Blog · Takes
Takes, page 4 of 4
Points of view from the Lily AI team on where retail discovery is going and what actually moves revenue.
TakesHigh-Conversion Shoppers Deserve a Seamless Search Experience
Type a typical, specific search term into your favorite fashion site's search bar and you are met with a surprising amount of resistance. High-conversion shoppers deserve better.
TakesProduct Attribution for Beauty Brands: A Q&A with Lily AI’s Joyce Lay
Joyce Lay, Lead Merchandise Analyst at Lily AI, on how beauty products differ from apparel and the challenges beauty brands face turning shopper intent into purchases.
TakesHow Customer-Centric Product Attributes Help Mitigate the Supply Chain Crunch
The pandemic and the associated supply chain crunch exposed how many retailers still use historical data to forecast demand. So, can better product attribution data save the day?
Takes3 Reasons Why E-Commerce Product Recommendations & Personalization Have Never Been More Pressing
Two years into the pandemic, we've learned why e-commerce success is tied to strong product recommendations, online personalization, and rock-solid demand forecasting.
Takes7 to Stay, 1 to Go: Retail Trends in E-Commerce That Will Outlast the Pandemic
Multiple pandemic-driven changes in retail trends are here to stay, though not every trend has staying power. A look at eight e-commerce trends, and which ones will last.
TakesWhy Product Data is Key to Your Search Engine Marketing and Optimization
More product data, and more granular product data, is simply better. Five ways customer-centric product attributes can inform your search engine marketing solution.