HK1110675A - Computerized system for performing a retail sales analysis - Google Patents

Description

Method for performing retail analysis

Background

The present invention relates generally to transaction data analysis and, more particularly, to a method for enabling a remotely located user to analyze retail data (or other transaction data) collections (compilations) via a computer system.

In order to succeed in the ever changing retail industry, many companies wish to maintain a constant view of market conditions. Demand for products and the price a consumer is willing to pay will vary continuously in response to consumer tastes, competitor activities, and overall economic situation. To win in a retail market, both the retailer and the supplier need detailed knowledge of market conditions, which is preferably obtainable from sophisticated retail data analysis. Accordingly, retailers and their suppliers have begun to gather ever increasing collections of data from retail transactions so that they can notice trends that can be clearly understood from sales data.

To maximize the benefits derived from such a large collection of complex data, retailers and their suppliers need to have access to the data shortly after it is collected and perform highly specialized analysis on the data. The present invention satisfies this need.

Summary of The Invention

Example embodiments of the present invention provide a method for retailers and other authorized users (e.g., suppliers) to access and perform highly specialized complex analysis of retail and consumer data from remote locations using the internet or other connected computers. Typically, the data accessed is a collection of the following data: retail transaction data (e.g., data collected from an EPOS system), and/or consumer data (e.g., data collected from frequent shoppers or from loyalty cards used by consumers while shopping), and/or related data collected from time to time from any resource available to a skilled technician. By way of illustration and not limitation, such data may also include demographic data related to the consumer, or data related to the status of the product promotion.

In one exemplary embodiment, the system and service provided by the present invention is web-based, whereby authorized users can access the service from their remote desktop and deliver the complete analysis project to them via email when the analysis project is complete. With this embodiment, the minimal software that needs to be installed on the authorized user's computer includes a web browser (or similar) application and appropriate spreadsheet software. Further, in the exemplary embodiment, the items are generated as spreadsheet-based interactive reports (examples of which are described below), which are easily manipulated and thus made available for further analysis and presentation. The awareness (insight) gained from these items can lead to better decisions for new product investment, sampling activities, commodity procurement, classification, circulation, and other sales and market prioritization. In an example embodiment, these items are interactive, which enables a user to manipulate and extract information that is specific to the user's particular needs. Of course, while the exemplary embodiment is web-based, it is certainly within the scope of the present invention if the service is implemented in other computer implementations, e.g., the service may be implemented on a separate computer system using dedicated software or over an intranet or private network.

The present service/system is designed for key sales, marketing, category management/planning queries, and in addition, the present invention is designed to provide brand/SKU ratings and consumer awareness, such as:

which of our latest three marketing activities pushed the greatest growth in market share?

What profile does a member consumer of product X have? What were they also purchased?

How does the competitor's brand/SKU operate?

What impact/effect our new product launch has on categories?

What stores we should be engaged in-store sampling activities?

For example, an indication of whether or not the re-engagement was successful can be provided at an early stage by using these recognitions (i.e., does our engagement achieve the level of anticipated initial and repeat purchases compared to our competitors and categories; providing robust and detailed consumer information at the individual product level that can be used throughout commerce; and to plan future marketing activities by reviewing the consumer's buying patterns over a certain period of time (e.g., a year).

Accordingly, a first aspect of the invention provides a method for performing an analysis, comprising the steps of: providing one or more databases containing transaction and/or consumer data for one or more companies, wherein the transaction and/or consumer data contains one or more transaction records associating at least one product identification code with a consumer identification code; formulating an analysis project request via a user interface operatively coupled ("operatively coupled" means electrically coupled, coupled via a direct or indirect data link, or capable of being coupled via a direct or indirect data link) to a computer system that accesses the database; and in response to receiving the analysis item request, the computer system generates an item relating to the transaction and/or consumer data. In a more detailed embodiment, the user interface is on a network device operatively coupled to the computer system via a global computer network. In a more detailed embodiment, the network device is a web-enabled device operatively coupled to the computer system via the world wide web. In a more detailed embodiment, the method further comprises the step of downloading the item from the computer system via the world wide web or transferring the item from the computer system via the global computer network to a user computer operatively connected to the global computer network.

In an alternative detailed embodiment of the first aspect of the present invention, the one or more transaction records associate the product identification code with a transaction time and/or a transaction date. In a more detailed embodiment, the step of formulating the analysis item request includes the step of selecting an analysis item from a predefined list of available analysis items via a user interface. In another detailed embodiment, the predefined list of available analysis items includes:

an analysis item to provide a rate of repeated purchases of products associated with the product identification code by a consumer associated with the consumer identification code; and/or

An analysis item to provide a rate of cross-purchasing of products associated with the vendor identification code by consumers associated with the consumer identification codes; and/or

An analysis item to provide a comparison of the rate of purchase of products associated with the first vendor identification code and products associated with the second vendor identification code; and/or

An analysis item to provide a comparison of the rate of purchase of a product associated with a product identification code by consumers in different categories of purchasers, wherein a category of consumers may be defined based on demographic information associated with the consumer identification code and may be defined based on data derived from a shopping history associated with the consumer identification code and/or based on price sensitivity-related data associated with the consumer identification code.

In another alternative detailed embodiment of the first aspect of the present invention, the step of formulating the request for an analytical item includes the step of selecting one or more products from a list of available products.

In another alternative detailed embodiment of the first aspect of the present invention, the method further comprises the step of saving at least part of the analysis item request for reuse in formulating future analysis item requests.

In another alternative detailed embodiment of the first aspect of the present invention, the step of generating items is performed periodically repeatedly.

In another alternative detailed embodiment of the first aspect of the present invention, the one or more transaction records associate the product identification code and the consumer identification code with a transaction price.

In another alternative detailed embodiment of the first aspect of the present invention, the method further comprises the step of downloading the item from a computer system.

In another alternative detailed embodiment of the first aspect of the present invention, the method further comprises the step of collecting at least a portion of the transaction and/or consumer data from the shopper loyalty card data.

A second aspect of the invention provides a method for performing an analysis, comprising the steps of: providing one or more databases containing transaction and/or consumer data for one or more companies, wherein the transaction and/or consumer data contains one or more transaction records that associate at least a product identification code with a consumer identification code; generating, by a computer system accessing the database, items relating to transaction and/or consumer data; and communicating, by the computer system, the item to a user interface operatively coupled to the computer system. In a more detailed embodiment, the step of generating the item is repeated periodically. In an alternative detailed embodiment, the one or more transaction records associate the product identification code and the consumer identification code with a transaction price. In another alternative detailed embodiment, the item provides a rate of repeated purchases of the product associated with the product identification code by the consumer associated with the consumer identification code. In another detailed embodiment, the one or more transaction records associate a product identification code with a vendor identification code, and the item provides a rate of cross-purchasing of the product associated with the vendor identification code by a consumer associated with the consumer identification code. In another detailed embodiment, the one or more transaction records associate a product identification code with a vendor identification code, and the item provides a rate of purchase of the product associated with the first vendor identification code and the product associated with the second vendor identification code. In another detailed embodiment, the one or more transaction records associate a consumer identification code with a category of purchasers, and the item provides a rate of purchase of a product associated with the product identification code by consumers in different categories of purchasers.

