The use of artificial intelligence delivers huge revenue gains and improved customer engagement.

In Symphony Retail Ai’s latest survey of more than 100 U.S. and European retailers, companies and brands are gleaning more “localized insights” about customers, but are failing to use these insights. The survey also found a marked difference between U.S. and European retailers in regard to customer and operational performance metrics.

Researchers at the company, which offers artificial intelligence-enabled solutions and platforms, said results of the survey revealed that “inefficient management of customer insights and operational performance represents a clear challenge to achieving desired category management business outcomes.”

This assessment echoes what retail analysts and consultants have been saying at recent trade events, such as the NRF’s Big Show earlier this year: while retailers and brands are making investments in technology and artificial intelligence, they’re not always using the data and insights in actionable ways.

Authors of Symphony Retail Ai’s “Customer-Centric Category Management Survey of Retailers,” said the survey findings “highlight the willingness of retailers to pursue a customer-centric approach and present a clear gap between intention and execution. This gap can be addressed by artificial-intelligence capabilities that synthesize complex data to enable more robust and efficient strategies that drive sales and loyalty.”

The researchers said U.S. retailers tend to rely on localized customer insights as a way to offer more “shopper-centric” offerings in their stores. And they do this “more pervasively than their European counterparts, resulting in much stronger customer-performance metrics.”

The company said 75 percent of U.S. respondents reported “significant to above average improvement” in customer-performance metrics, which compares to 54 percent of the Europeans polled. “This divide can be directly attributed to the fact that 73 ppercent of U.S. retailers implement location-based clustering as a best practice, while 70 percent of European retailers conduct centralized store planning and merchandising as a best practice.”

Researchers at the firm also noted that the U.S. retailers’ commitment to creating improved customer performance metrics comes at the expense of operational efficiency, “an area in which only 54 percent of retailers claim strong improvements.”

“The wide gap between customer and operational performance limits their ability to become more profitable, even as they increase customer value,” Symphony Retail Ai said in the report. “In contrast, although just 46 percent of European retailers report strong operational improvement, the gap between the customer and operational performance is much smaller — only 8 percentage points.”

Authors of the report said the European ability to execute “helps justify a more granular approach to assortment moving forward, in which AI identifies and promotes assortment optimizations for world-class execution that yields performance uplifts.”

The survey also showed the role of planning as a top priority for U.S. retailers — alongside pricing and promotion — when it comes to improving conversions. But Symphony Retail Ai quickly noted that planning is not well-defined, and when not thought out can lead to inefficiencies.

Matt Robinson, category planning solution director at the firm, said a successful planning process “is reliant upon how quickly and efficiently opportunities can be identified and executed. In order to capitalize on emerging market trends, retailers need to accelerate the rate of data collection, analysis and actions that are executable at store.”

All of which makes a case, the company said, for deploying AI.

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