While Retail’s digital migration has ushered in exciting new opportunities, it has also introduced a host of new challenges. Principal among the challenges is price transparency. With comparison shopping now just a few clicks or taps on a screen away, retailers are feeling more price pressure than ever before. If that wasn’t enough, Amazon upped the stakes by employing algorithms that drive intraday price changes, further challenging retailers deploying sluggish life-cycle based pricing processes. So how can traditional retailers compete and drive organic revenue growth in this environment? The answer, at least in part, lies in dynamic pricing.
At its core, dynamic pricing is about quickly adjusting price based on measured changes in defined decision variables. This concept is being pitched as the new must-have capability in retail, with retailers and solution providers alike scrambling to bring capabilities online. Sounds exciting, right? Well, before you spend too much time in pursuit of this new solution, consider one fact – this solution isn’t actually new, it’s just new to retail.
Dynamic pricing has been part of most leading Travel and Hospitality Revenue Management solutions for a long time, and Revenue Analytics played a large role in bringing those capabilities to market. Over the last decade we have partnered with many Travel and Hospitality industry leaders to deliver capabilities that dynamically adjust price based on changes in key input variables (i.e., customer demand, available inventory, and competitor price) and combat price transparency pressures. Additionally, we have adapted these capabilities to the retail industry, recently delivering 7% online revenue growth for a leading big box retailer through a bespoke dynamic pricing capability.
So before you rush into something “new”, below are a few market-tested learnings to consider as you embark on the dynamic pricing journey:
It’s about identifying where, when and how much to compete. Most retailers do not have the luxury of blindly following competitive online prices. Their cost structure simply won’t allow it. The good news is that you don’t have to meet or beat all prices on all products. The key is to identify which products are most critical to compete on, when you must respond to competitor price shifts, and how aggressive the response must be. The right analytics can answer these questions.
It’s about systematic blending of new decision inputs. Dynamic pricing should be about more than simply accessing traditional data sources more systematically in order to make traditional decisions more quickly. Successful dynamic pricing warrants inclusion of new decision metrics (i.e., cart abandonments, customer sentiment, and online return rates) to inform more targeted price recommendations, most of which are not explicitly captured in retailers’ pricing equations today.
It’s about decision speed. There is no doubt a critical technology component to enabling a successful dynamic pricing capability, processing speed counts and time is of the essence. That said, well-informed confident decisions trump fast decisions any day of the week. Yes, the data modeling outputs must be produced rapidly, but more importantly they must be presented in a form that enables the pricing decision maker to quickly digest, decide, and act upon the information.
The online retail pricing game has changed, and only those that adapt will continue to enjoy organic revenue growth. If deployed correctly, a dynamic pricing capability can unquestionably play a central role in helping retailers remain competitive.