Rand's unfair advantage is publishing data no one else has
Most marketers post opinions about the industry. Rand posts the original research the industry then argues about.
Rand Fishkin is the cofounder and CEO of SparkToro, the co-author of Zero Click Marketing, and, before that, the founder of Moz and one of the most-cited voices in SEO. His LinkedIn account is not a stream of hot takes. It is a running feed of proprietary studies: zero-click search data from tens of millions of devices, State of Search reports with Datos, analyses of where influence actually happens on the web. Each becomes a post, and each reads like the person who ran the numbers telling you what they found, not a pundit reacting to someone else's headline.
That is the whole engine. Research-led growth is when you turn original data your audience cannot get anywhere else into your content, so authority compounds because you become the source everyone else cites. Rand runs it with discipline: gather exclusive data, lead with the single most surprising number, credit every collaborator, and explain what it means for the reader's work.
Reacts to the trend of the week with a take anyone could have written. Scrolled past and forgotten.
Opens with 'NEW Research: 68% of searches now end without a click', a number only he has. You save it and cite it.
“We are living in a Zero Click World (and I am a zero click girl).”
— From his post debunking the 'search is dying' narrative (747 reactions)
Five findings that repeated across 100 posts
- Original research is the reach engine. His biggest posts open with 'NEW Research': the 68% zero-click study (1,459 reactions), the Datos State of Search preview (1,037), and 'search happens everywhere' (1,012).
- Conversation, not vanity reach. He averages 341 reactions but 73 comments a post, a 21% comment-to-reaction ratio, more than 3x the ~6% LinkedIn norm. People argue the data, they do not just like it.
- He shows his face. 53% of his posts are video, mostly short talking-head explainers, not text broadcasts, and video, image, and text all land within ~100 reactions of each other.
- He credits real collaborators. Similarweb, Datos, Ross Simmonds, Amanda Natividad, all named, which turns every post into shared authority instead of a solo flex.
- Weekday discipline. About 3.6 posts a week, Thursday and Wednesday heaviest, with only 11 of 100 posts landing on a weekend.
The numbers behind the account
The reach per post is modest. The conversation is not, and that, plus a heavy video habit, is the real signal.
Start with the number most people miss. Rand averages 341 reactions a post, which is unremarkable for a 211K-follower account, but he averages 73 comments, a 21% comment-to-reaction ratio, more than 3x the ~6% LinkedIn norm. This is a discussion account, not a broadcast one. If you only measure likes you would underrate him badly, which is exactly the trap we unpack in our guide to a good LinkedIn engagement rate.
Across the 100 posts we analyzed, Rand published about 3.6 times a week, almost entirely on weekdays, with Thursday and Wednesday driving the most volume. That midweek rhythm lines up with how the platform distributes B2B content, which we break down in our guide to how the LinkedIn algorithm works.
When he posts
The content-type mix
Where the engagement comes from
The top posts
| # | Post | Reactions | Comments | Reposts |
|---|---|---|---|---|
| 1 | 'NEW Research: 68% of Google searches end without a click' | 1,459 | 181 | 186 |
| 2 | The latest Datos State of Search debunk | 1,037 | 149 | 130 |
| 3 | 'NEW research: search happens everywhere' | 1,012 | 128 | 133 |
| 4 | 'AI responses aren't lies; they're rarely dead wrong' | 873 | 168 | 123 |
| 5 | 'Tech doesn't have an image problem, it has an intention problem' | 827 | 112 | 55 |
| 6 | 'NEW research: how consistent are AI tools?' | 827 | 179 | 152 |
Reach per post is not the whole story. Want to see where your own account really stands on engagement, not just likes? Run it through our free LinkedIn analyzer.
The six content pillars
Every post is one of six repeatable buckets, so a founder running three companies never runs out of things to say.
Exclusive zero-click and search data, published as 'NEW Research' with the headline stat in line one.
Correcting AI-vs-search hype with data from tens of millions of devices.
Short talking-head videos that make one complex marketing idea click.
Crediting other researchers and founders, which compounds his own authority.
Naming what's wrong with big tech, AI slop, and the traffic-obsessed old playbook.
SparkToro and Alertmouse launches, framed by the problem they solve.
Pillar 1: Original research drops (the reach engine)
Why it works: His single biggest post is a stat only he has, stated in the first line. He does not tease the research, he hands you the headline number ('68% ... end without a click'), then credits the people who built it. Proprietary data plus a plain-spoken finding is his widest-reaching combination.
