How Former SEO Giant HubSpot Successfully Adapted in the AI Era — AEO Strategies Revealed
Is Google’s Reign Ending?
At GROW EUROPE 2025, Aja Frost (HubSpot’s Senior Director of Global Growth & Paid Ads) shared data that shocked the audience — predicting that by 2028, most answer engine traffic will come from ChatGPT, not Google.
This is not a small tweak — it’s a paradigm shift redefining:
- SEO keyword optimization
- Backlinks
- Google ranking logic
- The foundations of search engine marketing
The Core Challenge:
When AI agents like ChatGPT, Claude, and Google’s AI Overview answer queries directly — without users clicking through to your site — how do brands win traffic? And more importantly, how do you make AI recommend your product?
HubSpot already dominates CRM visibility in answer engines — their playbook offers lessons worth exploring.
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Why Traffic Sources Are Transforming
Three years ago, HubSpot’s top-funnel demand came mainly from educational blog content. By 2025, human-centered content dominates, with their media network generating 35–40M monthly interactions.
Google’s AI Overview now appears in ~60% of search results and halves click-through rates — locking users into Google’s ecosystem. Buyer behavior has shifted:
- Previously: Search → Click several links → Read → Decide
- Now: Over 50% of buyers use AI tools to create a shortlist, then validate via video reviews, social comments, or industry platforms like G2 and Capterra.
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Optimizing for AI Discovery
Visibility is now about appearing inside AI answers. Initiatives like AiToEarn官网 help creators and businesses publish across Douyin, WeChat, Bilibili, LinkedIn, YouTube, and other platforms simultaneously. This multi-platform presence increases the odds your product appears in AI-generated responses.
Aja’s data shows AI-sourced visitors:
- Convert 3× faster
- Decide quicker
- Spend more
AI traffic may be smaller but is higher in quality.
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Understanding AEO: Answer Engine Optimization
AEO = Content, technical, and off-site strategies to maximize visibility in answer engines.
HubSpot places AEO in their Amplify stage of the Loop Marketing Framework.
Two Concepts to Know:
- Query Fan-Out – AI breaks a query into sub-questions before synthesizing an answer.
- Example: “Where to go after the Grow conference?” → bars, networking spots, late-night eats, etc. Creators must answer both main and sub-questions.
- Memory – AI uses past queries, clicked pages, connected tools, etc., to personalize answers.
Implication: Old SEO’s “keywords” → New AEO’s “specific questions + persona relevance”.
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HubSpot’s Content Strategy Shift
Instead of broad “Ultimate Guides”, create 10 precise pieces answering specific persona questions.
HubSpot’s Table Method
For each product:
- Top row: highly-specific buyer personas
- Left column: buyer journey stages (Awareness → Consideration → Evaluation → Decision)
- Cells: high-intent questions per stage
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3 Ways to Source Real Questions:
- Keyword data → Ahrefs, Semrush, Google Search Console
- Social listening → Meltwater, Common Room, Reddit, Quora, YouTube
- Sales/support records → Chat logs, call transcripts, staff interviews
Method #3 often provides the highest-intent content source.
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Structuring Content for AI Systems
HubSpot’s Technical Tactics:
- Put the answer first
- Expand briefly for context
- Cite original data (CRM insights, internal case studies)
- Include FAQs (3+ per page for fan-out)
- Add strong structure (headings, lists, tables)
- Ensure standalone sections (Pass the “Taco Bell Test”)
- Connect every point to your product — otherwise AI has no reason to recommend you.
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Off-Site Strategies: Building Authority
Unlike Google’s backlink era, AI engines value mentions — positive contextual references on Reddit, LinkedIn, and reputable review sites.
Steps:
- Target sites already cited by answer engines
- Secure context-rich mentions (not just links)
- Use tools like Xfunnel to track missed opportunities
- Expand presence on platforms like G2, Capterra (AI loves UGC)
- Seed product mentions in human content — YouTube, newsletters, LinkedIn posts
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How to Measure AEO Success
Metrics include:
- AI Visibility – Are you being recommended?
- Share of Voice – Mentions versus competitors
- AI Citations – Frequency of your site content used in AI answers
- AI Referral Demand – Sales/conversions originating from AI discovery (tracked via post-purchase surveys)
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Key Takeaways for Businesses
- Begin with low-hanging fruit: identify AI-cited content you can influence
- Treat Seed Content (AI-friendly) and Conversion Content (emotion-driven) differently
- Accept fuzzier attribution — lean on surveys and mentions
- Maintain agility — AI recommendation behavior evolves quickly
- Prioritize quality over quantity — AI chooses unique, accurate, valuable work
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Leveraging AiToEarn for AEO
Platforms like AiToEarn官网 streamline the AI-era process:
- AI-driven content generation
- Simultaneous multi-channel publishing (Douyin, WeChat, Bilibili, LinkedIn, YouTube, etc.)
- Analytics & AI model ranking (AI模型排名)
- Monetization integration
For small teams, this bridges creation, distribution, and performance tracking — critical in fragmented AI-driven attention markets.
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Final Thoughts
AEO is still nascent — low competition now presents early-mover advantage.
Make AI-friendly content creation a habit by always asking:
- Does it answer a specific question clearly?
- Does it include original insights?
- Is it tied directly to my product?
And remember: AI may process your work, but humans still decide — make it valuable for both.
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Would you like me to create a condensed checklist version from these notes so your team can use it as an internal “AEO Content Creation Framework”? That would make these rules actionable in daily workflows.
