WO2008142662A9

WO2008142662A9 - Method and system for providing media expenditure profiling

Info

Publication number: WO2008142662A9
Application number: PCT/IB2008/052041
Authority: WO
Inventors: Francesco Massimo Mariola; Francois Alwyn Venter
Original assignee: Identity Media And Business Tr; Francesco Massimo Mariola; Francois Alwyn Venter
Priority date: 2007-05-23
Filing date: 2008-05-23
Publication date: 2009-07-02
Also published as: WO2008142662A3; WO2008142662A2

Abstract

A method for media expenditure profiling and system are provided. The method comprises recording expenditure data including an expenditure value which relates to a media campaign. Data on units of measure and a units of measure value relating to products or services which are the subject of the media campaign are recorded, with the units of measure value representing unit sales of a particular product or service. At least one media cost per unit (MCPU) value for the media campaign is calculated by dividing the expenditure value with the units of measure value and then provided as a graphical presentation to a user of the system.

Description

METHOD AND SYSTEM FOR PROVIDING MEDIA EXPENDITURE

PROFILING

BACKGROUND OF THE INVENTION

THIS invention relates to a method and system for providing media expenditure profiling and particularly to a method and system providing an analysis of the relationship between media expenditure and the return thereon.

In order to differentiate and rationalize between a vast selection of advertising mediums for media campaigns, e.g., potential media schedules for television advertisements during certain time slots and/or programs, the advertising media placement industry has to date been reliant on theoretical averages generated from speculative statistics, research that may be deemed subjective and sampling data that may be gathered from a limited number of respondents in different categories, for example, different Living Standard Measure (LSM) scales, age groups, gender, race etc.

Based on this data, reports are typically generated by media placement agencies through the collation of the abovementioned data. For example, in the case of television advertising, the reports are generated using software packages developed by suppliers of computer-based advertising media information services, e.g., Telmar. Internationally and in countries where similar systems exist, such sampling information and the analysis of survey data is used to represent a complete set of data.

One of the problems identified by both the industry and media planners with the abovementioned methods is that the audience rating on which many of these reports rely is not factually precise and that the reports are theoretical assumptions based on averages of sampling data. Although it is accepted that there is value in these methods, it is further accepted that the industry norm is to acknowledge the subjective nature of these reports and to only use these reports as guidelines when planning and choosing different media exposure for clients. Media strategists, planners and buyers are therefore expected to also use their "gut feel" when selecting an appropriate method of media coverage and when making other critical decisions on advertising placements for advertisers and their products.

A need has therefore been identified to provide a more objective approach to analyse historical trends in the return on media exposure in order to use such analysis to make better decisions on media expenditure and media placement.

It is an object of the invention to provide an alternative method and system for media expenditure profiling.

SUMMARY OF THE INVENTION

According to one aspect of the invention there is provided a method for media expenditure profiling, the method comprising:

recording expenditure data including an expenditure value which relate to a media campaign;

recording data on units of measure refating to products or services, the data including a units of measure value for the products or services which are the subject of the media campaign;

calculating at least one media cost per unit (MCPU) for the media campaign by dividing the expenditure value with the units of measure value; and providing the calculated media cost per unit to a user.

Typically, the units of measure value may be a number of unit sales of a particular product or service, access to a particular product or service, e.g., a number of hits on a website, a number of calls to a call center, or a number of applications received for a particular product or service.

The method may further comprise calculating multiple media cost per unit values over the media campaign according to predetermined intervals and analysing these multiple media cost per unit values to determine trends with regard to the return on advertising expenditure.

Recording expenditure data on the media campaign may include recording expenditure data for predetermined expenditure intervals. The predetermined expenditure intervals may be daily intervals, weekly intervals, monthly intervals or the like. The expenditure data may be recorded per advertised products or services and may further be recorded by type of advertising medium used, positioning, timing or placement of advertising, the geographical region of advertising, genre of advertising or the like.

Recording data on units of measure relating to products or services may also include recording data for predetermined sale intervals, for example, daily intervals, weekly intervals, monthly intervals or the like. The units of measure data may be associated with particular groupings, categories or distribution channels used. The units of measure data may further include a product or service description, unit price, sale medium, category, sub- category, channel, agent, geographical area of sale or time and date of sale.

The predetermined expenditure intervals may be linked to corresponding predetermined sales intervals. Alternatively, predetermined expenditure intervals may be associated with different predetermined sales intervals. For example, a predetermined expenditure interval for a particular day may be associated with a predetermined sales interval for a following day. Where the predetermined expenditure intervals are linked to corresponding predetermined sales intervals, the time period between the start of the media campaign or spot flighting of an advert and a variance, e.g., a recorded variance, whether an increase or decrease, in the media cost per unit is calculated as a media reaction time (MRT) factor which is used to determine the efficacy of the media campaign.

The method further comprises recording a base or natural units of measure value (NUL) prior to the start of the media campaign and additionally, calculating a media generated units of measure value (MGU) once the media campaign has started, with the total units of measure value comprising at least the base or natura! units of measure value and the media generated units of measure value.

The method may further comprise calculating a point of media expenditure wastage or overspend during a media campaign where the units of measure values do not increase linearly with expenditure on a media campaign. Alternatively, the MCPU values may also be considered in determining the point of wastage.

The method may further include recording data and a value on units of measure relating to unadvertised products or services, where the unadvertised products or services may be related to the advertised products or services.

Additionally, the method may include:

calculating a combined media cost per unit for the advertised and unadvertised products or services by dividing the expenditure value with the units of measure value for both advertised and unadvertised products or services; and providing the combined media cost per unit to a user, preferably as a comparison to the calculated media cost per unit of the advertised goods or services.

Preferably, the media cost per unit provided to the user is presented as a table or graph.

The presentation of the media cost per unit information may be adapted to provide a drill-down functionality.

Typically, the recording of data on units of measure relating to products or services may be a manual process. Alternatively, the recording of expenditure data may be an automated process of receiving a file including expenditure data from a user.

The method may further include accessing the received file and parsing information in the file to obtain data on predetermined units of measure relating to products or services.

The method may further comprise determining a ranking of multiple media campaigns by determining adjusted media cost per unit values for multiple media campaigns where the media reaction time factor is taken into account in associating the predetermined expenditure intervals and the predetermined sales intervals.

Alternatively, the ranking of multiple media campaigns may be determined by calculating media cost per unit values for multiple media campaigns from the generated units of measure value, additionally taking the media reaction time factor into account.

According to another aspect of the invention there is provided a system to profile media expenditure, the system comprising: an expenditure data module to record expenditure data and an expenditure value relating to a media campaign;

a units of measure module to record data on units of measure relating to products or services, the data including a units of measure value for the products or services which are the subject of the media campaign;

a media cost per unit (MCPU) calculator to calculate a media cost per unit for the media campaign by dividing the expenditure value with the units of measure value; and

a presentation module to provide the calculated media cost per unit to a user.

The expenditure data module may record expenditure data for predetermined expenditure intervals. The predetermined expenditure intervals may be daily intervals, weekly intervals, monthly intervals or the like. The expenditure data may be recorded per advertised products or services and may further be recorded by type of medium used, time slot, genre, advertisement size or the like.

