Show the work.
State the limits.

We are a small independent team with a background in geospatial data science and retail location analytics.

We built LookAlike because we kept seeing the same pattern: location tools promised revenue forecasts the underlying data could not support. Teams learned that lesson the hard way, then stopped trusting location analytics altogether.

Our rule is simple: say exactly what the data supports, refuse what it does not, and show the work. Every score in LookAlike is explainable down to the feature level. The product states its limits inside the app and on every export. It measures neighborhood resemblance. It does not predict whether a store will succeed.

We believe good site selection combines open data, transparent methods, and experienced human judgment. Data should help a team screen markets, find overlooked neighborhoods, and ask better questions. The final decision still belongs to the people who understand the concept, the property, and the market.

That is the kind of location intelligence we want to use, so that is what we are building.