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How Retailers Can Use AI to Increase Sales

Tech can measure customer attention
Picking Out Item In Supermarket Main Image
By analyzing customer attention patterns in real time, retailers can quickly adjust their strategies and tactics to better meet customer needs and expectations.

Today’s retail shopping experience has differed drastically in recent years. In addition to visual clutter from store displays, excessive signage, crowded product shelves, loud music, bright lights and competing smells can be a distraction for many consumersFurther, smartphones enabling consumers to check their emails, browse social media or text while shopping vie for shoppers’ limited attention. All of these distractions and more lead to a decrease in customer encounters with products, which can negatively affect a retailer’s bottom line.  

Using AI to Capture Customer Attention  

How can today’s retailers mitigate these challenges? Most people are now familiar with artificial intelligence (AI), which promises to solve any problem, but which AI can help increase sales? There are two main types of AI individuals may be familiar with for measuring attention: Eye-tracking AI and biologically inspired AI are both types of artificial intelligence, but they differ in their approach to measuring and interpreting data.   

[Read more: "Google Uses AI to Tackle Grocers' Top Concerns"]

Eye-tracking AI involves using computer vision and machine-learning algorithms to track the movements of a person’s eyes as they look at different objects or areas of a screen or environment. In contrast, biologically inspired AI, also known as neuromorphic computing, is a type of artificial intelligence modeled after the structure and function of the human brain. Attention-measuring biologically inspired AI provides retailers with a powerful and superior tool to better understand and engage with their customers.   

By analyzing consumer attention patterns, retailers, both online and in brick-and-mortar stores, can identify which products and services are most popular, which marketing campaigns are most effective, and which areas of their stores are getting the most foot traffic. This information, in conjunction with a full analytics platform, can be used to optimize store layouts, product placement, supply chains and marketing campaigns to better connect with customers and increase sales and revenue.    

Uses of Attention-Measuring AI

Many global companies are using both “traditional AI” and biologically inspired AI to maximize insights into consumer behavior optimizing product placement, supply chain efficiency, marketing and new product development. CPG companies PepsiCoUnileverNestle, GSK, and Johnson & Johnson, as well as fashion retailers NordstromH&M and Zara, are among those that recognize the importance of AI to maintain a competitive edge.

Attention-measuring AI can also be used to improve the efficiency and accuracy of inventory management. By analyzing customer attention and product engagement patterns, retailers can identify which products are selling quickly and which aren’t, and adjust their inventory accordingly. This can help retailers avoid overstocking slow-moving products or understocking popular products, leading to improved profitability and customer satisfaction.  

Attention-measuring AI can help retailers to optimize their websites to enhance the online shopping experience. Retailers can identify which products are most popular and tailor website content to maximize the likelihood of consumers seeing those products. This can lead to increased website traffic, improved engagement and increased sales. Additionally, the technology can help retailers identify and correct any user experience issues that may be causing customer frustration or online shopping cart abandonment, resulting in a smoother, more productive online shopping experience.  

Attention-measuring AI can be used to measure, monitor, and improve customer service in retail. By analyzing customer attention patterns, retailers can identify areas where customers may be experiencing confusion, and adjust their customer service practices accordingly. Retailers can also use the insights provided by attention-measuring AI to develop training programs and leading practices for their customer service representatives, ensuring that they provide the best possible customer experience.  

Finally, attention-measuring AI can be used to provide real-time insights and feedback to retailers. By analyzing customer attention patterns in real time, retailers can quickly adjust their strategies and tactics to better meet customer needs and expectations. By leveraging the power of attention-measuring AI, retailers can gain a competitive edge and stay ahead of the curve in an increasingly data-driven marketplace.  

About the Author

Scott Schlesinger

Scott Schlesinger is a partner and the North America analytics leader at PA Consulting. He has more than two decades of experience helping client organizations make faster and more informed decisions leveraging business intelligence, analytics, AI and data management technologies. Schlesinger is a digital strategist, innovator and people leader with demonstrated success in building and leading large consulting practices as a senior executive/partner within global consulting firms.

About the Author

Scott Siegel

Scott Siegel is a data and analytics expert helping lead data strategy in North America at PA Consulting. Siegel is a result-driven information technology executive and recognized thought leader who has demonstrated the ability to successfully deliver complex and large multifaceted analytics, AI, data mesh and IoT projects. These initiatives involved organizational transformation across a multitude of stakeholders. As the strategy leader for a global organization, Siegel has more than 20 years of experience interacting with c-suite and architecture-oriented customer personas.
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