The challenge

A DIY product range was struggling to gain visibility in-store and was repeatedly rebranded in an attempt to improve sales. Each packaging redesign required short print runs and limited trial periods, making the process expensive and unreliable.

Sales data alone was difficult to interpret. Performance varied widely depending on external factors such as time of year, weather, school holidays, and aisle positioning. With relatively low sales volumes, short trial periods made it impossible to determine whether one design genuinely performed better than another.

In simple terms, there was no reliable way of knowing whether a new design was an improvement — or whether fewer customers were simply walking past the shelf.

The problem 

Sales figures without context were misleading.

For example, were 12 units sold on a sunny day better than 8 units sold on a rainy day? Without understanding customer footfall and engagement, design decisions were based largely on assumption rather than evidence.

The approach

To remove one of the key variables, we set out to measure how many customers were actually passing the product display.

During development of the prototype, we realised we could go further — by also measuring dwell time: how long customers stopped and engaged with the display itself.

We designed and installed a discreet, battery-powered sensing system using small infrared sensors positioned at the left, right, and centre of the display. A custom low-power data logger was developed to timestamp and store the data over extended periods.

Every two weeks, the data was manually collected during store visits, and the product packaging was replaced with the next design iteration.

The outcome

After three design cycles, the client was able to compare packaging performance using normalised data — combining sales figures with footfall, dwell time, and external factors such as weather.

For the first time, conversion rates could be calculated for a specific product range at shelf level, providing clear, objective insight into which designs genuinely performed better.

Decisions that had previously relied on instinct could now be made on evidence.