How modern pricing tools can build customer loyalty through unified data and analytics

A hot topic, and even election year fodder, is the price of food 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 out of line on prices that become national news? With the importance of maintaining customer loyalty, how did prices end up so disconnected that retailers have to backtrack on prices in a belated attempt to salvage customer sentiment?

Unfortunately, the new data shows that there is still work to be done. According to a Coresight Research report that was released in early September:

• On average, retailers misprice 10 percent of their products in a given sales period.
• More than 50% of retailers report that they failed to execute at least 10% of their promotional campaigns during a given sales period.
• Only 41 percent of US retailers have pricing fully integrated with key business functions such as assortment and promotional planning.

The answer is twofold: Retailers need modern pricing solutions that are holistic in their approach and must manage these tools to avoid disconnects between pricing and consumer loyalty goals.

Predictive analytics keeps retailers ahead of consumers

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

By doing so, not only will product pricing and promotions be accurate across all touchpoints, but retailers can run forward-looking scenarios on product pricing to fully optimize performance targets, knowing that the data is updated and fully synchronized with other applications. . Brands and retailers can increase the way they engage with consumers around price in a number of ways, including:

• Competing with private label: Leveraging product attributes within native AI solutions with predictive analytics built into product information can help CPGs optimize product pricing against private label competitors. Retailers with private labels can also better manage the prices of their “good-best-best” assortments.
• Comparison of the impacts of price on demand: AI can identify which products in a category are resistant to price increases, helping to forecast demand at the most profitable price. Similarly, granular modeling of price effects can identify which products are sensitive to consumer opinions. A more comprehensive pricing approach allows retailers to see how to reinvest margin and revenue maximization dollars to balance pricing and meaningfully support pricing imagery.
• Validation of product attributes: Using generative AI, digital teams can accelerate workflows by ensuring attributes are automatically generated and consistent, leading to product and pricing accuracy on shelf and online.
• Looking ahead with a proactive pricing strategy: The price and effect model recommends where prices should have been a month ago, based on historical data. A better AI-based model predicts and recommends where prices should be next month, including when nominal price increases test customer expectations and generate negative sentiment.

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

Striking a balance in price with AI

Food prices in the United States are still nearly 30 percent higher than in 2019, but retail organizations can build loyalty through efficient, price-optimized operations while maintaining profitability. Granular AI modeling, based on a wide range of non-traditional data sources, enables pricing accuracy that helps avoid pitfalls and pitfalls of overly simplistic pricing approaches.

CPGs and retailers can leverage price and promotion 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.