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The Continuing Debate: Build v. Buy for Price, Promotion and Markdown Optimization

For many of my 20+ years in the retail pricing arena, we often met initial resistance when retailers were assessing whether to implement AI-based Lifecycle Pricing (price, promotion and markdown optimization). Not only was the pricing arena the first to leverage AI, but it was also the first to do it in a cloud environment, hitting retailers with not just one but two levels of innovation.  Feeding the resistance further, was cultural reluctance, when organizations feared that it would be a complex and overwhelming commitment, or that science-based technology just could not be as effective as humans trying to address those same processes.

So I was excited to see the results after DemandTec commissioned a study[i] conducted by RIS News about how retailers view the world to come as we work our way through post-pandemic era. The cultural resistance is fast fading, with 70% of the retailers say they are willing to take humans out of key processes and rely on AI-powered automation and dynamic pricing.  It’s also heartening that 73% of retailers say fear of technology and processes is NOT a barrier to implementing and leveraging science-based pricing.

Now that we are (finally!) getting past knee-jerk resistance to adopting automated optimization capabilities, the next question is whether to try to create those capabilities in-house or partner with an established provider. For many reasons, retailers who carefully consider the options and their near- and long-term implications embrace the partnering approach.

  1. If It’s So Easy for Retailers to Build it Themselves, Why Isn’t Everyone Doing It?

This is a movie that has gone through of years of reruns only to end in failure.  When you look closely at the retail landscape, you find that virtually no retailers have successfully developed their own science-based pricing. On the flip side, hundreds of retailers worldwide successfully use leading vendor-provided solutions.

Why is building your own so challenging and something even the most sophisticated retailers have struggled to achieve? Designing such a solution requires an incredibly large and diverse team with depth in many distinct areas:

  • scientists who are familiar with the full toolkit of AI, Machine Learning and Analytics – and when to use which tool or algorithm for what sort of business challenge
  • platform engineers who can take the science and make it scale to handle the demands of pricing millions of item location combinations
  • domain experts with in-depth experience in retail pricing, retail promotion and retail markdown strategies, along with expertise in category management
  • teams with expertise in successful deployment of science-based solutions in real-world retail environments
  • Lack of vision to keep up with the innovation required to keep one step ahead of the velocity of retail

All told, retailers who approach the price optimization challenge as a one-off project, rather than something they needed to continue to invest in and innovate for, saw their efforts ultimately fail – and the end result is that they teamed with a provider after all, just years later than they could have, losing market advantage in the meantime.

  • Designing and Creating the Solution is Just a Fraction of the True Cost

No matter how elegant a science-based solution is when it is introduced, the investment required to maintain it is significant – and never-ending.

New data science tools and techniques continue to emerge rapidly as academics, technologists and innovators continue to push the envelope. Successful vendors have large science teams and remain relevant by attracting and retaining top retail pricing scientists who continually monitor the landscape, engage in dialog with other private, public and education sector scientists, and who themselves develop new innovations. At the same time, they are complemented by product innovators who engage in constant dialogue with customers and prospects to understand their evolving requirements and monitor other AI-based pricing competitors for new capabilities and approaches. Product strategists engage with retail industry analysts and associations to keep a finger on the pulse of market shifts to skate to where the puck will be, not where it is today. Finally, it takes Implementation experts to help define the pricing strategy and rules, a cohesive pricing process and the change management approach that is key for the retailer to make the transition from their legacy processes to the world of science-driven pricing.

Vendors who don’t maintain this multi-front vigilance and innovation eventually weaken competitively and grow irrelevant. It’s a daunting challenge for a retailer to sustain single-handedly the fierce focus that a pure-play technology competitor brings to the party.

  • Expertise across Multiple Retailers in Multiple Sectors

A significant factor in the long-term success of proven, science-focused price vendors is their wealth of experience across dozens or hundreds of retailers and regular interactions with industry analysts, from analyzing their historic data to driving successful implementation and adoption to tuning the solution to that retailer’s specific needs. Cumulatively, this provides the solution provider with deep primary experience on what science approaches and algorithms work in messy, complicated, ever-changing real-world conditions. A big benefit for retailers in going with pricing vendors is that they benefit from product enhancements that are being driven by industry thought leaders who are always one step ahead of retailers, ensuring right innovation exists to solve future retail challenges long before the retailers recognizes the problem exists.

Battle-hardened techniques are a requirement to continually drive success in the turbulent environment that retailers today face. First, their shoppers’ preferences, behaviors and price sensitivities change and evolve constantly, and the analytics, recommendations and forecasting science must be robust enough to keep pace. AI science is sophisticated to handle the variety of challenges that plague the retail environment like sparse historical data from new or slow-moving items, dynamic trends from highly seasonal items, and the interaction between multiple pack sizes, bulk pricing etc.

Meanwhile, in the COVID era, shoppers are flocking to online channels at an unprecedented rate. So retailers’ competitive landscapes are every bit as dynamic as their changing shopper preferences. Instead of the traditional brick-and-mortar competitive set of other physical retailers in the same sector, retailers today must become omni-channel and compete with a dizzying array of on-line competitors, ranging all the way from behemoths like Amazon to specialists like Dollar Shave. Meanwhile the categories and items carried by other retailers evolves dramatically as Target aims to be a one-stop destination across all sectors, restaurants take on the role of mini-grocers, and online competitors crowd shoppers’ online searches.

Clearly retailers need science that provide early and accurate detection of changing demand signals, separating the signal from the noise to provide recommendations relevant to today’s environment. The science must keep up with see-sawing price sensitivities and competitive elasticities. Once-stable KVIs now need to be viewed as being dynamic as well, requiring productized KVI analysis rather than one-time, big-footprint analytic engagements. In addition to automating the KVI analysis, pricing solutions bring in the design expertise to integrate the KVI insights into the pricing workflow to make them actionable.

Vendors serving retailers across all sectors and channels coping with every competitive, market and shopper behavior curveball, are best positioned to deliver science and capabilities that are relevant, robust, agile and dynamic – which is imperative for a retailer’s needs, today and in the future.

The survey results show retailers who are cognizant that current and future shopper, competitive and market trends are unprecedented and unpredictable. Fortunately, they recognize that science-based price, promotion and markdown solutions will enable them to succeed. The key is to find trusted resources that help them navigate through the market offerings to select the right partner for their long-term business success.

If You Buy It, They WILL Come

There’s a reason why top retailers in every geography are leading the adoption of science-based full-lifecycle vendor solutions at a pace never seen before. These innovators focus on what they do best and staying at the top of their game by turning to the experts for their pricing solution partners. Their reward? The ability to deliver the elusive win-win: carefully crafted prices on the items shoppers care most about, which in turn engages shoppers and ensures their loyalty, while making informed decisions about where to recover margins elsewhere to sustain a long-term healthy business. 

[i] “Smart Pricing Strategies for the Post-COVID World,” Tim Denman, Editor-in-Chief, RIS News, June 2020.