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 PepsiCo, Unilever, Nestle, GSK, and Johnson & Johnson, as well as fashion retailers Nordstrom, H&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.