Quick one before we begin:

100,000 people now read Strategy Breakdowns 🙌 

I've been sitting with this number for a few days, trying to find the right words.

Here's what keeps coming back: In June 2023, I announced I was launching a newsletter.

52 people reacted. A few dozen signed up. Most of them were mates who agreed to "have a look" (if you’re still here - appreciate you!)

I had no idea if anyone would enjoy reading obsessive strategy rambles as much as me.

Turns out - quite a few people do.

This milestone belongs to you as much as it does to me. Every reply-turned-40-email-thread, every shared article, every conversation that started with "I read your piece about..."—that's what built this. Strategy Breakdowns grew because you found it valuable enough to tell someone else about it.

So: thank you. For reading, for sharing, for pushing me to make this better each week.

Now, let's get into today’s breakdown.

(Spoiler: it’s a ripper for anyone playing the ‘how do I get more traffic in 2025’ game)

— Tom

P.S. In the background, I’m quietly chipping away at something big. I think it’ll end up bigger than this newsletter. Click here to be one of the first who knows about it.

Product teams are cracking under pressure

Atlassian’s State of Product 2026 surveyed 1,000+ PMs — and the findings are a wake-up call. 84% worry their product will fail, only 20% bring engineering into discovery early, and 70% don’t experiment.

AI is helping teams claw back time, but pressure is still rising. Collaboration gaps and no time to learn are leaving teams reactive instead of strategic. The report breaks down where teams are struggling — and how top performers are adapting:

• How AI is saving teams time — and how it’s letting them down

• Why pressure is rising, and where the biggest opportunities lie

• Practical tips for investing in experimentation and product ops to drive better outcomes

Getting compliant doesn’t take months anymore.

With Delve, it takes 15 hours - and today, alongside Bland, we’re rethinking security questionnaires.

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_{Thank you for supporting our sponsors, who keep this newsletter free.}

How Ahrefs is winning AI search

Chess Move

The what: A TLDR explanation of the strategy

When AI search emerged as a new frontier for traffic acquisition, marketing intelligence suite Ahrefs made their own company a living case study.

They spun up an internal program to optimise their own brand ranking in ChatGPT, Perplexity, and Google AI Overviews, while documenting every learning publicly.

The meta-strategy: Every experiment they ran on themselves drove both content marketing for Ahrefs.com and product development for their “Brand Radar” tool.

• Their research on AI visibility correlations became viral blog posts → These insights became Brand Radar's core tracking algorithms

• Their experiments optimising Ahrefs.com for ChatGPT became case studies → The most successful experiments became features for Brand Radar users

• Their competitive analysis became thought leadership content → This intelligence became Brand Radar's comparison and gap analysis tools

The result: By dogfooding their own product and sharing their research publicly, Ahrefs is now the most cited tool for “AI search optimization”.

The marketing drives their own AI visibility (proving the strategy works), while simultaneously creating the intellectual property that becomes their paid product features. Their success becomes both the proof point and the product.

‘Self-evident marketing’.

Breakdown

The how: The strategic playbook boiled down to 3x key takeaways

1.  Create a laboratory inside your company

Rather than theorise endlessly about AI search optimisation, Ahrefs made their entire company the test subject.

They systematically experimented with different approaches to improve their visibility in AI search:

• Creating content clusters around high business-potential topics

• Building relationships with publications that AI systems frequently cite

• Optimising content structure based on how AI systems parse information

• Testing which messaging frameworks get repeated in AI responses

But here's where it gets interesting: they document every experiment publicly.

Their research isn’t just academic - it includes their own brand as a primary data point, and informs their own traffic acquisition strategy.

When they discovered that branded web mentions correlate 66.4% with AI visibility, they published it freely.

→ A valuable finding to share in its own right

→ But also - a valuable insight into their own playbook for dominating AI search results

This creates a powerful credibility loop. They're not consultants theorising about AI search - they're practitioners showing you their actual results.

