CN101149830A - Computer system for planning and evaluating in-store advertising for a retail entity - Google Patents
Computer system for planning and evaluating in-store advertising for a retail entity Download PDFInfo
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- CN101149830A CN101149830A CNA2007101701831A CN200710170183A CN101149830A CN 101149830 A CN101149830 A CN 101149830A CN A2007101701831 A CNA2007101701831 A CN A2007101701831A CN 200710170183 A CN200710170183 A CN 200710170183A CN 101149830 A CN101149830 A CN 101149830A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0242—Determining effectiveness of advertisements
- G06Q30/0244—Optimization
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0255—Targeted advertisements based on user history
Abstract
A computer system for planning and evaluating advertising for a retail entit y comprising: a computer system including an advertisement publication database and a transaction database, the computer system being configured to perform the steps of: (a) collecting in the advertisement publication database a first set of advertisement publication data for a plurality of featured products published by the retail entity over a first period of time, the advertisement publication data including data taken from a group consisting of data concerning the featured products in the advertisements, data concerning the type of advertisement, data concerning t he term of the advertisement, and data concerning the region of the advertisement; (b) collecting in the transaction database a first set of transaction data for a plurality of transactions conducted by a plurality of consumers purchasing a plurality of products from the retail entity over the first period of time; (c) analyzing the first set of advertising publication data with respect to the first set of transaction data over the first period of time; and (d) classifying t he plurality of featured products into advertising roles based upon the analyzing of the first set of advertising publication data with respect to the first set of transaction data, the plurality of advertising roles including one or more advertising roles take from a group consisting of featured products that attract consumers to a particular part of a retail entity, featured products that promote attracting a mixture of consumers of different consumer classifications to purchase the featured products, featured products that promote a balance of different types of products purchased by a consumer, featured products that promote an overall increase in sales by the retail entity, and featured products that promote a combination of two or more of the above advertising roles.
Description
Background technology
Concerning retail division, plan, evaluation and correction advertising strategy are a kind of lasting challenges.Usually, this advertisement analysis is product or service-specific.This conventional process means pay close attention to which type of product type and/or advertising method is the most attractive to the consumer groups' type on the different population statistical significances.An example of conventional ads analysis is to use interesting data---quantity and type of particular advertisement being represented the client of interest---rather than what have been sold out by the product of advertisement as the result of advertisement.The example that another conventional ads is analyzed uses the special-purpose sales data of product---the difference that specific products is sold when advertising and not advertising.
Being limited in of above-mentioned two kinds of disposal routes, they only use one or two factors to predict the result of a complication system at attempt.The strategy of this one dimension or two dimension is not for example considered the influence of the sale of an other products of retail division being sold by the product of advertisement, the client's that attracts to the influence of retail division's total sales, by retail division quantity and the influence of type and the long-term consequence of these influences.In practice, different retail divisions wish that the success of obtaining is much more based on the sales growth than single product from advertising strategy.Have only when advertising strategy aiming client is attracted in the shop, instructs client to do shopping, aim at the main scope of client's Price Sensitive in the shop, when client is attracted to the most efficient mixing of the product do not showed, feedback client's informativeness and maximum overall profit in advertisement, could maximizes achieving success.
Except scope restriction too tight, as mentioned above, traditional solution other a lot of aspect validity very low.For large-scale interstate retail division, analysis validity in mechanism's scope is also very low, and this is because the client of different geographical zones trends towards having different needs, buy different products, have different shopping place senses and have different price sensitivity.Client's custom also in time and different.For example, client product and product availability that need and that want are usually with changing season.
Summary of the invention
The present invention interacts by the complexity of analyzing between advertisement widely and sales data array, keeps adjusting the ability to the analysis of specific geographical zone, period, product group and/or customers simultaneously.
So first aspect of the present invention provides the method for retail division's plan and evaluate advertisements, comprise step: (a) help by computing machine, be collected in a plurality of first group of ad distribution data that is demonstrated product (featured product) of issuing by retail division in first period, wherein, described ad distribution data comprise data, the data in relevant advertisement time limit and/or the data of relevant advertising area of the data that are demonstrated product in the relevant advertisement, relevant adline; (b), be collected in first group of transaction data of a plurality of transaction of being undertaken by a plurality of clients that buy a plurality of products from retail division in described first period by the help of computing machine; (c), analyze described first group of ad distribution data in described first period with respect to described first group of transaction data by the help of computing machine; And (d) help by computing machine, based on of the analysis of first group of ad distribution data with respect to first group of transaction data, with a plurality of product classifications that are demonstrated is a plurality of advertisement roles, and wherein, a plurality of advertisement roles comprise: the client is attracted to retail division specific part be demonstrated product; Promote the client's of the different client segmentations of attraction mixing to buy the product that is demonstrated that is demonstrated product; Promote the dissimilar products that the client buys equilibrium be demonstrated product; Promote the product that is demonstrated that the sales volume of retail division increases comprehensively; And/or promote above-mentioned advertisement role two or more combinations be demonstrated product.
Second each side of the present invention provides a kind of computerized method, be used to estimate and/or plan the advertisement of retail division, comprise the following steps: (a) help, from the transaction of in first period and second period, carrying out, collect a plurality of clients' transaction data with retail division by computing machine; (b) ad data of at least one product of being showed by advertisement is collected in the help by computing machine, and wherein, described ad data comprises related between the sign that is demonstrated product and described advertisement and described second period at least; (c) help by computing machine, at least compare between first period and second period and estimate the transaction data relevant with being demonstrated product, to determine: the validity that advertisement attracts client and retail division conclude the business, advertisement promote first kind client to increase one or more validity that are demonstrated product and are not demonstrated the income of product with respect to the validity and/or the advertisement of the second class client's transaction; (d) help by computing machine, the result of compiling evaluation procedure (c) and with the form of graphic user interface to client's display result; And (e) provide an instrument to the client by graphic user interface, be used for result based on compiling and select the one or more products that will show in the advertisement in future.
