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Home > AI for Retail > Assortment Optimization

Assortment Optimization

Place the best-fit products at the right time per store to avoid stockouts and minimize markdowns. Make predictions based on different factors including store layout, display capacity, previous purchases, weather, time of the year, and online behavior

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ROI Examples
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1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

More details on the technical aspects of the use-case

3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

Rossmann Store Sales

Historical sales data for 1,115 Rossmann stores. The task is to forecast the "Sales" column for the test set. Note that some stores in the dataset were temporarily closed for refurbishment


Off-the-Shelf Products using AI for Fraud Detection

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