A third aspect of the invention provides a method for performing transaction analysis, comprising the steps of: providing one or more databases containing transaction and/or consumer data for one or more companies; providing a computer system that accesses the one or more databases; obtaining parameters from a user for analysis of transaction data and/or consumer data via a computer interface provided by a computer system; the computer system feeds the acquired parameters to an executable job file; the computer system executing the executable job file on transaction and/or consumer data to return a result; and presenting the item reflecting the returned result to the user. In a more detailed embodiment, the parameters for analysis include parameters related to transaction metrics. In a more detailed embodiment, the parameters for the analysis include an analysis format identification, a retail product identification for the analysis, and a time frame identification for the analysis. In a more detailed embodiment, the analysis format involves:

the rate at which the consumer repeatedly purchases the product;

the rate at which a consumer repeatedly purchases a product at a particular type of company;

the rate at which consumers cross-buy a manufacturer's product;

the rate at which consumers cross-purchase manufacturer products at or through a particular company;

key sales metrics in a particular product category;

key sales metrics for the manufacturer's products;

key sales metrics for the manufacturer's product over time;

key sales metrics for a particular brand of product over time;

other retail products purchased by consumers of the manufacturer's products;

the location where a particular product is sold;

the location where the manufacturer brand product is sold;

the type of consumer purchasing the manufacturer's product;

consumer type of purchase vendor product over time; or

The type of consumer purchasing a manufacturer product at or through a particular company.

In another alternative detailed embodiment of the third aspect of the present invention, in the step of obtaining, the user is prompted to select at least one parameter for analysis from a menu containing a plurality of available parameters. In a more detailed embodiment, the user is prompted to select each parameter for analysis from a menu.

In another alternative detailed embodiment of the third aspect of the present invention, the computer interface is a web-based interface. In a more detailed embodiment, prior to the obtaining step, the method further comprises the step of verifying whether the user has access to the computer system.

In another alternative detailed embodiment of the third aspect of the present invention, the feeding step further comprises the step of integrating the obtained parameters with the segment of executable code to create an executable job file. In a more detailed embodiment, the segment of the executable code incorporating the acquired parameters is determined at least in part from at least one of the acquired parameters.

In another alternative detailed embodiment of the third aspect of the present invention, the item is presented as an interactive report, the method further comprises the step of generating the interactive report from the returned results, and the generating step comprises the steps of selecting an item template from a plurality of available spreadsheet item templates based on the analysis format, and populating the item template with at least a portion of the returned results.

In another alternative detailed embodiment of the third aspect of the present invention, the transaction and/or consumer data includes an identification of the purchased product, a quantity of the purchased product, a date of purchase, and a code associated with the particular shopping consumer.

In another alternative detailed embodiment of the third aspect of the present invention, the item is presented as a spreadsheet file. In a more detailed embodiment, the method further comprises the step of generating a spreadsheet file from the returned results, wherein the generating step comprises the step of selecting a spreadsheet project template from a plurality of available project templates based on the obtained parameters and populating the project template with at least a portion of the returned results.

In another alternative detailed embodiment of the third aspect of the present invention, the step of presenting to the user items reflecting the returned analysis comprises the steps of: informing the user that the item is available; and providing the user with access to the item after notifying the user and when the user requests access to the item. In a more detailed embodiment, the step of providing the user with access to the item includes the step of downloading the item to the user's computer. Alternatively, the step of providing the user with access to the item comprises the step of providing the user with access to the item by receiving the item via a web-based interface, via a web download, or by email.

A fourth aspect of the present invention provides a computerized system for performing an analysis, comprising: (a) one or more databases having transaction and/or consumer data for one or more retail companies, wherein the transaction and/or consumer data comprises one or more transaction records associating at least a product identification code with a consumer identification code; and (b) a computer system accessing the database, wherein the computer system is configured to perform the steps of: generating items relating to transaction and/or consumer data; and communicating the item to a user interface operatively coupled to the computer system. In a more detailed embodiment, the one or more transaction records associate the product identification code and the consumer identification code with a transaction price.

In an alternative detailed embodiment of the fourth aspect of the present invention, the item provides a rate of repeated purchases of the product associated with the product identification code by a consumer associated with the consumer identification code.

In another alternative detailed embodiment of the fourth aspect of the present invention, the one or more databases comprise one or more product records associating product identification codes with vendor identification codes; and the item provides a rate of cross-purchasing of a product associated with the vendor identification code by a consumer associated with the consumer identification code.

In another alternative detailed embodiment of the fourth aspect of the present invention, the one or more databases comprise one or more product records associating product identification codes with manufacturer identification codes; and the item provides a rate of purchase of the product associated with the first vendor identification code and the product associated with the second vendor identification code.

In another alternative detailed embodiment of the fourth aspect of the present invention, the one or more databases comprise one or more consumer records associating consumer identification codes with purchaser categories; and the item provides a comparison of the rates at which products associated with the product identification codes are purchased by consumers in different consumer categories. In a more detailed embodiment, the consumer category is defined based on demographic information associated with the consumer identification code. Alternatively, the consumer category is defined based on data (e.g., price sensitivity) derived from a shopping history associated with the consumer identification code.

In another alternative detailed embodiment of the fourth aspect of the present invention, the transaction and/or consumer data is obtained from shopper loyalty card data.

Brief Description of Drawings

FIG. 1 shows a schematic diagram of a system and software configuration in an example embodiment of the invention;

FIG. 2 is an example screen shot requiring a user to select a type of analysis item to be performed;

FIG. 3 is an example screen shot of a product group for which a user is asked to select for which to perform an analysis;

FIG. 4 is an example screen shot requiring a user to select a period during which sales data is to be analyzed;

FIG. 5 is an example screenshot summarizing an analysis item defined by a user selection;

FIG. 6 is an example interactive item for the example items generated from FIGS. 2-5;

FIGS. 7A-7J illustrate examples of interactive items generated in example embodiments of the present invention;

FIG. 8 is an example screenshot illustrating an item status for a particular user;

FIG. 9 is an example screenshot indicating a history of completed items;

FIG. 10 is an example screenshot for starting a subgroup creation process;

FIG. 11 is an example screen shot of a product listing several narrower ones of the wide categories that the user previously selected in creating the subgroup;

FIG. 12 is an example screenshot listing individual products within a user-selected group during subgroup creation;

FIG. 13 is an example screen shot of prompting a user to enter a name and description for a subgroup being created; and

FIG. 14 is an exemplary screen shot listing the newly created subgroup in a file tree format.

