In 2021, a typical center store category in a grocery store in USA got exposed to only 14% of the total store traffic. It attracted only 42% of the passing traffic to stop and engage with it. Of those who engaged, only 55% ended up buying from the category. (Source: VideoMining Grocery Shopper Insights Tracker using behavioral data from 1.2 billion store trips in 2021.)
Clearly, the in-store sales funnel is quite leaky for grocery (and other physical) stores!
Fixing the leaky in-store funnel is especially critical today, as physical stores continue to hemorrhage traffic due to online migration, trip consolidation and hyper-competition.
Thus both retailers and their CPG partners are under increasing pressure to find innovative ways to convert precious store visitors into buyers (while also investing in omni-channel strategies). A wide variety of levers in marketing, merchandising and store design are being employed to improve in-store customer experience and increase conversions.
However, one of the biggest shortcoming in current approaches to tackling the in-store challenge is lack of proper measurement, relying heavily only on sales/loyalty data for evaluating performance. Without visibility into the different stages of the shopper path-to-purchase, it is not surprising that investments in innovation, shopper marketing and trade marketing yield very poor ROI.
Measuring performance along the In-store Path-to-Purchase
There are three fundamental metrics derived from in-store shopper behavior that can help identify and optimize opportunities along the in-store sales funnel:
- Exposure Rate
- Engagement Rate
- Closure Rate
These metrics help in decomposing the in-store path-to-purchase into three distinct stages, each impacted by different marketing levers. These metrics can be standardized and benchmarked across all relevant in-store elements, e.g. all categories, product segments, displays. It provides a simple but powerful framework for maximizing the value of any investment aimed at improving the in-store shopping experience and retail performance.
- Exposure Rate
This is simply the percentage of total store visitors who pass by a category or a product display. Exposure Rate measures the volume of traffic for a given location relative to total store traffic. In other words, of every 100 people who walked into the store how many had the “opportunity to see” the category or a product display. After all, if they don’t come they can’t buy!
With the average exposure rate for grocery center store category being so poor, increasing the exposure rate is key especially through secondary displays or proper placement of a product. As in-store shopping behaviors and traffic patterns or “heat maps” continue to shift, it is important to carefully re-evaluate the exposure rate for different store placements, especially for impulse categories.
- Engagement Rate
This is the percentage of traffic that passed by a category or product display that engaged with it. Engagement Rate measures the rate at which passersby take interest in the product displayed at a given location. In other words, of every 100 people of who walked in front a category or product display, how many stopped to visually or physically interact with it. It measures the “stopping power” of a product display. After all, if they don’t stop, they can’t buy!
Retail environments are typically very busy, with numerous visual elements competing for the shopper’s attention. Many shoppers are in an “auto pilot” mode for portions of their store trips. Improving the engagement rate requires finding ways to stand out and to be relevant. It requires an understanding of who the shoppers are and the context of the surrounding area or the adjacent products. Sometimes it is simply a matter of the right signage. We have case studies from testing different versions of messaging (or copy) of display signage, demonstrating 200-300% differences in engagement rates for the same product promotion.
- Closure Rate
This is the percentage of engaged shoppers who buy a product from a category or display. In other words, of the 100 shoppers who actively engage with a category/display, how many ended up buying a product from there. Closure Rate is a very important metric since it represents the last stage of the in-store sales funnel. Shoppers have already travelled to the category/location and invested time in interacting with the products. It is hard enough to attract and engage shoppers in today’s retail environment. Letting them go without meeting their needs is a huge miss!
Fixing the “shopper leakage” and improving closure rates is a big opportunity in retail. In the grocery channel, where the average center store category closure rate is 55, it means there is an opportunity to influence 45 out of 100 shoppers to buy a product and not walk away after their interaction with the category. In fact, for some categories the “walk away” rates are much worse, e.g. 73 for hard seltzers.
The immediate financial incentives are obvious. Even a modest increase in closure rates of 2 to 4 can increase the category sales by 4% to 8% creating a significant revenue impact. But the benefits of paying attention to closure rate goes beyond short term sales. It can help in improving the shopping experience and reduce migration to other channels. After all, how many times will shoppers visit a category and experience the frustration of not having their needs met, before taking their business elsewhere?
What causes shoppers to walk away after engaging in a category? How do you plug this leakage?
Analyzing the shopping behaviors of “non-buyers”, or those who browse then walk away without buying, provides the needed diagnostics. The detailed behaviors of these shoppers help in identifying the barriers to purchase. There could be a multitude of reasons, such as, pricing, assortment, or out-of-stock (OOS) especially in recent times with supply chain challenges. The shopper leakage could also simply be due to confusion at the shelf or a “shoppability” issue, where shoppers are not able to find the right product quickly enough.
Shopper are impatient and if the planogram is mismatched to their decision making process or the assortment does not appeal to them or they perceive high pricing in a category, they can simply leave. It may be a matter of improving the layout of the category or tweaking the assortment/pricing to meet the changing demographics, trip missions and shopper preferences. Identifying and lowering the purchase barriers, by pulling on the right levers to improve the closure rates can really help both the category performance and overall shopper experience.
Exposure, Engagement, Closure leads to Sales!
When diagnosing in-store sales leakage and developing strategies for improving retailer performance, it is useful to remember the “amplifying” effect of the three funnel metrics. They feed off each other and in fact, multiplying the three metrics directly shows up as sales numbers.
Exposure Rate x Engagement Rate x Closure Rate x Store Traffic x Average Basket = Sales
where, Average Basket = Number of Units x Average Price
The above equation provides a quantitative basis for evaluating the financial impact of any in-store investment. It helps in estimating the “size of the price” for an opportunity and calculating the ROI. It helps in explaining past performance, identifying missed opportunities and testing/evaluating new ideas. Measuring the funnel conversions using behavior analytics can take the guesswork out of a potential ROI, allowing winning strategies to be rolled out with confidence.
So the next time you are wondering about the effectiveness of your current retail execution, or you are evaluating a new idea for improving sales, it’s time to bring in the behavior analytics plumber. It’s time to detect and fix the leaks in the in-store sales funnel with the right tools!
