As I mentioned in my recent blog on showrooming, on any given day the cheapest price on any widely distributed product is most likely not in your store (or on your website). In today’s hyper-connected world, where price is increasingly transparent, a pricing strategy based solely on lowest price is no longer sustainable for most retailers. This begs the question - are you priced right? Is your pricing based on fact, or feeling? Science, or supposition? Data, or directive?
Welcome to the complex world of retail pricing. Initial pricing, promotional pricing, clearance pricing, competitive pricing, personalized pricing, price matching, coupons, rebates. So much to consider, so little time. Let’s dig deeper.
As I’ve stated previously, not all products (or customers) are price sensitive. Analysis of historical sales will help you identify which products, channels, and locations have the greatest opportunities for price optimization…the more history, the better. This type of analysis can then be used to build an opportunity matrix focused on potential benefit versus ability to manipulate price. For those products with high potential benefit where price can be manipulated, price elasticity models should be run to determine optimal pricing. Keep in mind that this type of analysis may result in differing price recommendations by location and channel. How you execute should support your brand strategy.
When determining promotional pricing, it’s important to remember that any change in a product’s price may affect the sales of other products, either in positive or negative fashion. On the positive side, cross-selling occurs where sales of the reduced-price product increases sales of another product, and on the negative side, cannibalization occurs where sales of the reduced-price product decreases sales of another product. For promotional pricing, run analyses to determine both promotional elasticity as well as interaction elasticity. This will allow you to analyze promotional pricing both with and without cannibalization and cross-sell effects, and help determine which products and prices will drive desired results.
First and foremost, if you are not managing your clearance pricing to out dates, start now. The key a good clearance pricing strategy is in knowing when a product needs to be out of your assortment, and working backwards from there to determine when to reduce the price, and by how much. Monitoring product sell-thru over time versus a baseline curve will enable you to determine the optimal point for price reductions. Better yet, let your data warehouse automate the process via triggers and alerts by item.
I’m beginning to see leading retailers, with sophisticated pricing strategies, incorporate personalized pricing via targeted offers. By tracking a consumer’s shopping history, typically through a reward or loyalty program, these retailers can analyze price sensitivity by customer across categories. This analysis is then being used to make personalized offers (discounts) via the customer’s preferred channel (direct, digital or mobile). Based on response, future offers are then updated and improved, creating a closed-loop, learning-based system. While new to retail, gaming companies like Harrah’s have been effectively executing personalized pricing for years.
It goes without saying that pricing in retail has not only gotten more complex, but also more scientific. If you’re not leveraging data and analytics to inform your pricing decisions, now is the time to start. If you are, consider evolving your pricing strategy to include personalized offers. In today’s omni-channel, customer-centric environment, a relationship-based pricing model that combines both deep analytics and personalization provides a formula for retailers to compete…and win.
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