AI-Powered Predictive Merchandising is Shaping the Future of Shopping

Labor shortages and rising transportation costs are pushing consumer brands to increase efficiency. Having the right stock on the shelves is more important than ever, and the growing demand for data-driven insights is inspiring new AI-based predictive solutions.

In 2021, the producer price index, a measure of wholesale prices for goods and services, was up 9.7%. Due to supply chain issues and inflation, many big consumer brands have raised their prices. This trend is projected to continue through the coming year.

In March, Kraft Heinz plans to raise prices on several of their products, ranging from a 6.6% increase on Velveeta cheese to a 30% increase for a three-pack of Oscar Mayer turkey bacon. Procter & Gamble, too, announced price hikes on fabric care products, such as Tide detergent and Downy dryer sheets, coming at the end of February.

But higher prices alone aren’t enough to fight inflation or guarantee a net profit. Shoppers can turn to cheaper alternatives. That’s where technology comes in: to help brands stay ahead of the competition. AI could help big companies increase efficiency with better inventory management, improved customer experience, and data-driven insights.

Not only do the major consumer brands feel squeezed from inflation; the private labels, too, have tried raising their prices to absorb the increasing cost of goods. However, these brands have less power and control over pricing in wholesale channels than the major brands.

In a situation, where the margin squeeze is imminent and unavoidable, AI-powered merchandising could help private labels boost efficiency & sales.

Predictive Merchandising

Predictive merchandising is currently one of the most promising segments of the AI retail market, expected to reach 19.9 billion by 2027, according to a new report, published by Meticulous Research.

Key companies operating in the space include Amazon.com, Google, Intel, Microsoft, IBM, Intel, Oracle, SAP, Salesforce, and others. But the field is dynamic — new players and solutions are emerging.

For example, in early February, Onebeat, an AI-powered startup helping retailers and brands analyze their customers’ needs, received an initial $5 million round of funding. Pivot, a Miami-based startup allowing brands to pick the ideal location and in-store space to showcase their merchandise, raised a pre-seed venture capital round.

And an AI-based SaaS startup, Inspector Cloud, which lets vendors receive insights to increase stock performance, recently raised a new round, bringing its total investment to $1.25 million.

Using eleven different neural networks, Inspector Cloud recognizes goods, collects data, and provides reports. The platform also allows merchandisers and sales reps to save store visit time, eliminating the need for manual operations.

Currently, around 40,000 merchandisers and sales reps around the world are using Inspector Cloud. The platform processes over 50 million images monthly. A few big FMCG companies, including PepsiCo, Unilever, and Nestle have already implemented the startup’s solution.

Conclusion

The future looks bright for AI-powered startups that provide predictive merchandising services. A recent study from IBM revealed that 72% of customers out of 19,000 people shop at physical stores, despite the preponderance of online-only options. Reasons given include touching and feeling products before buying them online.

As long as consumers choose a hybrid shopping model, merchandising will keep driving sales. As a result, more brands and retailers will embrace AI to learn about their customers, receiving data-based insights and recommendations.