wherein the data presentation output comprises any of tables, charts, and plots. 83. The medium of claim 61, wherein the data presentation output further comprises a comparison of a data category associated with the brand product and the competitor brand over a period of time. 84. The medium of claim 61, further storing processor-executable instructions to perform data reduction over the calculated shares associated with the brand product and the competitor brand.
85. The medium of claim 84, further storing processor-executable instructions to determine whether data reduction is required for each data category. 86. The medium of claim 84, further storing processor-executable instructions to:
performing multicolinearity testing to determine viability of each data variable under each data category; and
removing the data variable when the viability of the data variable is undesirable. 87. The medium of claim 84, further storing processor-executable instructions to:
generating a correlation matrix of the data variables under each data category. 88. The medium of claim 87, further storing processor-executable instructions to:
determining at least one principal component based on the correlation matrix; and
combining correlated data variables into the one principal component. 89. The medium of claim 88, further storing processor-executable instructions to:
using the principal component associated with the data category for brand index calculation.
90. The medium of claim 61, further storing processor-executable instructions to:
determining a more determinative data factor that contributes to the brand index score based on a comparison of time-dependent changes of each data category and the brand index score associated with the brand product. 91. A low-latency and data-transformative brand index evaluating processor- implemented method, comprising:
receiving a brand index evaluation request from a user interface;
obtaining a low-latency and low network transaction consumer activity data batch related to a brand product at a low-latency data-processing server;
transforming the obtained consumer activity data batch associated the brand product into a single brand index data indicator based on a statistical procedure;
calculating a brand index score of the brand product based on the single brand index data indicator;
comparing a plurality of the calculated brand index scores of the brand product over a period of time; and
providing a data presentation output including the brand index score comparison via a user interface. 92. The method of claim 91, wherein the brand index evaluation request is submitted by a client. 93. The method of claim 91, wherein the user interface comprises a web based I application instantiated on a client device.
2
3 94. The method of claim 1, wherein the brand index evaluation request
4 comprises an identification of a client profile,
5 wherein the client profile comprises any of a client name, a client's
6 business category, and a client's business key terms.
7
8 95. The method of claim 1, wherein the brand index evaluation request
9 indicates the requested brand index is competitor independent.
10
I I 96. The method of claim 91, wherein the consumer activity data batch 12 comprises any of web visits, page view of a brand product's homepage.
13
14 97. The method of claim 91, wherein the consumer activity data batch
15 comprises any of web visits, page view of a brand product's advertising page.
16
17 98. The method of claim 91, wherein the consumer activity data batch
18 comprises social media mentions.
19
20 99. The method of claim 91, wherein the consumer activity data batch
21 comprises Google search times.
22
23 100. The method of claim 91, wherein the consumer activity data batch
24 comprises new sign-ups, new orders with the brand product. loi. The method of claim 91, wherein the consumer activity data batch is obtained from a third party data vendor. 102. The method of claim 91, wherein the consumer activity data batch is received in a CSV data file. 103. The method of claim 91, wherein the consumer activity data batch is loaded into a SAS compliant data format at the low-latency data-processing server. 104. The method of claim 91, wherein the consumer activity data batch further comprises sales data associated with the brand product. 105. The method of claim 91, wherein the consumer activity data batch is independent of competitor data. 106. The method of claim 91, wherein the data category comprises any of web visits, social media mentions, Google search times, and blog mentions. 107. The method of claim 91, wherein the statistical procedure comprises principal component analysis. 108. The method of claim 91, wherein the statistical procedure comprises principal component analysis comprises factor analysis.
109. The method of claim 91, wherein the obtained consumer activity data batch serve as correlated variables, and are combined into the single brand index data indicator as a principal component. 110. The method of claim 91, wherein calculating brand index scores of the brand product comprises scaling the single brand index data indicator into a 0-50 interval. 111. The method of claim 91, wherein the comparison of the calculated brand index scores over the period of time provides heuristics of consumer impression and market performance over time. 112. The method of claim 91, wherein the data presentation output comprises any of tables, charts, and plots. 113. The method of claim 91, wherein the data presentation output further comprises a plot of a data category associated with the brand product over a period of time. 114. The method of claim 91, further comprising performing data reduction over the obtained consumer activity data batch associated with the brand product and the competitor brand.
