Instead of relying solely on legacy, out-of-the-box product attributes, we help retailers and brands dramatically expand their product language into the sorts of attributes shoppers are looking for when choosing their next purchases. This then helps understand why they’re buying – not merely what they’re buying.
Automated proxy product identification based on visual similarity saves days of manual labor, boosts your forecast volume accuracy and increases your full-margin sales.
Now retailers can gather proxy products through Lily AI-powered computer vision to accurately forecast demand for brand-new product lines. We help replace wholesale pre-orders with a leaner, demand-led, made-to-order model that fuels product development with AI to launch lines that are guaranteed to sell out quickly.
What if you could increase your full-margin sales by making informed, customer-centric predictions about what shoppers are likely to buy in the coming months? By forecasting demand using a language of customer-driven attributes – not legacy, out-of-the-box attributes – you’re increasing your ability to sell those customers what they’re looking for, right now, and decreasing the need to mark that inventory down later.
The supply chain is only as robust as the data that feeds into it at the source. In retail, granular product attributes can help reduce mountains of unsold inventory in the warehouse, and Lily AI helps retailers reduce assortment complexity, clean up the product catalog, and use data analytics to identify the most profitable SKUs.