Our Retail AI Solution : propel-R

An AI Algorithms Suite For Shopping Malls & Retail Chains

Product Overview

The emergence of eCommerce has disrupted the Revenue & Margins of the Shopping Malls & Retail Chains. They must compete with the eCommerce giants to survive.

The key challenge for the Malls & Retail Chains are how to attract more visitors, drive loyalty , conversions & improve the brand value. More the visitors, greater the probability to improve the Revenue (Shop Rental, Adv Revenue) and brand value.

The mall management does not have access to the Customers / Visitors data. So, to attract visitors without any demographics is a challenge. Another challenges is lack of accurate data on the current & historical footfall, the visitors profile, the visitor traversal path, dwell time etc.

With propel-R, we have solved this challenge using Deep Learning Algorithms. The algorithms are based on Computer Vision & Natural Language processing. With propel-R, we have solved the business issue of increasing visitor footfall, loyalty & brand value.

Key Business Challenges
Business Problem We Are Solving

Propel -R Pricing Model

  • Cloud based Subscription
  • Minimum subscription commitment of 1 year
  • Cloud cost included
  • Edge Device Cost, if applicable, included
  • Deployment on private cloud is also supported
  • The pricing will be base on per algorithm , per camera number of users
propel -R Algo Suite Components

Case Study : Visitor Analytics for a Shopping Mall

A Shopping Mall in India

Business Problem :

A shopping mall in India is looking for a visitor analytics to understand visitor count and demographic profile. This will enable the mall to maximize revenue from the rent, choose better mix of tenants, plan events for targeting right audience and put in place customer centric strategy.

Technology Used :

Python, OpenCV, Tensorflow, Deep Learning

Solution :

The solution involved building deep leaning model to detect persons coming through entry gate and people moving through corridors on different floors of the mall. The detected persons are then pass through age, gender and emotion model to derive these information. This is a cloud based solution hosted on AWS cloud for data processing. The edge device is used to capture the camera frames and post motion detection passed to AWS based server for further processing.