InStore Analytics


    Key Features

  • Customer Footfalls Using Video Analytics
  • Identifies & Eliminates Employees In Footfall Counting
  • Accuracy of 80% plus
  • Customer Demographics and With Their Images
  • Age, Gender, Expressions and Other Demographics
  • Leverage AI and Machine Learning for Continued Deeper Insights on Customers
  • Temperature, Lighting and Other Sensor Based Real Time Info
  • Automatic Employee Attendance
  • Augment CCTV Recordings using Filtered Images of People Movement
  • Specially Important In Case of Security Event


TAAS

InStore Analytics


In the ever-growing competitive market of retail, the ability to analyze in-store performance is very critical. The ability to extract footfall information is vital. The insights gained allow retailers to react and adapt accordingly. People counting and conversion is the foundation of in-store analytics.

    Customer Footfalls Using Video Analytics
  • Identifies & Eliminates Employees In Footfall Counting
  • Accuracy of 80% plus
    Customer Demographics and With Their Images
  • Age, Gender, Expressions and Other Demographics
  • Leverage AI and Machine Learning for Continued Deeper Insights on Customers
    Real Time Monitoring
  • Temperature, Lighting and Other Sensor Based Real Time Info
  • Automatic Employee Attendance
    Security
  • Augment CCTV Recordings using Filtered Images of People Movement
  • Specially Important In Case of Security Event