Anthony Smith, VP of Science Services at Revionics.
As the New Year approaches for an always unpredictable retail industry, one thing is abundantly clear: the disruptive effects of retail technology will continue to be felt. In fact, it’s a safe bet that as the year unfolds retail technology will have an even greater and more widespread impact than was the case this past year. That’s the nature of technology.
When you work for a retail technology company and have the word “science,” in your title, you spend a lot of time envisioning the future and what innovations are likely to have an impact on retailers and their customers. My team and I spend every day on the front lines of applying artificial intelligence (AI) and machine-learning science to drive quantifiable business value and customer-centric pricing and promotions for retailers.
One of the things we’ve noticed is that there is a profound and accelerating change underway in how retailers think about AI in retail. It’s gone from an abstract discussion of what AI might do for retailers in which areas to a much more action-oriented consideration of how to get started now reaping measurable benefits in the business, both for their customers and for the bottom line. Fortunately, in retail pricing, AI has been around for more than a decade and has matured to a very robust, productized set of tools and capabilities that can yield quick win/win pricing and promotions that key in on what matters most to shoppers, factoring in rapidly changing variables like competitive elasticity and price sensitivity down to the item level to identify where retailers need to be aggressive on prices and where they can recover margin elsewhere to maintain long-term business health. These are exactly the type of use cases where AI is particularly effective.
Scores of retailers have successfully implemented these technological capabilities and charted successful, phased paths that deliver quick ROI at each phase to fund subsequent phases, all while avoiding known pitfalls to minimize threats to success. In 2019, I see this technology and implementation approach moving from the realm of cutting-edge retail innovators to more mainstream retailers who are committed to making themselves more relevant than ever to shoppers while also outperforming competitors who are still hesitating about what technology steps to take.
Retailers Get Dynamic
Today’s incredibly fast-paced retail environment sees new products and competitors disrupting markets daily, the expansion of global giants into ever-increasing geographies and market sectors, and new formats, from pop-ups to kiosks from specialists inside big-box stores. Where retailers once had the luxury of lead time to determine their price adjustments and promotional offers, today they must respond virtually in real time to changes in markets, customer preferences and the competitive environment. And as I recently heard an industry analyst say, we may be in an era of shopper hyper-adoption as they gravitate to new apps and delivery options, but we are also in an era of hyper-abandonment as a single sub-optimal experience or a fleeting out-of-stock event means they walk away from your brand forever.
So, it’s incumbent on retailers to reach shoppers with relevant, carefully crafted prices and offers, when and where they matter, across a variety of channels and vehicles. And that means retailers need to give serious consideration to taking a dynamic approach to pricing.
Contrary to many assumptions, the definition of dynamic pricing does not mean changing prices across all items at all hours of the day. Retailers justifiably suspect that shoppers will have little tolerance for adding an item to their cart at one price, only to find at checkout that the price has changed. But there are three elements that are critical when we think about dynamic pricing in the real world of retail. Dynamic pricing must be:
Targeted and smart, focusing on updates on those items where shoppers are most sensitive to prices and to competitive offerings.
Flexible in frequency, allowing price changes to happen at a speed that matches your business parameters.
Structured for a fast and automated process, leveraging self-learning, science-based algorithms and automated workflows
Today, retailers have access to unprecedented detail on their shoppers’ behavior, competitive data and market evolutions. Additionally, infrastructure to enable highly targeted updates at the speed of your business on select products is increasingly ubiquitous and affordable, from AI-driven price and promotion optimization to electronic shelf labels. I think 2019 will see retailers adopting AI powered science and automation and taking a much broader view of dynamic pricing that is fueled by intelligence. We’ll see it beginning to evolve to a more mainstream role — again, within the context of each retailer’s specific business model.
Dynamic systems, particularly those that incorporate machine learning, by definition should continually learn and improve. Dynamic pricing detects real-time demand signal changes, shifts in market factors, and evolving competitive practices to respond and recommend price changes in a way that traditional pricing could never achieve.
Yet human oversight remains important, so dynamic pricing must give retailers the ability to set “bumpers” in the form of defined tolerances. Recommendations falling outside these preset limits can be flagged for human review so retailers get the benefit of price agility with the assurance that any recommendation that violates business rules or other guidelines will trigger manual intervention to either accept or reject the recommendation.
Price Remains King — But Must Be Fair and Non-Arbitrary
In an industry dominated by discussions of fast-changing models for shopper experience, buy online and pick up in store and other cross-channel purchase and delivery options, loyalty programs and multi-channel engagement, it can be easy to overlook the most important factor of all: price. Recent Revionics-commissioned research conducted by Forrester Consulting surveyed shoppers globally, and it found that price was the number one factor shoppers cited when deciding where to shop. This was true across all retail sectors as diverse as grocery, apparel, DIY, and convenience.
At the same time, shoppers are surprisingly open to the very technologies that we’re discussing here. For example, shoppers are clearly ready for science-based dynamic pricing. In the Forrester study, an impressive 78 percent of shoppers say they are comfortable with the use of data science to determine prices — with the qualifier that they receive a fair price for the product. Conversely, just 6 percent of respondents say they don’t think it is fair at all for prices to change dynamically. This concept of fairness in pricing is critically important: 59 percent of shoppers reported that they would refuse to purchase an item if they perceived the price as arbitrary. They accept price increases or decreases that remain within the “fair” range if they are based on data science — that is, driven logically and not arbitrarily.
2019: A Year of Opportunity
Periods of rapid change present significant risk — and profound opportunities. Retailers willing to rethink the “tried and true” approaches to pricing and promotions can leverage the unprecedented advantages now available to them through AI-powered science and rich data sources that give deep insights into shoppers, competitors and the overall retail landscape. Taking advantage of the adoption curves from those who have already walked down that path gives them a jump-start on best practices and lessons learned, allowing for rapid-ROI initiatives that deliver the utopian win-win: prices and promotions that better engage and retain customers, while giving a boost to top- and bottom-line results that ensure a healthy business for the long run.
Anthony Smith Is Vice President of Science Services at Revionics, a leading global provider of pricing, promotion and margin optimization solutions.