Detailed Description

In summary, the present invention provides users with considerable flexibility in requesting and generating analytical items relating to transaction and/or consumer data stored in one or more databases. In particular, exemplary embodiments of the present invention provide retailers and other authorized users (e.g., suppliers) with a way to access and perform complex and highly specialized analysis of transaction and/or consumer data (e.g., retail and consumer data) from remote locations using computers connected to the internet. By way of example and not limitation, the accessed transaction and/or consumer data may be a collection of: retail transaction data (e.g., data collected from an EPOS system) and/or consumer data (e.g., collected from frequent shoppers or from loyalty cards used by consumers while they shop).

In the exemplary embodiment described below, the service provided by the present invention is a web-based tool whereby authorized users can access the tool from their remote desktop and, upon completion of the project, deliver the completed project to them via email. With this embodiment, no special software need be installed on the authorized user's computer-only the web browser (or similar) application is installed. Further, in an example embodiment, items are generated as spreadsheet-based interactive reports (examples of which are described below), which are easy to manipulate for further analysis and presentation. However, it is within the scope of the invention that the computerized tool may reside on a private computer or computer system, where the software is dedicated software, and further, it is within the scope of the invention that the tool may be provided (and accessible by an appropriate interface or tool) on an intranet or some other public or private computer or data network, as contemplated by those skilled in the art.

The present service/system is designed for key sales, marketing, category management/planning queries, and provides brand/SKU level awareness, for example:

which of our latest three marketing activities pushed the greatest growth in market share?

What profile does a member consumer of product X have? What were they also purchased?

How does the competitor's brand/SKU operate?

What impact/effect our new product launch has on categories?

What stores we should be engaged in-store sampling activities?

For example, an indication of whether or not the re-engagement was successful can be provided at an early stage by using these recognitions (i.e., does our engagement achieve the level of anticipated initial and repeat purchases compared to our competitors and categories; providing robust and detailed consumer information at the individual product level that can be used throughout commerce; and to plan future marketing activities by reviewing the consumer's buying patterns over a certain period of time (e.g., a year).

As used herein, "transaction and/or consumer data" refers to data relating to any one, several, or all transactions and/or interactions between a consumer and a business (or any other product provider as defined below). In an example embodiment, the transaction and/or consumer data may include "shopping purchase data" or "shopping history data," which may be information related to the consumer's shopping history, including the identity of the product and the amount of the product purchased by the consumer. In an example embodiment, the transaction and/or consumer data may also include demographic data, shopping preference data, funding data, and the like, of the consumer. Other sources of such transaction and/or consumer data may include, without limitation, data collected by financial institutions and/or retail companies and relying on consumer credit cards or similar financial products; data voluntarily provided by the consumer; transaction, consumer, and/or financial data that can be publicly accessed; data gathered by research organizations, consulting services, and the like; and data provided by the product manufacturer, supplier, and/or distributor.

The term "product" as used herein includes not only consumer products that may be purchased at a retail store, but also any other product, consumer product, service, or item of value that may be offered to a consumer by the store/provider.

The term "consumer" as used herein is any person, group of persons, or entity that may be identified, linked to or associated with transaction data relating to one or more transactions. The consumer may be, without limitation, a single person or consumer; may be a family, e.g. a group of people who contain a person who live at the same address or use the same credit card account; may be a group of individuals or entities (e.g., belonging to an organization) having some other association with each other; or may even be a commercial entity or a governmental entity.

The shopping purchase data may be obtained using a unique identification tag or card carried by each consumer, commonly referred to as a "frequent flyer card" or "loyalty card". Such cards or tags contain a unique identification code stored with a bar code, magnetic media, or other data storage device, and can be read by the electronic device in a variety of ways known to those skilled in the art. In addition to the code from the frequent flyer card, the consumer's shopping purchase data may be associated with the consumer using other consumer identification information (e.g., phone number, store credit card, bank card or check number, etc.). In this way, the details of a particular transaction may be matched with the consumer's previous transactions, thereby facilitating the continued addition of transaction information to each consumer record in the database.

As shown in FIG. 1, the system for providing web-based services of the illustrative embodiments is divided into several layers: a user layer 30; a presentation layer 32; a management layer 34; a processing layer 36 and a data layer 38. The user layer 30 is primarily the component that users use to access web-based services provided by web servers 40 in the presentation layer 32. In the user layer 30, a user accesses the presentation layer web server 40 using a suitable network enabled (web enabled) device, such as a personal computer 44, and via a computer network, such as the internet 42. Other network enabled devices (e.g., PDAs, cell phones, etc.) will be apparent to those of ordinary skill in the art. Preferably, the network enabled device includes a display and an input device (e.g., mouse, keyboard, voice recognition, etc.).

The presentation layer web server 40 provides a verification function 46 known to those of ordinary skill in the art to unambiguously identify the user. The presentation layer web server 40 also provides navigation functionality 48, known to those of ordinary skill in the art, to control user navigation through project bookings or other related applications/functions provided by the web server 40, as will be described in greater detail below. The web server 40 also includes an analysis project reservation and parameter collection function 50 to collect input data and user selections in the process of building analysis projects as described below. Finally, the presentation layer 32 also provides the user with access to interactive items 52 and other data generated by the processing layer as further described below.

The administration layer provides an administration database 54 in communication with the web server 40 for storing input data, parameters and other selections given by the user in building the analysis project. The input data, parameters and other selections are made available to analysis project processing software 56 located in one or more central servers in the processing layer 36.

In an example embodiment, an extended admission control system is implemented to control which explicitly identified and authorized users are permitted access to each of the features of the service/system and each portion of the data of the service/system. The license control system is managed by an authorized administrator who stores and retrieves information in store management database 54 about designated licenses that have been granted and/or denied for users and groups of users, using the authorization and configuration functions of the present invention. The admission control system is used to control individual users and whether a given group of users can access each part of the service/system. Each significant portion of a service/system function, whether large or small, has a specified permission associated with it. Some permissions are associated with a single portion of a service/system function and some permissions are associated with multiple portions of a service/system function. Users and groups of users are granted access to permissions deemed appropriate by the administrator. If a user is authorized to access a particular license, he or she will be able to use the features of the service/system associated with that license. Likewise, if a user is not authorized to access a particular license, he or she will not be able to use the features of the service/system associated with that license. Certain features that are not accessible to the user are visually presented to the user by the web server 40 in a manner that would indicate in a generally understood manner that they are not available to the user and that they are not responsive to the user. Other features that are not accessible to the user are not visible to the user. At any time, the authorized administrator may change the access permissions of the users and the group members, as desired by the service/system operator.

