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Step-by-Step Guide to Measuring Display & Visual Merchandising Effectiveness

Metrics Matter Episode 3

​​​Understanding how visitors interact with your displays is crucial for optimising exhibition spaces, museums, and retail environments. Using a computer vision-powered platform like Nola, you can gather real-time, actionable insights on how visitors engage with your displays. This step-by-step guide will show you which data points you should collect to measure display effectiveness and how to operationalise the data to meet the needs of your visitors.

This article is relevant to:

  1. Visual Merchandisers in Retail

  2. Exhibitions

  3. Museums

  4. Aquariums

Step 1: Track Foot Traffic and Area Occupancy

 

Objective: Measure the number of visitors entering and moving through different areas.

  • Analyse Traffic Flow: You can leverage an entry/exit line crossing approach or real time occupancy to identify which zones attract the most visitors. This helps you assess whether key displays are placed in high-traffic zones.

 

Why it matters: Understanding where visitors are entering and how they move through your space helps you determine if your displays are in prime locations to attract attention. It also enables you to detect the % of visitors you area capturing, a step which is important later one.

Step 2: Measure Interactions with the Target Display

Objective: Identify if visitors are interacting with your display or just passing by.

  • Track Visitor Movement: Using people counting software to monitor if visitors are stopping, facing, or physically interacting with a display. Platforms like Nola use advanced algorithms to analyse gaze direction, body pose, and movement to identify active engagement.

  • Distinguish Engagement: The system will differentiate between passive observation (walking by) and active engagement (stopping, looking, or touching the exhibit).

 

Why it matters: It's important to know if your display is actively engaging visitors, rather than just attracting a passive audience. This tells you if the display is truly resonating with people.

Step 3: Measure Dwell Time to Detect Legitimate Interest
Objective: Measure how long visitors engage with a display to determine if the interaction is genuine.

  • Set Minimum Dwell Time: Using computer vision, track how long a visitor stays in front of the display. Set a minimum threshold (e.g., 5 seconds) to define a legitimate interaction. If the visitor engages for longer than the threshold, the system will count it as a valid interaction.

  • Track Interaction Duration: The system records the exact time spent interacting. Longer dwell times generally suggest higher levels of visitor interest.

 

Why it matters: This step helps filter out quick glances and ensures you’re measuring meaningful interactions that indicate true engagement with your displays.

Step 4: Generate Heat Maps for Visual Insights

Objective: Visualise areas of high engagement and optimise placement.

  • Capture Foot Traffic Data: Generate heat maps based on foot traffic and engagement data collected by the foot traffic analysis tools. Heat maps will visually display which areas receive the most attention.

  • Identify High-Engagement Zones: Use these insights to identify the zones where visitors are spending the most time. This will help you determine which displays are performing well and which might need adjustments.

 

Why it matters: Heat mapping provides a visual overview of your space, showing you exactly where visitors are interacting most, enabling you to optimise the layout for maximum engagement.

Step 5: Implement a Strategy: Build and Optimise the Engagement Funnel

Objective: Analyse the visitor journey and optimise displays for better conversions.

  • Track the Visitor Journey: Use the data from foot traffic, interactions, and dwell time to create an engagement funnel. This will allow you to track how many people enter the space, how many engage with the display, and how many take a desired action (e.g., making a purchase or further interacting with the exhibit).

  • Identify Bottlenecks: If a display gets high foot traffic but only a few visitors engage, it may indicate that the display isn’t capturing enough attention. You can pinpoint where visitors drop off in the funnel and use that information to optimise your displays.

  • Optimise Displays: Use the insights from the funnel to adjust your displays—reposition them, change designs, or add interactive elements. These optimisations can guide more visitors through the engagement funnel and boost conversions.

Why it matters: The engagement funnel allows you to take actionable insights and strategically improve your displays, increasing the chances of engaging visitors and driving desired actions.

Step 6: Integrate with Other Data Sources (Optional)

Objective: Correlate engagement data with other performance metrics.

  • Integrate POS or Conversion Data: In retail environments, link your computer vision data with point-of-sale (POS) or other conversion data. This will show how visual engagement translates into sales or other desired actions.

  • Analyse Correlations: Compare engagement data (e.g., dwell time, interaction rates) with actual sales figures or actions taken. This will help you understand which displays are driving the most conversions and where improvements are needed.

 

Why it matters: Integrating engagement data with sales or conversion metrics gives you a holistic view of how your displays are influencing visitor behaviour and overall performance.

Step 7: Share Insights with Stakeholders (Optional)

Objective: Improve performance and strengthen relationships with third-party display organisers.

  • Provide Transparency: If your displays are organised by third parties, sharing the insights gathered from computer vision analytics helps you provide transparent, objective data. This can help stakeholders understand how their displays are performing and make data-driven decisions for optimisation.

  • Enhance Collaboration: By sharing these insights, you can improve the overall relationship with third-party partners, encouraging collaboration and fostering a culture of data-driven improvement. This transparent approach helps everyone involved align on goals and take joint action to optimise displays.

 

Why it matters: Sharing data-driven insights not only improves the performance of third-party displays but also strengthens partnerships, builds trust, and drives better results for your venue.

Conclusion: You’re Only as Good As The Data You Have

By following this step-by-step guide, you can leverage CCTV-based crowd analytics platforms like Nola to measure and optimise display engagement in real time. From tracking foot traffic to identifying legitimate interactions and building a conversion funnel, computer vision enables you to make data-driven decisions that continuously improve your displays.

Optimising your displays with real-time insights ensures you create more engaging, effective environments that not only attract visitors but also encourage meaningful interactions and conversions. By constantly refining your approach, you can enhance the visitor experience and drive greater performance across your venue.

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