How can first-party
and open source data
inform retail site selection?
A multi-billion dollar financial institution was looking to create a quantitative approach to branch selection. Previous efforts had been more subjective and hadn’t fully leveraged existing data to inform these critical decisions. The cost of selecting the wrong location or market had the potential to be incredibly costly.
Our team developed a scalable, quantitative model to create a benchmark for the new market. We used existing first-party, open source data and projections of community growth in both the retail and commercial sectors. This model informed retail site selections and established a comparative baseline modeled on previous organizational performance for both commercial and retail sectors.
