No More Disconnects: How Modern Pricing Tools Can Build Customer Loyalty Through Unified Data and Analytics

A hot topic — and even election-year fodder — is food pricing and the cost of groceries. In response, retailers like Target, Walgreens, and Walmart have made headlines by announcing price drops on thousands of items since May.

The question is, how did retailers with state-of-the-art pricing practices get so misaligned on pricing that it becomes national news? With the importance of maintaining customer loyalty, how did pricing end up so disconnected that retailers have to backtrack on pricing in a belated attempt to salvage customer sentiment?

Unfortunately, fresh data shows there’s still work to be done. According to a Coresight Research report that launched in early September:

• On average, retailers misprice 10 percent of their products in any given sales period.
• More than 50 percent of retailers report failing to execute at least 10 percent of their promotional campaigns properly during any given sales period.
• Only 41 percent of U.S. retailers have fully integrated pricing with key business functions like assortment and promotional planning.

The answer is two-fold: Retailers need modern pricing solutions that are holistic in their approach, and they need to manage these tools to avoid the disconnects between pricing and consumer loyalty goals.

Predictive Analytics Keeps Retailers Ahead of Consumers

Facilitating consistent results on product pricing relies on a modern, artificial intelligence-native approach that integrates real-time product information, digital assets, and master data management in one place.

By doing so, product prices and promotions will not only be accurate at every touchpoint, but retailers can run forward-looking scenarios on product prices to fully optimize performance goals, knowing that the data is up-to-date and fully synchronized with other applications. Brands and retailers can elevate how they engage with consumers on price in many ways, such as:

• Competing with private label: Leveraging product attributes inside native-AI solutions with predictive analytics built into product information can help CPGs optimize prices of products against private-label competitors. Retailers with private brands can better manage pricing of their “good-better-best” assortments, too.
• Comparing impacts of price on demand: AI can identify which products in a category are resilient against price increases, helping to forecast demand at the most profitable price point. Equally, granular modeling of price effects can identify which products are sensitive to consumer opinions. A more comprehensive price approach enables retailers to see how to re-invest margin and revenue maximization dollars to balance pricing and meaningfully support price image messaging.
• Validating product attributes: Using generative AI, digital teams can speed up workflows by ensuring attributes are auto-generated and consistent, which leads to product and pricing accuracy on shelves and online.
• Looking forward with a proactive pricing strategy: Price-and-effect modeling recommends where prices should have been a month ago, relying on historical data. Better AI-driven modeling predicts and recommends where pricing needs to be next month, including when nominal price increases test customer expectations and lead to negative sentiment.

Retail analytics and a modern pricing strategy can increase how brands and retailers collaborate in many ways, finding prices that satisfy consumers and lift bottom lines.

Striking a Balance on Price With AI

Food prices in the U.S. are still nearly 30 percent higher than in 2019, but retail organizations can build loyalty through efficient, optimized operations on price while maintaining profitability. Granular AI modeling, based on a wide range of nontraditional data sources, allows precision in pricing that helps avoid traps and pitfalls of overly simplistic pricing approaches.

CPGs and retailers can leverage pricing and promotions optimization tools to identify food prices and offers that resonate with consumers. They can also ensure that pricing is accurate and consistent, keeping consumers happy.

David Barach is senior vice president of solutions strategy at Digital Wave Technology, an AI-native, rapid-development platform and solutions provider for consumer industries.