By understanding the explanation of back, and by with reference to subsidiary accompanying drawing and additional claim, those of ordinary skills will understand and the present invention includes a lot of additional aspect and advantages.
Description of drawings
Fig. 1 has shown the overview flow chart of method according to an exemplary embodiment of the present invention;
Fig. 2 shows the graphic user interface that output is provided according to an exemplary embodiment of the present invention;
Fig. 3 shows the replacement of output graphic user interface is provided according to an exemplary embodiment of the present invention;
Fig. 4 shows the additional graphic user interface that output is provided according to an exemplary embodiment of the present invention; And
Fig. 5 shows electrical form output according to an exemplary embodiment of the present invention.
Embodiment
The invention provides a kind of method, be used for by Collection and analysis " distributing data " relevant with advertisement and with before the advertisement distribution, during and/or relevant " transaction data " of transaction of generation after the distribution, be retail division's plan and evaluate advertisements (and in a particular embodiment, storing leaflet and relevant advertisements); Be " influence (reach) ", " balanced (balance) " and " benefit (return) " according to the described analysis this advertisement of classifying; And utilize described classification to set up advertising strategy in the future.By comprehensive issue and transaction data, described method is derived with the most worthy combination for discrete geographical partition running " being demonstrated product ", to obtain " influence ", the combination of " equilibrium " and " benefit " of expectation the client.
" distributing data " will be further described below, and it is the typical ad data of collecting from retail shop itself; And comprise the relevant data that are demonstrated product, adline, advertisement time limit, advertising area etc." transaction data " also will be further described below, and it is from being carried by each client or the typical case of collections such as relevant with each client " patron's card ", " loyalty card " the dealing data of doing shopping.
" be demonstrated product " or " feature " refers to the specific products and/or the service that are demonstrated in the advertisement of retail division; Also can refer to by a set product of advertisement (for example, all changes of the product line of selling, for example all changes of soup product or soft-beverage brand/company).Though exemplary embodiment of the present invention is about the product that is demonstrated of the flyer that is used for given shop; Those of ordinary skills are demonstrated advertisement or distribution that product also can appear at distribution, e-advertising (Email, the Internet etc.) and other type in television advertising, commercials, in-store display, the shop with clear.
" influence ", " equilibrium " and " benefit " are meant that advertisement is demonstrated product may be to the different economic effects of shop transaction." influence " is a kind of certain shops that not only attracts clients, and also attracts the effect (influence can be calculated as and buy one or more number percents that are demonstrated the client of product in the particular customer classification) of their the one or more ad-hoc locations in the shop; " equilibrium " is with the most effective hybrid suction of the client of different customer types effect (for example price sensitivity, demography type or the above-mentioned two types combination of client's type of personality, for example life style type) of effective mixing to product; And " benefit " is to maximize not only to be demonstrated product but also to be that the number percent of all products of providing of retail division is sold and a dollar effect of selling; Perhaps in other words, be the effect of maximization gain on inventory taking.As what use herein, term " product " not only is included in the client's product that can buy in the retail shop, also comprises other products, service or can be offered client's valuable thing by enterprise.
In exemplary embodiment of the present invention, the publish data of collection comprises " characteristic dimension ", and it can be the relevant specific information that is demonstrated the commodity (commodity) of product, secondary commodity (sub-commodity), manufacturer and/or size.In more detailed embodiment, publish data comprises " advertisement dimension ", it can be the information of base price (can be MSRP, base price of being collected by retail division or the price that is similar to the estimation/calculating of this basic rank lattice), feature price (by the price of advertisement), advertisement demonstration and/or the advertisement execution of relevant special characteristic.Advertisement execution can comprise the scope and/or carry out the tabulation of the independent store position of described advertisement execution date of particular advertisement.Because each retail shop of retail division all plans and carry out advertisement, publish data can be recorded in the central database, and this central database can be visited by the management office of one or more retail shop and/or retail division.Described central database provides visit to publish data for all shops of independent store, the one group of shop that is positioned at specific geographical zone or retail division.The ability that data were observed and analyzed to this different tissues rank in retail division is called as " granularity ".
" transaction data " refers to any transaction between relevant client and the enterprise or mutual data.In the exemplary embodiment, transaction data comprises " shopping dealing data ", and it can be the information of relevant client's shopping history, comprises that the client has bought the sign and the quantity thereof of product.As what use herein, term " product " not only comprises the client's product that can buy at retail shop, but also any other products, service or the valuable thing that can be provided to the client by enterprise is provided.Can utilize attached to the unique identifier on label or the card and collect shopping dealing data, described card for example carries (perhaps being distributed to the client's) known " patron's card " or " loyalty card " by each client.This class card or label comprise by bar code, magnetic medium or other data storage device stores and can and well known to a person skilled in the art the unique identifier that variation pattern reads by electronic equipment.This unique identifier can certainly reside on the commodity and not on card.For example, this unique identifier can reside on RFID mechanism, the key chain etc.
When the client passes by the product of the cashier in shop and purchase when being scanned, the unique identifier on patron's card of client for example can be read by electronic equipment.So the computer system in shop can be compiled in the record of product purchased in the specific sale this time, and this tabulation is associated with client's unique identifier.All repeat this process when coming the shop and buying product by each client, the cumulative record of the shopping history of particular customer can be set up in the shop, comprises the sign and the quantity thereof of the product that the client has bought.As described here, client's purchase history of compiling can be stored in the database also analyzed.Being recorded and buying historical " client " can be that the individual also can be an one family, therefore, comprises the group who lives in same address or use same credit card, perhaps even can be enterprise or government entity.
