The Measurement Minute by Gary Angel

The traditional measure used to optimize space in store layout is sales per square foot. Optimizing sales per square foot doesn’t mean that the merchandise with the highest sales should have the most square feet. Some merchandise doesn’t need a lot of space. Some does.   The important metric isn’t the actual sales per square foot of an area, it’s the incremental gain or loss in sales if you took a square foot away or added one. A store layout is optimal from a space perspective when changing the size of any area would reduce sales per square foot.

That’s fine from a conceptual perspective but it’s nearly impossible to get at from a testing or metric perspective. And that’s where measures of density come in. The goal of density metrics is to help provide a behavioral proxy for potential problems in space layout.

You can measure how many shoppers use an area AND you can measure whether the conversion rate or basket size is impacted by crowding.

The simplest measure of density is just foot-fall. In our DM1 platform, for example, we can measure exactly how many shoppers visited an area down to individual square feet of the store. But foot-fall isn’t a very good measure of density because it doesn’t capture where shoppers are spending time. Time spent is a better measure that can be turned into a density metric by dividing it by the underlying size of an area.  The higher the number, the higher the density.

Another way to skin this metric cat is to measure occupancy. We measure both average occupancy – the number of shoppers typically in the area during a period of time and peak occupancy – the highest number of shoppers recorded in the area at any point during the period.

By combining any of these metrics with conversion rates for the period, you can measure whether and when density impacts sales. And understanding how often that’s happening is a great way to drive layout testing that involves expanding or shrinking the size of an area.

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