Latent Semantic Indexing / SEO Terms Latent Semantic Indexing Latent semantic indexing (LSI) is a method used in information retrieval to identify relationships between terms and concepts in a body of text. In the context of search engine optimisation (SEO), it refers to the idea that search engines use LSI to understand the meaning of content beyond exact keyword matches. LSI helps search engines interpret context, improve accuracy and deliver more relevant search results based on related or synonymous terms. Although Google does not confirm using traditional LSI in its algorithms, the concept has influenced how content creators think about keyword variation and topic relevance. Instead of repeating a single keyword, content should include related phrases, synonyms and contextually relevant terms that support a broader understanding of the subject. For example, a page about “solar energy” might include terms such as “renewable power,” “photovoltaic panels,” and “green technology,” all of which signal topic depth. Using LSI-inspired techniques in SEO supports better content quality and search performance. It helps pages rank for a wider range of queries, improves readability and aligns content with user intent. This approach is especially important in semantic search, where engines try to understand natural language and conversational phrasing. For nonprofits, LSI helps ensure that mission-driven content is discoverable across varied searches. For B2B and SaaS brands, it supports longer-form content strategies and educational resources that build trust and relevance.