In alternative embodiment, can use other client identification information (for example telephone number, shop credit card, bank card or current account number) that client's shopping dealing data are associated with the client rather than from the frequent customer block, the number of RFID label or similar articles.By this way, the details of particular transaction can be complementary with the transaction before the client, is convenient to like this to continue add Transaction Information in the database each user logging.
Each user logging in the database can comprise a plurality of transaction or record, and transaction or record are used for this client's transaction each time.For each these user logging, provide in the exemplary embodiment: the code of discerning the SKU/ product that the client buys in this transaction; The code of identification particular transaction or " basket "; The particular customer under the identification transaction or the code of family; The code in the shop that the identification transaction takes place; About product quantity of buying and the data that spend total value; The data of relevant purchase date, time etc.; And other data or code, for example indicate the code of geographical zone for the purposes of the present invention, can be used for generating report based on this transaction data.
The code of identification SKU/ product can be used for for each product in the transaction record, the retrieval details relevant with described product the independent database of a plurality of from comprising " product records ".Each " product record " in the product database provides: product grouping or grouped data or code in the exemplary embodiment; Product UPC data; Manufacturer or supplier data or code; And other data or code, Jian Yi retail price data for example, it can be used for generating report based on the combination of transaction data and product data.
The code of the client of identification transaction or family can be used for the independent database retrieval details relevant with described family of a plurality of from comprising " family's record " (each record is used for one family) in the transaction record.For each " family's record ", in the exemplary embodiment, provide and client's population, data and/or the code that shopping is historical, the shopping hobby is relevant, and any other data or the code that can be used for generating based on the combination of transaction data and client/family data report.
The code in the shop that the identification transaction takes place in the transaction record can be used for the independent database retrieval details relevant with described shop of a plurality of from comprising " store record " (each store record is used for a shop).For each " store record ", in exemplary environments, provide: the firm name data; Store locations data or code; And any other data or the code that can be used for generating report based on the combination of transaction data and store data.
Those of ordinary skills will expect, above-mentioned database record structure only is exemplary in itself, and can obtain the unlimited combination of data-base recording and hierarchy, so that mutual cross reference Transaction Information, product information, client/family information, store information, positional information, temporal information and any other adequate information.In addition, those of ordinary skills will expect, the invention is not restricted in retail shop's transaction, use, the present invention can be used for a large amount of (if not whole) type of transaction (for example finance/bank transaction, insurance transaction, service transacting or the like), and wherein database structure and hierarchy will be applicable to and generate this alternately report of transaction data.
Fig. 1 has shown the process flow diagram of describing illustrative methods of the present invention.The independent retailer shop 12 of retail division is grouped in the geographical zone 14.Each subregion is differently worked, so each subregion provides the data of product table 16 form respectively to system, and this tabular goes out the different product that the shop provided in this subregion.Product mark, commodity and the secondary commodity of each product that sell in the shop in these product table 16 identification this areas.System classifies to each product according to department of Call center 18 then, and described each department represents the particular spatial location of product in the shop.For example, salad bar, fresh meat, agricultural product, tinned food, dairy produce, laundry articles for use department, paper products, pet food, soft drink, packed snacks, freezing vegetable, frozen dessert, cereal etc. all are the examples that can be the department of Call center of typical supermarket definition.As what be well known to those of ordinary skill in the art, the classification of this " Call center " is based on the client and how treats retail division, rather than how retail division treats itself.
Except the product table is provided, each geographical zone plan will be by the product that is demonstrated of the store advert in its subregion.On behalf of the independent store of " advertisement coding weekly " data 20 input systems of last minute planning, these plans can will rehear and revise then.This correction can be carried out or be undertaken by the supervision body in the subregion level.The feature Packet engine 22 of system obtains the coding of advertisement weekly of independent store and replenishes this information with respect to being demonstrated product, display message, price, delivery method etc.From here, the advertisement coded data of replenishing and Call center's division data and analysis rule (following description) are comprehensive, to generate original distributing data 23.
Native system also uses above-mentioned any method to collect transaction data 24 from each shop.As top the introduction, transaction data is demonstrated product with comprising about how many clients have bought, also has the information that what other products is purchased, when buy described product or the like.Original distributing data 23 and original transaction data 24 are sent to tolerance engine 26 then, and it is set up by summarizing ﹠amp; Classification engine 28 is used for analyzing according to publish data the gauge (classifying according to its economic effect, each is demonstrated product: promptly, be demonstrated product and how promote influence, balanced and/or benefit) of transaction data.In a more detailed embodiment, system uses two types tolerance---independent characteristic tolerance and cumulative metric.Each is demonstrated the raw data of product the independent characteristic metric analysis, comprise the price when being demonstrated product and being demonstrated and not being demonstrated, and calculate relevant " attractive force part (appeal segment) ", " basket size (basket size) ", " rising " and " infiltration " of each feature.The cumulative metric analysis is relevant arbitrary or all be demonstrated the cumulative statistics of product, and provides baseline analysis for all products of selling.
