Location Analysis – Picking the Best Hands

Marc Smookler

The Problem

Winning at poker requires discipline and strategy. Making the correctly sized bet for the cards that you are dealt. The best poker players in the world know the odds of winning each hand they play. They know the probability cold. These players know when to bet big and when the hand needs to be folded. Choosing the right starting hands and having a disciplined approach and process is the difference between being a winning and losing player.

Real estate site selection is similar because it requires discipline and the results of an undisciplined process can be catastrophic.  The classic dilemma in site selection is finding the available property but are you making the best decision? Do you even know what the data components of a successful site look like?  

There are books and books written about poker strategy, lining up the probability,  but when was the last time you read a book on how to stack the odds in your favor for site selection?  Who talks about those probabilities? How would you even come up with what your starting hands should be?  


Those assigned the responsibility of site selection have the unenviable task of trying to cobble together sparse real estate availability with price and hope that the site fits the model of the franchise.  IdealSpot solves the unknowns of site selection by creating a probability type of metric for those looking at locations. The platform takes the guesswork out of site selection through the use of data science.

It is possible to extract data from 1000s of sources and find the criterion that makes your site more likely to succeed based on mathematics.


IdealSpot’s Core Process / Value Proposition:

1)    Isolate external key drivers of performance (KPIs) from multiple store data sets (demo/psychographic).

2)    build a map for success using the KPIs so that we know what to look for

3)    apply the map to the IdealSpot platform to search for the best location for a store

Marc Smookler
Marc Smookler has founded 6 companies—2 of which have been acquired and 3 of which are market leaders in their respective spaces—the leading brick-and-mortar retail analytics company (, a leading online retailer (, and a cutting-edge marketing services platform ( Marc’s companies have generated over $300M in lifetime revenues and sold over 150,000 products worldwide.

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