In the processing layer 36, the analysis item processing software 56 constructs an executable analysis item script 58 that is executed against retail, consumer, and other data residing in a database 60. As described further below, the executable analysis project script 58 is created from an appropriate script template 61 obtained from the data layer 38, where the script template 61 is loaded with input data, parameters and other selections entered by the user. Multiple instances of analytical project processing software 56 may be hosted on the same physical server, and multiple physical servers may process projects created in the same store management database 54.

The transaction and/or consumer data residing in the database 60 includes a plurality of record types, with the primary record type being a retail or "transaction" record type. For each transaction record, in an example embodiment, there is provided: code to identify a SKU/one or more products purchased by a consumer of the transaction; code for identifying a particular transaction or "shopping basket"; code for identifying a consumer that caused the transaction; code for identifying a store in which a transaction occurred; data relating to the number of products purchased and the amount spent; data relating to date, time of purchase, etc.; as well as any other data or code useful for generating items from such transaction data, such as codes indicating the geographic region of the purchase.

The code identifying the SKU/product in the transaction record is used as a lookup of the "product" record type, where for each product record, in the exemplary embodiment, there is provided: product grouping or classification data or code; product data; manufacturer or supplier data or codes; and any other data or code useful for generating items based on a combination of transaction, consumer, and product data, such as suggested retail price data.

The code in the transaction record identifying the transaction consumer is used as a "home" record type lookup, wherein for each of the home records, data and/or codes relating to consumer demographics, geographic demographics, purchase recency, purchase frequency, expense, affiliates, product purchase history, shopping preferences, and any other data or code that may be useful in generating items from a combination of transaction and consumer data may be provided in an example embodiment.

The code in the transaction record identifying the store at which the transaction occurred is used as a lookup of the "store" record type, where for each store record, in an example embodiment, there is provided: store name data; storing location data or codes; and any other data or code useful for generating items based on a combination of transaction, consumer, and store data.

As will be appreciated by those of ordinary skill in the art, the above database record structures are merely exemplary in nature and unlimited combinations of database records and hierarchies are possible for cross-referencing transaction information, product information, consumer information, store information, location information, timing information, and any other suitable information. Further, those of ordinary skill in the art will also appreciate that the present invention is not limited to use in connection with retail store transactions, and that the present invention may be used in connection with most, if not all, types of transactions (e.g., financial/banking transactions, insurance transactions, service transactions, telecommunications, etc.), where the data structure and hierarchy may be adapted to produce items related to such alternative transactions and/or consumer data.

Referring again to the system diagram of FIG. 1, a user logs into web server 40 from a remote location via personal computer 44 or other web-enabled device, enters and/or selects parameters defining the user's desired analysis project, and then submits the analysis project for processing. Once the user has submitted an order for an analytical project, the actual processing of the project is performed at the administration, processing and data layers 34, 36 and 38. The data returned by the analysis item processing software 56 will be inserted into the interactive spreadsheet template file 63 to produce an interactive item 65, where the result can be presented in a manner that is easily understood by the user. The particular format of the interactive spreadsheet 65 will vary depending on the type of analysis item being performed and, as described above, the script template 61 will specify the appropriate format to be used to encode the analysis item at the front end. The user may indicate that they wish to be notified when the project is complete-this notification may be by a messaging service, such as email or SMS 64. Thus, data collection and processing are managed by one or more central system servers, and individual users can design custom analytical projects that are tailored to the user's business needs.

Fig. 2-4 provide screenshots illustrating example menus/forms presented to a user by web server 40 in an initial step of ordering an analysis project. Generally, the entire process of the method is initiated by a user who can log into web server 40 from a remote location. The user first selects the type of analysis item that he wishes to subscribe to. The user may then be prompted an additional number of times to select those parameters needed to construct their desired analysis items.

As shown in FIG. 2, after the user logs into the web server 40 via the authentication function 46, the initial screen provided by the web server provides a menu 66 of selectable analysis items that may be executed. As described above, the licensing control system will limit the user's menu of available analytical items that are authorized to reserve licenses (i.e., available analytical items for which the user pays). The available analysis items may be arranged in a graphical hierarchical manner to make navigation of the predetermined process simpler. FIG. 2 shows an example of the classification of available analysis items into three categories: custom insight Project (Standard), custom insight Project (Regional), and extrcts (excerpts). The first two categories, both labeled with Customer Insight Project, contain many of the same analytical items, with the first category resulting in items extracted from the entire sales data collection and the second category resulting in items extracted from sales data that are specific to a particular geographic area.

Once the user has selected the type of analysis item to be run, further screens are presented if necessary that prompt the user to provide information and set data filters to ensure that analysis is performed on the particular data set of interest to the user. Project specific information selected, entered, and otherwise provided by the user is retrieved and stored within the management database 54 in the management layer 34. In this example, the user has selected an analysis item titled "What is the weekly key measures of my product" 67. The user is thus provided with an additional screen to select the product and week for which the analysis is to be performed.

For example, as shown in FIG. 3, in the next step, the user will be prompted to select a product group for which to perform the analysis. The product population defines exactly those products for which sales data is to be analyzed. These product groups may be either predefined or user defined (as described below). As shown in FIG. 3, product groups and categories may be presented to a user in the form of folder tiers 68 from which one or more product groups may be selected. In the example shown in FIG. 3, the selected product group is a user-defined group labeled "Eds Cheeses" 70 (the user is "edb").

After selecting the product group, in this example, the user is presented with a screen as shown in FIG. 4 that asks the user to select a period from the selectable period menu 72 for analyzing the sales data. As can be seen in FIG. 4, the exemplary embodiment presents a time period comprising one or more weeks. In this example, The user selects a period labeled "The week 22-Mar-2004 to 28-Mar-2004 (one week from 22/3/2004 to 28/3/2004)" 74.

Once the user makes the necessary selections (in this example, item type, product group, and period), the job or analysis project request ends. The user is then presented with a screen as shown in FIG. 5, which briefly summarizes the analysis items defined by the user's selection. Once the user verifies that the analysis item is correctly described, the user may submit the item for processing by clicking or activating the indicated "Finish" button 76.

Once the user has submitted an analysis project for processing, the project is encoded in such a way as to introduce the user-selected parameters into an executable script written in a suitable commercially available scripting language. Some suitable scripting languages include, but are not limited to, VBScript, JavaScript, Perl, Korn Shell, and the like.