115. The method of claim 114, further comprising determining whether data reduction is required for each data category. 116. The method of claim 114, further comprising:
performing multicolinearity testing to determine viability of each data variable under each data category; and
removing the data variable when the viability of the data variable is undesirable. 117. The method of claim 114, further comprising:
generating a correlation matrix of the data variables under each data category. 118. The method of claim 117, further comprising:
determining at least one principal component based on the correlation matrix; and
combining correlated data variables into the one principal component. 119. The method of claim 118, further comprising:
using the principal component associated with the data category for brand index calculation. 120. The method of claim 91, further comprising:
determining a more determinative data factor that contributes to the brand index score based on a comparison of time-dependent changes of each data category and the brand index score associated with the brand product.
121. A low-latency and data-transformative brand index evaluating system, comprising:
a memory;
a processor disposed in communication with said memory, and configured to issue a plurality of processing instructions stored in the memory, wherein the processor issues instructions to:
receive a brand index evaluation request from a user interface; obtain a low-latency and low network transaction consumer activity data batch related to a brand product;
transform the obtained consumer activity data batch associated the brand product into a single brand index data indicator based on a statistical procedure;
calculate a brand index score of the brand product based on the single brand index data indicator;
compare a plurality of the calculated brand index scores of the brand product over a period of time; and
provide a data presentation output including the brand index score comparison via a user interface. 122. The system of claim 121, wherein the brand index evaluation request is submitted by a client. 123. The system of claim 121, wherein the user interface comprises a web based application instantiated on a client device.
124. The system of claim 121, wherein the brand index evaluation request comprises an identification of a client profile,
wherein the client profile comprises any of a client name, a client's business category, and a client's business key terms. 125. The system of claim 121, wherein the brand index evaluation request indicates the requested brand index is competitor independent. 126. The system of claim 121, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's homepage. 127. The system of claim 121, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's advertising page. 128. The system of claim 121, wherein the consumer activity data batch comprises social media mentions. 129. The system of claim 121, wherein the consumer activity data batch comprises Google search times. 130. The system of claim 121, wherein the consumer activity data batch comprises new sign-ups, new orders with the brand product.
131. The system of claim 121, wherein the consumer activity data batch is obtained from a third party data vendor. 132. The system of claim 121, wherein the consumer activity data batch is received in a CSV data file. 133. The system of claim 121, wherein the consumer activity data batch is loaded into a SAS compliant data format at the low-latency data-processing server. 134. The system of claim 121, wherein the consumer activity data batch further comprises sales data associated with the brand product. 135. The system of claim 121, wherein the consumer activity data batch is independent of competitor data. 136. The system of claim 121, wherein the data category comprises any of web visits, social media mentions, Google search times, and blog mentions. 137. The system of claim 121, wherein the statistical procedure comprises principal component analysis. 138. The system of claim 121, wherein the statistical procedure comprises principal component analysis comprises factor analysis.
139. The system of claim 121, wherein the obtained consumer activity data batch serve as correlated variables, and are combined into the single brand index data indicator as a principal component. 140. The system of claim 121, wherein calculating brand index scores of the brand product comprises scaling the single brand index data indicator into a 0-50 interval. 141. The system of claim 121, wherein the comparison of the calculated brand index scores between the brand product provides heuristics of consumer impression and market performance of the brand product. 142. The system of claim 121, wherein the data presentation output comprises any of tables, charts, and plots. 143. The system of claim 121, wherein the data presentation output further comprises a plot of a data category associated with the brand product over a period of time. 144. The system of claim 121, wherein the processor further issues instructions to perform data reduction over the obtained consumer activity data batch associated with the brand product. 145. The system of claim 144, wherein the processor further issues instructions I to determine whether data reduction is required for each data category.
2
3 146. The system of claim 144, wherein the processor further issues instructions
4 to:
5 performing multicolinearity testing to determine viability of each data variable
6 under each data category; and
7 removing the data variable when the viability of the data variable is undesirable.
8
9 147. The system of claim 144, wherein the processor further issues instructions
10 to:
I I generating a correlation matrix of the data variables under each data category.
12
13 148. The system of claim 147, wherein the processor further issues instructions
14 to:
15 determining at least one principal component based on the correlation matrix;
16 and
17 combining correlated data variables into the one principal component.
