METHODS AND APPARATUS TO IDENTIFY LOCAL TRADE AREAS
Methods, apparatus, systems and articles of manufacture to identify local trade areas are disclosed. An example method includes selecting, with a processor, census block groups (CBGs) associated with a retailer location, identifying, with the processor, a plurality of stores within the selected CBGs and associated all commodities volume (ACV) values for respective ones of the plurality of stores, calculating, with the processor, similarity index values associated with respective pairs of the plurality of stores, generating, with the processor, local trade areas (LTAs) of subgroups of the plurality of stores based on a comparison of the similarity index values to a similarity threshold value, and when a respective one of the LTAs includes a violation of a releasability criterion, preventing, with the processor, erroneous disclosure of market share information by re-distributing the stores within the respective one of the LTAs to a geographically adjacent LTA.
This disclosure relates generally to market research, and, more particularly, to methods and apparatus to identify local trade areas.
BACKGROUNDIn recent years, clients, businesses and/or entities with an interest in identifying geographical markets in which to promote/advertise a product or service of interest have relied upon U.S. Census Bureau information. The Census Bureau information includes detailed demographics information in census blocks or census block groups (CBGs) that represent statistical divisions of census tracts that are defined to contain between 600 and 3,000 people. In some examples, clients evaluate Census Bureau information to identify particular geographic portions of a market for promotion/advertising activity in an effort to reach as many potential consumers as possible.
Census Bureau information provided by the U.S. Census Bureau includes detailed demographic data, such as age, gender, race, housing details, employment status, type of employment, income, educational attainment, field of degree, marital status, etc. While the Census Bureau information includes detailed information that may help businesses and/or entities (hereinafter referred to as “clients”) seeking to market one or more products and/or services, such Census Bureau information does not reveal information associated with existing market share information of retailers within a particular geographic area. As such, in the event an example client chooses to initiate marketing activity within a particular census block group (CBG), that client may not appreciate how saturated the CBG is with respect to competitive retailers in that area. Market share information is also represented as All Commodities Volume (ACV) information, which indicates how much people spend at a particular retailer from a defined CBG. For example, a retailer ACV of $100,000 means that households within a CBG of interest will spend $100,000 with that particular retailer.
The Nielsen Company® develops and manages a data service referred to as Spectra™, which includes trading area decomposition models that identify spending (e.g., channel spending, store spending, etc.) of households from retailers in particular CBGs. While the ACV information developed by the Spectra™ services reveals spending amounts at retailers from consumers within CBGs, such retailers may have an influence on two or more particular CBGs. In the event a retailer targets only that CBG within which their store is located (e.g., their “home CBG”), one or more competitive stores outside the geographical boundary of their CBG may have a degree of influence on the retailer's store. As such, marketing efforts within the home CBG may result in wasted advertising resources that do not accurately target other geographical areas having potential consumers. Example methods, apparatus, systems and/or articles of manufacture disclosed herein improve the granularity of trading areas over existing ACV information services, thereby providing improved precision in marketing efforts, improved marketing productivity, and reduced waste of marketing and/or computational resources.
Additionally, examples disclosed herein prevent erroneous exposure of retailer data in view of releasability criteria. In some examples, releasability criteria includes contracts and/or rules established by retailers to protect the disclosure of information that may be deemed harmful to their competitive strategies within a market of interest. In some examples, the releasability criteria require a threshold number of stores present within a particular geographic area of interest before any data associated with that area can be divulged. In still other examples, the releasability criteria require that stores present within a particular geographic area of interest exhibit a particular channel mix, such as stores that participate in one or more of a drug category, a food category, a home furnishings category, etc. In some examples, a retailer may only agree to provide sales information to a market research entity if the revealed sales data is less than a releasability criterion identifying a 50% market share for a disclosed trading area of interest. Examples disclosed herein generate local trading areas (LTAs) that identify clusters of retailers/stores in discrete sets such that a mean ACV similarity value is maximized within each set, and minimized between sets. However, after generating the LTAs, examples disclosed herein evaluate each set to verify erroneous disclosure of retailer market information does not violate the releasability criteria/criterion established by the respective retailer.
Turning to
In operation, the example CBG interface 104 selects one or more census block(s) of interest from the example census bureau service 124, and the example ACV interface 106 identifies ACV information in the example ACV data source 126 that is associated with each store within the selected CBG. The example similarity index engine 108 builds a list of store identifiers and associated CBGs to which they belong, as well as associated ACV information that is associated with each store, as shown in
To calculate similarity index values for all pairs of stores, the example similarity index engine 108 calculates similarity index values (e.g., a Jaccard similarity index) for pairs of stores based on an overlap of their trading areas (e.g., whether a store has a market influence in one or more CBGs). The Jaccard similarity index for a pair of stores is calculated in a manner consistent with example Equation 1.