The units of measure module may record data for predetermined sale intervals, for example, daily intervals, weekly intervals, monthly intervals or the like. The units of measure module may further record units of measure data associated with particular groupings, categories, sub-categories or distribution channels used. The units of measure data recorded by the units of measure module may further include a product or service description, unit price, sale medium, geographical area of sale or time and date of sale. The predetermined expenditure intervals may be linked to corresponding predetermined sales intervals. Alternatively, predetermined expenditure intervals may be associated with different predetermined sales intervals. For example, a predetermined expenditure interval for a particular day may be associated with a predetermined sales interval for a following day.

The units of measure module may further record data on units of measure relating to unadvertised products or services, where the unadvertised products or services may be related to the advertised products or services.

The media cost per unit calculator may further calculate a combined media cost per unit for the advertised and unadvertised products or services by dividing the expenditure data with the units of measure for both advertised and unadvertised products or services; while the presentation module may provide the combined media cost per unit to a user, preferably as a comparison to the calculated media cost per unit of the advertised goods or services.

Preferably, the presentation module may provide the media cost per unit data to the user in a graphical presentation, such as a table or graph.

The presentation module may further include drill-down functionality to show details of the products or services. For example, the details may comprise the product or service description, unit price, sales medium, geographical area of sale or time of day of sale.

The units of measure module may be adapted to record data on units of measure relating to products or services during a manual process in which the presentation module provides the user with a web-based form. Alternatively, the system may include an interface to receive a file including expenditure data from a user. The units of measure module may be adapted to access the received file and to parse information in the file to obtain data on predetermined unit sales of products or services.

The system may further comprise a registration module to receive registration data from a user.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 shows a network diagram of a system within which an example embodiment of a media profiling system is employed, in accordance with an example embodiment;

Figure 2 shows a block diagram of the different modules of the media profiling system of Figure 1 ;

Figure 3 shows a user interface in the form of a web page to be used by a user to select certain user management functionality, in accordance with an example embodiment;

Figure 4 shows a user interface in the form of a web page to be presented to a user to allow a user to select certain options on a customer menu, in accordance with an example embodiment;

Figure 5 shows a user interface in the form of a web page to be presented to a user to register a media campaign and to obtain units of measure data, in accordance with an example embodiment; Figure θ shows a user interface in the form of a web page to be presented to a user to obtain media expenditure data on a media campaign, in accordance with an example embodiment;

Figure 7 shows a user interface in the form of a web page to be presented to a user to allow a user to select certain options on an activity menu, in accordance with an example embodiment;

Figure 8 shows a user interface in the form of a web page to be presented to a user to obtain or record units of measure data, in accordance with an example embodiment;

Figure 9 shows a user interface to upload a text file comprising units of measure information to the media profiling system, in accordance with an example embodiment;

Figure 10 shows an example embodiment of a graph that may be presented to a user, the graph indicating media cost per unit values in comparison to a maximum threshold level for media wastage, in accordance with an example embodiment;

Figure 11 shows a user interface in the form of a web page to be presented to a user to allow a user to select various presentations of data recorded by the system, in accordance with an example embodiment;

Figures 12 to 21 show various other user interfaces to either obtain data from a user or to present data to users, in accordance with various example embodiments;

Figure 22 shows another example drill down screen where detailed program schedules and time slots are presented, in accordance with an example embodiment; Figure 23 shows a table of media campaigns which are ranked according to media cost per unit values and level of efficacy, in accordance with an example embodiment;

Figure 24 shows a high-level entity-relationship diagram iilustrating various tables or data structures that may be stored in a database;

Figure 25 shows a flow diagram of an example method for providing media expenditure profiting is shown, in accordance with an example embodiment; and

Figure 26 shows a diagrammatic representation of machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.

DESCRIPTION OF PREFERRED EMBODIMENTS

Figure 1 is a network diagram showing a client-server system 10, within which an example embodiment of the invention may be deployed. A networked system 12 provides server-side functionality, via a network 14 (e.g., the Internet or a Wide Area Network (WAN)) to one or more users. Figure 1 illustrates, for example, a web client 16 (e.g., a browser, such as the Internet Explorer browser), and a programmatic client 18 executing on respective user machines 20 and 22.

An Application Program Interface (API) server 24 and a web server 26 are coupled to, and provide programmatic and web interfaces respectively to, an application server 28. The application server 28 hosts a media profiling system or application 30, in accordance with an example embodiment of the invention. The application server may, in turn, be coupled to at least one database server 32 that facilitate access to one or more databases 34.

The media profiling system (alternatively called a media cost per unit application or system) 30 may provide a number of media analysis functions and services to users that access the networked system 12.

Further, while the system 10 shown in Figure 1 employs a client-server architecture, the present invention is not limited to such an architecture, and could equally well find application in a distributed, or peer-to-peer, architecture system, for example. The media cost per unit application or system 30 could also be implemented as standalone software programs, which do not necessarily have networking capabilities.

The web client 16 accesses the media profiling system 30 via the web interface supported by the web server. Similarly, the programmatic client 18 accesses the various services and functions provided by the media profiling system 30 via the programmatic interface provided by the API server 24.

Turning to Figure 2, a block diagram iilustrating different modules of the media profiling system 30 is shown, in accordance with an example embodiment. The modules of the media profiling system 30 may be hosted on dedicated or shared server machines (not shown) that are communicatively coupled to enable communications between server machines. The modules themselves are communicatively coupled (e.g., via appropriate interfaces) to each other and to various data sources, so as to allow information to be passed between the applications or so as to allow the applications to share and access common data. The modules may furthermore access one or more databases 34 via the database servers 32.

The media profiling system 30 includes a registration module 40 to receive registration data from a new user or customer. For example, the registration module 40 may request a user to provide a customer name, customer login, customer password, customer details (e.g., address, contact numbers etc), payment details and other similar information. Once the user has registered with the media profiling system 30, the user may access, in one example embodiment, the media profiling system 30 through the web-interface, as described above. It will be appreciated that the registration module 40 may receive registration data on a new user or customer from a system controller. For example, an IT manager or web controller may receive information on a new user telephonically, and may then register the new user in order to provide the user with access to the system.

Figure 3 shows a user interface where different options may be selected by a user of the system to either set user rights, modify users or manage users. It will accordingly be appreciated that the media profϊiing system 30 provides for different levels of users that may have differing levels of access to the system.

The media profiling system 30 may further include a presentation module 42 which is responsible for the presentation of information to the user. The presentation module 42 may therefore be associated with and coupled to a number of other modules of the media profiling system 30 in order to present a graphical user interface (e.g., a web-interface) to the user. These graphical user interfaces may either be used to provide the user with information or to prompt the user for information that requires manual input from the user.

in an example embodiment, the media profiling system 30 may include an expenditure data module 44 and a units of measure module 46 to record different information and data on a media campaign.