18
19 149. The system of claim 148, wherein the processor further issues instructions
20 to:
21 using the principal component associated with the data category for brand index
22 calculation.
23
24 150. The system of claim 121, wherein the processor further issues instructions to:
determining a more determinative data factor that contributes to the brand index score based on a comparison of time-dependent changes of each data category and the brand index score associated with the brand product. 151. A low-latency and data-transformative brand index evaluating processor- readable storage medium storing processor-executable instructions to:
receive a brand index evaluation request from a user interface; obtain a low-latency and low network transaction consumer activity data batch related to a brand product;
transform the obtained consumer activity data batch associated the brand product into a single brand index data indicator based on a statistical procedure;
calculate a brand index score of the brand product based on the single brand index data indicator;
compare a plurality of the calculated brand index scores of the brand product over a period of time; and
provide a data presentation output including the brand index score comparison via a user interface. 152. The medium of claim 151, wherein the brand index evaluation request is submitted by a client. 153. The medium of claim 151, wherein the user interface comprises a web based application instantiated on a client device.
154. The medium of claim 151, wherein the brand index evaluation request comprises an identification of a client profile,
wherein the client profile comprises any of a client name, a client's business category, and a client's business key terms. 155. The medium of claim 151, wherein the brand index evaluation request indicates the requested brand index is competitor independent. 156. The medium of claim 151, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's homepage. 157. The medium of claim 151, wherein the consumer activity data batch comprises any of web visits, page view of a brand product's advertising page. 158. The medium of claim 151, wherein the consumer activity data batch comprises social media mentions. 159. The medium of claim 151, wherein the consumer activity data batch comprises Google search times. 160. The medium of claim 151, wherein the consumer activity data batch comprises new sign-ups, new orders with the brand product.
161. The medium of claim 151, wherein the consumer activity data batch is obtained from a third party data vendor. 162. The medium of claim 151, wherein the consumer activity data batch is received in a CSV data file. 163. The medium of claim 151, wherein the consumer activity data batch is loaded into a SAS compliant data format at the low-latency data-processing server. 164. The medium of claim 151, wherein the consumer activity data batch further comprises sales data associated with the brand product. 165. The medium of claim 151, wherein the consumer activity data batch is independent of competitor data. 166. The medium of claim 151, wherein the data category comprises any of web visits, social media mentions, Google search times, and blog mentions. 167. The medium of claim 151, wherein the statistical procedure comprises principal component analysis. 168. The medium of claim 151, wherein the statistical procedure comprises principal component analysis comprises factor analysis.
169. The medium of claim 151, wherein the consumer activity data batch associated with the brand serve as correlated variables, and are combined into the single brand index data indicator as a principal component. 170. The medium of claim 151, wherein calculating brand index scores of the brand product comprises scaling the single brand index data indicator into a 0-50 interval. 171. The medium of claim 151, wherein the comparison of the calculated brand index scores between the brand product provides heuristics of consumer impression and market performance of the brand product. 172. The medium of claim 151, wherein the data presentation output comprises any of tables, charts, and plots. 173. The medium of claim 151, wherein the data presentation output further comprises a plot of a data category associated with the brand product over a period of time. 174. The medium of claim 151, further storing processor-executable instructions to perform data reduction over the consumer activity data batch associated with the brand product. 175. The medium of claim 174, further storing processor-executable I instructions to determine whether data reduction is required for each data category.
2
3 176. The medium of claim 174, further storing processor-executable
4 instructions to:
5 performing multicolinearity testing to determine viability of each data variable
6 under each data category; and
7 removing the data variable when the viability of the data variable is undesirable.
8
9 177. The medium of claim 174, further storing processor-executable
10 instructions to:
I I generating a correlation matrix of the data variables under each data category.
12
13 178. The medium of claim 177, further storing processor-executable
14 instructions to:
15 determining at least one principal component based on the correlation matrix;
16 and
17 combining correlated data variables into the one principal component.
18
19 179. The medium of claim 178, further storing processor-executable
20 instructions to:
21 using the principal component associated with the data category for brand index
22 calculation.
23
24 180. The medium of claim 151, further storing processor-executable instructions to:
determining a more determinative data factor that contributes to the brand index score based on a comparison of time-dependent changes of each data category and the brand index score associated with the brand product.
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