In particular, referring again to FIG. 1, once the project is built and submitted for processing using the project reservation and parameter collection function 50 on the web server 40, the web server inserts the job parameter identification and associated data into the store management database 54. The store management database 54 contains a log of the various analysis items requested by each user, and it also maintains a record containing selected values entered by the user defining each item. When a project is ready to be executed, the analysis project processing software 56 resident on one or more central servers retrieves selected parameters from the store management database 54 and begins creating an analysis project script 58 for the particular analysis by inserting these parameters into a new script file template 61.

In an example embodiment, the analysis item script is a package of executable code that acts on retail, consumer, and other data in the database 60 to perform a particular analysis item requested by a user. The analysis project script 58 is created by the analysis project processing software 56 using a combination of:

item type specific: code specific to the type of analysis item that has been predetermined (e.g. the query required to perform the requested analysis item)

Project specific: codes specific to particular analytical item reservations (e.g., username, product of interest, week of interest, etc.)

General purpose: code common to all analysis jobs

The data layer 38 of the architecture contains project type specific code and generic code that will be retrieved by the analysis project processing software 56 and added to the analysis project script 58, with the project specific code retrieved from the store management database 54 as described above.

In the next step, the analysis project script 58 is executed on the transaction and/or consumer data in the database 60, or a subset thereof. The script 58 queries the relevant records in the database 60 and returns the collected data to answer questions posed by the user's analysis project. In this search/query operation, the script 58 looks up the transaction, consumer, and other data that match the user-entered search parameters (filters), which may include the type of sales information sought, the product or products to be searched, and the time frame or time frames to be searched, as described in the above embodiments.

Other filters (other than the product groups and time frames used in this example) that fall within the scope of the invention include, but are not limited to: any different period, multiple periods (including weeks, days, hours), stores, geographies (regions), individual products, and consumer groups with specific consumer/demographic/behavioral attributes. By way of example and not limitation, the product group filter may be based on category, price, brand, variation, package size, taste, and the like; or any combination thereof.

After the analysis project script is executed, the data returned by the search operation will be inserted into the interactive spreadsheet template file 63 to produce an interactive project 65, where the results may be presented in a format that is easy for the user to understand. The specific format of the interactive spreadsheet 65 will vary depending on the type of analysis item being performed and, as noted above, the appropriate format will be dictated by the script template 61 used to encode the analysis item at the front end. For each analysis item type, the script template 61 used is associated with a corresponding spreadsheet template formed in a manner suitable for receiving and presenting data returned by the search/query for that analysis item. For use in connection with the present invention, any suitable spreadsheet product may be used to generate these items, such as Microsoft Excel, Lotus 1-2-3, StarOffice Calc, OpenOffice.org Calc, and the like. The item may also be generated in other suitable formats and by using other suitable tools (whether off-the-shelf, custom, or a combination thereof) for generating the type of item described herein, which are within the scope of the invention and will be appreciated by those of ordinary skill in the art.

After importing the analysis data into the interactive spreadsheet file, the completed analysis item implemented in the spreadsheet file will be published/transmitted to the user requesting the item. The appearance and content of the final item will depend on the type of analysis item. For example, FIG. 6 provides a "What are the weekly keyeasuresures for my products" project 78 constructed as above in FIGS. 2-5 based on the product sub-population "Eds Cheeses", analytical sales data for one week from 3 month 22 to 3 month 28 of 2004. The structure and arrangement of such items will be discussed herein with reference to FIG. 7H and the accompanying description below.

As shown in FIG. 7A, another example interactive item 80 provided by the example embodiments is named "Who buys my brand? ". As shown in this example item, a plurality of products 82 are provided along with an indication of the type of consumer 84 that purchased the products in a specified period of time. The purchase of these products can be segmented based on the "specific Lifestyle" of the consumer shown in this example, where the consumer Lifestyle is divided into the following categories: "Lifestyle a", "Lifestyle B", "Lifestyle C", "Lifestyle D", "Lifestyle e", and "Lifestyle F". An indication of these truncated Lifestyle categories may be provided for each consumer record in the consumer records of database 60. These categories may be determined by any number of methods. In an example embodiment, the type of product most often purchased by a consumer is determined by analyzing consumer purchases over time (where such products may be labeled with a category of consumer types that typically purchase the product-that is, wholewheat bread products may be labeled as a category of products purchased by "healthy-focused" consumers, caviar may be labeled as a category of products purchased by "affluent" consumers, etc.). From the purchase history, the consumer may be archived or classified into one of the above labeled categories ("Lifestyle a-F"). Alternatively, the consumer may be archived or categorized according to other or additional information, such as demographic information or information provided by the consumer (e.g., by filling out a questionnaire). Other consumer profiles/segments in example embodiments may include, but are not limited to: demographics, age, shopper frequency, location, geographic demographics, and data obtained directly from consumers or derived from their address or shopping behavior.

In this example, the interactive results display is displayed in two ways: table format 86 and histogram format 88. In this interactive item, the user is allowed to select a different consumer profile via the pull-down menu 90, whereby the item can re-tabulate and display the results based on another selected profile, and also to select an index via the pull-down menu 92 to limit the item display to only certain consumer categories.

As shown in FIG. 7B, an item 94 similar to that described above is entitled "Who buys mybrand over time (Who bought my brand during this time)? ". In this project, the sales of one or more products at different time periods are compared, such as "First 4 weeks", "Second 4 weeks", and "Third 4 weeks". As with the example item above, this sale is broken down by the profile/category of the consumer purchasing the product in these three periods. For example, such analysis/projects allow a user to determine sales figures before, during, and after a particular promotional period.

As shown in fig. 7C, another title is "How do people repeatedly buy my product"? "allows a user to assess the repetition rate of a new or existing product relative to a competitor product or relative to a product category. This project allows the user to study periodic (e.g., weekly) data or to study cumulative effects over a period of time. The number of times a consumer repeatedly purchases a given product is displayed for a corresponding number of weeks (or any selected period) in the form of a histogram 98 and a tabular form 100. In the histogram 98, if the product is first purchased by the consumer (purchase count is 1), it is displayed in the first color; if the consumer purchases the product a second time (purchase times 2), it will be displayed in a different color; and so on, with the last color being for a product that was purchased 6 or more times. The interactive item allows the user to switch between a weekly data view (as shown) and an accumulated data view; and allows the user to switch between consumer counting (as shown) and units sold. Finally, the drop down menu 102 allows the user to filter the item by passing through selectable store types.

