#search-algorithms

#search-algorithms

Effective search and discovery in e-commerce significantly boosts customer conversion rates and loyalty, necessitating a shift from traditional keyword-based methods.

Focus on engaging the middle of the audience funnel rather than just attracting top-level traffic.

2025 should be dedicated to journey mapping to improve audience engagement strategies.

Google AI Overviews is slower to remove blocked or deindexed content compared to traditional web search.

Publishers must adapt to the decline in audience loyalty and reliance on search/social referrals to survive.

Reliable sites appear in search results 19 to 45 times more often than low-quality content sites.

User behavior plays a significant role in the proliferation of misinformation, beyond algorithmic influence.

Trie data structures enhance search efficiency and user experience in applications like auto-complete and spell-checking.

Filter bubbles are algorithmically constructed isolation seen in personalized search results.

Google and other search engines track online activities to curate search results, potentially limiting exposure to diverse information.

AI search systems vary in when they deliver LLM-aided results (ranging from on request to every time) and the extent of control users have over AI usage.