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

ROI Examples

Data Needed

Understand the Use-case under 5 minutes

Video (2 minutes)

4R Assortment Optimization | Thriving In Retail

Machine Learning based Assortment Optimization combining agile continuous improvement methodology, and flexible customization to accommodate unique business requirements, delivering superior results every week in every category

Article (2 minutes)

Assortment Optimization With H2O.ai

H2O.ai is a leading AI cloud company, presenting assortment optimization use-case with the challenges of it, and how to solve those challenges using AI.

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

White Paper (17 minutes)

Inventory optimization through SKU assortment + machine learning

Detailed use-case by Microsoft and Neal Analytics building a solution that is meant to maximise sales at every outlet or store, by tuning product assortments using advanced analytics

Article (5 minutes)

A five (5) min guide that will walk you through what you need to know about assortment, simulation, optimization & AI

How to optimise your category assortments using AI, what ML is, how it works, how it’s used in retail, what analytical assortment optimization do, and how to start implementing it

White Paper (15 minutes)

AI Brings Precision to Grocery Assortment Optimization

Grocery assortment optimization using AI. This whitepaper that’s presented by Symphony RetailAI goes through the traditional assortment optimization, the need for AI in such a case, and the key benefits expected

How AI & Machine Learning Make Assortment Optimization More Profitable

This article goes through how AI contributes effectively compared to humans in some cases such as assortment optimization, the main role of AI in assortment optimization, questions retailers should ask before choosing an assortment optimization solution, and tips for them.

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

White Paper (17 minutes)

MkKinsey: Analytical assortment optimization

McKinsey & Company guide for using Advanced Analytics to empower Assortment optimization. Topics include: Navigation of the assortment optimization cycle, Role of Advanced Analytics, Laying the organisational foundation, & Gettin Started

Article (11 minutes)

H&M Pivots to Big Data to Spot Next Big Fast-Fashion Trends

How H&M is using AI on three fronts to optimise assortment planning for it’s 4,200+ stores: analysing online trends, demand & sales forecasting per store, & applying dynamic price optimization

Video (37 minutes)

Why Your Assortment Isn’t Returning Maximum ROI

A webinar about how 4R’s Assortment Optimization solution drives two key factors: increasing your profits and, at the same time, increasing the overall customer experience.

Article (4 minutes)

The four steps to infuse artificial intelligence into merchandise planning

Tech focused

More details on the technical aspects of the use-case

Article (10 minutes)

Assortment Recommendation Using Reinforcement Learning For CPG Companies

Assortment recommendation in CPG Beverages industry using Reinforcement Learning

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

Video (30 minutes)

Building A Product Assortment Recommendation Engine

AB InBev expands on their ML-based Assortment Planning engine using Regression Models and Collaborative Filtering to predict product demand, in addition to robust optimization techniques

Visit

Paper

A Review of Artificial Intelligence used in Assortment Planning

Literature review of many papers showcasing different AI methodologies to optimise Assortment Planning

Paper

A Probabilistic Simulator of Spatial Demand for Product Allocation

Building a stochastic model of spatial demand in physical retail, and learning optimal product allocation policy using deep reinforcement learning

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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