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    3. Heat maps in retail: understanding zones of interest

    Heat maps in retail: understanding zones of interest

    07/11/2022
    Use cases, Retail, Smart buildings
    1 min
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    Accurate data on which parts of a physical store receive the highest and lowest volume of customer traffic can help retailers to make more precise decisions about store layout and product positioning. Improving engagement and conversion rates are common goals for brick-and-mortar stores, targets that can be more easily and quickly achieved by better understanding the customer journey and zones of interest. Heat mapping is a tool that translates density rates into quick visualization tool that can help guide decision-making. 

     

    Challenge

    Better understanding the relationship between product placement and sales is a goal of retailers looking to improve conversion rates and space utilization. “Gut feeling” and designating staff to do manual counts with hand-clickers, methods that have guided placement decisions for decades, are woefully outdated. Modern retailers want accessible data on:

    • Footfall trends in different parts of physical locations
    • Product performance data based on positioning changes
    • Responses to product placement based on demographic splits  


    Solution

    Actionable insights into store layout and the customer journey based on the popularity of in-store areas at different times accessed as an image including historical traffic flow maps help retailers to:

    • Identify areas with the highest and lowest in-store marketing potential  
    • Planning store layout in response to traffic trends
    • Testing the impact of product positioning, staff adjustment and store concepts 


    Benefits

    The real-time and historical data visualized as a traffic flow map help with:

    • Increasing conversion rates: right products, right place, right time 
    • Lowering operating costs: better positioning sales and support resources  
    • Maximizing infrastructure: adjusting staff planning and scheduling at a
      granular level

    Access a free Use Case PDF version now!

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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.

     

    Customer counting for retail

    Understand customers by analyzing flow. Improve store performance and enhance customer journeys.

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