Walmart Search
Search at Walmart is a hundred-to-a-hundred problem — a mature system where the work is squeezing reliable basis points out of enormous volume. I worked on relevance and the retail knowledge graph underneath it.
At Walmart’s scale, small relevance and discovery gains move enormous absolute volume — but the search stack lacked the structured understanding to make those gains reliably for grouped items.
When you operate at this scale, basis points are the product.
Built variant grouping into the result surface so shoppers could discover the choices available to them easily — more relevant choices, higher conversion.
Surfaced the right variant out of a group of items to the user, to match their intent and speed their shopping journey —most relevant choice, higher conversion.
Mature-system product work is emotionally different from 0→1 — there’s no launch high, just basis points that compound into real money. The skill is believing the small numbers matter and having the measurement discipline to prove they do. Two USPTO patents came out of this work on search and item identification.