To illustrate the application of example Equation 1, store ID 1 from the illustrated example of
The example similarity index engine 108 builds a similarity matrix 300 for all store pairs of interest, as shown in the illustrated example of
As such, stores associated with store ID 1 (302) and store ID 2 (304) meet the threshold criteria of a pair with an index value of 0.75 or higher, and the example LTA builder 118 assigns them to a first LTA, as shown in the illustrated example LTA table 400 of
However, releasing these LTAs for syndicated distribution may not be authorized in the event that one or more releasability requirements are violated. To illustrate, an example market share table 500 of
To protect the interests of the client, satisfy contractual obligations and/or otherwise prevent unauthorized or erroneous disclosure of LTA information that fails to comply with the releasability requirements, the example offending LTA (i.e., LTA 1 in this example) is dissolved and/or otherwise disbanded by the example LTA spatial engine 116 to distribute the stores within LTA 1 to one or more geographically adjacent LTAs. For this example, assume that the example LTA spatial engine 116 identifies LTA 2 as the adjacent LTA to LTA 1, in which all of the stores previously associated with LTA 1 (i.e., store ID 1, store ID 2 and store ID 3) are distributed to LTA 2.
To prepare the LTA for syndicated distribution, the example LTA spatial engine 116 calculates a geographical boundary of each LTA of interest. Additionally, the example shape file generator 120 generates a distribution shape file associated with the geographical boundaries associated with each LTA of interest.
When the example LTA builder 118 detects a selection of a particular LTA via the client interface 122 or the example LTA map 600 detects a selection of a particular LTA, the information associated with that LTA and/or Census Bureau information is presented to a viewer (e.g., the client 128). In the illustrated example of
Knowledge of relevant LTAs for marketing efforts permits the retailer to apply examples disclosed herein to any type of marketing effort. In some examples, the retailer may pursue a digital marketing campaign to advertise via digital media, such as localized web pages, music services (e.g., Pandora®) and/or social media (e.g., Facebook®, Twitter®, etc.). If the retailer is monitoring Twitter® for indicators of a product or service that the retailer provides (e.g., Bourbon), then the retailer can identify particular geo-locations in which those indicators occur. For example, the retailer may identify Bourbon tweets associated with Twitter® that coincide with particular locality indicators (e.g., #Chicago, #Schaumburg, #Lincoln Park, etc.). Because the retailer has information related to (a) their product of interest and (b) location(s) with which their product of interest has a degree of interest, then example methods, apparatus, systems and/or articles of manufacture disclosed herein can identify relevant LTAs within which the retailer should invest further marketing resources. Additionally, because product information and location information are identified with one or more relevant LTAs, LTA sales data may be analyzed and/or reported (e.g., sales responses to marketing activity within one or more LTAs) without concern for releasability violation(s).
While an example manner of implementing the LTA engine 102 of
Flowcharts representative of example machine readable instructions for implementing the LTA engine 102 of
As mentioned above, the example processes of
The program 700 of
While the stores associated with the CBGs of interest are assigned to particular LTAs, the example release requirement manager 112 verifies that release requirement rules (releasability criteria) for each store have been satisfied without violation (block 710). As described above, and as described in further detail below, in the event one or more LTAs includes a store in which releasability rules have been violated, the offending LTA is disbanded and the stores previously associated with that offending LTA are distributed to one or more neighboring LTAs in an effort to satisfy the releasability rules and prevent unauthorized disclosure of retailer information that could jeopardize a competitive advantage. The LTAs that are deemed appropriate for release are built by the example LTA builder 118 in a manner that permits graphical representation in response to one or more client requests for data associated with one or more LTAs (block 712), thereby facilitating analysis and/or reporting of sales responses. Additionally, because markets may change over time with particular new stores emerging in particular geographic areas and/or other particular stores closing in the particular geographic areas, the example LTA engine 102 determines whether to build/rebuild new LTAs to reflect the changing landscape (block 714). In some examples, releasability criteria are time dependent and such criteria are checked/verified over time periods of interest. LTAs of interest may be generated for a particular time period (e.g., two years) so that no releasability violations occur when analyzing past sales information. In other words, LTA information may be built at a first time, and re-built at a second time to consider a dynamic nature of the LTAs (e.g., new stores added and/or otherwise participating in a geographic area of interest).
