. Dwell time in the store
2. Average shop times across a particular time of day or day of the year
3. Parts of the store that customers visit the most and the least
4. Where customers live or work in relation to the store
5. Cross-store data comparisons
What should you do with all that information? The first step to turning data into something useful is to analyze what those numbers mean and figure out how you can improve. For example, if the numbers tell you that checkout time in your store is longer than the industry average, use that information and find ways to streamline the checkout process.
Or, say you know which parts of your store are getting the most and least traffic. The next step is to figure out why certain store sections are getting more visits than others. Is it because of the products in those departments or is it their positioning in the shop?
And don’t forget to consider factors outside your store, such as the weather, environment, time of year, etc. As David put it:
Retailers need to understand what the above metrics mean and how to explain the differences, such as was there bad weather one day that increased or decreased the dwell time? Did some other store nearby run a major sale that brought people into the mall or the block? Did a special advertisement bring more customers in for a particular reason? Did a store layout encourage or discourage shoppers from going to a particular place?