" attractive force part " refers to be emphasized so that attract the part client, for example the client of Price Sensitive come any client properties part of the part of retail division or retail division.To determine the group that particular customer is included into by the relevant client's that can from client's purchase history, determine feature.Because client's purchase history comprises the sign and the quantity thereof of the product that the client buys, it provides valuable inherent observation the to client's life style, way to manage money and other key character, and this permission is divided into the client in a plurality of groups according to different choice criteria.The group that particular customer is included into also can be according to consensus data and/or personality data, and above-mentioned data may or can not be determined from client's transactions history.The consensus data may comprise, but be limited to age data scarcely, income data, geodata, education degree data.Personality data (" the transaction individual character " that also refer to the client) can comprise, but be limited to price sensitivity scarcely, the tendency of negotiating a price, complimentary ticket are used, the attention to promoting, informativeness, to attention of product space or profile or the like.Those of ordinary skills will expect the multiple source of these consensus datas and/or personality data.In a more detailed embodiment, product is classified as follows: " low side " product is typically by the product that the highstrung client of price is bought; " centre " or " mainly " product is the product of typically being bought by mainstream customers; " high-end " product is typically by the product that the insensitive client of price is bought; And " mainly " product also can be bought by a part of client in the Price Sensitive customers.By analyzing similarity or the difference when purchase is demonstrated product and is not demonstrated product between the customers, system can analyze the portfolio effect of each special characteristic.Classifying client's additional support by this way can be at common unexamined patent application sequence No.10/955, finds in No. 946, and its applying date is on September 30th, 2004; Its disclosed content is here incorporated into by reference.
" basket size " refers to the number of articles bought in any one transaction between a client and shop.In more detailed embodiment, the basket size is divided into three types: little, neutralization is big.System obtains the basket size of each transaction of having bought feature, and calculates the middle basket size of each independent characteristic.Can described method determine how described feature is adapted to that the extensive attractive force in shop---the client only comes the shop and buys described special article by determining the middle basket size of each feature? has still the client also bought other products?
" rising " is meant the income increase that is brought by the specific products that is demonstrated.Rising can be described to number percent " sales volume rising ", it has shown that the percentage of sales as a result that is demonstrated as product increases (if any), perhaps be described to " dollar rising ", it has shown the growth (if any) of the result's income that is demonstrated as product.The combination that sales volume rises and dollar rises provides the tolerance of " benefit " of product feature.
" infiltration " refers to by the client's of feature " influence " quantity.It can be expressed as " client's infiltration ", and it has represented the number percent of having bought the client who is demonstrated article in all clients in shop in designated period of time.
At last, " the relevant sale " is the weighted version of infiltration.For example, it can represent the number percent of the overall cost of client of having bought character representation.In this example, if all clients of certain shops have spent in a period altogether, 000.00, and all clients of the described feature of purchase have spent altogether in this period, and 000.00, then the relevant sale of this feature is 50%.Described weight also can be come weighting with respect to other attribute (rather than the total sales volume in the previous example), for example can come weighting according to following Column Properties: basket size, demographics, price sensitivity or the like.This can calculate for unit store, geographical zone or whole retail division, and is the impact effect how described method determines each feature.
Although " independent tolerance " analyzes data on the independent characteristic rank, " cumulative metric " analyzes the data from bigger product group.The extensive data of all products that the present invention uses cumulative metric to generate to show in given period, and the base-line data of relevant all products.For example, cumulative metric can comprise and buys any the be demonstrated client's of product quantity, the total sales that is demonstrated product that all are sold and/or the total rising that is demonstrated product that all are sold.As baseline, the total sales of all products of client's sum, purchase of any product and/or total rising of all products of buying will calculate be bought in addition.
Summarize ﹠amp; It is autotelic " type " classification that classification engine 28 also is demonstrated each product classification, so that used by the personnel of retail division.In more specific embodiment of the present invention, be demonstrated product and be divided into three general " type " classification---" pillar ", " assisting " and " the unknown "." pillar " class is demonstrated product and promotes influence and the economic effect that benefits, and " assisting " class is demonstrated the economic effect that the product promotion is balanced and benefit." the unknown " type is used to when system is not provided enough announcements and/or transaction data, special characteristic is had a mind to the free burial ground for the destitute analyze its economic effect.The pillar class is that particular retail mechanism has the high main article of rate of heavily buying basically.For example, the pillar product of food supply retail shop can be bread, milk and/or cola; And the pillar product of e-shop can be DVD, CD and battery.The assisted class product replenishes the pillar series products by promoting equilibrium.The assisted class product will have more limited a little influence than pillar series products; For example, those are usually purchased but be not the product of going shopping at every turn and all can buy.For example, in provisions shop, the assisted class product comprises detersive, paper products, fish, frozen food; And in e-shop, the assisted class product comprises annex, DVD player, CD Player and loudspeaker.
In more detailed embodiment, pillar class and assisted class further are divided into subclass.For example, the pillar class is demonstrated product can be divided into " feedback pillar ", " excitation pillar ", " flow pillar ", " high price pillar ", " low side pillar " or other pillar type, for example according to the pillar type of demography classification.The feedback pillar is the product that is demonstrated that the consumer do not consider the main article that advertisement also will be bought is bought in feedback.Milk is an example of feedback pillar.The excitation pillar is high-end product when not being demonstrated, but when being demonstrated, encourages the client of those purchase main products or low-end product to go " purchase ".Consistent purchase is demonstrated product and causes described product to redesignated as main flow or low-end product when being demonstrated.The flow pillar is to attract clients to come the shop in order to buy the specific purposes that are demonstrated article, therefore orders about the product that is demonstrated that the client entered and passed the shop.The exemplary of flow pillar is laughable, seeks special price soft drink weekly because a lot of client trends towards " going window-shopping ".The high price article are to have higher advertising rates and a lower relevant product sold, so the high price pillar should be the high price article that become pillar when being demonstrated.
The assisted class product also can be divided into the subclass of same type, for example " low side assisted class ", " high-end assisted class " and " assisted class in the shop ".Low side and high-end assisted class be help respectively to increase low side and high-end product benefit be demonstrated product; And in the shop assisted class product be increase extensive and middle article benefit be demonstrated product.In more detailed embodiment, how system can effectively limit classification aspect the generation related economic effect according to described feature.For example, the feature that moderately increases the benefit of extensive and medium article is designated as " assisted class in the weak shop ".Although system keeps minimum sandards to each classification, particular criteria can be based on the difference of selling, hobby between zones of different and economic difference or not even with the difference of independent store.