If no stores within the selected LTA satisfy (e.g., exceed) the releasability rule (block 906), then the release requirement manager 112 identifies the selected LTA as suitable for syndicated distribution and further market analysis (block 912). If one or more additional LTAs of interest are to be checked to determine compliance with releasability rules, as determined by the example release requirement manager 112 (block 914), then control returns to block 902 to select another LTA of interest.
The processor platform 1100 of the illustrated example includes a processor 1112. The processor 1112 of the illustrated example is hardware. For example, the processor 1112 can be implemented by one or more integrated circuits, logic circuits, microprocessors or controllers from any desired family or manufacturer.
The processor 1112 of the illustrated example includes a local memory 1113 (e.g., a cache). The processor 1112 of the illustrated example is in communication with a main memory including a volatile memory 1114 and a non-volatile memory 1116 via a bus 1118. The volatile memory 1114 may be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/or any other type of random access memory device. The non-volatile memory 1116 may be implemented by flash memory and/or any other desired type of memory device. Access to the main memory 1114, 1116 is controlled by a memory controller.
The processor platform 1100 of the illustrated example also includes an interface circuit 1120. The interface circuit 1120 may be implemented by any type of interface standard, such as an Ethernet interface, a universal serial bus (USB), and/or a PCI express interface.
In the illustrated example, one or more input devices 1122 are connected to the interface circuit 1120. The input device(s) 1122 permit(s) a user to enter data and commands into the processor 1112. The input device(s) can be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touchscreen, a track-pad, a trackball, isopoint and/or a voice recognition system.
One or more output devices 1124 are also connected to the interface circuit 1120 of the illustrated example. The output devices 1124 can be implemented, for example, by display devices (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display, a cathode ray tube display (CRT), a touchscreen). The interface circuit 1120 of the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip or a graphics driver processor.
The interface circuit 1120 of the illustrated example also includes a communication device such as a transmitter, a receiver, a transceiver, a modem and/or network interface card to facilitate exchange of data with external machines (e.g., computing devices of any kind) via a network 1126 (e.g., an Ethernet connection, a digital subscriber line (DSL), a telephone line, coaxial cable, a cellular telephone system, etc.).
The processor platform 1100 of the illustrated example also includes one or more mass storage devices 1128 for storing software and/or data. Examples of such mass storage devices 1128 include floppy disk drives, hard drive disks, compact disk drives, Blu-ray disk drives, RAID systems, and digital versatile disk (DVD) drives.
The coded instructions 1132 of
From the foregoing, it will be appreciated that the above disclosed methods, apparatus and articles of manufacture prevent erroneous disclosure of client information that may violate contractual agreements between market research entities and retailers from which market information is obtained (e.g., purchased). While particular retailers may generate revenue by selling marketing information (e.g., sales data) to the market research entities, the granularity of such sold marketing information may, in some circumstances, reveal too much about the retailer that may affect its competitive advantage. As such, examples disclosed herein identify a balance between data granularity allowed by such retailers, as defined by particular releasability rules and/or contracts, and useful market information that can be sold via syndicated market services.
Examples disclosed herein also improve retailer marketing efforts such that particular geographic areas of interest may be targeted that have a degree of relevance to the retailer's operation(s), which is not available through publically available Census Bureau information. As a result, examples disclosed herein reduce wasteful marketing efforts based merely on a target geography associated with a CBG with which the retailer is associated.
Although certain example methods, apparatus and articles of manufacture have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all methods, apparatus and articles of manufacture fairly falling within the scope of the claims of this patent.
Claims
1. (canceled)
2.-28. (canceled)
29. An apparatus to identify a local trade area (LTA), the apparatus comprising:
- means for determining a similarity index to determine similarity index values associated with respective pairs of stores associated with a retailer location;
- means for building a local trade area to generate local trade areas (LTAs) of subgroups of stores corresponding to the retailer location based on a comparison of the similarity index values to a similarity threshold value; and
- means for managing a release requirement to, when a respective one of the LTAs does not satisfy a releasability threshold, prevent erroneous disclosure of market share information by re-distributing the stores within the respective one of the LTAs to a geographically adjacent LTA.
30. The apparatus as defined in claim 29, further including:
- means for interfacing a census block group (CBG) to select census block groups (CBGs) associated with the retailer location; and
- means for interfacing an all commodities volume to identify (a) the stores within the selected CBGs and (b) identify associated all commodities volume (ACV) values for respective ones of the stores.
