Traffic Counting - What you need to Know

Written By zack haque

I have implemented several traffic solutions in my career. Let me share with you some of my learnings. I am happy to discuss further if you are looking for expert consultations on this topic.

Whether you are implementing a traffic counting solution for the first time or upgrading your current solution, here are some key considerations.

1. Business Objectives

  • Business Case: Know what you are trying to achieve and create your business case: Are you trying to increase sales, improve conversion rates, optimize staffing, better allocate labor, improve your forecasts, AND measure marketing effectiveness?

  • KPIs: Align traffic counts with metrics like conversion%, average transaction value, and Average sales per footfall,

2. Technology Selection

  • Sensor type: There are a lot of options. Your use case will decide what works best. Cameras are the best but sometimes the older infrared light sensors may work well.

  • Accuracy and calibration: Ensure solution offers >95% accuracy and has mechanisms for adjusting to real-world conditions. Consider the Imputation* method being used. Who and what is being counted - groups when families shop together, children, pets, shadows, and air movements (happens more often than we think!)

  • Advanced capabilities: Look at solutions that can provide key insight to traffic flow such as heatmaps showing how customers behave once inside the store. This can be useful to make data-driven merchandising decisions.

3. Installation & Store Layout

  • Entry/exit point coverage: Place sensors at all customer entry points, including side entrances, escalators, and connected malls.

  • Internal Store Coverage: Place counters inside the store if you are looking for insights on customer behaviors e.g., which product/presentation are the "dwelling" in front of.

  • Mounting height and angles: For cameras and overhead sensors, ensure optimal height (usually 8–12 feet) and unobstructed views. Your traffic vendor will take care of this usually.

  • Lighting and environmental factors: Ensure lighting doesn’t interfere with sensors (e.g., glare on glass doors, poor lighting in vestibules).

4. Data Integration

Most solutions provide the ability to pull data as batch jobs or using their APIs. Store the traffic data centrally and push to your internal platforms or create direct integrations.

Look for intraday APIs - This is critical if you are reporting KPIs real time (or close to it):

  • POS integration: To calculate retail KPIs e.g., conversion rate (sales ÷ traffic).

  • WFM integration: To align labor scheduling with Traffic patterns. Traffic, when reviewed as big data - is highly predictable. Your WFM forecasts will be better if you include Traffic data.

  • Marketing analytics: Attribute traffic changes to campaigns or promotions.

5. Data Privacy & Compliance

  • Anonymity: Ensure compliance with privacy laws (e.g., GDPR, CCPA) by anonymizing video or tracking data. Discuss with your Legal Department.

  • Clear signage: Inform customers if video analytics or Wi-Fi tracking is used.

6. Operational Considerations

  • Staff exclusion: Ensure the system can filter out employees from the court, especially during opening/closing or breaks. There are privacy considerations- consult your Legal Department when making these decisions.

  • Regular maintenance: Schedule calibration, firmware updates, and sensor cleaning.

  • Exception handling: Have protocols for outages or unusual spikes (e.g., mall events or emergencies).

  • Imputations*: For systems that impute data - have a process to shut off/exclude counts when a store is closed.

7. Reporting & Insights

  • Real-time dashboards: For store managers and regional leads to view performance by hour/day/store/district/region/country or your internal market hierarchy.

  • Historical analytics: Identify trends, seasonality, and cross-location benchmarks.

  • Actionable alerts: Notify when footfall exceeds thresholds (for staffing, service, security).

8. Scalability and Cost

  • Cost per location: Hardware, installation, data storage, and ongoing support.

  • Multi-store consistency: Use the same platform across stores for standardized reporting.

  • Cloud-based vs. on-premises: Choose based on IT infrastructure and scalability goals.

  • Remember as always - Prioritize solving your business needs - not cost.

*Imputations - the assignment of a value by inference from historical values present in the dataset.

 

zack haque
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