Another title is "What other products are found in my consumer's shopping basket"? "allows a user to assess which products are being purchased simultaneously as a particular product or group of products. The output item views the shopping basket level data as well as the consumer data, and the user can view all retailer shopping baskets as well as a shopping basket that is specified to contain the selected product and a second specified product area.

As shown in fig. 7E, another label is "Where my brand is sold (product grade))? "allows the user to evaluate the entire consumer purchasing his or her products and competitor products, as well as the top and bottom stores. The user may also view the entire list of stores, if desired. The output items can be used to view the operation of a product in different stores. The knowledge gained from these projects can make better decisions for new project investment, sampling activities, commodity procurement, classification, circulation, and other sales and market prioritization. As shown in this item, three tables are provided: sale Total 114, Sale by Store Type 116, and Sale by Store 118. In each table, the first column gives the total number of consumers who purchased a selected brand of merchandise; the second column gives the total number of units sold for the brand; column three provides the value of these sales; the fourth column provides the percentage of purchases of consumers in a given row (store type or store) relative to all consumers; the fifth column provides the percentage of consumers in a given row relative to the units sold by all consumers; the sixth column provides the percentage of these sales for the specified row; column seven provides the percentage of consumer penetration; the last column provides the average amount each consumer spends on a given brand.

Another label, as shown in FIG. 7F, is "What is the key measures of my product? "allows users to evaluate key consumer and sales metrics for their products and competitor products. The metrics contained in the item are, over a given period of time: a store sales distribution; the amount of units sold; a sales value of the unit sold; a number of consumers purchasing the selected product; number of visits by all consumers who purchased the selected product; consumer penetration; an average weighting for each purchase of the selected product; frequency of purchases; market share and unit price. As shown in FIG. 7F, the interactive item is in tabular form 122 and histogram form 124 to provide such key measures. A drop down menu 126 allows the user to select which key metric is illustrated in the histogram display 124. The sub-table 128 provides another view of the particular key metrics. 7H-7I, described below, provide alternative examples of key-measure interactive items.

Another title is "How many people cross-buy my products"? "allows the user to assess how the consumer cross-purchases different products/SKUs, brands, or categories. Both the consumer volume and the number of units due by the consumers are included in this project. For example, the project may be used for new product development/enumeration. Another area where this project can be used is to identify link savings or whether a multi-pack (multi-pack) format is appropriate in different SKU/product areas. This cross-shopping statistic is given by the Venn diagram 132 and the intersection table 134.

As shown in fig. 7H, the title "What is the key metric of my product every week? "provides an overview of brand execution metrics for the user-defined product groups. The project is designed to be interactive, thereby allowing the user to manipulate and extract information specific to the user's particular needs. The project may provide:

sales value, units, consumers, and number of visits;

average weighting of consumer quantity, purchase (by value or units)

Percentage share of the subgroup and penetration at all selected retail stores of the consumer;

these metrics can also be viewed in different ways, for example:

table 138 Cross-Mark products by week

A histogram (not shown) that can be selected by activating the View as Chart button 139, thereby allowing the user to View the data by individual product or week

Ability to analyze in depth on a weekly or SKU level

Ability to sort alphabetically or by a selected metric

A drop down menu 140 allows the user to select the format and characteristics of the display. In FIG. 7H, the sales values for the selected products are displayed in tabular form on a week-by-week basis.

As shown in FIG. 7I, another name is "What is the key measures for myproducts over time (What is the key measure of my product at this time)? "interactive item 142 provides an interactive item for a particular product group that illustrates a comparison of two time periods. Item 142 includes dynamic text in text box 144 that provides an explanation of the changes and which key metrics drive those changes. This project provides a quick "health check" of the selected product performance. The project can be used to easily see if market share is increased and if the number of units sold is decreased. This is a very desirable item for performing a monthly or yearly analysis. As shown in FIG. 7I, a drop down menu 146 allows the user to select item characteristics and selected metrics displayed in a tabular form 148, thereby comparing the most recent time period to the previous time period, and containing a comparison index and histogram table 150.

As shown in fig. 7J, another title is "How do my brand and sell over time (How do my brand sell this time)? "by hour, day, and weekend versus weekday, decomposes consumers, sales, and visits. The project 152 provides information that can be used to understand out-of-stock issues and identify demand during the day, weekday, and weekend, thereby facilitating supply chain management. The items provide selected key measures of the product or group of products in tabular form 154 and line graph form 156. Button 158 provides a menu for the user to change one or more key metrics displayed when activated. The icon table 156 within the project may display several SKU products (different line colors) simultaneously and may include a complete subgroup of products (as shown in the example project of FIG. 7J).

In many or all of the above example items shown in fig. 7A-7H, buttons/icons are provided that allow a user to initiate support for multiple functions/programs, such as: print (printing) 160; toolbar (Toolbar) 162; glossary (vocabulary) 164; contact Us 166; sort 168; and Export Chart/Table/Diagram/Data 170.

At any time, the user can log into the system and view the status of those analysis items that have been submitted for processing. FIG. 8 is an example screen view showing an item status of a particular user. In this example, the screen shows the items waiting at 4:36:10pm at 4/14/2004 for username "edb". The list contains two items, for each of which a job number, a user name, an item status, and an item description are listed. In this example, all listed items have a state of "PROCESSING". FIG. 9 illustrates a status screen for indicating a history of completed items, showing various events and steps performed during the processing of the items, and the time at which each event or step was performed.

As described in the above example process shown in FIG. 3, the product for which the sales data analysis is performed is selected from the product group list. A user may create a product group by identifying those individual products that they wish to group together. FIG. 10 illustrates a screenshot for starting a product group creation process. In the left hand box 172, a wide variety of categories of goods are listed and the user can select the appropriate category of goods for the products he wishes to group together. In this example, the user selects the "Wines & Spirits" category 174. The next frame shown in FIG. 11 lists several narrower categories in the product box 176, all of which fall within the broad "Wines & Spirits" category previously selected by the user.

After the user has further selected a narrower product category, a screen similar to that in FIG. 12 is provided listing the individual products in the selected category. In this example, the user has selected "Bacon Products" and block 178 lists all available Bacon Products that are predefined for that category. The user selects individual products from this list of products in block 178 to add to their predetermined product group. The user highlights the desired product by clicking on it and then clicks on the "add" button 180 which causes the highlighted product to appear in the right box 182, thereby indicating that it has been selected for inclusion in the user's customized subgroup. This selection process may be repeated until the customized subgroup contains all of the individual products that the user wishes to contain. The user is then presented with a Save Product Group screen as shown in fig. 13, which prompts the user to enter the name and description of the created subgroup. In this example, the user names the subgroup "david's back". As shown in FIG. 14, once a subgroup is created, the subgroup is listed in a folder structure and can be selected to perform an analysis project.

