Content Marketing Glossary

  • What are Search Engines?

What are Search Engines?

Search Engines

Search Engines are systems that index vast amounts of web content and return ranked results in response to user queries. The dominant general-purpose engines are Google, Bing, Yandex, Baidu, and DuckDuckGo; alongside them sit domain-specific engines (YouTube, Amazon, GitHub) and a growing class of AI-powered answer engines (Perplexity, ChatGPT search, Gemini) that blur the line between search and conversational AI.

Market share reality

In 2026, the general web search market looks roughly like this:

  • Google: roughly 85โ€“90% globally
  • Bing: 3โ€“7% (higher since the ChatGPT integration boosted visibility)
  • Yandex: dominant in Russia and parts of CIS
  • Baidu: dominant in China
  • DuckDuckGo, Ecosia, Brave, Kagi: aggregated single-digit share

Practically, “SEO” for most Western businesses means “Google SEO”. Bing and other engines matter, but the gravitational pull of Google market share means the optimisation work you do for Google covers most of the others by default.

How search engines work

Three phases, consistent across engines:

Crawling. Automated programs (crawlers or spiders) follow links across the web, discovering new pages. Crawl frequency depends on the page’s historical update rate and perceived importance.

Indexing. Crawled pages are parsed, their content analysed, and information about them stored in the index. Not every crawled page is indexed - poor quality, duplicates, and low-value pages get skipped.

Ranking. When a query arrives, the engine selects candidate pages from the index and ranks them using hundreds of signals: relevance to query, page quality, authority of the domain, user-engagement patterns, query-intent match, and increasingly, semantic understanding via language models.

The last phase is where the interesting complexity sits. Google’s ranking system has gone from PageRank-dominated to RankBrain to BERT to MUM to current LLM-assisted systems over 25 years of evolution.

The shift to answer engines

A structural change in 2023โ€“2026: search engines are increasingly answering queries rather than returning links to answers. Three implications:

Zero-click searches are rising. More queries produce a satisfactory answer on the SERP itself - in the AI Overview, featured snippet, or knowledge panel - without requiring a click through. For publishers, this caps traffic growth even on ranking pages.

Citation-level visibility is now a target. Being cited as a source in an AI Overview or ChatGPT answer is a new type of ranking win. Optimising for citation - clear factual claims, named data, crawlable content - overlaps with but diverges from traditional SEO.

AI-answer engines are their own distribution channel. ChatGPT, Perplexity, Gemini, Claude, and Copilot collectively serve millions of queries daily. They use different ranking signals than Google. A content strategy that ignores them will miss a growing share of information-seeking traffic.

Specialised search engines

Four worth naming for the SEO context:

YouTube. The second-largest search engine in the world. A separate SEO discipline entirely, with different ranking signals (watch time, retention, channel authority).

Amazon. Dominant commerce search. Product SEO on Amazon is governed by conversion rate, review volume, sales velocity, and ad spend rather than link signals.

App Store Search (Apple / Google Play). ASO (App Store Optimization) is a related but distinct discipline.

GitHub. For technical content and developer tools, GitHub’s internal search is a non-trivial traffic source. Optimising README content for GitHub’s indexing behaviour is a niche craft.

Implications for strategy

Three recommendations from the current landscape:

Plan for Google-dominant but AI-diversified distribution. Most traffic will still come from Google, but AI-answer surfaces will make up a growing, not shrinking, share. Content invisible to LLM crawlers concedes that future.

Optimise for citation as well as ranking. Clear attribution, named sources, unique data, expert voices - the factors that help you get cited in AI answers are increasingly the same factors that help you rank on Google.

Monitor platform-specific signals. The playbook for Amazon is not the playbook for Google is not the playbook for Perplexity. Cross-platform SEO requires platform-specific thinking. See search engine optimization for the Google-specific foundation, which still applies most of the time.

We built Penfriend to produce content that performs across search engines - primary focus on Google, but structured to survive Bing, DuckDuckGo, and the growing class of AI-answer engines like Perplexity and ChatGPT search.

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