You know how much money you win, but do you know how much money you lose?

A full understanding on how to improve the Shopability of your store is easier than before when we were only able to get simple people counter information. Now retailers are able to track the entire shopper journey and translate the data into decision-driving insights. The question is,  are we doing it right or are we just measuring profitability without achieving full profit potential? If the potential loss is left unrecorded and undetected, it grows.

Is there more room to improve when you are already a successful retailer on well known high streets? Monolith recently did an extensive research and unveiled multiple lost opportunities that could be solved with simple changes. Simply by knowing how shoppers behave in your store.


One of the most interesting findings by Monolith was in a multi-story flagship in London. With a wide range of products for various demographic groups, this retailer is recognized globally as a leader in its field. With multi million sales annually, they attract over hundred thousand visitors per month. Once Monolith started collecting more extensive data on demographic mix, directional flow of visitors and zone performance, it became clear that a floor dedicated exclusively for females was underperforming. Less that 50% of the total female visitor population reached this floor. So even though the store and this floor are profitable, there was a huge potential they weren’t even aware of. So now the question is: “How can we increase Shopability and how do we quantify the loss?”


In this day and age, we are able to get comprehensive insights for the entire shopper journey such as demographics, capture rate from shopping windows, time spent in the store and in specific zones, interaction with specific shelves or products and staff performance.​ In the above-mentioned case, we discovered that:

  • 90% of customers asking for directions were female.
  • 70% of customers who were looking at directories when entering were female

The next was to look at why the females were unable to find their way to the third floor. Our first conclusion was that there were not enough signs showing them where they had to go. Our second conclusions was that visitors could not easily find the escalators going up and got distracted on other zones.


We suggested to change the escalator directions starting at ground floor, spiraling up to 3rd floor so ladies were able to reach the 3rd floor easier. These small changes resulted in 36% revenue uplift! By the end of the month, 82% of all females that have entered the store have landed on the 3rd floor. The number of female visitors increased by 26%. A simple low-cost change that immediately, significantly increased the revenue which would otherwise be a lost opportunity. The investment in in-store analytics paid itself back instantly.

A small change resulting in 36% revenue increase.


  • It is essential to understand what drives conversion
  • We have proven in all cases that engagement is the key driver of conversion
  • Dwell time is the largest contributor to engagement
  • The key driver of dwell time is staff performance and spacial design.
  • We need to remove barriers and enhance carriers of engagement to drive Shopability

Financial results give an essential dimension in understanding in-store analytics. Behavioral insights should always be plotted against financial results to obtain a full understanding of what effects your store decisions have. Too often we see learnings stay within a division and are not applied and shared throughout the organization. Monolith encourages customers to save the impact of changes in our Actionboard impact module, to keep for future learnings.


The insights in-store analytics technology gives is of no use, if you are not empowered to make decisions and test new changes based on the insights. However, when the potential loss is shown it makes it easier to prove why changes are necessary. A potential loss becomes an opportunity. That is why we need to evolve towards actionable insights opposed to sheets of data.

How retailers will set themselves apart from competitors will remain a joint effort between their marketing and product experts. To ensure they measure the impact on behavior, that converts to sales, retailers should now move from knowing to understanding. Simple interventions could have dramatic effects but interventions start by first understanding how shoppers engage with your products, store and brand.