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SUBMISSION INSTRUCTIONSUsing Spatial Analytics for Retail Site Analysis
Using Spatial Analytics for Retail Site Analysis
Author: Jason Claunch - President
Company: Catalyst
Business Partner: Slalom Consulting - Sean Hayward and; Marek Koenig
Originally Published: 2017 Excellence Awards Entry
Use Case Overview:
The developed solution used many of the Spatial Analytics components available within Alteryx:
- Trade Area – have user select target area to analyze
- Spatial Match – combine multiple geospatial objects,
- Intersection – cut objects from each other to create subject area
- Grid tool – sub-divide the trade blocks to determine complete coverage of trade ring
- Distance – use drivetime calculation to score and rank retailers in the vicinity
Describe the problem you needed to solve:
Retail site analysis is a key part of our business and was taking up too much time with repetitive tasks that could have been easily automated.
Describe the working solution:
To support selection of best-fit operators, Catalyst partnered with Slalom Consulting to develop a tool to identify potential uses to target for outreach and recruitment. Previously, we would have to manually build demographic profiles using tools like qGIS, ESRI, and others, but found the process to be cumbersome and quite repetitive. Demographic data was acquired at the trade bloc level, which was too granular for identify target locations and would not mesh well with the retail data.
Alteryx and its spatial capabilities was used in a few ways:
1) Minimize our retail data selection from the entire US to a selected state using the Spatial Match tool.
2) Create a demographic profile for each retail location that consisted of data points such as median income, population, daytime employees, and others. The data was aggregated around a 3 mile radius of the specific retail location with an Alteryx Macro composed of a Trade Area, Grid Tool, Spatial Match, and Summarization tool.
3) Using a Map Input, the user selected an area to profile and candidate retailers were output for further review.
4) After selecting specific retailers to do an in-depth analysis on, Alteryx would score all possible locations by distance (Drivetime Analysis) and by score (proprietary weighting of various demographic attributes). The profiled results were then used to build a client presentation; the automated profiling tool saved us countless hours and allowed us to deliver more detailed analysis for our clients.
Describe the benefits you have achieved:
Using Alteryx was a massive time saver, the tool that we built took a process that normally required at least 8 hours of manual work down to merely a few minutes. This has directly benefited our bottom line by allowing us to focus on more key tasks in our client outreach and recruitment. A return-on-investment was immediately realized after we were able to close a deal with a major client using our new process.
