Over the years, my family has been shopping mostly at four big box retailers. Let’s call them A, B, C and D. Unlike D, Retailers A, B and C run loyalty programs, of which we’re members. Recently, we stopped making any purchases at the first three and diverted our entire custom to Retailer D.
It’s only at Retailer D that
- Checkout never takes longer than 10 minutes, and
- We escape “checkout sticker shock”. This relatively uncommon term is an extension of the more familiar term ‘sticker shock’ and matches the following broad definition of the latter given in Urban Dictionary: “the condition resulting from seeing the total price of a bunch of items and realizing the damage is much greater than you originally expected.” In simple English, as my wife or I quickly scan the price tag on each item that we add to our shopping cart in Retailer D’s stores, we get a feel of the total bill by the time we reach the checkout. Once the store attendant rings up our purchase, the actual bill amount more or less matches our estimated figure at Retailer D and far exceeds it at the other three retailers.
While there could be several reasons for checkout sticker shock, my personal experience suggests that ‘price optimization’ could be a major culprit. Flaunted by research analysts and IT vendors as a best practice for the retail industry for boosting topline while preserving margins, price optimization works as follows: A retailer identifies a few ‘high-involvement’ items in a typical shopper’s basket. Research shows that a typical shopper only looks at the price of such items – constituting roughly 20-25% of a typical basket – before deciding whether a store is a rip-off or offers value-for-money. A retailer adopting price optimization marks down the prices of these high-involvement items and drums up footfall to its stores by aggressively advertising only these prices. Once shoppers are attracted by these low prices, they visit the stores and first pick up these items. But, they don’t stop there. They tend to load up on many more items without realizing that these items are selling at full price. As a result, the aggregate discount on the total basket is negligible.
As long as all consumers shop in this manner, the retailer can indeed boost its topline while preserving margins.
However, personal experience shows that different consumers exhibit different shopping behaviors.
Let’s take my family’s example. In all likelihood, Retailer A has adopted price optimization because, while shopping there, we’ve often received receipts saying, “You have saved 3 Rupees”. What? A measly three bucks savings on over INR 4,000 worth of shopping? On a few occasions, this line was missing altogether, suggesting that we actually saved nothing. Add to this our experience of checkout sticker shock at Retailer A. When seen together, it does appear that price optimization and checkout sticker shock are strongly correlated.
On the other hand, Retailer D doesn’t deliver checkout sticker shock, thus managing to earn my family’s loyalty. Interestingly, Retailer D doesn’t even run a loyalty program. Ironically, Retailers A, B and C have lost my family’s patronage despite running loyalty programs.
Is this reason enough for us to conclude that price optimization, which is the most likely cause of checkout sticker shock, is a bane for big box retailers? No. It’s a well-known fact that Retailer A has been consistently posting profits when most of its competitors are still making losses and, worse still, some of them have even downed their shutters. Therefore, the ability of ‘price optimization’ to protect margins can’t be denied, even if it might cause checkout sticker shock and result in the defection of a certain segment of customers.
If this segment is small, price optimization is a boon for big box retailers. But, if it’s large, it’s a bane for them.