Pillar 2: Myth-busting the narrative (the debate)
Why it works: He takes the loudest consensus and answers it with 'Nope' plus a number. Framing his data as a correction to what everyone believes gives readers a side to take, which is why the myth-busting posts draw the heaviest comment threads on the account.
Pillar 3: The #5MinuteWhiteboard explainer (the format)
Why it works: The talking-head video is his workhorse format, and the caption does the same work: a clean 'here's what we're NOT saying / here's what we ARE saying' structure. Showing his face on more than half his posts is what makes a data account feel like a person you trust, not a spreadsheet.
Pillar 4: Amplifying peers (the network)
Why it works: He routinely puts other people's research in front of his audience, named and credited. Amplifying peers costs him nothing and earns him everything: the goodwill of the people he features, and a reputation as the curator worth following even when the data isn't his own.
Pillar 5: Conviction and criticism (the stance)
Why it works: He is not neutral, and that is the point. Taking a clear, unfashionable side against big tech and AI hype gives his audience a tribe to belong to. The data earns the trust; the conviction earns the loyalty. A researcher with no point of view is just a chart.
Pillar 6: Building the products in public (the steady drumbeat)
Why it works: Product launches are the quiet drumbeat between the big research drops. He never leads with a spec sheet; he opens with a joke ('MICE. MICE. BABY.') and frames the feature by the problem it solves. The playfulness is what keeps a promotional post from reading like an ad.
The hooks that earned the click
The through-line is a stake in line one: a number, a 'Nope', or a plain declaration. Rand never buries the finding.
Open with 'NEW Research' and the number. 'NEW Research: 68% of Google searches now end without a click.'
Name the myth, then knock it down. 'AI is disrupting traditional search! Nope. Look at the numbers.'
State the shift as fact. 'Top of Funnel was always done on rented land.'
Talk to one reader in the feed. 'No, person-in-my-feed-today, we're not saying...'
Lead with a peer and a number. 'My buddy Ross Simmonds analyzed 8,566 B2B SaaS keywords.'
Put your own accuracy on the line. 'I don't just make predictions, I grade myself on them.'
For the mechanics of writing openers like these, our guide to writing LinkedIn hooks goes deeper, and you can pressure-test your own first line in the free hook generator.
His top hooks, by the numbers
| Hook type | Opening line | Reactions |
|---|---|---|
| Research headline | 'NEW Research: 68% of Google searches end without a click.' | 1,459 |
| Narrative correction | 'The latest Datos State of Search... narratives data doesn't support.' | 1,037 |
| Plain declaration | 'Top of Funnel was always done on rented land.' | 808 |
| Direct address | 'No, person-in-my-feed-today, we're not saying...' | 747 |
A voice that reads like a smart friend, not a report
It sounds like a researcher who is genuinely delighted by the data, with jokes, asides, and strong opinions left in.
- Leads with the number. The first line is the finding, never a warm-up.
- Credits everyone. Similarweb, Datos, and named collaborators appear in almost every research post.
- Playful and profane-adjacent. 'dag nab report', 'MICE. MICE. BABY.', a shrug emoji when the data is inconvenient.
- Takes a side. He names big tech, VC culture, and AI hype as the problem, plainly.
- Teaches, doesn't just claim. Numbered breakdowns and 'here's what this means for you' framing.
- Grades himself. He revisits his own predictions and marks them right or wrong, on purpose.
The voice is recognizable partly because of recurring devices: the 'NEW Research:' opener, the #5MinuteWhiteboard video series, the running Zero-Click saga, and an ending that points to the full report or a collaborator rather than a like-and-follow ask.
What he does, and doesn't, do
- Lead with original data
- Credit every collaborator
- Take a clear side
- Show his face on video
- Teach what the number means
- React to trends with no data
- Take sole credit
- Play it safe and neutral
- Hide behind text-only broadcasts
- Post a stat with no takeaway
Publishing original research, shooting the explainer video, crediting collaborators, and holding a point of view at three-plus posts a week is the part almost nobody sustains, and it is exactly the gap CaptureFlow closes. CaptureFlow is an AI content agent that turns your expertise into weeks of on-brand content for every platform. You capture one idea in 5 minutes (a voice note, a screen recording of the data, a quick talk to camera), and CaptureFlow, trained on your voice and your past posts, drafts native content for each channel, a LinkedIn post, an X thread, a carousel, a short video, so a research-heavy cadence never costs authenticity. See how the AI content agent works.
