Shrinking Center Store, Expanding Opportunities (Part 2): Re-imagining Displays
Rajeev Sharma
February 15, 2022

Displays to Drive Center Store Traffic and Boost Impulse Purchases

With the accelerating online migration of grocery sales, there is an opportunity for retailers and manufacturers to collaborate and re-invent the physical store. The last VM Nugget focused on the potential of “destinations” in the center store as a way to elevate the in-store shopping experience. In this VM Nugget, we explore how secondary displays could serve as a strategic tool to make up for the inevitable erosion in center store traffic.

Secondary displays today are largely used by brands as a tactical tool to gain category share especially in combination with price promotions. While retailers see displays as a way to bring in incremental sales and trade marketing dollars. Also, without precise in-store measurement and analytics, significant inefficiencies exist today in both display practices and execution. With changing in-store shopping patterns and evolving store formats, there is an urgent need to “re-imagine” display strategies and to optimize display performance using shopper insights.

Two key considerations for optimizing displays in the transformed store should be:

A. Driving Traffic to Center Store: Displays can engage and help draw traffic into the center store – especially for destination categories. Our data has shown that displays can have a significant impact in influencing shoppers to visit the center store aisle – sometimes adding more value by driving traffic than driving direct sales off displays. This “halo” or signpost effect of displays can be very valuable in driving incremental traffic to center store, inviting shoppers to (re-)experience shelf interactions in making their product choices. With potential innovations in center store merchandising, displays can become a valuable partner in attracting consumers to re-consider the experience of in-store shopping.

B. Boosting Impulse Purchase with Reduced Traffic: Impulse sales from secondary displays – end caps, in-aisle shippers or perimeter displays can be quite significant; with displays even today contributing as much as 70% of total sales for some categories in a given promotional week. With the evolution of store formats, there are a lot more opportunities for secondary displays, especially in new “service” areas where waiting and lingering is now part of the store dynamic. These “under displayed” areas include – the Deli, Food service, Coffee, Bars, Pharmacy, and Online pickup areas (BOPIS: Buy Online Pickup In-Store). There is a lot of room for developing productive display strategies in these areas to drive impulse sales. While there are new display possibilities, the changing traffic patterns and in-store dynamics means that both retailers and manufacturers have to adapt their display/promotion strategies, otherwise they risk losing a valuable source of incremental revenues or sub-optimal promotions.

Inefficiencies in Display Strategy

A big part of optimizing displays is getting the location/proximity right. Location plays a huge role in display performance with as much as 600% variance for some categories based on just location (Source: VideoMining Display Deep Dive). With the shifts in traffic patterns and shopping behaviors old display placement rules are very likely to be outdated for optimizing impulse.

 Consider these facts from VideoMining Display Dataset (that has the path-to purchase conversions measures and detailed attributes for 100s of thousands of in-store displays):

  • Beer displays in grocery stores only close 23% shoppers who stop and engage (on average for 21 seconds)
  • Carbonated Soft Drinks (CSD) displays can close sales 40% poorer depending on relative position to main beverage aisle
  • The closure rate for a Beer display at a given location varies as much as 68% for different pack sizes on display
  • Bottled water displays performance varies by as much as 450% depending on in-store location

This is just the tip of iceberg in the widespread inefficiencies we see in display execution. There is obviously a corresponding significant opportunity loss in financial returns for the promotional dollars spent. Simply improving the display location can have an immediate positive impact on ROI. From the retailer standpoint, data-driven allocation of the display locations (end caps, other secondary displays) to create the right combination of categories every week can lead to substantial increase in total store sales.

Since displays can play a strategic role, better allocation of display space not only leads to more incremental sales but also enhances the in-store shopping experience. This was especially evident during the pandemic when the shoppers made more “stock up” trips and spent a significant proportion of their time in the perimeter areas of grocery stores, making displays even more important for incremental sales and shopper convenience.

Location is not the only parameter that has a significant impact on display performance. The brands promoted, number of products on display, pack sizes, messaging, price, etc. greatly impact the engagement rate and closure rates for displays.

A good location can override the need for a sharper price discount during promotions. We have also documented cases of significant improvement (2-3 x) by simply changing the messaging content for a given display. Clearly knowing who the primary shoppers (not consumers) are for a product and creating content that appeals to that segment goes a long way in enhancing the stopping power and performance of displays.

Further, in-store path analysis of the targeted audience, for example, shoppers on a “barbeque” mission can create opportunities for special displays, for examples for “beans” to help shoppers consider additional products not on their original shopping list.

Using Behavioral Data to Optimize Displays

Optimal display strategies can be evolved by following a principled approach, driven by data and analytics, based on measurement of actual in-store shopper behaviors. This allows for quantitative behavioral feedback on the impact of displays and optimizing the displays against multiple objectives.

Fortunately AI technologies have now made it possible to precisely measure display performance under different conditions, providing a formal fact-based approach for developing display strategies that are optimized for the current shopper and retail dynamics. Below are some key metrics that are relevant for measuring and optimizing impulse performance.

> Exposure Rate measures the volume of traffic for a given location relative to total store traffic. Out of 100 store visitors how many pass by in front of the location? This metric is key to quantifying the value of a location for driving impulse.

> Engagement Rate measures the rate at which passersby take interest in the product displayed at a given location. This metric represents the “stopping power” and depends both on the location and the category/product displayed. For the same display, shoppers may engage differently at two different locations so all “exposure” is not equally valuable.

> Closure Rate measures the percentage of engaged shoppers who buy a product from the display. This metric is largely influenced by product, packaging and pricing. It is also inherently impacted by the “impulsivity” of the category and is also a useful metric for benchmarking across all categories that are competing for a given space.

> Relative Directional Traffic Flow measures how much of a location’s traffic is moving toward another specific location. This metric can be used to determine the traffic dynamics in relation to the promoted item’s primary stocking location or even a complementary product or category. For example, a salsa display could be used to encourage shoppers to make a trip to Salty Snacks (for complementary tortilla chips) as well as Condiments or International Foods (primary stocking locations for salsa as well as complementary products). This is a metric that helps in leveraging proximity for driving impulse purchases across multiple locations/categories.

Applying the above metrics to a large number of actual in-store displays with different attributes (category, product, brand, price, signage, display type, display size, etc.) allows a systematic analytical framework for developing a fact-based “playbook” for optimizing displays for a given category or brand using the latest in-store behavior data for a given store format.

The Display Opportunity

Displays can serve as strategic tool for both driving traffic to center store and for valuable incremental revenues from impulse purchases. Displays also help in enhancing the overall in-store shopping experience. Data-driven displays strategies are critical to keep up with the changing in-store dynamics in the increasing omnichannel and competitive retail landscape.


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