Guide: AI SEO Strategy 2025
AI SEO strategy for B2B: Optimise SEO and content for AI, and map the AI-powered digital customer journey.
How to future-proof your SEO strategy for Google’s AI Overviews, AI-Driven Search, and Chatbots.
Why traditional SEO alone isn’t enough anymore
Search is evolving — and fast. Where traditional SEO focused on keywords, backlinks, and links in Google search, the new reality of AI-powered search demands something deeper: contextual understanding, semantic relevance, and real-time value delivery.
Search isn’t just a search results page anymore. It’s:
Google AI Overviews synthesising answers from multiple sources
ChatGPT, Claude, and Perplexity, etc., generating real-time citations from the web
AI “agents” deciding which content gets surfaced, and how
👉 Read also: Future of SEO: Navigating the future of Search
What is AI SEO?
AI SEO (Artificial Intelligence Search Engine Optimisation) means optimising your content and site for AI-driven discovery, not just Google’s legacy algorithm. It includes ranking in:
Generative search experiences (SGE)
AI-powered chatbots (ChatGPT, Claude, etc.)
Conversational assistants (voice and browser-based)
Answer boxes, featured snippets, and knowledge graphs
You now need to optimise for machines that think more like humans — understanding nuance, user intent, and structured context.
For B2B marketers, the shift is clear: if your content doesn’t help AI understand your value, you don’t exist in the buyer’s decision journey.
How AI Search is changing the digital customer journey
1. The journey starts earlier — and more independently
With AI-powered tools like ChatGPT, Perplexity, and Google’s AI Overviews, buyers can start solving problems before they ever land on your website. They ask complex, contextual questions — and get synthesised answers instantly.
Old journey:
Google → keyword search → click → browse site
New journey:
“Hey ChatGPT, what are the best B2B CRMs for a remote sales team?” → AI delivers ranked suggestions with context → Buyer narrows options before visiting a site
✅ Implication: You must now influence discovery and decision before the buyer even sees your landing page.
2. AI becomes a new gatekeeper
In AI search, it's not just what buyers are searching — it's how AI interprets the intent and chooses to present answers.
AI models prefer:
Structured, up-to-date, trustworthy content
Sites with strong E-E-A-T (Experience, Expertise, Authoritativeness, Trust)
Clear answers, not just keywords
✅ Implication: You’re now optimising content for a “thinking” system, not just an algorithm.
3. Buyers skip stages or loop back more easily
AI search collapses the funnel. A buyer can go from problem-aware to vendor evaluation in one conversational query.
They might:
Discover a solution
See customer proof
Compare vendors
Ask for ROI
All within a single AI chat or Google AI Overview.
✅ Implication: Your content needs to serve multiple stages of the journey at once, not siloed funnel pieces.
4. Search becomes conversational & contextual
Buyers now use AI tools to ask real questions — in full sentences, with context like “...for startups,” “...with GDPR compliance,” or “...under $1k/month.”
This means:
Long-tail, high-intent queries dominate
Search is now personalised by use case, role, industry
✅ Implication: Keyword targeting alone is not enough. You need to understand buyer context and write like you’re solving their real-life problems.
5. AI changes what counts as a touchpoint
In traditional digital journeys, touchpoints were trackable: ad → click → page → form.
Now?
A buyer might interact with your brand name, feature list, or customer story without ever clicking your link
AI may summarise or paraphrase your content, not link to it
✅ Implication: Attribution gets fuzzier. Brand trust and content visibility in AI models matter more than pixel-perfect conversion paths.
6. AI search shortens (or bypasses) sales cycles
Buyers who use AI tools often arrive with:
Pre-evaluated shortlists
Deeper technical understanding
Specific objections already answered
✅ Implication: Sales conversations are happening after buyers have made up their minds, and your marketing must feed the AI to influence that mindset.
SEO strategy in the age of AI
#1: Understand the AI-powered digital customer journey
Modern B2B buyers begin their journey long before they speak to sales — and now, AI search is a growing part of that self-directed discovery phase.
Your new search audience isn’t just the buyer — it’s the AI agent deciding what to show them.
Where do they look along their digital customer journey?
Google AI Overviews
ChatGPT + Bing for business queries
Voice assistants
Search-powered tools like Perplexity
Your competitors' well-structured blog content and FAQs
#2: Create content that works for both AI & humans
AI SEO isn’t about writing for machines — it’s about helping AI understand and trust your human expertise.
