Live shopping marketplace Whatnot has a need for speed — more specifically, to deliver product recommendations to shoppers more quickly.Improving Whatnot’s discovery and recommendation system has been a major focus for Chief Product Officer Tom Verrilli over the years. The latency on its recommendations is now down to just minutes, meaning Whatnot’s technology can now quickly ingest information — like, if a product has sold out on a particular livestream — and use that to inform what products it recommends to buyers.
The desire to keep improving its recommendation systems is what drove Whatnot to acquire machine learning startup Shaped in a deal announced last week. Shaped, founded in 2021, bills itself as a “real-time retrieval engine for search, feeds and agents.” The company has worked with companies like Vox Media and QVC, using its technology to develop a more personalized news feed for New York Magazine as just one example.
According to Verrilli, discovery is one of the things that has “historically set Whatnot apart.” Recommendations are uniquely challenging in live commerce, where inventory changes quickly, sellers don’t know ahead of time what questions a shopper may ask, and buyers are clamoring to get their hands on collectibles and rare items ahead of everyone else.