A media campaign may relate to any advertising campaign for which the user has paid. Examples of media campaigns may be or include a television or radio advertising campaign, advertisements in any publications (e.g., magazines, newspapers), other printed media (e.g., flyers), billboards, electronic or internet advertisements, in-store promotions, advertisements at public events, or the like. Each media campaign may have a specific expenditure value associated with it. For example, for television or radio advertising campaigns each flighting of the campaign has a specific expenditure associated with it. The expenditure may be pre-calculated based on the time of day of flighting, the channel on which the campaign is to be run, level of rating based on viewership, listenership or readership, the length of the advertisement, etc.

Each media campaign may also be focused on a particular unit of measure which typically relates to products or services. It will be appreciated that a units of measure value may be a number of unit sales of a particular product or service, access to a particular product or service, e.g., a number of hits on a website, a number of calls to a call center, or a number of applications (such as successfully processed applications) received for a particular product or service. For example, a media campaign may promote a specific mobile telephone (e.g., a product), or alternatively, the services and different mobile telephone subscription packages made available by a mobile service provider (e.g., a service).

Information associated with the products or services of the media campaign (units of measure) and the media campaign itself may be recorded through the use of various user interfaces in the form of web pages. Figure 4 shows one such web page where a user may make a selection to do any of the following:

• Manage customers - i.e., users of the system

• Modify customers

• Modify campaigns - i.e., advertising campaigns of particular users

• Manage campaigns

• Modify stores - e.g., stores in which an advertising campaign is run or where goods and services advertised wil! be sold

• Manage stores

• Modify products or services - e.g., on which advertising campaigns are run • Manage products or services

Figure 5 shows an example embodiment of a user interface in the form of a web-page 80 which is to be presented to a user of the media profiling system 30 in order to obtain at least some of the units of measure data, in this instance, details of goods to be sold under a media campaign, and basic media expenditure data on a media campaign. The presentation module 42 creates the user interface 80 to prompt the user to enter information relating to a media campaign. For example, a media campaign description 82 may be entered, products 84 forming part of the campaign may be entered (or selected), i.e., advertised products, and products not forming part of the campaign 86, which may be related to the advertised products, i.e., unadvertised products, may also be entered or selected. It will be appreciated that when a product or service is recorded on the campaign, a product identifier may be allocated to the product or service in order to simplify processing of expenditure data.

Additionally, the type of advertising medium 88 to be used may be recorded (or selected, e.g., type of magazine, type of newspaper, press, radio, billboards, electronic media, and the like. The start and end date of the campaign 90, 92 may also be recorded, as well as the frequency of running the campaign 94. The budget 96 for the campaign may also be entered by the user or may alternatively be calculated automatically by the system by adding the individual costs, e.g., of various advertisements, forming the campaign.

It will be appreciated that more advanced parameters relating to the units of measure (e.g., units of sales) and advertising campaign may also be recorded, e.g., a particular chain which may promote or sell the products, stores that may promote or sell the products, geographical area of promotions or sales, or date or time when the sale took place.

This information is captured by the units of measure module 46 and the expenditure data module 44, stored in the databases 34 and is utilized by the media profiling system 30 to establish a direct relation between units of measure value relating to products or services (which is to be recorded) and media expenditure as well as to do additional analysis.

The units of measure may typically be associated with a single element which is important to the business and which may be the underlying reason for a business' success. For example, and as mentioned above, the units of measure may be a value for unit sales of a particular product or service, access to a particular product or service, such as the number of hits on a website, calls to a call center, or applications received for a particular product or service (e.g., successful (approved) bond applications).

Specific expenditure data relating to the media campaign is also recorded by the expenditure data module 44 which stores the information in the database 34. Figure 6 shows an example embodiment of a user interface in the form of a web-page 100 which is to be presented to a user of the media profiling system 30 in order to obtain the expenditure data of a specific media campaign 102. The web page enables a user to record expenditure data relating to specific advertising mediums (e.g., Press, Radio, All TV Stations) in which the campaign has been run (shown respectively by reference numerals 104.1 , 104.2 and 104.3), over various days or alternatively called expenditure intervals of a particular month 106, which in this example embodiment is February, with only 28 days.

The expenditure data module 44 may record expenditure data and particularly expenditure values (costs) for various predetermined expenditure intervals during a media campaign. For example, the predetermined expenditure intervals may be a daily interval, weekly interval, monthly interval or even yearly intervals. It will be appreciated that the expenditure data module 44 may record the data for minimum intervals, e.g., daily intervals (even hourly intervals depending on the client's reporting capabilities and needs), and that the expenditure data module 44 or another appropriate module may collate this information into different intervals. It will further be appreciated that the more detail recorded by the expenditure data module 44, the greater the insight into the results of the media profiling system would be. The recorded expenditure data and expenditure values (costs) are also stored in the databases 34 for later processing.

In one example embodiment of the invention, the expenditure data may be recorded according to the advertising space or advertising flighting time in relation to a particular product or service. For example, a 30 second advertising spot on television or radio may comprise a typical "top and tail" which contains a generic "signature" or corporate jingle used by the retailer on all its television or radio advertisements, if this "top and tail", for example, make up 6 seconds of the duration of the 30 second spot, a first product may make up 7 seconds of the advertisement, a second product may make up 9 seconds and a third product may make up the remaining 8 seconds (totaling 30 seconds). If the media expenditure of the flighting costs a total of $1 ,000, an amount of $200 is allocated to the corporate retailer, while $233.33 is allocated to the first product, $300 is allocated to the second product and $266.67 is allocated to the third product.

The same methodology may be adopted to record the media expenditure value for other mediums of advertising. For example, with print media there may be five advertised items on a full page displaying the advertiser's logo, four products taking up the same space and a fifth taking double the space of the others. The advertiser's logo and each advertised product would attract its rightful cost according to the amount of size and space used, all totaling 100% of the full page cost.

Media or advertising expenditure is directly linked to or associated with the product being advertised and appropriate costs get apportioned directly to those particular products depending on advertisement size, length of time and cost utilized solely by that particular product or service being advertised.

The units of measure module 46 of the media profiling system 30 may further record specific data on, e.g., a value of, units of measure relating to products or services, such as number of units of measure. Additionally, the units of measure module 46 may also record the unit gross profit margin relating to the products or services. As mentioned, these products or services may be advertised products or services which are the subject of the media campaign. Alternatively, the units of measure module 46 may record data on units of measure of unadvertised products or services. It will be appreciated that the unadvertised products or services may be related to or associated with the advertised products or services and are selected as described above. For example, if a particular model of a Nokia mobile telephone is the subject of an advertising campaign, the units of measure module 46 may also record units of measure data on similar Nokia mobile telephone models. The sale information on unadvertised products may be spin-off sales as a result of the advertising on the advertised products and this spin-off effect may have to be taken into consideration in order to efficiently profile the media expenditure.

Figure 7 shows a user interface where different options may be selected by a user of the system to either record data on media spend, register units of measure (sales) (e.g., the number of units sold), manage media, access flighting sheets or import alien file formats. The flighting sheets, which may comprise a schedule of television programs, may also be captured and stored by the media profiling system.

Figure 8 shows an example embodiment of yet another user interface in the form of a web-page 120 which is to be presented to a user of the media profiling system 30 in order to obtain specific information on the units of measure data e.g., units of sale of products or services which have been pre- registered through the use of the web-page of Figure 5.

