Search Relevance Algorithms

Search relevance algorithms refer to the formulas and tools search engines use to evaluate how relevant a webpage is to a particular search query.

What Are Search Relevance Algorithms?

Today, most algorithms are backed by machine-learning (ML) capabilities that can rapidly analyze massive datasets to derive insights for a business or individual. Search relevance algorithms utilize this technology to evaluate several factors of a webpage in terms of its relevance to a user's search query. Many brands and retailers use search relevance algorithms — which are typically integrated into their data collection and analysis systems — to assess shoppers' search intent and refine their websites to align with that intent. Google's RankBrain, for example, interprets search queries and semantic terms to give brands insight into their customers' search intent. Natural language processing (NLP) tools can do the same for spoken search queries. By employing these algorithms, brands can enhance their digital presence to better align with their customers' needs.

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