When system overview raw data and each feature carried out after the classification, system uses " final instrument " 30 that integrated information is sent to each user.In specific embodiment of the present invention, final instrument is a graphic user interface.It is with following detailed description and as shown in Fig. 2-4, and it is accessed by the user that graphic user interface organizes described information that it can be easy to.
Now again with reference to figure 1, monitor raw data and classification by " benchmark tracking " parts 32 of system.These parts provide periodicity analysis, are used to revise grouping and the summary of data and the rule that is demonstrated the classification of product of being responsible for being demonstrated product.This periodicity is revised extremely important, because client's behavior is for example along with season, change along with the growth of specific geographical zone and along with the introducing of new product on the market.In specific embodiment more of the present invention, " benchmark tracking " parts 32 generate " season analysis " 33.Should " season analysis " be used for per season revising rule., constantly produce and analyze and constantly revise as required rule more in the specific embodiment at another.In another optionally more detailed embodiment of the present invention, the user can at any time observe the modification of benchmark tracking and analysis and triggering rule.
Except the cycle that changes the modification rule, the present invention can also carry out in the different grain size rank and revise.In specific embodiment more of the present invention, can revise rule independently for each geographical zone 14 of retail shop.Optionally more in the specific embodiment, is that rule is revised by each retail shop at another independently.This shop dedicated rules is called as " the special-purpose tolerance in shop is searched " 34.
Fig. 2-4 provides the exemplary embodiment of the graphic user interface that is used for the display analysis result.The user can select to watch specific geographical zone and specific period specific information.In the exemplary embodiment, graphic user interface allows to come the display analysis result with three kinds of different-formats: achievement form, cycle trend form and characteristic library format weekly.Can be by activating each the corresponding button on the graphic user interface: achievement button 36, cycle trend button 38 or characteristic library button 40 show each of these forms weekly.
Demonstration shown in Figure 2 is that property data base shows.It has shown that each is demonstrated product and how shows in given period.First hurdle " subregion ", 42 identification users select the geographical zone of viewing information.Second hurdle " week " 44 has shown the period of collecting video data.As producing different-effect, therefore, also be like this at different times advertisement like product at different geographical zone advertisement like products.
Third and fourth and five hurdles have shown sign " feature " 46, the client's Central Department under the feature or " loyal department " 48 that is demonstrated product and the classification " type " 50 that is demonstrated product by system.Third column 46 or the analyzed special characteristic of feature hurdle identification.By clicking " watching the feature title " button, the user can trigger between the main UPC that watches the feature title that appears in the advertisement and each syndrome (main UPC is the UPC that the highest sales volume that is demonstrated product is described) back and forth.Described triggering can allow all UPC of indicating characteristic rather than only a main UPC is also within the scope of the invention.48 identifications of the 4th hurdle are demonstrated the department of Call center under the product.For example, " Big K Diet Root beer " belongs to the loyal department of soft drink.The classification type that in the 5th hurdle 50, shows each feature.Notice that in this embodiment, as mentioned above, classification type is by summarizing ﹠amp; Classification engine 28 generates, and this engine is divided into classification type subclass and qualification is provided.For example, if feature is classified as assisted class in the weak shop, then this will represent that described feature moderately increases the sale of main product.
All the other hurdles of describing among Fig. 2 have shown the deal with data that system uses when each feature of classification.The 6th hurdle " shop distribution " 52 is notified how much number percent in the shop in the described subregion of user to provide and is demonstrated product; Nine hurdles, the 7th hurdle to the " price point variation " 54, " base price " 56 and " front end price " 58 provide the price variance when product is demonstrated and be not demonstrated.The tenth hurdle and the 11 hurdle " home position " 60 and " front position " 62 provide in base price and have bought the customer type of product with respect to the classification of buying the customer type of product in advertising rates; Has indicated with the quantity that is demonstrated the other products that product buys on the 11 hurdle " basket size " 64; The number percent of having bought the client who is demonstrated product has been listed on the 14 hurdle " Cust.Pen. " 70; The 15 hurdle " Assoc.Sales " 72 has been listed and has been demonstrated the number percent that total sales volume that product represents is compared with other products.The 12 hurdle " is sold and is risen " the 66 and the 13 hurdle " dollar rising " 68 and shown the growth of selling when product is demonstrated and be not demonstrated.66 expressions of sell rising are demonstrated and the percentage increase of product specific products sales volume when not being demonstrated when product.Dollar rise and 68 to have shown when product and be demonstrated and the income increase that sale produced of product specific products when not being demonstrated.
Graphic user interface provides the percentage difference of base price (price when product is not demonstrated), front end price (price when product is demonstrated) and two kinds of prices.Also come sort product by the price sensitivity of base price and front end price.When these hurdles allowed users to check not to be demonstrated with respect to product, when product was demonstrated, whether described product had attracted the client of different groups/type.For example, when not being demonstrated, the client that some products attractions have high-end price sensitivity, but when it was demonstrated, this product then attracted to have the client of mean price susceptibility.Because some products attract different attractive force parts when it during by advertisement with respect to not by advertisement the time, this information is very important for current " equilibrium " effect of analyzing special characteristic and prediction " equilibrium " effect in future.
