Paid Attention: View Direction in Retail
Challenge
Knowing how customers respond to changes in product placement and onsite marketing is crucial for unlocking the value of the physical retail space.
Retailers constantly adjust product and promotional layouts in pursuit of optimal positioning for catching customers’ attention and improving conversion rates, but basing adjustments on point-of-sale data or on manual observation leaves too much room for uncertainty and costly guessing.
- To adequately measure the effectiveness of in-store testing and advertising, retailers need:
- Accurate, real-time data about customers' movements
- Precise measurements of consumers' visual engagement with products
- Automated data capture capabilities
Solution
A growing number of global retailers use behavioral analytics to understand how customers interact with in-store spaces and staff. View direction measurement, which lets retailers know how long consumers interacted with a particular product or designated space, is part of that trend.
By utilizing objective view direction data, retailers can make informed decisions about staff allocation and test layout changes.
View direction data can help retailers by:
- Delivering KPIs that support fact-based decision-making
- Alerting floor managers of the need to reposition staff or product
- Determining whether conversion rates are product or site-specific
- Differentiating between engaged shoppers and passersby
- Validating the effectiveness of product promotions and positioning
Benefits
Robust, highly-accurate data capture systems can provide retailers with cost-saving insights and actionable KPIs.
A resilient in-store analytics protocol is an excellent way to:
- Manage operational costs by matching resource allocation to observable trends
- Improve A/B testing by accurately measuring before and after testing
- Expand profit by optimizing the position of higher-margin products
- Enhance effectiveness of dynamic and digital signage supporting marketing
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Customer counting for retail
Determine customer patterns and characteristics, such as group and individual flow, gender and view directions. Communicate waiting times to floor staff. Analyze real-time occupancy data for safety and security and exclude staff from customer counts.
