retail-intelligence

In the retail industry a trade area, also known as a catchment area, is the geographic area from where you draw your customers. Here I derive trade area from scratch

The target in this case, is to create a model of machine learning to know the behaviour of users. What is required is an end-to-end model such as those seen in practice in the module. In this case, you have to apply three models and choose the best one, but the previous part is common to all three.

Identified the most popular combos that can be suggested to the restaurant chain after a thorough analysis of the most commonly occurring sets of menu items in the customer orders

Research done about the application of computer vision to merchandising resets

coachoutlet japan data extractor

CX experience in retail stores

Research Papers and Posters

Data Analysis of a retail store data to suggest possible strategies to maximize profit earned.

Wiser Solutions is a retail and commerce intelligence company that provides pricing, market, and MAP (minimum advertised price) intelligence to brands and retailers. Its platform collects online and in-store data, tracking billions of products daily across hundreds of thousands of stores, to power price optimization, competitive price monitoring…

Project with real retail data. This repository shows my proposed solution to estimate the sale using information obtained from IT sensors. Due to confidentiality issues, the entire data analysis and transformation process is not shown.

EDITED is an AI-powered retail intelligence platform that helps retailers, buyers, merchandisers, planners, designers, and eCommerce teams make data-driven decisions across assortment, pricing, and promotions.

Welcome to my Data Science Portfolio — a collection of hands-on projects, end-to-end Machine Learning systems, business analytics case studies, EDA projects, dashboards, and recruiter-level practical work built to solve real-world problems using data.

Computer Vision Solutions For Retail and Venue Analytics

In this project, I analyzed the point of sale transactional dataset to identify sales trends, suggest menu changes, and the impact of pricing changes.