The units of measure module 46 may record units of measure data in the form of units of measure values for a predetermined sales period in a predetermined sales interval, for example, daily intervals over a period of a month, as is shown in Figure 8. As mentioned above, the units of measure module 46 may further record units' gross margin relating to the products and services. For each advertised or unadvertised product the units of measure value and gross profit margins may be recorded and stored in the database. Depending on the pre-registration process, these values may be recorded with reference to any one of the criteria that has been predefined. For example, Figure 8 shows that units of measure values are recorded per advertised product 122.1 , 122.2, 122.3 and 122.4, as well as per store where the product has been sold (shown for example by reference numerals 124.1 to 124.5). It will aiso be appreciated that the data (values) may be captured for different intervals or periods, e.g., per week, month or the like, or that the units of measure module 46 or another appropriate module may collate this information into different intervals or periods.

The predetermined expenditure intervals may be linked to corresponding predetermined sales intervals. Alternatively, predetermined expenditure intervals may be associated with different predetermined sales intervals. For example, a predetermined expenditure interval for a particular day may be associated with a predetermined sales interval for a following day. That is, in circumstances where an advert is flighted at night, the predetermined expenditure interval should be associated with the following predetermined sales interval, e.g., expenditure interval is 1 February, while the sales interval is 2 February.

It will be appreciated that, in most cases, a certain level of sales of a particular product would have been achieved without any expenditure on media campaigns, tt may therefore be of value to determine or record a base or natural units of measure value (NUL) which is representative of the units of measure prior to the start of the media campaign, as well as a media generated units of measure value (MGU) which is representative of the sales or units of measure that were specifically generated in response to a particular media campaign. Typically, the totai units of measure value comprises at least the base or natural units of measure value (NUL) and the media generated units of measure value (MGU), although other factors may contribute to the total units of measure value. For example, other factors may include depreciating factors such as a level of saturation during the media campaign, or the like. The interfaces described above show that the units of measure module 46 may be adapted to record data on unit sales of products or services during a manual process in which the presentation module 42 provides the user with a web-based form. However, the media profiling system 30 may also include a communication interface 48 to receive a file that contains units of measure information from the user. This communication interface 48 may plug in to the back end of the media profiling system 30 and may receive the file, which may be a text export from the various software sales applications different stores may use.

Figure 9 shows an interface which is used by the communication interface 48 to upload a particular text file to the media profiling system 30, once the text file has been received. The media profiling system 30 is adapted to import the media expenditure and schedule data electronicaliy using a pre- formatted file through the interface.

The units of measure module 46 may be adapted to access the received file and to parse information in the file thereby to obtain data on the predetermined unit saies of products or services with relation to different fields of information, e.g., product range, chain/store where sale has been made, geographical area of sale etc.

In an example embodiment, the media profiling system 30 also comprises a media cost per unit (MCPU) calculator 50 which caiculator is primarily responsible for the analysis and processing of expenditure data and units of measure data thereby to ensure media profiling. The MCPU calculator 50 calculates a media cost per unit (MCPU), e.g., various media cost per unit values, for particular intervals over a period of time of the media campaign. A standard media cost per unit (MCPU) is calculated by dividing a media campaign expenditure vaiue with the value associated with the units of measure data for the same period. An adjusted MCPU value (described in more detail beiow) is caiculated by dividing a media campaign expenditure value with the units of measure value, but considering an interval or media reaction time (MRT) factor which is calculated as set out below.. Typically this division will be dependent on the associated intervals for which the data has been captured.

The MCPU calculator 50 may further calculate a combined media cost per unit of unadvertised products or services for the media campaign by dividing the media expenditure value with the units of measure value for both the advertised and unadvertised products or services, while the presentation module 42 may provide the calculated combined media cost per unit to a user, as a comparison to the calculated media cost per unit of the advertised goods or services.

In one example embodiment, it is the MCPU calculator 50 which associates different expenditure intervals with units of measure intervals, it may also, in one example embodiment, be the MCPU calculator 50 that aggregates data for different intervals into combined intervals, thereby to provide more comprehensive media cost per unit results.

Where the predetermined expenditure intervals are linked to corresponding predetermined sales intervals, the time period between the start of the media campaign and where the media campaign affects the sale of the advertised product, i.e., where there is a variance in the units of measure resulting from the campaign, is calculated by the MCPU calculator 50. This time period is the media reaction time factor (MRT), which factor is used to determine or evaluate the efficacy of the media campaign. Therefore, the MRT factor is the time elapsed from flighting an advertisement, independent of the type of 'media' used, until the effect thereof is noticed in the sales volume of the particular product, promoted by the collective advertisements.

For example, the MRT factor may be 1 day when there is a delay of one day before there was a change (or variance) in the MCPU of the advertised goods. Different advertisements influence sales differently. Superior advertisements would dominate the stimulation of sales, but due to the diversity of the market to be reached by an advertisement for a specific product, a related diversified media-approach is taken towards marketing a product.

By evaiuating the MRT it is possible for the system, and in particular the MCPU calculator 50, to isolate a particular advertising group of media or placements that caused a positive or negative effect on the MCPU. This enables the MCPU calculator 50 to identify the best types of media campaigns, when and where to flight advertisements, mediums of advertisements etc.

Apart from evaiuating a variance (e.g., rise or fall) in the MCPU value to determine a MRT factor, the expenditure data and units of measure data may alternatively or additionally be processed as described below in order to determine the MRT factor.

In analogy to wave functions, the fluctuation in media expenditure and consequent fluctuation in sales volumes obtained, both the units of measure values and the media expenditure may be represented by wave functions.

The units of measure values are simplified by starting off with a single product, which is then later on expanded by adding more products of the same brand. The media-part of the problem is complicated by the variety and typical fluctuation of media expenditure. In addition to these, it is also required to take into account the fact of so called natural sales (i.e., values for natural units of sales), which are sales made without the influence of media, opposed to 'media-generated' sales (i.e., media generated units of measure value).

The following equation may be used to present collective media expenditure, which is a La Place notation of a wave function:

1 δ²ø M

V²0_M = — . δt² AM = amplitude of a media expenditure curve

With the above media expenditure, it was taken into account that the wave function represents the cumulative effect of individual wave functions, each referring to a specific advertisement.

The following equation is used to represent the units of measure {sales volume):

1 δ²φ_s ψ^{ψs =}τ_s-w

φ_s = amplitude of a units of measure (sales volume) curve

By the following Fourier Transforms, noise was filtered from both functions.

ølf] = f f(t)e-'^ωtdt in this case i = V¹T

From the above equations, a so-called wavelength was obtained, say λ_M for media expenditure and λ_s for units of measure, from which time periods T_M and T₅ are determined.

The Fourier Transform of the superimposed of these two wave functions allows obtaining the so-called MRT (media reaction time) factor, e.g., the difference between the two time periods T_M and T_s.

