Consumers shop online for price, but don’t always expect retailers to match prices or to set prices at the same levels in stores and on websites. Pricing systems based on artificial intelligence can interpret demand signals to offer effectively targeted prices to consumers.

Jeff Smith, founder and executive vice president, corporate strategy and development, Revionics

Jeff Smith, founder and executive vice president, corporate strategy and development, Revionics

In an always-connected world where shoppers have full price transparency across all channels on all items at all times, the fight to remain relevant to your target customers takes on a new level of urgency. Fortunately for retailers, AI-powered pricing and promotion can enable them to craft engaging, targeted pricing and offers on the items shoppers care most about—while recovering margins elsewhere to sustain a healthy business model.

First, let’s clear up some widely held myths. Just because shoppers can—and do—look at multiple sites when they’re shopping doesn’t mean that they expect or demand price-matching.  Interestingly, a recent Revionics-commissioned global shopper study conducted by Forrester Consulting found that a whopping 76% of retailers market their price-matching guarantee—but that only 17% of shoppers demand price-matching on products they want to purchase.

The reality is that retail shoppers expect lower prices online.

What shoppers dowant is a fair and non-arbitrary price: 59% of shoppers say they are angry when they encounter prices that are arbitrary and don’t make sense.

Recommendations ranked for impact

Here’s where retailers who embrace AI-based pricing solutions have the advantage. Using sophisticated algorithms, today’s solutions suggest optimal prices down to the item level leveraging up-to-the-minute competitive elasticity and shopper price sensitivity analysis.  Price recommendations are ranked to indicate which will have the most impact, and are tuned to the retailer’s defined strategy for that item or category—whether to prioritize driving sales, traffic or margin, for example.

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Shoppers are ahead of retailers in being comfortable with this AI algorithm-driven approach.  An overwhelming 78% of shoppers think it is fair to use data science to increase and decrease prices as long as—and this goes back to that expectation of fair and non-arbitrary—they are presented with prices they’re willing to pay.

Another important imperative for retailers who sell online is to understand shoppers’ pricing expectations for items on-line versus in-store.  Despite many industry gurus who counsel complete consistency between a retailer’s online and in-store prices, shoppers feel otherwise. The reality is that retail shoppers expect lower prices online, particularly for electronics, media/games and apparel, and ‘considered’ infrequent purchases such as jewelry and furniture. A notable exception is grocery, where only 22% of shoppers expect lower prices online.iii

It’s not surprising then that 76% of retailers believe AI-based pricing would have a positive impact on shoppers. And increasingly, retailers are embracing these capabilities and finding that in a noisy, competitive world of constantly changing shopper expectations, AI-based pricing delivers a competitive advantage today. And its ability to detect changes in demand signals also enables retailers to respond immediately to changes in shopper, competitive and market environments—a huge asset in an industry as fast-changing and dynamic as retail.

Fortunately, SaaS-based pricing solutions deliver the power of AI-based pricing at an affordable cost and with ease of deployment that enables retailers to create measurable business impact, both in the near term and over the long run.  Most importantly, these solutions enable online retailers to deliver prices to customers that are targeted, relevant and engaging.

Revionics provides price-optimization software for retailers.

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