Customer Behavior Analysis

Track the length of time a person spends looking at a display or remains in a specific area.

What is Customer Behavior Analysis?

Customer behavior analysis is an essential issue for retailers. It is used for optimized store performance, enhanced customer experience, reduced operational costs, and therefore higher profitability.

Computer Vision methods use deep learning models to automatically extract information to analyze customer behavior in retail stores. AI models can detect, track and analyze customer behavior in retail stores using the real-time video of common surveillance cameras.

Key Features of Customer Behavior Analysis

State-of-the-art deep learning algorithms perform people detection for retail analytics with image recognition algorithms.

  • Detect people in real-time inside a retail store using the videos of multiple cameras.
  • Estimate the number of customers in real-time to detect hot spots automatically.
  • Analyze the footfall by measuring time spent in specific areas (attention to shelves, queue times, and more).
  • Edge Computer Vision allows guaranteeing privacy by performing machine learning on-device without sending any visuals externally.

Value of Intrusion Detection with Deep Learning

Computer Vision is a highly scalable method, especially for large-scale use and use across branches. Compared to alternative customer behavior analysis techniques, no physical sensors are required, installation and maintenance are much less costly.

  1. Automation of customer behavior analysis, fully contactless, non-invasive, privacy-preserving, and scalable.
  2. High accuracy, even using inexpensive cameras such as surveillance cameras, can be simultaneously used for conventional surveillance security.
  3. Actionable insights about store performance and the customer experience. AI vision provides high consistency over time.
  4. Quantify important customer information and measure the impact of changes (allowing A/B testing with variants, compare marketing strategies).
  5. Avoid blindspots by tracking key metrics for multiple store sections and compare metrics across multiple locations.
Last updated
September 18, 2021
Requires Viso Suite

How to get started

This solution is built on Viso Suite, the all-in-one computer vision platform to deploy, run and scale the solution with powerful tools and infrastructure.

To get started, request a personal demo, we will put together a plan that includes all the services you need to get started.

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