A fundamental challenge that all types of retailers face everyday is merchandising. Part of this entails selecting goods or services to sell and price appropriately for their target markets. This is especially challenging for retailers who develop and coordinate their merchandising strategy for several different retail outlets from a central office. Every retail market can vary significantly and making incorrect guesses about what to sell, where to sell, and how to sell can significantly affect a retailer’s bottom line.
While it may be obvious that a retailer shouldn’t stock winter coats in Miami in the summertime; it may not be as obvious that a certain brand and type of yogurt at a certain price point will sell better in one store compared to another. The demographics, lifestyle, and consumer behaviors of the underlying population of a retailer’s market could affect sales as much as the climate and seasons. Retailers must understand that a key part of developing a successful merchandising strategy is to acknowledge and take into account these other factors.
Leveraging Your Sales Data
Retailers can leverage their sales data associated with their retail outlets along with Esri’s Consumer Spending, Market Potential, and Tapestry Segmentation data as part of their effort to optimize their merchandising strategy. In this discussion, we’re going to focus on how Esri’s Tapestry Segmentation data accessed through the Business Analyst API can help retailers understand their customers and better anticipate their needs.
The Business Analyst API gives application developers the ability to flexibly query and analyze Esri’s Tapestry Segmentation data. Developers can leverage Tapestry Segmentation to find out
- Who are the customers of a market
- What these customers buy
- Where can more of these types of customers be found
- How can they be reached
One of the most significant features of Esri’s Tapestry Segmentation is its ability to classify locations into one of 65 unique market segments. Each segment is a unique combination of socioeconomic and demographic characteristics which effectively describes the majority of households within an area.
In many instances, retailers will use test markets to determine product interest and price points. Part of a comprehensive merchandising strategy can entail the determination of expansion markets for a promising new product based on the similarities (or differences) with the test markets.
With Esri’s Tapestry Segmentation, this can simply mean determining the dominant Tapestry Segments of the test markets where the new products showed the most promise and; identification of expansion markets with a similar composition of dominant Tapestry Segments and their associated household socioeconomic and demographic characteristics.
Esri’s Tapestry Segmentation can take a lot of guess work out of selecting the right markets for a retailer’s products. Developers can develop applications which target retailers and leverage the Tapestry Segmentation data in a variety of ways through the Business Analyst API
- The Get Summarizations service (REST, SOAP, Flex, Silverlight) gives developers the ability to list all of the Tapestry Segmentation variables available in their Business Analyst API subscription. Many of these variables are the Tapestry Household counts for each of the 65 segments.
- The Benchmark Report service (REST, SOAP, Flex, Silverlight) is a report generation service which gives developers the ability to query a list of analysis variables, including Tapestry Segmentation variables, for study areas which can be described as custom polygons describing user-specified map areas or standard administrative boundary areas such as ZIP codes, counties, Census Tracts, etc. The output of the Benchmark Report service can be PDF for presentation purposes or the API’s simplified XML format (S.XML) for easy integration into systems or applications.
- Like the preceding service, the Smart Map Facts (Thematic Query) service (REST, Flex, Silverlight) also gives developers the option to query a list of analysis variables for study areas described as standard administrative boundary areas but; with a few differences. These differences include the ability to query all standard administrative boundary areas of the same type within an extent or which intersect or overlap with other types of input geographic features such as points, lines, or polygons. An additional difference includes the ability to parse the results from a JSON response.
REST request examples of the three services to query Tapestry Segmentation variables can be found in the supplemental developer notes.