Defending Against Delisting – A Hoarder’s Dream

We all have a tendency to hoard. Hoarding is the compulsive behavior of acquiring and keeping items due to various psychological factors, including deep emotional attachment to possessions, fear of scarcity, or anxiety about discarding things that might be needed in the future. For example, I have a suit waiting for me to return to the size I was at 22, just in case it gets worn again. This article highlights the good side of hoarding, particularly for clients who may not realize they possess a powerful tool that can be repurposed beyond its original intent.

Survival of the Fittest

Retailers frequently evaluate their product offerings to optimize shelf space and profitability, often leading to the delisting of products perceived as underperforming. When a product is in this "relegation zone," every day at work is accompanied by the fear of getting the call that the product has reached its end and is now on its final lap.

Common defences against delisting

There are several methods to defend against delisting:

• Spend, Spend, Spend: Investing heavily in margin, unique promotions, TV ads, and tagged media promoting the retailer, or offering exclusive products or promotions. These approaches can be costly and may seem desperate, but they can work temporarily.
• Social Listening: Highlight the share of voice your product commands on platforms like Instagram or Snapchat. Given the younger demographics on these platforms, you can argue that future sales will be captured by other retailers if your product is delisted.
• Switching Data (Panel e.g., Kantar): This common tool shows what consumers switch to when there are competitive promotions. It can demonstrate that, even with deep competitor promotions, your product retains a loyal shopper base that will be lost if it is removed. However, if your product is niche, it might not register on Kantar.
• Loyalty Card Data (e.g., Dunnhumby): Similar to Kantar, but more granular and expensive. It provides insight into actual shoppers and their in-store behavior, though it lacks data on competitor purchases.
• EPOS Data Estimate: Use EPOS data to analyze performance during competitor promotions, highlighting a secure base unaffected by price changes. The challenge is that if the base is small, the retailer might not suffer enough when the product is removed.
• Test and Control: Propose a test by removing the product from a few stores to measure the category impact. However, proving the case can be difficult, especially for seasonal products, and requires a supportive buyer.
• Call in the Old Guard: In the past, a brand manager at a major blue-chip company mobilized retirees to demand a relist, with great success. Unfortunately, this tactic may not be available to newer companies like Red Bull or Monster, as their retired employees are likely off skydiving or bungee jumping.
• Compromising Photos of Your Buyer: Not advisable and likely to involve legal complications.

 

Repurposing Your Conjoint Study

A more strategic way to demonstrate the impact of delisting is to repurpose an existing conjoint analysis study. Conjoint analysis is a statistical technique used to understand how consumers value different attributes of a product. By presenting respondents with choices between products with varying attributes, this method infers the relative importance of each attribute.

In the context of product delisting, conjoint analysis can simulate how removing a product might impact consumer behavior, such as switching to another brand, reducing purchases, or leaving the category altogether. This simulation provides valuable insights into the potential impact on overall category value and shopper retention.

Assessing Category Value Impact

Conjoint analysis can demonstrate what happens to specific cohorts when a product is delisted. It can show the decline in overall category value and the behavioral changes that may affect other products. Even if a product is not the top seller, it may play a critical role in maintaining the health of the entire category by attracting a specific segment of shoppers or offering unique attributes that enhance the category’s appeal.

 

Quantifying Shopper Loss

Retailers must also consider the potential loss of shoppers. Delisting a product might result in customers switching to competing retailers that carry their preferred items. Conjoint analysis provides insights into the proportion of shoppers likely to defect if a product is delisted. By understanding customer loyalty to a particular product and their willingness to switch retailers, businesses can estimate the potential loss in sales and market share.

For example, if the analysis shows that a significant portion of the product’s customers are loyal and unlikely to switch to another product within the same retailer, this indicates a high risk of shopper loss. Companies can argue that delisting the product could result in a loss of foot traffic, ultimately harming the retailer’s overall business.

If you have conducted a conjoint analysis study recently, you can use the existing data to examine the impact of removing a SKU on category value or your brand. This approach may not even require additional investment, as it’s part of the functionality of the methodology and tool provided.

Conclusion

Conjoint analysis is a powerful tool that can be effectively deployed to defend against product delisting, often without needing to run an additional study. It offers an objective method that retailers and category teams can trust. If you have any questions or need help getting the most out of your data, reach out to us. And if you’re not yet a client, perhaps you’re feeling a bit curious now—give us a call, and we’d be happy to give you a test drive.