Another feature of graphical interfaces shown in Fig. 2 is that it allows the user to generate advertisement evaluation template, feature that described advertisement evaluation template permission user relatively proposes and influence, equilibrium and the re-set target that benefits.By selecting from the product that was demonstrated in the past, by clicking the subregion hurdle (perhaps being dragged in the evaluation table 74 by being demonstrated article itself) of correlated characteristic, the user can generate the advertising plan of a suggestion in table 74.For example, each user can provide target or standard, and these targets or standard specify expectation to be comprised in the specific advertising plan weekly about quantity with each type 50 of " influence ", " equilibrium " that realize expectation, " benefit " effect.This standard can provide in the granularity of different stage.In more specific embodiment of the present invention, for each geographical zone 14 provides this standard independently.In more detailed embodiment alternatively, for each independent retail shop 12 provides this standard independently.By this standard of reference, the user can estimate the advertising plan of each proposal, and plan for adjustment is to satisfy the needs of " influence ", " equilibrium " and " benefit ".
In case what the user will propose is demonstrated in the product combination adding table 74, the user just can click and generate advertisement evaluation template button 75 so, and deposit being proposed feature and will being output in the electronic form file that is called as the matrix template, as shown in Figure 5 in the table 74 in.Described matrix template allows the user to observe all products, how to carry out together with the feature of checking proposal.Described matrix template comprises row/space and row: the feature that described row/space is used to propose; Described row are used for the key metrics that is associated with the feature of proposing, and it has shown how this feature is carried out in the past.Described matrix also comprises the zone that is used for the additional annotations that can be added by the user and estimates towards influence, balanced and benefit the additional space of the full-motion of three targets.These data allow retail division to observe the strongest potentiality which feature has influences the client, produces the added selling volume and contain all types of clients.This information allows retail division's (perhaps during other advertisement) balanced its investment weekly, satisfies the mixing of the required feature of intended target with maximization.Although exemplary embodiment of the present invention is at auxiliary this matrix template evaluation procedure of manually carrying out down of computerize electrical form instrument, obviously within the scope of the invention, processing (if not whole words) is selected and further estimated to the permission software automation.
Fig. 3 has shown exemplary graphical user " achievement weekly " screen.This screen provides influence, equilibrium that is reflected in specific geographical zone in the specific period (perhaps any other selection or the combination of retail division) and is experienced and raw data, number percent data and the graph data that benefits effect for the user.In this exemplary embodiment, the user can be by clicking " selection subregion " combobox 76 and/or " selecting week " combobox 78, the data and/or the data in different weeks of selecting to observe different geographical zones.
" comprehensively achievement " weekly figure 80 provides comprehensively " influence ", " infiltration " and " rising " data for the user.Percent of total " influence " 82 is with the numerical data that derives this number percent-provide at the sum 84 of the family of any retail shop shopping of selected week 78 in selected geographical zone 76 and the quantity of buying in those families 86 that select any family product that are demonstrated in week 78.Also represent influence from the income skeleton view by the number percent of " associated store sale " 88.This figure represents so-called " halo effect ", and recently calculates (i.e. " associated store total sales volume ") 92 by the percentage that finds " the shop total sales volume " 90 of being sold to the client who buys one or more feature.Influence is further segmented, so that by finding the number percent of " the total VPS/PS family " 96 that in selected week 78, has bought one or more feature, the very responsive client of price (" VPS ") that attracted by feature weekly and Price Sensitive client's (" PS ") 94 ratio (that is, " the total VPS/PS that is attracted by the homepage feature ") 98 is shown." sales volume infiltration " number percent 100 representative " homepage feature total sales volumes " 104 account for the number percent of " shop total sales volume " 102.At last, " rising " representative is as the income increase that is demonstrated product of advertisement result experience.Fig. 3 has shown number percent " sales volume rising " 106, and the dollar figure that " basic sales volume of homepage feature " 108 and " the total dollar that rises on basic dollar " 110 are provided.
Fig. 3 also its " how my feature is partly carried out? " influence and climb data that the power that is attracted is partly segmented have been shown in the figure 112.Influence in family's sum of being attracted by one or more feature in family's sum in each attractive force part that Figure 116 shown shopping, each attractive force part and each the attractive force department by the number percent of the family of feature " influence ".Shown also that by column Figure 118 the number percent of comparing each attractive force part with the percent of total influence influences data.Rising Figure 120 has shown that the number percent of basic sales volume, homepage feature sales volume and each attractive force part rises and total basic sales volume, total homepage sales volume and the number percent that always rises.The basic sales volume and the homepage sales volume that also in column Figure 122, have compared each attractive force part.
Fig. 4 has shown exemplary graphical user " achievement trend " screen.Influencing cycle trend Figure 123 allows the user to determine that whether the shop in the specific geographical zone 126 has also experienced higher total sales volume in it experiences week of higher total influence.Once more, the demonstration of exemplary embodiment is segmented by geographical zone, but the present invention makes flexibly that enough this demonstration also can be by other combination segmentation of retail division, cycle, product category etc.Figure 124 has been described a nearest week of report data.The x axle 132 of Figure 123 is represented each week in component analysis cycle.Histogram y axle 128 has been represented the shop total sales volume, and line chart y axle 130 has been represented the number percent influence.By total sales volume is covered with influence data, this screen allow user's evaluation in the long term in specific geographical zone to the impact effect of shop total sales volume.
Embodiment by reference example has described the present invention, will be appreciated that the present invention is defined by claim and be not interpreted as restriction claim at any restriction of the exemplary embodiment of preceding description or element, unless in claim clear these restrictions or the element listed.Similarly, also can be clear, because the present invention is defined by claim and since the relevant and/or intrinsic advantage of the present invention may be present among the clear herein content of discussing, therefore in order to adapt to the claim restricted portion, one or all advantage and target must not reach described herein of the present invention.
