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
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The estimated time for customers to finish their in-store journey and proceed to complete transactions
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Customer profiles, like gender and age group, compliant with data privacy standards
Foot Traffic in Shopping Malls: Identifying Hot Spots
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:
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Access to comprehensive data-driven KPIs, facilitating informed decision-making
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Tailored notifications for repositioning staff or infrastructure relevant to sales
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Prevention of queue abandonment caused by lengthy wait times
Exceptional service with quick responses and immediate support. Implementation was rapid and effective, and remote maintenance is a big advantage in comparison to other systems.
Benefits
Retailers can rely on queue prediction to optimize various in-store processes. Accurate predictions can also:
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Enhance loyalty by reducing wait-time frustration
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Optimize staffing with customer visit predictions
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Reduce costs by avoiding overstaffing
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Boost sales by minimizing wait times and cart abandonment
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Additional retail use cases
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Measure Customer Engagement
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Improving Store Layout
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View Direction
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Customer Counting
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Optimizing Product Positioning / Assortment
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Real-Time Waiting Analytics
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Preventing Queue Formation
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Expanding Sales with Demographic Data
Understanding gender-specific shopping trends helps retailers optimize resources.
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Customer Centric Staff Allocation
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Staff Exclusion and Sales Performance
Real-time KPIs help retailers optimize performance across all locations
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Use-Based Cleaning
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Group Shopping Analytics
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Window Shopping Analytics
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