Queuing Up: Predictive Wait Times in Retail
Challenge
Brick-and-mortar retailers often face the challenge of managing long queues, particularly during peak hours or periods of high demand. Long wait times can negatively impact customer satisfaction, and even lead to lost sales.
Knowing how and when to reposition resources, such as checkout desks and changing room staff, ahead of a rush is difficult to accomplish without a reliable system informing managers about:
- The number of customers entering the store within a given period
- The estimated time for customers to finish their in-store journey and proceed to complete transactions
- The public-facing profile of the entering customers, such as gender estimation and adult/ child differentiation, in compliance with data privacy standards
Solution
Queue prediction involves using data analytics to forecast queuing based on the number of visitors entering the store at a given time. This information can then be used to optimize staffing levels, adjust store layouts, and proactively manage queues.
- There are several reasons why retailers need queue prediction, including:
- Access to comprehensive data-driven KPIs, facilitating informed decision-making
- Tailored notifications for repositioning staff or infrastructure relevant to sales
- Prevention of queue abandonment caused by lengthy wait times
Benefits
Retailers can rely on queue prediction to optimize various in-store processes. Accurate predictions can also:
- Enhancing customer loyalty by managing expectations and decreasing frustration associated with lengthy wait times
- Optimizing staffing levels by predicting the number of customers who will visit the store and adjusting staffing accordingly
- Reducing operational expenses by avoiding overstaffing or underutilizing resources
- Boosting sales by minimizing wait times and lowering the possibility of customers abandoning their purchases
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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.