It is to be appreciated that the interpretation of the MRT factor may be complex as, for some products, with extremely short media reaction time, the MRT factor may need to be treated differently. A parameter used for this distinction, is the difference between the two periods, T_M and T_s. The practical value of the media reaction time (MRT) factor is simply to be able to make a proper time-shift between two values recorded for media expenditure and units of measure. With this corrected correlation between these values, it is possible to determine the natural sales level and the superimposed media-generated sales more accurately.

Therefore, in effect, when the MCPU calculator 50 associates different expenditure intervals with units of measure intervals, an adjusted MCPU value is calculated which already takes into effect the media reaction time factor.

From the above equations, in order to return the wave functions again to a discrete particle character, for ranking the components of the collective media expenditure, the Euler equation of momentum may be applicable.

By effectively allocating a so-called weight factor, the discrete, individual contributions of particular media campaigns or advertisements may then be ranked by the MCPU calculator 50, in order of effectiveness.

The two sets of values for media-expenditure and units of measure recorded may for instance be transformed to two new variables using the following equations:

Y - ∑U{A_s sin (^r)] [2]

where MRT_M is a measure of the period of the media wave function (λ = 1/T); and where MRT_S is a measure of the period of the sales (units of measure) wave function (λ = MJ); The advantage of this transformation is the smoothing of the data for further evaluation of the trends of the media expenditure.

The MCPU calculator 50 may additionally be adapted to calculate a saturation point indicating that a "ceiling effect" associated with a particular media campaign has been reached. This effect indicates that a point of media wastage or overspent has been reached during the media campaign as the units of measure value does not increase linearly with expenditure on a media campaign. The ceiling effect may be calculated per advertised products, category and medium type and provides an indication on the period a media campaign is to be run and maximum media spend to be used, whereafter media expenditure on the specific campaign may no longer have the desired effect.

Following from the above, it is evident that with increasing media expenditure, sales (units of measure) may either increase linearly, or it may taper off as there may be progressively less unite of sales as a ratio on media expenditure. This curve may be theoretically be represented by the following equation:

/ _ (media expenditure)-*.

Sales - (Projected Sales) I l - e {shape factor^, s^«o )

The MCPU calculator 50 accordingly statistically tests the recorded data to determine whether the recorded data follows a linear or a tapering off curve.

A linear curve would indicate that no change in the current pattern of spending on media is recommended, while in the case of an exponential tapering off curve, an indication was observed for possible media wasting.

In this latter case, the 'turning-point' is calculated, by differentiation of the above curve, and setting it equal to 1. The reason for this is to find the point where the ratio of sales to media expenditure would reach 1. Altematively, the following equation may be used (a mirror function of the above) to simplify solving the problem:

With the value of b determined by:

X and Y are the values as calculated in accordance with the equations [1] and [2],

And the value for S₀ is determined by: i∑L inn jSLiM

S₀ =J * ^"^^"I

In general the gradient of the curve is given by

At the turning point, the gradient is equal to 1, therefore:

This value of X represents the media expenditure value where the gradient of the curve indicates the optimised expenditure on media and that further expenditure may result in wastage. However, from practical experience it has been proved that this value may be exceeded a bit.

Figure 10 shows an example embodiment of a graph that may be presented to a user. The graph indicates fluctuating media cost per unit values in comparison to a maximum threshold level for media wastage. Where the media cost per unit curve exceeds the vaiue of the maximum threshold line curve, it is indicative that media expenditure is no longer optimal.

The presentation module 42 is to provide the calculated media cost per unit to a user, preferably as a graphical presentation, e.g., a table or a graph. For example, the presentation module 42 may provide the user with different options as to the presentation of the information. Figure 11 shows a user interface where a user is presented with the following options:

• Calculate and Display Daily MCPU

• Calculate and Display Weekly MCPU

• Calculate and Display Monthly MCPU

• Daily MCPU - Single Period {or interval)

• Daily MCPU - Multiple Periods

• MCPU by Distribution Channel

• MCPU by Region and Area

• MCPU by Category, Sub-Category and Product

• Sales on Media Spend - Weekly Analysis

• Compare Different Campaigns

• Analyse D.O.W. (Day Of Week) Trends

• Monthly Recap

From the above, it is evident that the MCPU value can be calculated in terms of various associations, e.g., product, distribution channel, category etc., as set out above.

The media cost per unit calculator 50, in association with a reporting module, accordingly performs comparative analysis on different dimensions or parameters, coupled to the units of measure and the media expenditure, to evaluate the media, the products, the periods, etc.

Once the user has selected any of the abovementioned options, further options may be presented to the user in order to select particular periods, intervals, or display options. Some of these options are shown in the user interfaces of Figures 12, 15 and 17,

Through the interface shown by Figure 12, the user can select a graphical presentation of the standard media cost per unit, as well as an adjusted media cost per unit for a particular month, and this data is then presented to the user, in one example embodiment as a table (shown in Figure 13 as a graph of standard MCPU values). In Figure 13, the MCPU (media cost per unit) column, indicated by reference numeral 140, shows the different media cost per unit values for advertised products or services (resulting from dividing the media expenditure value with the units of measure value) relating to particular media campaigns. It will be appreciated that the lower the MCPU value, the more efficient a particular media campaign has been run, as the MCPU value effectively provides a measure of how much it had cost in advertising to sell/provide one units of measure, e.g., to sell one unit of a product or service.

The MCPU 2 column, indicated by reference numeral 142, shows the combined media cost per unit values for both advertised and unadvertised products or services relating to the same media campaigns. It will be appreciated that the combined media cost per unit values should be an equal value (in the event that no related unadvertised products have been taken into account) or a lower value than the MCPU value, as more sales would have been generated from the media campaign with unadvertised products or services.

The presentation module 42 may also include drill-down functionality to show details of the goods or services. For example, in selecting the detail tab indicated by reference numeral 144 in Figure 13, the details of the particular units of measure may be shown. Figure 14 shows an example of a drill down screen indicating the store sales and store information, as well as the number of units sold, the group MCPU and details of the type of media used are shown. It will be appreciated that this information may also include a product description, unit price, sales medium, geographical area of sale or time of day of sale. Further drill-down functionality may also be provided in that by clicking on the medium type (e.g., television), the television programming details of Figure 22 may be presented to the user. Although not shown, a user can select a graphical presentation of the MCPU values by category, sub-category, product, distribution etc, with further drill down capabilities provided.

Figure 15 shows a user interface where a user can select a bar or line graph for the presentation of monthly media cost per unit information. For example, the line graph of Figure 16 shows an example of the graphical analysis of the media cost per unit module 50 performed on two different time periods (November and December 2006), thereby comparing the media cost per unit of the two periods. From this information, a user should be able to determine possible trends in media expenditure and the value of units of measure (e.g., the sale of products or services).

Similarly, Figure 17 shows a user interface where a user can select to view weekly media expenditure on units of measure data. An example of this is shown in the bar graph of Figure 18, wherein the % units of measure generated in a particular month is compared to the % media expenditure in the particular period, but on a weekly basis. The significance of this analysis is that a user could identify and minimize "wastage" (whilst considering the MRT factor), e.g., if the MRT factor is just one day, in week 3 the % units sold were very low in comparison with the % media expenditure. Taking this analysis into account, a user spend less in week 3 and would be able to take better advantage of the budget expenditure where units are "maximized", e.g., week 1.