Claims (32)
1. computer system that is used to retail division plan and evaluate advertisements comprises:
The computer system that comprises advertisement publishing database and transaction data base, described computer system is configured to carry out the following step:
(a) in the ad distribution database, a plurality of first group of ad distribution data that is demonstrated product that collection is issued in first period by retail division, described ad distribution data comprise the data that obtain from comprise following group: about the data that are demonstrated product in the advertisement, about the data of adline, about the data in advertisement time limit and the data of relevant advertising area;
(b) in transaction data base, be collected in first group of transaction data of a plurality of transaction of being undertaken by a plurality of clients that buy a plurality of products from retail division in described first period;
(c) the described first group ad distribution data of analysis in described first period are with respect to described first group of transaction data; And
(d) based on of the analysis of described first group of ad distribution data with respect to described first group of transaction data, with a plurality of product classifications that are demonstrated is a plurality of advertisement roles, and described a plurality of advertisement roles comprise the one or more advertisement roles that obtain from comprise following group: the specific part of the retail division that attracts clients be demonstrated product; Promote the client's of the different client segmentations of attraction mixing to buy the product that is demonstrated that is demonstrated product; Promote the dissimilar products that the client buys equilibrium be demonstrated product; Promote the product that is demonstrated that the sales volume of retail division increases comprehensively; And promote above-mentioned two or more advertisement roles combination be demonstrated product.
2. the computer system described in claim 1, wherein, described computer system is configured to further execution in step: (e) set up first advertising strategy based on described advertisement role.
3. the computer system described in claim 1, wherein, described computer system is configured to further carry out the following step:
(f) be collected in second group of next group ad distribution data that is demonstrated product using by retail division in next period;
(g) be collected in next group transaction data of a plurality of products of selling by retail division in described next period;
(h) described next group ad distribution data of analyzing in described next period are organized transaction data with respect to next; And
(i) based on the analysis of described next group ad distribution data with respect to next group transaction data, being demonstrated product classification with second group is a plurality of advertisement roles.
4. the computer system described in claim 1, wherein, the output of described analytical procedure comprises one or more in the following output class:
The percent of total sales volume rises;
Each number percent sales volume that is demonstrated product rises;
Total dollar is risen;
Each dollar that is demonstrated product rises;
Total client's infiltration;
Each is demonstrated client's infiltration of product;
Total correlation sales volume number percent; And
Each is demonstrated the relevant sales volume number percent of product.
5. the computer system described in claim 1, wherein, the step of collecting distributing data comprises the following steps:
Generate the kind tabulation that be demonstrated product relevant with retail division;
A plurality of each that are demonstrated product that retail division provided are distributed to one or more product categories that are demonstrated; And
Generate the tabulation of the advertisement dimension relevant with retail division; And
Each of the employed a plurality of in-store advertisings of retail division is distributed to one or more advertisement dimensions.
6. the computer system described in claim 5, wherein, the tabulation of described characteristic dimension comprises one or more in the following characteristic dimension:
The commodity class;
Secondary commodity class;
Manufacturer's class;
Department's class; And
The size class.
7. the computer system described in claim 6, wherein, the step that generation is demonstrated the kind tabulation of product further comprises: based on the position of the like product in the retail shop of retail division, be mapped to one or more in the loyal department of a plurality of clients with being demonstrated product.
8. the computer system described in claim 5, wherein, the tabulation of described advertisement dimension comprises one or more in the following advertisement dimension:
The product code dimension;
The base price dimension;
Feature price dimension;
Show dimension; And
The advertisement execution dimension.
9. the computer system described in claim 8, wherein, described advertisement execution dimension comprises one or more in following:
The scope of execution date; And
The tabulation of executing location.
10. the computer system described in claim 1, wherein, the step of described collection distributing data is restricted to: collect distributing data from a plurality of retail shops of one or more subclass of the geographical zone that is arranged in retail division.
11. the computer system described in claim 1, wherein, the step of described collection distributing data is restricted to: collect distributing data from the single retail shop of retail division.
12. the computer system described in claim 1, wherein, the step of described collection transaction data comprises the following steps:
Generate the product category tabulation relevant with retail division;
Each of a plurality of products of selling is distributed to one or more product categories;
Generate the transaction dimension tabulation relevant with retail division;
Each of a plurality of transaction is distributed to one or more transaction dimensions;
Generate the client kind tabulation relevant with retail division;
Each of a plurality of clients is distributed to one or more client's dimensions.
13. the computer system described in claim 12, wherein, the tabulation of described product category comprises one or more in the following products kind:
The commodity class;
Secondary commodity class;
Manufacturer's class;
Department's class; And
The size class.
14. the computer system described in claim 12, wherein, the step of described generation product category tabulation further comprises: based on the position of the like product in the retail shop of retail division, product category is mapped to one or more in a plurality of loyal departments.
15. the computer system described in claim 12, wherein, the tabulation of described transaction dimension comprises one or more in the following transaction dimension:
The basket size;
The quantity of the feature of buying;
The total expenses of the product of buying;
The average cost of the product of buying;
The total expenses of the feature of buying;
The average cost of the feature of buying; And
The tabulation of the product of buying.
16. the computer system described in claim 15, wherein, described basket size transaction dimension comprises one or more in the following size:
Little basket size;
Medium basket size; And
Big basket size.
17. the computer system described in claim 12, wherein, the tabulation of described client's kind comprises one or more in following:
Client's kind tabulation based on client;
Client's kind tabulation based on feature.
18. the computer system described in claim 17 wherein, comprises one or more in the following subclass based on client's kind of client:
The price sensitivity subclass; And
Loyal subclass.
19. the computer system described in claim 18, wherein, described price sensitivity subclass comprises one or more in following:
The insensitive class of price;
The main flow class;
The Price Sensitive class;
Price is sensitive kinds very; And
Unknown Price Sensitive class.
20. the computer system described in claim 17 wherein, comprises one or more in following based on client's kind of feature:
Buy the client's of any feature sum;
The total expenses of all features of buying; And
Total rising of all features of buying.
