RSR Research: Following the Pricing Learning Curve - One Retailer's Experience

Through a special arrangement, presented here for discussion is an excerpt of a current article from Retail Paradox, Retail Systems Research's weekly analysis on emerging issues facing retailers.

Last year, Retalix announced a new solution and partnership around pricing - one involving Retalix's price execution, KSS's price optimization, and Willard Bishop Consulting's accelerated strategy program designed especially to help mid-size retailers get a pricing strategy off the ground. A year later at Retalix's User Conference, one of the first retailers to take on the solution, Super S Foods, provided an update on where they've been and where they're headed as they make their way along the pricing learning curve.

In Super S's case, they identified three pricing strategies. One was for highly competitive markets where a Walmart or an HEB were close by; another for geographically isolated locations (where Super S might be the only game in town); and one for Hispanic stores.

The operator of about 50 stores in south-central Texas started on its new pricing path when it decided to centralize pricing in 1990. Although centralized pricing improved gross margins by one percent, Super S became aware that even more was possible when they started seeing that one price really did not fit every store for the same SKU. They realized they needed tools to help them create more granular prices - both the analytics side of setting prices, and the execution side of passing the right price for the right item to the right store. To do that, Super S implemented Retalix's Category Analyzer and HQ for price execution.

With those solutions in place, Super S embarked on the second phase of the learning curve - the part where their capability grew exponentially beyond what they were capable of before. Just the Retalix implementation helped the chain post seven percent comp store sales gains in 2006 and 2007. But Super S found itself wanting to move forward faster than Category Analyzer could support - for the analytics to produce a good result, it needed 12-13 weeks of history. This was too long to wait in a highly competitive market, so Super S turned to KSS and its price optimization solution, which provides daily insight into prices, and weekly insight into the price elasticity for each item. With not anywhere near all categories rolled out, 2008 is on track to beat even the results of the previous two years, with 12 percent comp store sales on track.

On the accelerated part of the learning curve, Super S is now learning that their three price strategies don't fit as well at the store level as they thought - that there are actually opportunities to apply these strategies at a category or even sub-category level, so that one store might have all three strategies at work under one roof, as each category requires.

Other retailers who have already gone through the full price optimization rollout have started talking about better integration into other parts of the organization - integration to inventory, actuals as well as planned, along with better planning and optimization of promotions, bringing in marketing as well as merchandising.  These next steps are more incremental improvements on top of what is a significant step-level change to pricing processes. That's where the learning curve starts to flatten out again - at least, until the next big innovation hits.

Discussion Questions: How does the learning curve around pricing strategies differ from other implementations at retail? What common mistakes are continually occurring as retailers refine their pricing strategies to include category analysis and price optimization tools? What are the particular challenges to mid-size retailers undergoing price strategy changes?
[Author's commentary] An interesting note, and one that we've found to be true of learning curves in general, is that it's nearly impossible to skip a step along the curve - there is no leap-frogging on a learning curve. For pricing, the critical first step that you can't skip is where you identify your price strategy. I've heard time and again from retailers implementing price optimization that they started down the path only to realize that they had to step back and start over a little bit, because they realized they didn't have a price strategy to implement to begin with. It's tempting to think that price optimization will provide you with the analysis that will help you identify what price strategy you should follow, but it simply doesn't work that way - there isn't one "magical" price strategy that a retailer should follow. It has to be tied into your company strategy, the reality of your economics, your competition, and the brand promises that you make to your customers. It's an objective, not a math problem.

• Following the Pricing Learning Curve: One Retailer's Experience - RSR Research