Want AI to feature you in AI search results? Focus on:
Topical authority:
Become the source on your niche.
Use consistent author bios, brand tone, and expertise signals.
Original data: Share benchmarks, proprietary research, or client stories.
Build trust and authority: E-E-A-T. (More in step #4 below).
Structured content:
Use FAQ blocks, bullets, tables, and semantic headings.
Include schema. Schema markup is a code (structured data) added to a website's HTML to help search engines and AI understand and display content more effectively in search results.
Intent-first content:
Write for actual questions, not keywords.
Start with a direct answer (30–50 words).
Support with explanation and internal links.
Conversational tone:
Match the natural language that AI and humans both understand.
#3: Optimise technical SEO for AI crawlers
AI crawlers have limited time and need structured context fast. Speed, clarity, and accessibility matter more than ever.
Key technical moves:
Fast load speed (Google Lighthouse score > 90)
Mobile-first design
Clean code (semantic HTML, no JS-heavy clutter)
Robots.txt + up-to-date sitemap
Schema markup (especially for FAQs, People, Organisation, Product)
SSL + HTTPS (AI filters for secure content first
#4: Build E-E-A-T for AI (and traditional search) authority
AI engines cite content they trust — and they assess that trust based on your Experience, Expertise, Authoritativeness, and Trustworthiness. By following Google's E-E-A-T principles (Experience, Expertise, Authoritativeness, Trustworthiness), you ensure your content ranks higher and builds trust in both humans and AI.
How to build EEAT:
Publish under real names with bios and credentials.
Get third-party mentions and backlinks from reputable sites.
Stay active on LinkedIn and relevant communities.
Keep your content up to date — AI loves fresh, fact-based info.
Promote thought leadership: podcasts, bylines, interviews.
AI SEO isn’t just search optimisation. It’s brand building.
#5: Monitor AI-specific metrics
In addition to traditional SEO KPIs, track metrics that reflect how AI platforms are interacting with your content:
1) Featured snippet appearances
Featured snippets are often the source of answers in AI Overviews or chatbots. If you’re in the snippet, you’re likely influencing AI responses — or being cited.
How to monitor:
Google Search Console: Check "Performance → Search Results → Filter by appearance = ‘Rich results’ or ‘Featured Snippet’"
SEMRush / Ahrefs / Moz: Most track SERP features; you can filter keywords with snippets.
SurferSEO / Frase: Helps you structure content optimised to win snippets.
What to look for:
High impressions + low clicks = you're getting seen in AI responses
Keywords that trigger snippets you don’t own (opportunity gaps)
2) Google’s AI Overviews
Google SGE (Search Generative Experience) often cites sources inline in AI summaries. Visibility here means trust.
How to monitor:
Manual tracking: Google your key terms in Chrome's SGE Labs (US-only) or use VPN-based SERP emulators (e.g. SERP API, SearchPilot)
Tools:
There are multiple tools that you can use to track AI Overviews, including Keyword.com, Semrush, Ahrefs, and SE Ranking.
What to look for:
Are your blog pages or domains being referenced?
Are competitors dominating answers for your key topics?
3) Bounce rate, time-on-page, engagement signals
AI engines may prioritise high-engagement content to inform answers. If users leave quickly or don’t scroll, your content looks irrelevant.
How to track:
Google Analytics 4 (GA4): Use “Engaged Sessions,” “Engagement Rate,” “Scroll Depth,” and “Average Session Duration”
Hotjar / Microsoft Clarity: Session recordings and heatmaps to spot content drop-offs or usability issues
What to monitor:
Pages with high impressions but low engagement.
Drop-off right before CTA or critical value sections.
Engagement benchmarks by content type (blogs vs landing pages).
4) Visibility on AI platforms like Perplexity or ChatGPT
These tools often scrape and synthesise from trusted, indexable sources — especially .com domains with clear topical authority. So, how to track brand mentions in AI platforms?
How to check:
Manually:
Perplexity.ai: Enter a query and check which links it cites
ChatGPT (with browsing enabled / Bing): Ask queries like “Best B2B go-to-market blogs” and see what content it uses.
Pro tip:
Ask: “What are the top sources for [your topic]?” or “Show me credible info about [your brand/solution].”