21. the computer system described in claim 1, wherein, the step of described collection transaction data is restricted to: collect transaction data from a plurality of retail shops of one or more geographical zones of being positioned at retail division.
22. the computer system described in claim 1, wherein, the step of described collection transaction data is restricted to from the single retail shop of retail division and collects transaction data.
23. the computer system described in claim 1, wherein, described advertisement role comprises one or more among the following role:
The pillar role; And
Secondary role.
24. the computer system described in claim 23, wherein, described pillar role comprises one or more in the following type:
The feedback pillar;
The excitation pillar; And
The flow pillar.
25. the computer system described in claim 23, wherein, described secondary role comprises one or more in the following type:
Low side is auxiliary;
High-end auxiliary;
Main flow is auxiliary; And
Auxiliary in the shop.
26. the computer system described in claim 1, wherein, described computer system is configured to further carry out the step that generates report.
27. the computer system described in claim 26, wherein, described report comprises:
At least a portion distributing data;
At least a portion transaction data; And
Relevant at least a portion advertisement role's output.
28. the computer system described in claim 26, wherein, the user can visit described report by graphic user interface.
29. the computer system described in claim 28, wherein, described graphic user interface is one or more in the following kind with described reporting organization:
Geographical zone;
The scope of execution date;
Each is demonstrated the Universial Product Code of product;
Each is demonstrated the title of product;
Each is demonstrated the retail sectors of product;
Each is demonstrated the advertisement role of product;
Each price point that is demonstrated product changes;
Each is demonstrated Price Sensitive client's kind of the base price of product;
Each is demonstrated Price Sensitive client's kind of the feature price of product;
The average basket size that comprises each basket that is demonstrated product;
Each number percent sales volume that is demonstrated product rises;
Each dollar that is demonstrated product rises;
Each client who is demonstrated product permeates number percent; And
Each is demonstrated the relevant sales volume number percent of product.
30. the computer system described in claim 26, wherein, described computer system is configured to further carry out creates the step that template is estimated in advertisement.
31. the computer system described in claim 30, wherein, the step that template is estimated in described establishment advertisement comprises the following steps:
Distributing data, transaction data, advertisement role and the effect data of gathering one or more combination of features in one or more periods; And
At influence, the equilibrium of expectation and the scope that benefits, the data of pair set are analyzed.
32. the computer system for retail division's plan and/or evaluate advertisements comprises:
The computer system that comprises advertising database and transaction data base, described computer system is configured to carry out following step:
(a) in transaction data base, from the transaction of in first period and second period, carrying out, collect a plurality of clients' transaction data with retail division;
(b) in advertising database, collect the ad data of at least one product of showing by advertisement, described ad data comprises related between the sign that is demonstrated product and described advertisement and second period at least;
(c) carry out at least estimating the transaction data relevant with being demonstrated product than the school between first period and second period, to determine one or more in following: the validity that advertisement attracts client and retail division conclude the business, advertisement promote first kind client to increase one or more product and last validity that are demonstrated the income of product of being demonstrated with respect to the validity and the advertisement of the second class client's transaction;
(d) form with graphic user interface compiles the result of evaluation procedure (c) and shows described result to the user; And
(e) provide an instrument by described graphic user interface to the user, be used for result based on compiling and select the one or more products that to show in following advertisement.
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| BR (1) | BRPI0706135A (en) |
| CA (1) | CA2590027A1 (en) |
| MX (1) | MX2007006266A (en) |
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| CN109614548A (en) * | 2018-12-07 | 2019-04-12 | 中国银行股份有限公司 | Information displaying method, device and storage medium based on service-user number change rate |
| CN110599039A (en) * | 2019-09-16 | 2019-12-20 | 平安科技（深圳）有限公司 | Product management method and device, electronic equipment and storage medium |
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| US9342835B2 (en) | 2009-10-09 | 2016-05-17 | Visa U.S.A | Systems and methods to deliver targeted advertisements to audience |
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| US10354268B2 (en) | 2014-05-15 | 2019-07-16 | Visa International Service Association | Systems and methods to organize and consolidate data for improved data storage and processing |
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2007
- 2007-05-22 AU AU2007202292A patent/AU2007202292A1/en not_active Abandoned
- 2007-05-23 CA CA002590027A patent/CA2590027A1/en not_active Abandoned
- 2007-05-25 BR BRPI0706135-8A patent/BRPI0706135A/en not_active IP Right Cessation
- 2007-05-25 MX MX2007006266A patent/MX2007006266A/en not_active Application Discontinuation
- 2007-05-25 KR KR1020070050868A patent/KR20070114041A/en not_active Application Discontinuation
- 2007-05-25 JP JP2007164347A patent/JP2007317209A/en active Pending
- 2007-05-25 CN CNA2007101701831A patent/CN101149830A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109614548A (en) * | 2018-12-07 | 2019-04-12 | 中国银行股份有限公司 | Information displaying method, device and storage medium based on service-user number change rate |
| CN109614548B (en) * | 2018-12-07 | 2020-10-27 | 中国银行股份有限公司 | Information display method and device based on service user number change rate and storage medium |
| CN110599039A (en) * | 2019-09-16 | 2019-12-20 | 平安科技（深圳）有限公司 | Product management method and device, electronic equipment and storage medium |
| CN110599039B (en) * | 2019-09-16 | 2023-06-06 | 平安科技（深圳）有限公司 | Product management method and device, electronic equipment and storage medium |
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| AU2007202292A1 (en) | 2007-12-13 |
| JP2007317209A (en) | 2007-12-06 |
| CA2590027A1 (en) | 2007-11-25 |
| KR20070114041A (en) | 2007-11-29 |
| BRPI0706135A (en) | 2008-09-23 |
| MX2007006266A (en) | 2008-12-08 |
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