It will be apparent to those skilled in the art from this disclosure that, while the systems and processes described herein constitute exemplary embodiments of the invention, it is to be understood that the invention is not limited to these precise systems and processes and that changes may be made in these systems and processes without departing from the scope of the invention as defined in the appended claims. Furthermore, it should be understood that the invention is defined by the claims, and no limitations or elements are intended to be included within the meaning of the claims unless such limitations or elements are recited in the claims for describing the example embodiments set forth herein. Also, it is to be understood that it is not necessary here to meet any or all of the identified advantages or objects of the invention disclosed herein in order to fall within the scope of any claims, since the invention is defined by the claims, and since: inherent and/or unforeseen advantages of the present invention may still exist even though they may not have been explicitly discussed herein.

Claims (82)

1. A method for performing transaction related analysis, comprising the steps of:

providing one or more computerized databases containing transaction and/or consumer data for one or more companies, the transaction and/or consumer data containing one or more transaction records associating at least a product identification code with a consumer identification code;

formulating an analysis project request via a user interface operatively coupled to a computer system accessing the database; and

in response to receipt of the analysis item request, the computer system generates an analysis item with respect to the transaction and/or consumer data.

2. The method of claim 1, wherein the user interface is on a network device operatively coupled to the computer system via a global computer network.

3. The method of claim 2, the network device being a web-enabled device operatively coupled to the computer system via the world wide web.

4. The method of claim 3, further comprising steps from the group consisting of:

downloading an analysis item from a computer system via the world wide web; and

the analysis items are transmitted from the computer system via the global computer network to a user computer operatively connected to the global computer network.

5. The method of claim 1, wherein the one or more transaction records associate a product identification code with at least one of a transaction time and a transaction date.

6. The method of claim 5, wherein the step of formulating a request for an analysis item comprises the step of selecting an analysis item from a predefined list of available analysis items via a user interface.

7. A method according to claim 6, wherein the step of formulating a request for an analysis item comprises the step of selecting a time frame to limit the analysis of the transaction and/or consumer data.

8. The method of claim 6, wherein the predefined list of available analysis items includes analysis items that provide a rate of repeated purchases of products associated with the product identification codes by consumers associated with the consumer identification codes.

9. The method of claim 6, wherein:

the one or more transaction records associate a product identification code with a vendor identification code; and

the predefined list of available items includes an analysis item to provide a rate of cross-purchasing of products associated with the vendor identification code by consumers associated with the consumer identification code;

10. the method of claim 6, wherein:

the one or more transaction records associate a product identification code with a vendor identification code; and

the predefined list of available items includes an analysis item to provide a comparison of the rate of purchase of the product associated with the first vendor identification code and the product associated with the second vendor identification code.

11. The method of claim 6, wherein:

the one or more transaction records associate a consumer identification code with a buyer category; and

the predefined list of available items includes analysis items to provide a comparison of rates of purchase of products associated with product identification codes by consumers in different categories of purchasers.

12. The method of claim 11, wherein the consumer category is defined based on demographic information associated with the consumer identification code.

13. The method of claim 11, wherein the consumer category is defined based on data derived from a shopping history associated with the consumer identification code.

14. The method of claim 13, wherein the consumer category is defined based on price sensitivity-related data associated with the consumer identification code.

15. The method of claim 6 wherein the step of formulating a request for an analytical item includes the step of selecting one or more products from a list of available products.

16. The method of claim 15, wherein the step of selecting one or more products from the list of available products is subsequent to the step of selecting a product category from the list of available product categories.

17. The method of claim 1, further comprising the step of saving at least a portion of the analysis item request for reuse in formulating future analysis item requests.

18. The method of claim 1, wherein the step of generating an analysis item is performed repeatedly on a periodic basis.

19. The method of claim 1, wherein the one or more transaction records associate a product identification code and a consumer identification code with a transaction price.

20. The method of claim 1, further comprising the step of downloading the analysis item from the computer system via a user interface.

21. The method of claim 1, wherein the analysis item request relates to an analysis item to be used to repeat a rate of purchase of a product associated with a product identification code by a consumer providing the product associated with the consumer identification code.

22. The method of claim 1, wherein:

the one or more transaction records associate a product identification code with a vendor identification code; and

the analysis item request relates to an analysis item to provide a rate of cross-purchasing a product associated with a vendor identification code by a consumer associated with a consumer identification code;

23. the method of claim 1, wherein:

the one or more transaction records associate a product identification code with a vendor identification code; and

the analysis item request relates to an analysis item to provide a comparison of a rate of purchase of a product associated with a first vendor identification code and a product associated with a second vendor identification code.

24. The method of claim 1, wherein:

the one or more transaction records associate a product identification code with a buyer category; and

the analysis item request relates to an analysis item to provide a comparison of rates at which consumers in different purchaser categories purchase products associated with product identification codes.

25. The method of claim 24, wherein the category of the purchaser is defined based on demographic information associated with the consumer identification code.

26. The method of claim 24, wherein the buyer category is defined based on data derived from a shopping history associated with the consumer identification code.

27. The method of claim 26 wherein the buyer category is defined based on price sensitivity related data associated with the consumer identification code.

28. A method according to claim 1, wherein the step of formulating a request for an analytical item includes the step of selecting one or more products from a list of available products.

29. The method of claim 28, wherein the step of selecting one or more products from the list of available products is subsequent to the step of selecting a product category from the list of available product categories.

30. The method according to claim 1, further comprising the step of collecting at least a portion of the transaction and/or consumer data from the shopper loyalty card data.

31. A method for performing transaction analysis, comprising the steps of:

providing one or more databases containing transaction and/or consumer data for one or more companies, the transaction and/or consumer data containing one or more transaction records associating at least a product identification code with a consumer identification code;

a computer system accessing the database generates items relating to transaction and/or consumer data; and

the computer system communicates the item to a user interface operatively coupled to the computer system.

32. The method of claim 31, wherein the step of generating items is performed repeatedly on a periodic basis.

33. The method of claim 31, wherein the one or more transaction records associate a product identification code and a consumer identification code with a transaction price.

34. The method of claim 31, wherein the item provides a rate of repeated purchases of the product associated with the product identification code by a consumer associated with the consumer identification code.

35. The method of claim 31, wherein:

the one or more transaction records associate a product identification code with a vendor identification code, an

The item provides a rate of cross-purchasing of products associated with the vendor identification code by consumers associated with the consumer identification codes.

36. The method of claim 31, wherein:

the one or more transaction records associate a product identification code with a vendor identification code; and

the item provides a rate of purchase of a product associated with the first vendor identification code and a product associated with the second vendor identification code.