Figures 19 and 20 show similar graphic representations of information that is presented to a user, where Figure 19 is similar to Figure 18, while Figure 20 compares the % media expenditure on a particular day against the % units of measure generated in relation to the media expenditure. From this information, a user would be able to identify trends, in order to spend more of an allocated advertising budget during periods where higher units of measure are recorded (e.g., Wednesday, Thursday and Friday as opposed to Saturday to Tuesday).

Lastly, Figure 21 shows a table where the media cost and total units of measure generated are displayed in relation to whether the results were good or bad.

It will be appreciated that this information provides a user with the means to identify better resulting media expenditure in terms of period and trends. For example, the user may be able to determine that media expenditure provides better results over pay-days, or perhaps that expenditure during certain weeks or particular days typically render better efficiency over others. The user would then be able to intelligently select time periods when the media expenditure would produce better results and less expenditure when this produces worse results, thus maximize valuable budget spend for clients where it would be most valuable to a client's business.

The drill-down functionality may further aϋow the user to drill down in the screen shown in Figure 13, with the presentation module 42 able to access additional information that may be stored in the database 34. For example, and as shown in Figure 22, this information may relate to detailed program schedules and time slots, in order to enable a user to assess why a certain media campaign may have been more or less successful. The user would then be able to repeat campaigns on marketing efficient days, which may relate to particular programs, television channels and time slots.

The system 30 and in particular the MCPU calculator may further be adapted to provide projections by inserting an expected budget per product based on existing trends provided by the media profiling system, e.g., based on the MCPU. The system may further calculate projected unit sales, e.g., by category, distribution channel, group, etc. The system may also be adapted to provide the best possible media and spots to be used for particular products based on previous results and provide a suggested media schedule based on most efficient data used.

Through a media ranking process and buiit-in intelligence, the system is capable of automating and identifying good and bad placements of media campaigns, thereby to enable media planners to more easily identify good return on investment placements of media campaigns and allow them to omit the negative return on investment placements in order to improve the client's return on investment.

For example, a report generation module, not shown in Figure 2, may identify or record events affecting the units of measure. These factors may be customer or industry specific and may include (for example in a retail environment):

• Stores being out of stock;

• Store distribution (Sudden increase or loss of stores);

• Competitor activity (e.g.: lower prices);

• Pricing;

• Media planning (e.g.: advertisement in wrong slot);

• Noπ flighting of planned advertisements.

Once these factors have been recorded by a user, the MCPU value may be based on "normalised" information for the purpose of forecasting. For example, the MCPU values of a store following a campaign the previous year may have been very high due to an uncommon shortage of stock of the advertised products, resulting in abnormally low sales numbers. If the user determines that sales would have typically been 33% higher, the system can allow for the MCPU to be adjusted accordingly, not on historical values but for improved forecasting. This normalisation encourages more sound decision making as these decisions are then based on more relevant information.

The system, in particular the MCPU calculator and the report generation module, would further have the ability to rank all media campaigns, e.g., in order of preference - by level of efficacy against a client's advertised products. Ranking may be displayed with weighting, genre, units of measure, medium, flighting date, flighting code and timeslots.

On the following pages, a specific example of the methodology that the MCPU calculator will apply for ranking advertisements is discussed:

Although detailed media cost is known per product {i.e., through recording such data), this cost is not directly known in terms of how much sales a particular advertisement has generated.

Variations in the types of advertisements used for the same product causes fluctuations in sales generation. The following mathematical methodology implemented by the MCPU calculator in accordance with the invention was developed to filter through the fluctuations in sales generated by a varying marketing campaigns and advertisements. With this method, a process was established by which guidance is given to users concerning improved profitable advertising.

The basis of the filtering model was set to be as objective as possible within the freedom allowed by the data available. This means that the cost or expenditure element of media should not dominate. However, the cost of media is a crucial element to determine profitability. For this very reason, the MCPU value (media cost per unit sales) is used. Over and above this, a cross check parameter, be, is used to verify the distinction between 'good and bad' advertisements.

Data that is recorded prior to calculations:

• Detailed Media ID - an identification number for a media item

• Media cost per flight (per product)

• Tota I med i a cost/expe nditure per day

• Total product sales per day, per store, per area,

Principles applied by the MCPU calculator: • Determine the level of 'natural sales',

• Determine the media effect on sales, in terms of the type of media, and other media !D's.

In order to determine the level of correlation between sales and media expenditure, the following test was performed:

From sales data (e.g., units of measure values), the day numbers of the 5 lowest (non-zero) turning points in sales curve were determined, as well as a mean spacing (e.g., number of days) between these 'Low-Sale' days.

From media expenditure data, the day numbers for 5 lowest turning points in the media expenditure curve were determined as well as a mean spacing (e.g., number of days) or period between these days.

After this was determined, it was necessary to test the hypothesis that the two means (number of days between lowest turning points in sales and media expenditure) are related (statistically the same). The hypothesis was tested with the following equations:

XmI

Where x_s was the number of days

Sample sum of squares:

(n_m - 1)_4 =

The t-statistic test:

It has been assumed that the hypothesis is to be accepted at 95% level of significance, if t > -t_.O5 where t_O5 is obtained from the t-statistical table at (n_s + n_m - 2) degrees of freedom.

It should however be noted that should this test indicate that the hypothesis is to be rejected, the test could be repeated at a lower level of significance (90%).}

It may be an option to take this test into account and the MRT factor may be cross checked with the mean values obtained above, to apply built-in operation required, shift media-data back with the number of days, equal to this "updated" MRT factor.

The MRT factor could also be interpreted as an immediate media reaction, although the calculated MRT factor could be equal to a number of days. This case is derived from the statistical analysis shown above, where sales and media expenditure is practically 'the same', both in means and variances.

The following methodology is applied to rank media data:

Again, from the sales data, the days with the highest turning point in the sales curve are to be determined. From adjusted media-data (with respect to appropriate day number taking the MRT factor into account), identify the type of media involved with high sales volume. This is to be compared with the type of media involved with low sales volume. The steps to determine the media ranking may comprise: • Allocating a weighted media by taking into account the currency-value of the applicable media;

• From the adjusted media-matrix (shifted in MRT days) and sales volume per day, calculate total MCPU value per day;

• Rank the days from high MCPU (bad) to low MCPU (good) associated with the type of media applicable in each case; and

• Sort and count presence of type of media along with the ranking.

By using the mean sales volume per day, over the period considered, as reference, the presence or absence of the type of media is to be checked, in order to correlate this with the sales generated.

The 'good' advertisements will be associated with the low MCPU -days, and the less sales generating advertisements, will be associated with high MCPU -days. In some cases, though, other factors may dominate, such as a supplier being out-of-stock. This is then checked for zero-sales.

The above methodology is now described in terms of the table and mathematical equations:

Sum of occurrence of same 'type' of advertisement (e.g., flighting during

CSI) - horizontal in table

Sum total media cost for each of these 'same' advertisements - horizontal in table

For each day, sum the total media spending - vertical in tabie

For each day, determine the total sales and finally the grand total of sales over the period of n days.

