Every store has sales and transaction data. It shows which products were sold, when they were sold and at what price. For many retail chains, these figures form the primary basis for decisions about assortment, store layout and marketing. However, they fail to answer one crucial question: Why do customers buy what they buy? And why do they choose not to buy other products?
Point-of-sale data is valuable. It provides clear figures on revenue, sales volumes and basket composition. For inventory management and product performance assessment, it is indispensable.
However, between the moment a customer enters the store and the moment they pay at the checkout lies a black box. What happens in between? Which routes do customers take? Which shelves do they stop at? Which products do they pick up but then put back? Which areas of the sales floor receive little customer traffic?
Sales data cannot answer these questions. And this highlights a fundamental problem: decisions about store layout, assortment and marketing are often made based on outcomes rather than the behavioural drivers behind those outcomes.
Consider the following example: a product located in the back of the store delivers weak sales performance. The obvious response may be to reduce the price or remove the product from the assortment altogether.
But what if the real issue lies elsewhere?
Perhaps very few customers ever reach that part of the store. Perhaps the shelf location is poorly positioned. Perhaps a competing brand displayed nearby attracts more customer attention.
Sales data reveals the outcome. It does not explain why that outcome occurred. Without that explanation, every corrective action remains an assumption.
To make informed decisions, retailers need data that reflects actual customer behaviour on the sales floor. This includes:
These metrics bridge the gap between what is being sold and why it is being sold. They make the impact of layout changes, assortment decisions and marketing initiatives directly measurable for the first time.
In e-commerce, customer behaviour analysis has been standard practice for years. Retailers know exactly which products are clicked on, how long customers spend viewing them and at which point they abandon the purchase journey. This level of insight enables continuous optimisation.
For a long time, physical retail lacked the ability to capture comparable information. Today, modern technology is closing that gap. Customer movement can be measured anonymously, in compliance with GDPR requirements and without requiring customers to carry any device. The result is behavioural data that does not replace point-of-sale data but complements it and explains it.
For retail chains seeking to systematically optimise their sales floor, the combination of sales data and behavioural data provides the foundation for informed decision-making. And Respory helps make that possible.
