Scalable Machine Learning Applications in Retail

Arrikto introduces some new use cases where machine learning is being used to solve retail problems.

Explore use cases pertaining to retail where machine learning is being used to solve complex business problems:

The retail market has changed globally, requiring retailers to rapidly adapt throughout the value-chain from supply chain, inventory management, consumer buying behaviors, and launching new channels.
To gain a competitive advantage, retailers need to unlock data gathered in all channels and build scalable machine learning models to meet new customer demands and maximize value generated.

Personalization

Personalize value in every part of the customer’s journey. Whether it is assortment selection, promotions or communications – deploy highly targeted campaigns to understand shopper intent and to provide individualized solutions that increase ROI.

Shopping Patterns

Model tune individual item performance by store, improving forecast replenishment orders to warehouses and suppliers to meet daily demands. Reduce shrink and provide customers with fresh products – just in time.

Pricing and Promotion Optimization

Accurately predict the best time to promote and the optimized discount price while maximizing the value generated. Demonstrate success of specific promotions such as increase in basket sizes or store level customer foot count metrics.

Customer Loyalty

Use predictive analytics to review customer buying patterns to customize and incentivize customers to complete the purchases as well as customize the assortment offer that is promoted to increase basket size.

Supply Chain

Accurately forecast models and place purchase orders to fill customer demand with adequate lead times, helping retailers improve service and save on inventory holding costs.

Labor Management

Predict store operational needs and better plan colleague schedules taking into account shopping patterns and timing. Optimize labor allocation in the store to better serve the customer and thereby increase NPS scores.

Real Estate

Use geospatial data analytics to identify critical new prospective locations and where to upgrade existing assets based on customer location, competitor presence, market and assortment preferences to optimize business outcomes.

Fraud Detection

Efficiently analyze transactional data at scale to accurately predict buyer behavior and historical purchases to identify fraudulent transactions and block them as they occur.

Schedule a Workshop for your Team

Check out the growing list of e-commerce & retail companies using Kubeflow in production

Technology

Nielsen shapes the world’s media and content as a global leader in audience insights, data and analytics.

global.nielsen.com

eCommerce

IndiaMART is India’s largest online B2B marketplace, connecting buyers with suppliers.

indiamart.com

Retail

A global technology consulting and services company, helping enterprises marry scale with agility to achieve competitive advantage.

mindtree.com

Retail/eCommerce

Lenskart is India’s fastest growing eyewear company and largest eyewear company online.

lenskart.com

Media & Advertising

Magicpin is India’s #1 shopping savings app driving $1B+ of annual business to retailers across the country.

magicpin.in

Market Research

Numerator blends proprietary data with advanced technology to create unique insights for the market research industry that has been slow to change. The majority of Fortune 100 companies are Numerator clients.

numerator.com

E-Commerce

AI-powered visual shopping for inspiration-driven shoppers. Fynd Now enables consumers to search similar products online and seamlessly complete product purchase journey—from discovery to purchase.

gofynd.io