Space Shop Self Storage (SS) is an Atlanta-based self-storage company that has a successful business formula for operating profitable storage centers. The leadership team wanted to scale its footprint to cover the United States, but it did not have the staff to personally visit all of the possible locations. SS needed to identify geographies and locations it could prospect for acquisition and development.
The question to Rocket Partners was seemingly simple: If SS wanted to develop 100 locations, then what were the top-10 markets and the top-10 neighborhoods in those markets that met the investment criteria. The leadership team believed the data existed that would lower its risk and accelerate the growth of the company, but did not know how to pull the data and correlate it to solve the specific business problem. There was no shortage of advanced tooling that allowed users to query individual locations for a fit, but there were no off-the-shelf solutions that could look across the country in a single view to find all locations that met the given criteria.
Space Shop Self Storage (SS) manages a portfolio of self-storage locations across the Southeast United States.
ROCKET PARTNERS SOLUTION
Rocket Partners worked with the SS business analysts to understand the evaluation criteria that would drive the rules-based engine, which included population density, income demographics, and competitive intelligence such as local market self-storage rate information.
The build out of the data set required acquiring and cleaning public-record census data, securing storage-rate information from other third parties, and merging the data on to a one-quarter-mile-by- one-quarter-mile grid of the entire United States so that self-storage locations could be identified. Finally, a precise, custom “trading area grid” visualization was created that allowed the evaluation criteria to be scored for 100,000 unique locations simultaneously.
“We believed that we could bring public data sources together in a new way that would give us a competitive advantage in new market analysis. I will never forget the first time the leadership team saw the recommended acquisition sites of known markets―it matched our existing sites exactly! The Rocket Partners’ team made the solution easy to implement into our existing business model, and the results were immediately impactful for the company.”Jason Linscott,
The final outcome was an interactive heat map that provided instant insights for the SS leadership team. It could now use the tool to evaluate new cities, such as Denver, Dallas and Phoenix, where it did not have detailed local-market knowledge. SS could now instantly prioritize neighborhoods and identify specific trading areas where investments should be targeted.
- Merged private and public databases (i.e. census data, self-storage location data, storage retail-rate data, etc.) into a queryable SS database.
- Created an interactive visualization tool that would dynamically search the SS database as new criteria was entered to discover ideal locations across the United States.
- AWS ECS (Elastic Container Search)
- AWS Elastic Map Reduce
- GIS Systems
- Google Mapping API
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