Computer with a preview of Lily AI's demand forecasting master class webinar.

Take our demand forecasting master class.

The more insight retailers have into a customer’s preferences, the better positioned they are to anticipate demand and eliminate the uncertainty that causes overstocking – and yet the supply chain is only as robust as the data that feeds into it at the source.

 

In this short “master class,” you’ll learn how granular product attributes can help reduce mountains of unsold inventory in the warehouse, reduce assortment complexity, clean up the product catalog, and use data analytics to identify the most profitable SKUs.

 

You’ll hear perspectives on these issues from Lily AI CTO and Co-Founder Sowmiya Narayanan, VP of Product Byron Jones and Director of Styling Kathy Lee, with an emphasis on how to apply new learnings to YOUR retail e-commerce operations.

Trusted by global retailers and industry leaders

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Ready to Help Your Shoppers Find What They’re Looking For?

If you’re ready to start your journey with better demand forecasting, you’ve come to the right place. Lily AI helps retailers boost product discovery and conversions by turning qualitative product attributes into a universal, customer-centered language at a high volume with unprecedented accuracy and scale.

Why Lily AI?

Lily AI enables brands and retailers to speak in the language of their customer, helping to boost site conversion, order size, and full margin sales. By automating and dramatically enhancing the product data attribution process, Lily AI increases product sell-through and drives 8-9 figure revenue uplift for some of the world’s leading retailers and brands.  

 

With the deepest image recognition platform for retail, the Lily AI product attributes platform injects customer-centric attributes across the breadth of the existing retail stack to drive immediate relevance and connect shoppers with the products they’re really looking to buy.

Resources.

Customer Centric Predictions Guide

Customer-Centric Predictions: A Better Way to Forecast Retail Demand

It all starts with understanding why – not what consumers are buying. To meet the challenges of demand forecasting head on, the key for retailers lies in using the language of customer-driven product attributes – not legacy, spreadsheet-based attributes.
Read
Woman packing up a retail shipment of clothing for her business.

It’s All About the Margins: A Better Way to Forecast Retail Demand

What if retailers could increase their full-margin sales by making informed, customer-centric predictions about what shoppers are likely to buy in the coming months? It all starts with understanding why – not what they’re buying.
Read
A variety of clothing and fashion items hanging on a rack.

How to Improve Retail Demand Forecasting with Customer-Centric Predictions

It’s no secret that demand forecasting in retail can be a bit tricky. However, no matter how complex, it’s a game changer for retailers when it comes to planning out inventory accurately for the coming seasons.
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