Many retailers grapple with a dilemma that we like to call “The Seventy Shoes Dilemma”. Let us explain. Let’s say a shoe retailer sells 70 kinds of shoes. These shoes are all modeled exactly the same. The only difference is in the colors and patterns. How does the retailer price each shoe? Does the retailer price them all the same, or does it stamp different prices for different patterned shoes?
If the Shoe Sells, Wear It
When the shoes are the same, it’s kind of hard to predict which shoe design will sell better than the others. The shoes are just a metaphor – the same goes for t-shirts, jeans, dresses, etc. Most retailers will begin with a little “trial and error”. At first, some may price all shoes exactly the same, and gradually change the prices based on customer behavior. Some may try to predict potential best sellers and raise the price accordingly in advance. The bottom line is this: when retailers have many products that are very similar, they can utilize many pricing scenarios. And once all shoes (or all other items) are introduced to customers on the salesfloor, dynamic pricing optimization can come in very handy.
Customer Behavior Analysis
Once sales data is entered into the retailer’s computerized system and analyzed, store management can better understand which shoes their customers liked best, and which received lesser degrees of attention. Once this preliminary data comes in, they can effectively manage their shoe prices via dynamic pricing.
Dynamic pricing works really well after customer data analysis. When retailers have numerous items in stock that are virtually identical, they can begin to optimize specific prices for specific items in real-time. The more day-to-day data they accumulate, the sharper their pricing optimization. The result is larger profits and a better bottom line.
The Simplicity of Pricing Management
Before the current era of cutting-edge dynamic pricing, daily price management for 70 virtually identical shoes seemed like an impossibility. It was a tough task to perform manually via excel sheets. So naturally, pricing managers moved at a much slower pace. Price changes, if they occurred, took place on a weekly or monthly basis, at best.
This is not the case today. Exciting dynamic pricing platforms allow retailers to price-manage huge stocks comprised of countless items, in real-time, knowing that their pricing is optimal. They can work a lot less and receive vast amounts of valuable data. This data helps them make the best decisions, day in and day out.
At the end of the day, retailers may not sell their entire 70-shoe model stock. Some models will sell better than others. But with dynamic pricing, the shoes that do sell will most likely sell at the most profitable price. In today’s retail world, that means a lot.