The systems underneath the posts
Two loops quietly turn 100 posts into authority, product demand, and a network that amplifies him.
The research-to-authority flywheel
- 1Publish original dataA zero-click study, a State of Search report, an AI-consistency analysis.
- 2Lead with the headline numberThe single most surprising stat, in the first line.
- 3Others cite itMarketers, press, and podcasters quote the finding, crediting him.
- 4The citations build authorityHe becomes the default source for the whole topic.
- 5The next study lands to a bigger audienceMore reach means more data partners want in, and the cycle repeats.
The authority-to-product funnel
The research is the product demo. Every study is a live proof that SparkToro's audience data and Alertmouse's monitoring work, so the content pre-sells the tools without a hard pitch.
Choosing the media
An image of the key chart, with the headline stat in the caption.
A short talking-head video that walks through one finding.
Text or video, structured as claim then 'Nope' plus data.
A quote or link to the collaborator, credited by name.
Plain text; the point of view carries it.
A demo clip or screenshot, opened with a joke, not a spec.
This research-led model is a close cousin of the educator engine we mapped in the Amanda Natividad playbook, his SparkToro colleague and Zero Click Marketing co-author, and it is the template most marketing teams should study: own a data set, lead with the finding, and let the citations do the selling.
Your 30-day challenge
Run the playbook for a month. Trade opinions for evidence, one pillar at a time.
- Days 1-2: List every number only you have (your product data, a poll, a client result)
- Days 3-4: Post your most surprising stat, headline in line one, with the source named
- Days 5-7: Record a 60-second video explaining what the number means for the reader
- Days 8-9: Name a popular narrative and answer it with your data ('Nope, here's why')
- Days 10-11: State one belief about your industry as a plain declaration
- Days 12-14: Grade one of your past predictions right or wrong, in public
- Days 15-17: Amplify another researcher's finding, credited by name
- Days 18-19: Turn one comment thread into a follow-up post
- Days 20-21: Launch or update something, opened with a joke, framed by the problem
- Days 22-24: Publish a second data drop that builds on week 1's
- Days 25-27: Reshare your best study for the people who missed it
- Days 28-30: Review which posts drove comments, not just likes, and do more of those
Want the cadence without shooting and writing every post from scratch? That is exactly what CaptureFlow's content agent automates, and you can see what it costs on the pricing page.
The metrics to track weekly
| Metric | Benchmark to aim for |
|---|---|
| Comments per post | 40+ |
| Comment-to-reaction ratio | 15%+ |
| Posting cadence | 3+ per week |
| Original data points shared per month | 2+ |
| Collaborators credited per month | 3+ |
| Saves and shares on research posts | Trending up |
The takeaways
- 01Own the data. Rand's biggest posts lead with original research: the 68% zero-click study earned 1,459 reactions, a State of Search debunk earned 1,037.
- 02Optimize for conversation, not likes. His 21% comment-to-reaction ratio is more than 3x the LinkedIn norm.
- 03Lead with the finding. His first line is the headline stat or the flat declaration, never a warm-up.
- 04Show your face. 53% of his posts are short talking-head videos, which is what makes a data account feel human.
- 05Credit everyone. Naming Similarweb, Datos, and peers turns each post into shared authority, not a solo flex.
- 06Take a side. The data earns trust; the conviction against big tech and AI hype earns loyalty.
Frequently asked questions
- How did Rand Fishkin grow his LinkedIn following?
- By publishing original research (zero-click search data, State of Search reports, AI-consistency studies) and leading each post with the headline number, about 3.6 times a week. Across 100 recent posts he averaged 341 reactions and 73 comments each, and grew past 211K followers.
- What kind of post performs best for Rand Fishkin?
- Original research drops that open with 'NEW Research' and a surprising stat. His top post, that 68% of Google searches now end without a click, earned 1,459 reactions, and a State of Search debunk earned 1,037.
- How often does Rand Fishkin post, and what makes his engagement unusual?
- About 3.6 times a week, almost entirely on weekdays. His standout metric is a 21% comment-to-reaction ratio, more than 3x the ~6% LinkedIn norm, because his data and his contrarian takes drive discussion, not just likes. He is also unusually video-heavy, with 53% of his posts to camera.
- How do you apply this playbook without spending hours a week?
- Batch-capture your data and lessons, then let a content agent draft in your voice. CaptureFlow turns one 5-minute capture into a week of native posts across platforms, so you can hold the cadence without writing and shooting every post from scratch.
