AI Mall Marketing Automation
Case Study
Problem Statement:
The client, a prominent mall chain, sought to leverage cutting-edge technology to enhance their marketing strategies and security measures. Traditional approaches lacked the ability to gather real-time data on customer behavior, demographics, and movement patterns, limiting their ability to tailor marketing efforts and ensure a safe environment.
Proposed Solution:
To address these challenges, we developed a comprehensive AI-powered solution comprising two desktop applications and a backend server. The first desktop app, built with Python, PyQt, Flask, Deepface, TensorFlow, Keras, OpenCV, and MediaPipe, utilized facial recognition and demographic analysis to identify and track individuals as they entered the parking lots. This data was seamlessly integrated with the online server, which fed into the second desktop app deployed within the mall premises.
Result:
The AI Marketing Automation for Malls solution revolutionized the client's operations by providing unprecedented insights into customer behavior and movement patterns. Through real-time monitoring and analysis, the client could optimize marketing strategies, tailoring promotions and offerings based on visitor demographics and preferences. Additionally, the solution enhanced security measures, ensuring a safe environment for all visitors. By respecting privacy and deleting data upon exit, the system struck a balance between functionality and ethical considerations, solidifying the client's reputation as a responsible and innovative business.
Technology Used:
QT, Python, Django, TensorFlow, Keras, OpenCV, MediaPipe, Deepface, Flask, PyQT