StoreGround floorG02 · Personal project
Same store, two streets
Picture one store, built and run the same way on two different streets. Shoppers behave the same once they're inside, so the only thing that changes is how many people walk past the door. Pick a street and see what share of them the store has to win over just to break even.
Pick a street
Same store, same prices, same shoppers inside. Only the street outside changes.
1 in 171people walking past has to come in. One in five of them buys.
- Walk past a year
- 12.8M
- Visitors who buy
- 1 in 5
- Average spend
- $80
- Sales to break even
- $1.2M / yr
How to read it
The store needs $1.2 million in sales a year to cover its costs. With an $80 average spend and one visitor in five buying, that takes 75,000 visits a year. On a corner where 12.8 million people walk past, 75,000 is 0.6 percent of the crowd. On a quiet side street with 1.1 million, it's 6.8 percent, more than ten times harder for the exact same store.
That's why location decisions start with the street, not the store: the traffic outside sets how good everything inside has to be.
Where it comes from
At Under Armour I built a scenario model in Excel to size a chain-wide rollout across store tiers: how cost per store and cost per square foot fall as you open more, against break-even benchmarks. This model is an anonymized cousin of that thinking, with illustrative figures. None of Under Armour's numbers are here.
The street side uses public data: two years of hourly counts from Melbourne's open pedestrian sensors, 1.6 million rows cleaned in Python. The 78 most complete sensors are being sorted by traffic quality in Tableau, so each street type can feed the model as a tier instead of a guess.
What's next
The full version opens in a later release: the Excel rollout model with every store size, and the Tableau view of the 78 streets.