Preparing Optimal 2022 Retail Strategies With Data-Driven Pricing
The once-familiar cadences of retail prices and promotions — quarterly or even annual rhythms, with perhaps just minor variations on prior years’ assumptions — are a distant memory today. The retail landscape has become almost unrecognizable as shoppers flock to online channels, demanding 24/7 complete price transparency, along with a wider array of competitors. Retailers must have business agility as they grapple with fast-evolving shopper, market and competitive behaviors.
Fortunately, today’s artificial intelligence-based pricing and promotion tools ably support innovative retailers ready to rethink their pricing strategies and embrace more autonomous, data-driven pricing across the entire price lifecycle — from everyday prices through promotions and markdowns. Let’s look at how retailers can deliver the most business impact from data science-based solutions.
Invest in Data Integrity
A data-driven approach to pricing and promotions is only valuable if the data is current and accurate. Yes, AI-based science can deliver price recommendations based on insights to accurate, current demand signals and price elasticities, but only if it receives reliable, current and comprehensive data. Working closely with your IT team, take the time up front to ensure the systems have access to point-of-sale transaction data at the store and channel level. It’s equally important to have current competitive price data, particularly on the key value items (KVIs) whose prices have significant influence on shoppers’ perceptions of your price image.
In times of significant change and uncertainty, such as various waves of pandemic and lockdowns or when supply chains are lurching from crisis to crisis, knowing you have science working on real-time data gives you a clear path forward when other retailers struggle trying to make sense of an unfamiliar environment where the past doesn’t meaningfully provide a blueprint for what’s effective today. Having the confidence that your AI-based systems are making price and promotion recommendations that reflect current-day conditions make both pricing teams and category managers more strategic contributors to business success.
Start With the Most Critical Categories
If you’re just beginning to take advantage of data science-based systems, take a methodical, phased approach beginning with those categories that impact your business the most. Moving to a data-driven price strategy category by category is particularly important with your KVIs. You can leverage the science at each step to thoughtfully consider the optimal role for each item. Is it a traffic driver? Does it drive basket size or is it a margin enhancer? Modern pricing systems enable the pricing team to “dial the knobs” and change the weighting of each factor at the item level, specific to the channel, zone or store.
Cross-item effects are critical, too. AI-based systems provide insights into halo, cross-elasticity and cannibalization effects. Armed with these insights, pricing and category managers can strategically accept price recommendations to, say, set a more aggressive price on an item than earlier business rules allowed, knowing that halo effects will drive up related purchases of high-margin items and have a positive impact on the category overall.
As you move through these early critical categories with deliberation, you can take the accumulated experience forward to then bring additional, less-critical categories under management at accelerating speeds in later phases.
Leverage Simulations and Scenario Planning
Using the simulations and scenario planning capabilities, the pricing team can work collaboratively with category managers to demonstrate the impact that accepting a recommended price or promotion will have on an item, again with granularity from the banner level down through zone, store and channel. As the pricing team grows more sophisticated in their use of these advanced science-driven capabilities, they continue to gain the confidence and trust of each category manager, which in turn accelerates adoption and delivers more powerful results for the organization.
While the current chaotic retail landscape is creating growing uncertainty for retailers globally, innovators are increasingly turning toward sophisticated yet easy-to-use AI-based solutions to deliver the elusive win-win: prices that engage and resonate with shoppers on the items that matter most to them, while strategically recovering margin elsewhere in the assortment to deliver healthy, predictable financial results.
Debbi Ingersoll is senior director, customer success at DemandTec, the industry pioneer of using data science to optimize retail pricing.
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