Daily MCPU's, MCPU₁ for day i.

Total MCPU over the period of n days

(note that n, is the number of times the same type of advertisements occur)

Total media expenditure over n days MCPU₁- = ■

Total units of measure (sales)over n days

Mean MCPU for all advertisements over n days

MCPU_T mcpu = ^■ n_τ

Weight per advertisement according to frequency of occurrence

U_j-mcpu MCPU₇

MCPU per advertisement per day (derived)

mc-pu_ιs = YfICpU₁

Similarly the units of measure per advertisement per day, over n days (derived) salesi_j — X sales_z

The Boolean be when media^ost,₎ =0 then be,, = 0 and when media^ost._j > 0 then be_tj = 1

The total be per advertisement is therefore provided by the equation: beT_j = V be,

I=I

The tota! be per day:

"^■ads beT_L = Y^ be_tI j=i

The grand total of all be values represents the total number of advertisements flighted during the n days, and is calculated by:

nαcJs ⁿads n

A weight factor, Wbe_h for a specific type of advertisement, which is based upon the frequency of occurrence of that type of advertisement, over the period of n days, is calculated by:

From the total number of advertisements flighted on a specific day, the weight factor for each type of advertisement is used to calculate the weight of each advertisement. This weighted advertisement is then calculated by:

All advertisements are now ranked or sorted according to derived sales, derived MCPU and finally also according to Wbe_u, while keeping track of the identification of the advertisement.

Figure 23 shows a table listing various media campaigns which are ranked according to media cost per unit values and level of efficacy. For each campaign or advertisement, details are given on the flighting time of the advertisement, the genre of the television program during which it was flighted, the television channel on which it was flighted as well as the date of the flighting. The first column of the table shows the ranking of the campaign, whiie the last column of the table shows the MCPU value. It is evident from the table that campaigns with low MCPU values have a better ranking than campaigns with high MCPU values.

The report generation module wouid further report on the effects of competitor activity, where appropriate, plot the "Ceiling Effect" which exists on media expenditure resulting from unit sales not reacting linearly to the expenditure (or as calculated by the MCPU calculator), would measure media wastage in the case of an over-spend or saturation point scenario, and may further plot the optimum level of expenditure and clearly define the efficacy of each spot by displaying the media ranking.

It is evident from the above that the MCPU values calculated for media campaigns most often become the basis and gauge by which the system according to the invention gains its insights to qualify the efficacy of all advertising campaigns, determines business intelligence and levels of efficacy derived from an advertiser's products or services and the various media placements. The results of the data and business insights produced by the system provides advertisers and users with the ability to improve their return-on- investment, stock management, production requirements, warehousing, cash flows, forecasting and overall delivery.

The MCPU values will additionally help a user to determine the level of effectiveness of a new advertising medium (compared to another), thus be able to deduce whether worth repeating (if MCPU value decreased or improved) or not worth repeating (if MCPU value increased or declined).

Figure 24 shows a high-level entity-relationship diagram 160, illustrating various tables or data structures that may be stored and maintained in the database 34 by the registration module 40, the expenditure data module 44, the units of measure module 46 and the MCPU calculator 50.

Media profiling data 162 is gathered and generated by the various modules of the media profiling system 30. As mentioned, registration data 164 may be recorded in a registration table during a registration process. The registration module 40 may, for example, record a customer name, customer details (e.g., an e-mail address), customer account details, customer login, customer password. It will be appreciated that the registration module 40 may record any other details that relates to a particular customer or user.

Campaign data 166, units of measure data and values 168 and media expenditure data and values 170 may further be recorded by the expenditure data module 44 and the units of measure module 46. For example, campaign data 166 may include a campaign description, information on goods to be advertised during the campaign, non-advertised (or related goods), information on the advertising medium to be used, information on where the products or services will be sold or provided, as well as any other relevant information.

Units of measure data 168 recorded by the units of measure module 46 may include details on the units of measure, e.g., units of the sale of both advertised and non-advertised goods or services. For example, units of measure data may comprise the number of units sold in a particular store on a particular date.

The expenditure data 170 recorded by the expenditure data module 44 may include specific information on a media campaign, for example, the period or date when the campaign was run, the products or services to which the campaign relates, related products or services which may be sold in response to the media campaign and sale details of these products or services sold.

Information generated by the MCPU calculator 50, e.g., MCPU values, media reaction time factors, ceiling effects and saturation points and the like, may also be recorded in a media cost per unit table 172. This table 172 may link information of the other tables, for example campaign information, units of measure information and expenditure data with generated values of the media cost per unit of particular products.

Additional media campaign information 174, for example program schedules as shown in Figure 22, may also be stored and be associated with information in the other tables.

Turning now to Figure 25, a flow diagram of an example method 180 for providing media expenditure profiling is shown, in accordance with an example embodiment. In one example embodiment, the method 180 may be implemented by the media profiling system 30 of Figure 1.

The method commences with a user registering a media campaign through the use of a web- interface, with the expenditure data module 44 and the units of measure module 46 prompting the user and recording relevant media campaign information (block 182).

At biock 184, the expenditure data module 44 records expenditure data in the form of a media campaign expenditure value on the registered media campaign. Typically this data is recorded for a particular predetermined period and for predetermined intervals, e.g., per day, week or month.

Similarly, as shown by block 186, the units of measure module 46 records data on units of measure relating to products or services, the products or services being the subject of the media campaign. In one example embodiment, shown by block 188, the units of measure module 46 may also record data on units of measure relating to unadvertised products or services, the unadvertised products or services being related to the advertised products or services.

As mentioned above, the units of measure data of advertised or unadvertised products or services may be recorded for predetermined sales periods and intervals, for example, a day, a week, a month or the like.

The MCPU calculator 50 may associate the predetermined expenditure intervals during periods with the same intervals of the predetermined sales period. Alternatively, the media cost per unit module 50 predetermined expenditure intervals may be associated with a different predetermined sales intervals thereby to enable the generation of an adjusted media cost per unit value . (Shown by block 190)

As shown by block 192, the MCPU calculator 50 now calculates standard and adjusted media cost per unit values for particular intervals within periods of the media campaign by dividing the expenditure data with the units of measure data of the advertised products or services and/or unadvertised products or services. The MCPU calculator 50 also determines a media reaction time factor when there is a delayed response in the value of the media cost per unit, or alternatively may calculate an adjusted media cost per unit values as mentioned above. The presentation information provides this calculated media cost per unit value to a user, whether through generated reports, graphs or other graphical presentations (block 194). As mentioned, the calculated media cost per unit value of advertised products may be presented to the user as a comparison to the calculated media cost per unit of the unadvertised products or services to a user, and may be provided as a table or graph. A user may also select how this information should be displayed.

The present invention therefore provides a measure of factual information especially relating to a client's business, media expenditure and units of measure generated through such expenditure, rather than inaccurate sampling information. This is possible as the media expenditure is shown in relation to the number of units of measure, e.g., sales units.