With tools:
Keyword.com, Peec.ai, Advanced Web Ranking, and other AI rank trackers can help you monitor your brand mentions in AI search results.
5) Page speed + mobile usability scores
Both AI and traditional search engines deprioritise slow, clunky, or mobile-unfriendly content, especially in mobile-first indexing.
Tools:
Google PageSpeed Insights (free): https://pagespeed.web.dev/
Lighthouse (in Chrome DevTools): Technical SEO + performance audits
GTmetrix / WebPageTest: For deeper diagnostics
Google Search Console → Mobile Usability report
What to aim for:
Load speed under 2.5s
Core Web Vitals in the “Good” range
No mobile errors or text-overflow issues
6) Voice search visibility
Voice assistants and smart devices often pull answers from content structured as direct, conversational Q&As — a growing component of AI and local search.
How to monitor:
Search Console: No direct "voice" filter, but look for queries phrased as natural language (e.g. "how do I…” or “best way to…”)
Answer the Public / AlsoAsked: Helps identify voice-like queries to target
Use schema markup: FAQPage, HowTo, Q&A to increase chances of being featured
7) How to track AI traffic on your site
Tracking traffic from AI tools and crawlers (like ChatGPT, Bing Chat, Perplexity, etc.) is tricky because many don't pass clear referrer data, or they access content via APIs or direct page scraping (not full browser sessions).
That said, here’s how you can monitor AI-driven activity on your site
1. Track referrals from AI interfaces (where possible)
While most AI tools don’t pass “referrer” data consistently, some do—especially if they link out to your site:
Check in GA4:
Go to Reports → Acquisition → Traffic Acquisition
Filter by Source / Medium
Look for sources like:
Perplexity.ai / referralBing / organicchat.openai.com / referralbard.google.com(rare, but possible)copilot.microsoft.com
Pro tip: Create a custom segment in GA4 to isolate and monitor traffic from these domains over time.
2. Use UTM parameters to tag AI exposure links
If you're actively prompting AI tools with your links (e.g. sharing blog URLs in ChatGPT threads, Perplexity citations, or outreach), use unique UTM parameters like
utm_source=ai&utm_medium=referral&utm_campaign=chatgpt_testing
This helps you attribute indirect discovery via AI if the visitor later clicks the link.
3. Analyse server logs for bot activity
GA4 doesn’t detect non-human activity well, but your web server logs can reveal:
Page requests from known AI crawlers (e.g.
ChatGPT-User,CCBot,PerplexityBot,Google-Extended)Frequency and depth of crawl
Bot IPs and user-agents
Use tools like:
Cloudflare → Bot management + user-agent filtering
Loggly, New Relic, or Logz.io → for deep log analysis
Custom scripts to extract and flag unusual bot patterns
Pro tip: Look for spikes in pageviews with 0-second sessions and no events — possible signs of AI scrapers.
4. Set up custom dimensions in GA4 for AI signals
Since most AI referrals aren’t well-tagged, you can:
Create a custom dimension for "Referral Source Contains ‘ai’ or ‘chat’"
Build a GA4 exploration report to track any related sessions over time
Monitor engagement metrics (bounce, scroll, conversions) from these visits
5. Use Google Search Console + Bing Webmaster Tools
These tools won't show “AI traffic” directly, but they’ll give you a proxy for crawlability and indexation, which matters for AI engines that pull from public search data.
Monitor:
Crawl frequency by page
Indexing status
Mobile usability + speed (important for AI surfacing)
Rich results and schema enhancements
Referring queries related to your AI-focused content
Caveat: AI traffic ≠ Human traffic
AI tools may visit your site without ever triggering a GA4 session. So think of AI metrics as:
Indirect influence on brand discovery
Upstream exposure that leads to direct visits, branded search, or demand generation
#6: Let AI be your collaborator, not just your audience
AI isn’t just changing how users find your content — it can also help you create better, faster, smarter.
Use AI to:
Generate keyword clusters + semantic variations
Outline and structure long-form content
Repurpose high-performing posts into social/email assets
Summarise analytics and recommend actions
💡 Just remember: your voice, your data, and your perspective are the differentiators AI can’t copy.
AI Search is already here — are you ready?
In 2025 and beyond, AI agents will make decisions on behalf of your buyers. If you’re not visible in their answers, you’re out of the game.
👉 Want help auditing or rethinking your SEO for the AI era?
