Over the past months, much attention has focused on how consumers are changing the way they shop as a result of the pandemic. Research suggests they are narrowing the range of grocery items they typically purchase, increasing the quantity of those they do purchase, and trying to spend less time in stores.1 Now that we have an understanding of how consumers have changed their behaviors, the next logical question is what we can do to better meet customers’ needs. One particularly popular option in recent discussions with clients and industry colleagues is limiting the options available at the shelf.2
Evidence showing the pros and cons of limiting consumer choices has been accumulating for years. A 2000 paper showed that while shoppers might have interest in being offered a larger assortment of jam, when it comes time to make a purchase, they're more likely to do so if they are able to select from a smaller set of options.3 On the other hand,4 some retailers who have reduced the variety of SKUs stocked with the goal of simplifying the customer experience ended up facing a decline in sales.
So, how do we know where limiting choices may be beneficial? And, further, which options we eliminate? As with most decisions, there is not a simple formula to tell us the optimal number of SKUs to offer. However, addressing questions of how to optimize a line of products is a foundation of brand management and marketing research, so we have many tools at our disposal to guide us in making those decisions.
SKU Rationalization – Via Sales / Secondary Data
One of the first steps in the process of deciding which products should stay on the shelf is looking at available data, such as sales and manufacturing costs. Though this can be a useful starting point, relying solely on secondary data is limiting because it only reflects products’ historical performance in the market. For example, based on secondary data alone we may decide to remove a lower performing instead of a moderately performing product. However, it may be that if the moderately performing product is removed, customers who typically purchase it would switch to another product in the line, while if the lower performing product is removed, customers who typically purchase it would switch to a competitor. In this case, it would potentially be more advantageous to remove the moderately performing product. These types of insights on the impact of removing products from the shelf on customer choices and category sales can be captured via primary research methods.
SKU Rationalization – Via Primary Research Methods
In situations where the secondary data review provides a handful of hypotheses on what to remove from the shelf, primary research can be used to test how consumers are likely to react to each of those specific scenarios. In situations where the possible changes to the shelf cannot be narrowed down to a handful of scenarios, a conjoint methodology can be employed to predict consumers’ likely reactions to a broad range of changes to the shelf.
In either situation, shelves can be mocked up with product images and details to match planograms and pricing at different retailers to correspond with where a customer typically shops. Research can be administered via a traditional online platform or even a virtual reality platform.
Depending on the category, respondents could be able to select multiple products and indicate quantity purchased. As certain products are removed, we can see which other products respondents would choose, the impact on overall quantity selected, and even if they would choose to go to another store (or decide to purchase nothing from the category). Some key business questions that could be addressed to provide guidance to both manufacturers and retailers include:
|Which product(s) may be removed from the shelf without significant impact on brand share and/or category sales?|
|If a competitive product is unavailable, what products in our line are most likely to appeal to the competitive product’s customers?|
|If one of our products is unavailable, what will our customers purchase instead? Will they switch to another product in our line (maintaining the typical quantity purchased), to a competitor, or purchase nothing at all?|
|If Covid19-related supply chain issues limit what retailers are able to stock, which combination of available products will maximize category sales?|
In conclusion, now might be a good time to re-evaluate the impact of limiting the options available at the shelf. And, the best way to be confident in making the decision of what to remove is to leverage learnings from both secondary and primary research.
3. Journal of Personality and Social Psychology (JPSP, Vol. 79, No. 6)
About the Authors:
Meagan’s areas of focus include conjoint research, psychometric scale development, demography and segmentation. She has more than fifteen years of experience conducting research across various industries including pharmaceuticals, healthcare, consumer packaged goods, automotive, retail outlets, banking/insurance, online panels, and travel & tourism. Meagan received a bachelor’s degree from Miami University and a Masters in Applied Demography from Bowling Green State University.
Andrew Zoota, PhD
Andrew has over 20 years of experience in qualitative and quantitative research both on the client-side and supplier-side. Currently, his main focus is on building and maintaining relationships with clients, as well as leading teams to provide clients with meaningful, actionable insights based on sound, reliable methodological approaches. Prior to joining MarketVision Research, Andrew led consumer insights for a 5,000+ unit retailer. Andrew has a BA from Northern Arizona University in Psychology and an MS and PhD in Experimental Psychology from Texas Christian University.