We all enjoy seeing those fancy Super Bowl displays in the stores. And if you are directly involved with the promotions, you feel the sense of pride in seeing those displays! You also wait excitedly for the “sales lift” numbers to proclaim success of the marketing campaign.

But did you know that a vast majority of these promotions perform FAR BELOW their potential, simply because they are not aligned with in-store shopper behaviors? Scorecards based on sales data do not capture the missed opportunities. Despite considerable efforts/expense in designing and executing in-store displays, without fact-based behavioral insights, the financial returns for most of these investments remain extremely poor.

Inefficiencies in Display Strategy

One of the most important part of optimizing in-store displays is getting the location and adjacencies right. Consider these facts from VideoMining Display Deep Dive, which analyzes the path-to-purchase conversion measures and detailed attributes for 100,000s of in-store displays across different time periods.

• Carbonated Soft Drinks (CSD) displays can close sales 40% poorer depending on the display location relative to main beverage aisle
• Bottled water display performance varies by as much as 450% based on in-store location
• Candy display performance can be improved by 42% with better adjacency or as much as 600% by changing in-store location.
• Beer displays in grocery stores only close 23% shoppers who stop and engage (on average for 21 seconds)
• The closure rate for a Beer display at a given location varies as much as 68% for different pack sizes on display

This is just the tip of iceberg in the widespread inefficiencies that exist in display execution. There are obviously corresponding financial lost opportunities for both manufacturers and retailers. Simply improving the display location can have an immediate positive impact on the ROI.

Display Attributes that Matter

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

A good location and messaging can override the need for a sharper price discount during promotions. We have 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 impact of displays.

Another key way to improve display performance is understanding the behaviors of shoppers on specific trip missions. Analysis of the in-store paths of shoppers for different trip missions and their propensity to engage with displays at different parts of the trips can drive effective display strategies (See Reaching Shopper on a Mission: 3 Case Studies). 

Displays from a Retailer’s Perspective

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 boost in total store productivity.

Impulse sales from secondary displays – end caps, in-aisle shippers or perimeter displays can be quite significant; with displays contributing as much as 70% of total sales for some categories during a given promotional week.

Better allocation of display space not only leads to greater incremental sales but also enhances the in-store shopping experience. It can also help drive traffic to less visited areas in the store, for example, some of the center store aisles in a grocery store. This is especially true during special promotions such as for Super Bowl, when shoppers are typically on a special mission and well executed displays can improve the overall shopper experience and store performance.

Optimizing in-store displays and promotions is in fact, one of the lowest hanging fruits for leveraging in-store behavior data enabled by AI technology. Access to historical data on path-to-purchase conversions and display analytics can help in improving the promotional plans for a brand, for a category or for the store as a whole.

Behavioral Data for Optimizing 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 display 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 reaching shoppers.
• 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. This is a metric that helps in leveraging proximity for maximizing the value of a display.

Applying the above metrics to a large number of actual in-store displays with different attributes (category or categories, products, brands, price, signage, display type, display size, etc.) helps in systematically evolving winning “playbooks” for displays. Fact-based playbooks using the latest display data is especially important today with recent shifts in shopper behaviors in almost all store formats. Further, use of behavioral for in-store testing helps validate a display strategy, reducing the risks of failure.

So if you are waiting for the sales numbers after a promotional event, think about the missed opportunities from not using behavioral data as a “coach”. Next time use behavioral insights to create a much higher financial return from the promotional dollars for all your stakeholders!