2. Research becomes features, features enable more research

When Ahrefs’ analysis revealed that different AI platforms favour different content types, this insight didn't just become a blog post.

It became core functionality in Brand Radar:

• Platform-specific tracking (ChatGPT vs Perplexity vs Google AI Overviews show different citation preferences)

• Domain analysis features that identify which publications drive AI mentions for your company

• Gap analysis showing what platforms and topics competitors rank for in that you don't

When they found that mentions on highly linked pages correlate 70% with Google AI Overview visibility, this became the "Cited Domains" feature that helps users identify which authoritative sites to target for PR.

Similarly, CMO Tim Soulo's experiments in getting traffic from ChatGPT directly shaped how Brand Radar measures and tracks AI-driven website traffic.

The feedback loop is seamless: internal optimisation creates research insights, research insights become published content (which boosts AI visibility), and those insights become paid product features.

3. The learning-in-public moat

By sharing their AI search research publicly, Ahrefs creates multiple strategic advantages:

• Market category creation: They're not just competing in AI search optimisation - they're defining what it means. Their frontier research papers and case studies become the industry standards that others reference (which increases their own rankings).

• Built-in content marketing: Their optimisation experiments become case studies, their research becomes thought leadership content, and their product usage becomes proof points. The company’s own operations is content marketing.

• Data network effects: Every company that uses Brand Radar generates data about AI search patterns. This creates a proprietary dataset that becomes more valuable as it grows, making their insights increasingly comprehensive and difficult to replicate.

• Product-market fit validation: By testing strategies on themselves first, they ensure Brand Radar solves real problems. They're not building features based on hypotheses - they're productising solutions that actually work.

Consider their approach to the "AI Overview correlation" study. They:

1. Analysed their own brand alongside 75,000 others, and discovered the correlation between web mentions and AI visibility

2. Published the research, establishing thought leadership, which drove mentions and increased rankings

3. Built this insight into Brand Radar's core functionality, so customers can take advantage of the findings too

4. Used their improved AI visibility as social proof for the tool

The meta-strategy works because Ahrefs operates in a domain where they can credibly be both the researcher and the test subject.

Their SEO and marketing intelligence origin gives them unique data and product advantages for tackling AI search, while their willingness to experiment publicly creates trust and category authority.

The company's own growth drives R&D, and R&D drives growth. 

Rabbit Hole

The where: 3x high-signal resources to learn more

Ahrefs gave away their entire AI playbook ↗

[2 minute read]

The page that shouldn't exist yet.

Ahrefs documented their AI strategy in public, then built all of their learnings into Ahrefs itself.

They're basically offering you the same toolkit they use themselves to dominate AI search.

Whether you use Ahrefs or not, worth seeing what the next era of AI marketing looks like.

See exactly how often ChatGPT recommends your competitors over you ↗

[3 minute read]

Brand Radar is a free Ahrefs tool that makes competitive analysis uncomfortably transparent:

→ Head-to-head comparisons of brand mentions across all major LLMs
→ Topic gap analysis showing where competitors dominate AI responses
→ Trend data revealing which brands are winning AI mindshare
→ Citation sources identifying which domains drive AI mentions

They're literally giving you the same dashboard they used to become the most-cited “AI Search” tool in ChatGPT.

Meta-strategy at its finest.

The privacy-first alternative to bloated analytics ↗

[2 minute read]

Remember Google Analytics?

Before it became a data surveillance nightmare that requires cookie banners and GDPR lawyers?

Ahrefs Webmaster Tools is the antidote:

• No cookies by default, no personal data collected

• Clean interface showing only essential metrics

• Historical graphs that actually load quickly

• Traffic source breakdowns (including LLM referrals)

Plus all the SEO fundamentals: rankings, backlinks, site audits

It's the analytics setup you wish you'd had from day one.

Free for unlimited sites. No credit card required. No hidden gotchas.

Ahrefs is essentially betting: "If we give away world-class tools for free, some percentage will upgrade to premium when they need deeper data."

Based on their growth trajectory, the bet's working.

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