37. The method of claim 31, wherein:

the one or more transaction records associate a consumer identification code with a purchaser category, an

The item provides a comparison of the rate at which products associated with the product identification codes are purchased by consumers in different categories of purchasers.

38. The method of claim 37, wherein the category of the purchaser is defined based on demographic information associated with the consumer identification code.

39. The method of claim 37, wherein the consumer category is defined based on data derived from a shopping history associated with the consumer identification code.

40. The method of claim 39 wherein the consumer category is defined based on price sensitivity-related data associated with the consumer identification code.

41. A method according to claim 31, further comprising the step of collecting at least a portion of the transaction and/or consumer data from the shopper loyalty card data.

42. A method for performing transaction analysis, comprising the steps of:

providing one or more databases containing transaction and/or consumer data for one or more companies;

providing a computer system that accesses the one or more databases;

obtaining parameters from a user for analysis of transaction data and/or consumer data via a computer interface provided by a computer system;

the computer system feeds the acquired parameters to an executable job file;

the computer system executing the executable job file on transaction and/or consumer data to return a result; and

the user is presented with items reflecting the returned results.

43. The method of claim 42, wherein the parameters for analysis include parameters related to retail metrics.

44. The method of claim 43, wherein the parameters for the analysis include an identification of the analysis format, an identification of the retail product for the analysis, and an identification of the time frame for the analysis.

45. The method of claim 44, wherein the analysis format relates to a rate at which the consumer repeatedly purchases the retail product.

46. The method of claim 44, wherein the analysis format relates to a rate at which the consumer repeatedly purchases retail products at a particular type of retail establishment.

47. The method of claim 44, wherein the analysis format relates to an identification of whether a retail product newly released for a retail establishment was successful.

48. The method of claim 44, wherein the analysis format relates to a rate of cross-purchase of the vendor retail product by the consumer.

49. The method of claim 44, wherein the analysis format relates to a rate at which the consumer cross-purchases the vendor retail product at one of a particular retail establishment and a particular type of retail establishment.

50. The method according to claim 44, wherein the analysis format relates to key sales metrics in a particular product category.

51. The method of claim 44, wherein the analysis format relates to key sales metrics for the factory retail product.

52. The method of claim 51, wherein the analysis format relates to key sales metrics for the factory retail product over a period of time.

53. The method according to claim 44, wherein the analysis format relates to key sales metrics for a particular brand of retail product over a period of time.

54. The method of claim 44, wherein the analysis format relates to other retail products purchased by consumers of the factory retail products.

55. The method of claim 44, wherein the analysis format relates to a location where the particular retail product is sold.

56. The method of claim 44, wherein the analysis relates to a location at which the vendor brand retail product is sold.

57. The method of claim 44, wherein the analysis relates to a type of consumer purchasing the vendor retail product.

58. The method of claim 57, wherein the analysis relates to a type of consumer purchasing the factory retail product over a period of time.

59. The method of claim 57, wherein the analysis relates to a type of consumer purchasing the factory retail product at one of a particular retail establishment or a particular type of retail establishment.

60. The method of claim 44, wherein in the step of obtaining, the user is prompted to select at least one parameter for analysis from a menu comprising a plurality of available parameters.

61. The system of claim 60, wherein the user is prompted to select each parameter for analysis from a menu.

62. The method of claim 44 wherein the computer interface is a web-based interface.

63. The method of claim 62, further comprising the step of verifying that the user has access to the computer system prior to the obtaining step.

64. The method of claim 44 wherein the feeding step further comprises the step of integrating the acquired parameters with the segment of executable code to create an executable job file.

65. A method according to claim 64, wherein the segment of executable code incorporating the acquired parameters is determined at least in part from at least one of the acquired parameters.

66. The method of claim 44, wherein:

the item is given as a spreadsheet file;

the method further includes the step of generating a spreadsheet file from the returned results; and

the generating step includes the steps of selecting a spreadsheet item template from a plurality of available spreadsheet item templates based on the analysis format, and populating the spreadsheet item template with at least a portion of the returned results.

67. A method according to claim 42, wherein the transaction and/or consumer data includes an identification of the product purchased, the quantity of the product purchased, the date of purchase and a code associated with the particular purchasing consumer.

68. The method of claim 42, wherein the item is presented as an interactive item.

69. The method of claim 68, further comprising the step of generating an interactive item from the returned results, and the generating step comprises the step of selecting an item template from a plurality of available item templates based on at least one obtained parameter and populating the item template with at least a portion of the returned results.

70. The method of claim 42, wherein the step of presenting items to the user reflecting the returned analysis comprises the steps of:

informing the user that the item is available; and

after notifying the user and when the user requests access to the item, the user is provided access to the item.

71. The method of claim 70, wherein the step of providing the user with access to the item comprises the step of downloading the item to the user's computer.

72. The method of claim 70 wherein the step of providing the user with access to the item comprises the step of providing the user with access to the item via a web-based interface.

73. A computerized system for performing an analysis, comprising:

one or more databases having transaction and/or consumer data for one or more companies, the transaction and/or consumer data comprising one or more transaction records associating at least a product identification code with a consumer identification code; and

a computer system accessing the database, the computer system configured to perform the steps of:

generating items relating to transaction and/or consumer data; and

the item is transmitted to a user interface operatively coupled to the computer system.

74. The computerized system of claim 73, wherein said one or more transaction records associate a product identification code and a consumer identification code with a transaction price.

75. The computerized system of claim 73 wherein the item provides a rate of repeated purchases of products associated with the product identification code by consumers associated with the consumer identification code.

76. The computerized system of claim 73 wherein:

the one or more databases include one or more product records that associate a product identification code with a vendor identification code; and

the item provides a rate of cross-purchasing of products associated with the vendor identification code by consumers associated with the consumer identification codes.

77. The computerized system of claim 73 wherein:

the one or more databases include one or more product records that associate product identification codes with vendor identification codes; and

the item provides a rate of purchase of a product associated with the first vendor identification code and a product associated with the second vendor identification code.

78. The computerized system of claim 73 wherein:

the one or more databases include one or more consumer records associating consumer identification codes with purchaser categories; and

the item provides a comparison of the rate at which products associated with the product identification codes are purchased by consumers in different consumer categories.

79. The computerized system of claim 78, wherein the consumer categories are defined based on demographic information associated with the consumer identification codes.

80. The computerized system of claim 78, wherein the consumer category is defined based on data derived from a shopping history associated with the consumer identification code.

81. The method according to claim 80, wherein the consumer category is defined based on price sensitivity-related data associated with the consumer identification code.

82. A computerized system according to claim 73 wherein the transaction and/or consumer data is obtained from shopper loyalty card data.