Planogram Design Axioms Are Being Upended By Shopper Marketing Analytics In-Store

In-store retail analytics is such a hot field in large part because the store continues to be a black box from everything to store traffic optimization to planogram design.   We have analytics about who enters the store, and what transactions come out, but not a lot of data about what happens in the store.  That’s like knowing your unique visitors to your website and sales, but not knowing where they clicked around.  That’s certainly beginning to change.   

Retail analytics have begun to look at traffic flows, but given that shopping is inherently about connecting people and products, the next frontier is at the shelf behavioral analytics on what products shoppers engage with (and hence our focus on product engagement marketing).  And that’s why in-store analytics is growing much more rapidly than eCommerce analytics. This level of data that’s being turned on by platforms such as Raydiant is shaking up traditional norms of in-store design – some of which had been taken as gospel.  

Planogram Design Axioms Are Being Upended By Shopper Marketing Analytics In-Store

Let’s take planogram design, which is a great example where the lack of data makes in-store shopper marketing more art than science – until now.  The most common phrase I’ve heard repeated about planogram design is that “eye level is buy level,” that height is what’s important in driving shopper engagement.  Is the axiomatic belief in the primary value of shelf height true?  Maybe not, and now we have the data to prove it.  At a major pet client deploying end caps at grocery, we saw something groundbreaking.   The planogram heat map did indeed confirm eye-level shelving generally increased product interactions and pickups by 42% compared to -X% for the bottom shelf.   So yes, height matters a great deal. 

But an even greater factor, and one that had not been anticipated by the client was that the left and right edges of the end cap was a bigger factor, with the left edge increasing engagement by 99% and right side by 97%.   In fact, it was better to be on the left of the middle shelf than in the center of the top shelf. Minds blown! 

To paraphrase the feedback in the meeting: “if this is true, this would completely change the way we approach planogram design everywhere.”   But before rethinking all planogram design, we do need to acknowledge where correlation could be causation.   If you put the most popular products on the edges, for example, you could increase engagement.    That said, this appeared to be consistent across shelves and both middle-left and middle-right positions out performed the dead center.  The trend is clear.  The next step to rigorously determine the true effect is to randomize assortment, A-B test, and confirm.  

More Than A One Off - The Power Of Planogram Design Analytics Across Raydiant Clients

While the results were shocking to our client, we at Raydiant were not surprised.  Now that we are instrumenting shelves everywhere, we regularly provide data that challenges our clients understanding of planogram design.   And we also see patterns emerging.

Let’s take an example of the Macy’s Fragrance Bar. The Macy’s Fragrance Bar is organized into 6 scent families (floral, woodsy, sweet, spicy, etc.).  When you approach the display, there are 5 fragrances in a row, and if you pick up the tester or fragrance for any of them, it responds with digital media (videos, QR codes, ratings and reviews, etc).   And because we are detecting which products shoppers are touching, we can look at the interaction data again. What do we see?

I regularly ask what position people would pick as the most popular position and 70% of people choose the center. Is that the best choice? Actually not.

What we actually see is that the edges are the most popular, with the left seeing an additional 12% interactions and the right seeing 10% more product interactions.   The center, which was the most popular guess, was the third best choice.  And that’s the thing.  It is a guess, because we don’t have data – until now.  Now educated guesses can be tested.  Qualitative feedback in design can be married with quantitative feedback in the field and at scale.  Insights can lead to new testing.   Concepts emerge.  Iterate again. 

This is the future of physical retail and why it can become ever more powerful in connecting people and products.   We are opening up the black box inside the store and beginning to understand how it works, how we can influence shopper journeys and how we can attribute merchandising, pricing, packaging and digital content in influencing behavior. 

Retail Analytics Applied To Every Operation Of In-Store Retail

This is the brave new world of shopper marketing.  Organizations that adopt the new world of IoT sensors, computer vision and interactive display will learn faster – out maneuvering their competition and gaining market share.  

In-store engagement will become even more highly valued for its insights onto the business at large and its ability to capture first party data to convert in-store customers into omnichannel shoppers.   And retail analytics will transform customer management, store operations, strategy, merchandising and supply chains.

We are at the precipice of a data-driven shopper marketing revolution.  Are you ready?  Book a Demo with Raydiant!