A tweet on Monday from Google search liaison Danny Sullivan provides an explanation for the rankings shakeup that has perplexed the local search community since the beginning of November. Google began using neural matching to generate local search results.
Local search has just undertaken a huge evolutionary step. No longer are local results being matched to user queries solely on the basis of identifiable ranking factors, such as proximity to searcher, keywords in business names, primary category of the listing, review count, and so on. That isn’t to say such factors are now unimportant, but they have been augmented by a broader and more general sense of relevance delivered by neural matching.
It’s Neural Matching: Google Explains the November Ranking Shakeup
A tweet on Monday from Google search liaison Danny Sullivan provides an explanation for the rankings shakeup that has perplexed the local search community since the beginning of November. Google began using neural matching to generate local search results.
Local search has just undertaken a huge evolutionary step. No longer are local results being matched to user queries solely on the basis of identifiable ranking factors, such as proximity to searcher, keywords in business names, primary category of the listing, review count, and so on. That isn’t to say such factors are now unimportant, but they have been augmented by a broader and more general sense of relevance delivered by neural matching.