31. The apparatus as defined in claim 30, wherein the similarity index determining means is to calculate the similarity index values based on a ratio of (a) a sum of ACV values of respective pairs of the stores that share a common CBG and (b) a sum of ACV values of the respective pairs of the stores from all CBGs in which they contribute.
32. The apparatus as defined in claim 29, further including means for calculating an LTA to calculate a geographical center of the LTAs, the geographical center based on geographical coordinates of the subgroups of the stores.
33. The apparatus as defined in claim 29, wherein the releasability threshold represents a store sales amount within a geographical area defined by one of the LTAs.
34. The apparatus as defined in claim 29, wherein the release requirement managing means is to re-distribute to two or more geographically adjacent LTAs.
35. The apparatus as defined in claim 34, further including means for calculating a market share to verify the two or more geographically adjacent LTAs satisfy the releasability threshold by re-calculating a market share value of respective stores in the two or more geographically adjacent LTAs.
36. The apparatus as defined in claim 29, wherein the local trade area building means is to identify the geographically adjacent LTA as ready for syndicated distribution when the releasability threshold is not violated.
37. An apparatus to identify a local trade area (LTA), the apparatus comprising:
- a similarity index engine to determine similarity index values associated with respective pairs of stores associated with a retailer location;
- a local trade area builder to generate local trade areas (LTAs) of subgroups of stores corresponding to the retailer location based on a comparison of the similarity index values to a similarity threshold value; and
- a release requirement manager to, when a respective one of the LTAs does not satisfy a releasability threshold, prevent erroneous disclosure of market share information criterion by re-distributing the stores within the respective one of the LTAs to a geographically adjacent LTA, at least one of the similarity index engine, the local trading area building, and the release requirement manager including a logic circuit.
38. The apparatus as defined in claim 37, further including:
- a census block group (CBG) interface to select CBGs associated with the retailer location; and
- an all commodities volume (ACV) interface to: (a) identify the stores within the selected CBGs; and (b) identify associated ACV values for respective ones of the stores.
39. The apparatus as defined in claim 38, wherein the similarity index engine is to calculate the similarity index values based on a ratio of (a) a sum of ACV values of respective pairs of the stores that share a common CBG and (b) a sum of ACV values of the respective pairs of the stores from all CBGs in which they contribute.
40. The apparatus as defined in claim 37, further including an LTA spatial engine to calculate a geographical center of the LTAs, the geographical center based on geographical coordinates of the subgroups of the stores.
41. The apparatus as defined in claim 37, wherein the releasability threshold represents a store sales amount within a geographical area defined by one of the LTAs.
42. The apparatus as defined in claim 37, wherein the release requirement manager is to re-distribute to two or more geographically adjacent LTAs.
43. The apparatus as defined in claim 42, further including a market share calculator to verify the two or more geographically adjacent LTAs satisfy the releasability threshold by re-calculating a market share value of respective stores in the two or more geographically adjacent LTAs.
44. The apparatus as defined in claim 37, wherein the local trade area builder is to identify the geographically adjacent LTA as ready for syndicated distribution when the releasability threshold is not violated.
45. The apparatus as defined in claim 37, further including a shape file generator to generate a distribution shape file of the geographically adjacent LTAs.
46. A tangible computer-readable storage medium comprising computer-readable instructions that, when executed, cause a processor to, at least:
- determine similarity index values associated with respective pairs of stores associated with a retailer location;
- generate local trade areas (LTAs) of subgroups of stores corresponding to the retailer location based on a comparison of the similarity index values to a similarity threshold value; and
- when a respective one of the LTAs does not satisfy a releasability threshold, prevent erroneous disclosure of market share information by re-distributing the stores within the respective one of the LTAs to a geographically adjacent LTA.
47. The tangible computer-readable storage medium as defined in claim 46, wherein the instructions, when executed, cause the processor to:
- select census block groups (CBGs) associated with the retailer location;
- identify (a) stores within the selected CBGs and (b) identify associated all commodities volume (ACV) values for respective ones of the stores.
48. The tangible computer-readable storage medium as defined in claim 47, wherein the instructions, when executed, cause the processor to calculate the similarity index values based on a ratio of (a) a sum of ACV values of respective pairs of the stores that share a common CBG and (b) a sum of ACV values of the respective pairs of the stores from all CBGs in which they contribute.
Type: Application
Filed: Jun 28, 2019
Publication Date: Jan 2, 2020
Inventors: John P. Mansour (North Aurora, IL), Michael J. Zenor (Cedar Park, TX), Mitchel Kriss (Long Grove, IL), Congrong Lou (Naperville, IL)
Application Number: 16/457,127