At Nexo we believe that every part of our solution should be valuable on its own, but when combined should be greater than the sum of its parts.
When we built our solution this was a driving force in development. How can we utilize all of our inputs to develop better insights, and improve recommended actions?
We can measure a fridge’s door openings very simply, and from a single data point, one can build an actionable recommendation. Low sales rate against the average for the channel? Reduce the size of your fridge, surely. High sales rate? Increase the size of your fridge, right?
As an example, lets look at the first scenario: low sales. Using a single data point, reducing the size of the fridge looks like the right thing to do. However, simply add ‘footfall’ to this equation and you can see that this could be the wrong decision. If footfall is low against the average then it’s no surprise that sales are low; the action here is to improve footfall, either by moving the fridge, or by driving increased footfall through other activities.
If footfall is high but conversion is low, we can theorize that the planogram may be wrong for that location, and can look at merchandising other brands. Alternatively… we can add another data point from another of the Nexo services, and see that the temperature of the fridge is too high. Therefore the reason for the lack of sales is simply that the drinks are warm, and consumers have worked this out. Remerchandising would not only be wrong, but it would lose even greater sales over the long term.
Where other services might use single or limited data points to develop their recommendations, Nexo uses the power of three.