Search engine optimisation has shifted dramatically from simple keyword-matching to a complex interplay of many signals, primed around quality, authority, user-experience and trust. At the heart of it, the aim of Google (and many search engines) remains the same: deliver the most relevant, useful and trustworthy answers to users’ queries. One of the key frameworks now referenced in this context is the E-E-A-T model (Experience, Expertise, Authoritativeness, Trustworthiness) — an evolution of earlier signals of quality. For anyone who cares about organic visibility, traffic sustainability and resilience to ranking fluctuations, understanding how algorithm changes, user behaviour signals and E-E-A-T work together is essential.
Algorithm history
Google’s algorithm has undergone major transformations over the years — from link-based heuristics to semantic understanding, machine learning, user-intent and experience-driven signals. For example:
- Early updates such as Panda (2011) targeted low-quality, thin content and content farms.
- The Penguin update targeted spammy link-practices.
- Later updates such as Hummingbird (2013) emphasised natural language, context and intent rather than just keywords.
- More recently, broad “core algorithm updates” and the so-called “helpful content” updates have sought to elevate content depth, user-experience and trust signals.
In short: what was once heavily dominated by links and keywords now depends much more on content quality, site experience, user behaviour and trustworthiness.
User behaviour
User behaviour signals are the measurable actions users take when interacting with search results and webpages — and these actions increasingly serve as indirect cues to Google and other engines about how well a page is satisfying its audience. According to one article:
Examples of key user behaviour signals:
- Click-through rate (CTR) — the proportion of users who click your result from a search listing.
- Dwell time — how long a visitor stays before returning to search results.
- Bounce rate — percentage of users who leave after one page; though context matters.
- Pages per session, return visits, and deeper engagement metrics (scrolling, clicks, comments, shares).
Why these matter:
- If users click a result and stay engaged (rather than “pogo-sticking” back to results), that indicates the page met their need.
- Sites that aim purely for ranking but neglect UX, readability, relevance or trust may suffer: slow-loading pages, thin content, intrusive pop-ups all degrade behaviour metrics.
- Behaviour signals differ by content-type: blog posts need depth and engaging layout; product/about pages need clarity, speed and conversion-friendly structure.
In effect, optimising user behaviour is not just a nice-to-have: it’s part of building for the algorithm and for users — a symbiosis.
E-E-A-T Signals
The concept of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is a framework that helps contextualise what “quality” means in Google’s eyes.
Understanding each component
- Experience: The newer “E” — emphasises first-hand or real-world experience with the topic. For example, content written by someone who has lived or worked through the topic, not just theoretical.
- Expertise: Depth of knowledge or skill demonstrated. Author credentials, research, case-studies, data-backing content all help.
- Authoritativeness: Reputation of the author or the site—backlinks from credible sources, mentions in reputable publications, recognised domain.
- Trustworthiness: The reliability, honesty and safety of the site: secure browsing (HTTPS), clear contact info, transparent policies, accurate information.
Why it matters
- For YMYL (Your Money or Your Life) topics — health, finance, legal — Google places even stricter scrutiny on E-E-A-T.
- While E-E-A-T itself isn’t a direct “score” users can optimise in a vacuum, the signals that reflect it (user behaviour, content depth, trust features) are increasingly important.
- Technical SEO supports E-E-A-T: a secure, fast, well-structured site helps ensure users and search engines trust your brand.
Actionable steps
- Include author biographies with credentials.
- Publish in-depth, well-researched content rather than superficial posts.
- Show social proof (case studies, testimonials, awards) and garner quality backlinks.
- Use technical best practices: mobile responsiveness, fast loading, structured data, secure connections.
When you align user-behaviour signals and algorithm updates with a strong E-E-A-T footing, you are building for both users and search engines.
Recovery after Updates
When a major algorithm update (such as a core update) rolls out, many websites experience ranking drops, traffic volatility or worse. The good news: recovery is possible — but it requires strategy, not just waiting.
Understanding core updates
Core algorithm updates are broad changes that adjust how Google evaluates relevance, authority, trust and experience. They differ from minor updates (which might tweak small ranking signals) in that they often shift the “rules of the game”.
Common effects on websites
- Top-ranking pages may drop if they no longer satisfy evolving criteria (content depth, user engagement, trust).
- Traffic may decline dramatically overnight, even for previously strong sites; while others rise rapidly.
- The impact varies by industry (e.g., e-commerce, local services, publishers) depending on how aligned the site is with new signals.
Recovery best practices
- Conduct a full content audit: identify thin/outdated pages, duplicate or overlapping content.
- Ensure content is aligned to search intent—not just keywords. A page must answer what the user is really looking for.
- Strengthen internal linking so authority flows to newer pages and related resources.
- Enhance author and brand profiles (for E-E-A-T) especially in niches requiring expertise/trust.
- Monitor analytics to spot patterns in winners/losers — what content improved, what changed? Use these insights to guide decisions.
Pairing behaviour signals + E-E-A-T for recovery
Because user behaviour and E-E-A-T overlap so much with what algorithm updates reward, improving experience metrics (dwell time, return visits, engagement) while reinforcing trust/authority signals can accelerate recovery.
For example: if a site lost rankings after a core update because it had thin content and low dwell time, steps might include:
- Merging thin pages into a comprehensive pillar page
- Improving readability/layout and adding visuals
- Building authority by linking out to and getting mentions from reputable sources
- Encouraging deeper engagement (internal links, interactive elements)
Recovery may take time, but sites that build resilience via user-first experience + authority + trust are far better positioned for future updates.
Key Takeaways
- SEO is no longer just about keywords and links — it’s about quality, user experience, trust and relevance.
- Algorithm history shows a clear evolution: from link/keyword heuristics → to intent/context → to experience/trust signals.
- User behaviour metrics (CTR, dwell time, bounce rate, return visits) are increasingly meaningful proxies for how well your content meets user needs.
- The E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) provides a useful lens to assess and improve your site from a holistic quality standpoint.
- When you’re hit by an algorithm update, treat it as a signal to audit and improve — focusing on content depth, user-experience, authority and trust rather than quick gimmicks.
- Ultimately: building a site that genuinely satisfies users and establishes trust will yield more sustainable search visibility than trying to “game” the algorithm.
