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    1. Home
    2. Insights
    3. Measuring In-Store Dwell Times
    A woman in a retail store looking at her phone, surrounded by new fashion items.
    Use cases, Retail

    Measuring In-Store Dwell Times

    Measuring customers’ in-store dwell times can boost sales of higher margin products
    Download Use Case

    Challenge

    Physical retailers want to replicate metrics already used by e-commerce sellers to gauge a customer’s interest in a particular product. Manual observation of how long customers spend looking at a product or shelf can be costly and inexact, especially if the behavior is responsive to observation. In addition to potentially creating an unnecessary obstacle, positioning a designated employee or third-party contractor to measure dwell times in a specific zone also interferes with optimal staff allocation.   

    Retailers wanting to make the most of store layout and product positioning need to know:   

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      The relationship between dwell time and conversion rate  

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      The impact of product position on dwell times  

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      When a customer is browsing or visually engaging with a product

    • A bicycle store from the outside with a big logo and illuminated windows.

      Accurate Footfall Counting at a Bike Retailer

      Germany's Bike & Outdoor Company (BOC) used a Xovis sensor system for precise footfall counting, enhancing customer analysis and in-store service across locations.
      Read more

    Solution

    Accurately mapping the customer behavior across the in-store journey can improve category merchandising and enhance sales and profits by placing higher-margin products where customers are more likely to buy them. Using an automated system to capture objective, actionable data is critical for:       

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      Understanding the path to purchase, including dwell time and view direction    

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      Adapting the product arrangements based on data-driven insights   

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      Moving high-margin products to top locations to increase sales  

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      Differentiating between engaged shoppers and passersby   

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      Delivering real-time data about in-store performance 

    A man with glasses and a beard wears a dark coat, standing outdoors with a neutral expression.

    The system offers flexibility and incorporates mixed technologies tailored to the appropriate solution, delivering accurate and reliable counts that can be utilized for further analyses.

    Henning Schorling Head of IT, B.O.C. GmbH & Co. KG

    Benefits

    Adding an automated solution to measure in-store dwell times and their impact on sales performance can help retailers:   

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      Improve engagement and capture rates in designated zones 

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      Test the effect of adjustments to product placement  

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      Eliminate costs associated with manual data collection  

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      Optimize placement and shorten the trial-and-error process

    Download now

    Access a free Use Case PDF version now!

    Download


    Additional retail use cases

    A dynamic retail complex features supermarkets, clothing stores, and transport hubs with bustling activity.
    • Frictionless Checkout

      Automation helps balance customer flow and prevent loss at self-service zones

    • Measure Customer Engagement

      Measuring customers’ in-store dwell times can boost sales of higher margin products

    • Improving Store Layout

      Accurate store traffic data helps retailers optimize layout and product placement

    • View Direction

      Retailers can boost revenue by measuring in-store attention

    • Customer Counting

      Optimal staff and layout depend on real-time customer engagement data

    • Optimizing Product Positioning / Assortment

      Retailers looking to support their category manager are turning to tech

    • Real-Time Waiting Analytics

      Retailers need a robust queue management system to eliminate friction points

    • Preventing Queue Formation

      Queuing up can become a costly friction point for brick-and-mortar retailers

    • Expanding Sales with Demographic Data

      Understanding gender-specific shopping trends helps retailers optimize resources.

    • Customer Centric Staff Allocation

      Retailers need a robust queue management system to eliminate friction points

    • Staff Exclusion and Sales Performance

      Real-time KPIs help retailers optimize performance across all locations

    • Use-Based Cleaning

      Smart Retail requires Smart Cleaning to enhance customer experience

    • Group Shopping Analytics

      Shopping habits change with company, aiding retailers in boosting sales

    • Window Shopping Analytics

      Tracking capture rates from window shoppers can boost store performance

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