The first blog in this two-part series focused on the primary challenge facing retailers today: mega-retailers have forced prices down, based on their economies of scale and hyper-optimized supply chains. Smaller retailers have responded by creating short-term promotions that draw shoppers into the store, but erode already-thin margins. This strategy is not sustainable over the long term.

So what can smaller retailers do? They need to move beyond price, to define a personalized shopping experience and customized offers — creating the basis for a meaningful relationship with shoppers that transcends price.

A Personalized Shopping Experience: The New Imperative

While low price and availability have been key value drivers for the past decade, shoppers today possess more disposable income, have greater confidence in their own opinions, are more willing to shop across channels and are less loyal. As their demands have grown, they have come to expect higher levels of service and customization. A Harris poll in April 2019 revealed that 63% of US, UK, and Canadian consumers have grown to expect personalization from retailers — and they believe special offers recognize their individuality.

Multiple studies by RSR Research have confirmed that consumers dislike the impersonal shopping experience that characterizes mega-retailers, and this creates an opportunity for smaller retailers to differentiate themselves. By focusing on the perceived value of the entire shopping experience, they can gain ground in the retail war.

So what do shoppers value? The simple answer is, it depends on the individual consumer.

The good news is that thanks to the digitalization of the retail environment, retailers now have a wide range of both transaction and non-transaction data on individual shoppers. They just need to analyze that information, and translate it into meaningful retail offers, on a massive scale. That’s where artificial intelligence (AI) comes in.

The Power of AI and Analytics

Artificial intelligence has ushered in a new set of analytics that helps transform large-scale data into individualized offers that consumers perceive as valuable. As retailers collect information about their shoppers’ digital paths-to-purchase, new AI-based analytics detect patterns — then define offers that should trigger a predictable response.

For example, retailers can leverage AI to study each consumer’s price tolerance, past loyalty and lifetime value to the brand, based on their real-world shopping behaviors. Then they can define a custom-tailored promotional offer, or discounted price, that considers both the consumer’s definition of value and the retailer’s own profitability targets. They can minimize markdowns and waste, while also building a closer relationship with consumers that goes beyond the “one size fits all” value proposition of mega-retailers.

Customized Pricing: It’s Only the First Step

Artificial intelligence is already proving critical in helping leading retailers develop smarter, more personalized pricing strategies. However, intelligent pricing only hints at the true strategic power of AI and analytics.

By combining internal data about shoppers with external data streams — for example, third-party information on competitors, fashion trends and weather forecasts — retailers can move beyond pricing in their efforts to develop close shopper relationships. They can create targeted products, assortments and services that represent real value to consumers because they reflect both personalized shoppers’ needs and the larger forces that impact the retail environment.

Not only can retailers drive traffic to their stores and win short-term sales, but they can shape demand via AI and analytics, creating a long-term competitive advantage that transcends promotional pricing and in-store specials. While pricing is a great place to start applying AI, in truth, it’s only the beginning.