The system is accordingly adapted to calculate various trends relating to the efficiency of media expenditure, i.e., the media ranking will define the "weighted" results of every spot or media flighted in order of efficiency and the system may provide documentation on the efficacy of one media campaign verses another, or documentation on the efficacy of different aspects of the media campaign, e.g., preferred media used, time of day, day of the week, genre etc. Based on these types of comparisons, users would be able to evaluate which advertising medium may deliver better sales results over other mediums, in particular also as to when and where such a campaign needs to be run.

Users would also therefore be able to better plan their cash flow, stock requirements, warehouse space, distribution per customer, field staff and other factors which have an impact on their business.

In particular, when the present invention is compared with the existing Telmar reports (in the case of television), the Telmar report may for example reflect identical audience ratings and cost per 30 second spot over many separate television programs and offer no distinction. However, the present invention would provide more efficient results as the MCPU values would give different results for each of the advertised products during the various television programs and therefore clearly provide the cost to sell any unit of product across each advertisement that has been advertised.

Figure 26 shows a diagrammatic representation of machine in the example form of a computer system 300 within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a server computer, a client computer, a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

The example computer system 300 includes a processor 302 (e.g., a central processing unit (CPU) a graphics processing unit (GPU) or both), a main memory 304 and a static memory 306, which communicate with each other via a bus 308. The computer system 300 may further include a video display unit 310 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 300 also includes an alphanumeric input device 312 (e.g., a keyboard), a cursor control device 314 (e.g., a mouse), a disk drive unit 316, a signal generation device 318 (e.g., a speaker) and a network interface device 320.

The disk drive unit 316 includes a machine-readable medium 322 on which is stored one or more sets of instructions (e.g., software 324) embodying any one or more of the methodologies or functions described herein. The software 324 may also reside, completely or at least partially, within the main memory 304 and/or within the processor 302 during execution thereof by the computer system 300, the main memory 304 and the processor 302 also constituting machine-readable media.

The software 324 may further be transmitted or received over a network 326 via the network interface device 320.

While the machine-readable medium 322 is shown in an example embodiment to be a single medium, the term "machine-readable medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term "machine-readable medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention. The term "machine-readable medium" shall accordingly be taken to include, but not be limited to, solid- state memories, optical and magnetic media, and carrier wave signals.

Claims

CLA(MS:

1. A system to profile media expenditure, the system comprising:

an expenditure data module to record expenditure data and an expenditure value relating to a media campaign;

a units of measure module to record data on units of measure and a units of measure value relating to products or services which are the subject of the media campaign, the units of measure value representing unit sales of a particular product or service,

a media cost per unit (MCPU) calculator to calculate at least one media cost per unit value for the media campaign by dividing the expenditure value with the units of measure value; and

a presentation module to provide the calculated media cost per unit value to a user.

2. A system as claimed in claim 1 wherein the expenditure data module records expenditure data for predetermined expenditure intervals.

3. A system as claimed in claim 1 or claim 2 wherein the units of measure module records data on units of measure for predetermined sale intervals.

4. A system as claimed in any one of claims 1 to 3 wherein the media cost per unit (MCPU) calculator links predetermined expenditure intervais to corresponding predetermined sales intervals and calculates a media cost per unit value for each of the linked intervals.

5. A system as claimed in any one of claims 4 wherein the media cost per unit (MCPU) calculator links predetermined expenditure intervals to different predetermined sales intervals based on a media reaction time factor.

6. A system as claimed in any one of claims 1 to 3 wherein the media cost per unit (MCPU) calculator calculates the media reaction time factor based on the time it takes for the media cost per unit value to vary, whether increase or decrease, due to the impact of a media campaign after the start of the media campaign, the media reaction time factor being used to determine the efficacy of the media campaign.

7. A system as claimed in claim 1 wherein the units of measure module further records data on units of measure and units of measure value relating to unadvertised products or services, where the unadvertised products or services are related to the advertised products or services.

8. A system as claimed in claim 7 wherein the media cost per unit calculator calculates a combined media cost per unit for the advertised and unadvertised products or services by dividing the expenditure data with the units of measure for both advertised and unadvertised products or services.

9. A method for media expenditure profiling, the method comprising:

recording expenditure data including an expenditure value which relates to a media campaign;

recording data on units of measure and a units of measure value relating to products or services which are the subject of the media campaign, the units of measure value representing unit sales of a particular product or service; calculating at feast one media cost per unit (MCPU) value for the media campaign by dividing the expenditure value with the units of measure value; and

providing the calculated media cost per unit to a user.

10. A method as claimed in claim 9 wherein the units of measure value is a number of unit sales of a particular product or service, access provided to a particular product or service or a number of applications received for a particular product or service.

11. A method as claimed in claim 9 or claim 10 wherein the method further comprises calculating multiple media cost per unit values over the media campaign according to predetermined intervals and analysing these multiple media cost per unit values to determine trends with regard to the return on advertising expenditure.

12. A method as claimed in any one of claims 9 to 11 , further comprising recording expenditure data on the media campaign for predetermined expenditure intervals and recording data on units of measure relating to products or services for predetermined sale intervals,

13. A method as claimed in claim 12 wherein the predetermined expenditure intervals are linked to corresponding predetermined sales intervals.

14. A method as claimed in claim 12 wherein the predetermined expenditure intervals are associated with different predetermined sales intervals based on a media reaction time factor.

15. A method as claimed in claim 14 wherein the media reaction time factor is calculated based on the time it takes for the media cost per unit value to vary, whether increase or decrease, due to the impact of an advertisement campaign after the start of the media campaign, the meclia reaction time factor being used to determine the efficacy of the media campaign.

16. A method as claimed in claim 15 wherein a base or natural units of measure value is determined prior to the start of the media campaign and wherein a media generated units of measure value is calculated once the media campaign has started by subtracting the base or natural units of measure value from the units of measure value recorded during the media campaign.

17. A method as claimed in any one of claims 9 to 16 further comprising calculating a point of media expenditure wastage or overspent during a media campaign where the units of measure value does not increase linearly with expenditure on a media campaign.

18. A method as claimed in any one of claims 9 to 16 further comprising recording data and a value on units of measure relating to unadvertised products or services, where the unadvertised products or services may be related to the advertised products or services.

19. A method as claimed in claim 18 further comprising:

calculating a combined media cost per unit for the advertised and unadvertised products or services by dividing the expenditure value with the units of measure value for both advertised and unadvertised products or services; and

providing the combined media cost per unit to a user, preferably as a comparison to the calculated media cost per unit of the advertised goods or services.

20. A method as claimed in any one of claims 9 to 16 wherein recording of data on units of measure relating to products or services is a manuai process or an automated process of receiving a file including expenditure data from a user.

21. A method as claimed in claim 15, further comprising determining a ranking of muitiple media campaigns by determining adjusted media cost per unit values for multiple media campaigns where the media reaction time factor is taken into account in associating the predetermined expenditure intervals and the predetermined sates intervals.

22. A method as claimed in claim 21 and claim 16, wherein the ranking of multiple media campaigns is determined by calculating media cost per unit values for multiple media campaigns from the generated units of measure value.