Kyle Poyar is most useful for practical B2B growth, go-to-market, pricing, and signal-based outbound guidance backed by research and examples.
Best for
B2B SaaS growth tooling brands seeking sponsored research or playbooks on signal-based outbound and AI-native GTM.
Not for
AI SDR vendors wanting high-volume cold outreach or claims that automated cold email beats every channel.
Key takeaways
Pricing plans now go stale within about six months, so pricing needs a standing system.
Fix existing pricing before switching to usage- or outcome-based models, which can complicate forecasting.
The best channel depends on company size, so no single ranking applies to everyone.
Check first: Confirm audience demographics and recent performance on signal-based outbound, AI-native GTM, and pricing placements.
Main ideas
Pricing plans now go stale within about six months, so pricing needs a standing system · Fix the pricing you already have before switching to usage- or outcome-based models · Pricing is a positioning exercise, not just a number
Audience
90k+ Growth Unhinged newsletter subscribers · 300 B2B teams/leaders State of B2B GTM survey respondents
Kyle Poyar writes and advises on growth, go-to-market strategy, and pricing for B2B software and AI companies. As founder of Growth Unhinged, he turns research and company examples into practical guidance for teams deciding how to grow, reach buyers, and charge for their products.
Poyar connects broad market patterns to specific choices a team can test.
In research with Maja Voje involving 300 B2B leaders, he compares the reported performance of go-to-market channels and shows how priorities can differ by company size.
His breakdown of buying signals goes further than listing survey results: it suggests plays for combining a company’s own customer data with external signals.
A champion-tracking example shows how that might work in practice, including waiting for a relevant moment before contacting a former customer.
His pricing advice is similarly grounded in tradeoffs: usage- and outcome-based models may appeal, but can make forecasting and sales compensation harder, so smaller changes to an existing model may be a better starting point.
Across their posts, Kyle Poyar makes a consistent case that little in B2B go-to-market stays settled for long: pricing plans expire faster than annual planning cycles, channel rankings change with company size, and the motions that work pair first-party data with automation instead of replacing one with the other.
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The recurring shape of the argument is a barbell — deep relationships at one end, serious AI leverage at the other — with the broad, undifferentiated middle as the place companies stall. The posts mix original survey research run with partners, close reading of public documents such as the Anthropic S-1, and named practitioner examples.
Pricing plans now go stale within about six months, so pricing needs a standing system
Kyle Poyar argues that pricing used to hold for 18 to 24 months and can now be out of date within six, which makes a one-off repricing project the wrong response.
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The method they recommend is a continuous loop: keep collecting fresh evidence on what customers value, treat call recordings as the best real-time source, extract themes monthly with an AI skill, and watch for changes rather than waiting for the next review. They point to Salesforce being on its fifth AI pricing model in under two years, and to Anthropic overhauling enterprise pricing by lowering per-seat prices, embracing usage-based pricing at API rates, and testing Claude Code on the Max plan only, which drew backlash.
Their close reading of Anthropic's S-1 picks out the least-discussed part: pricing gets its own risk factor, including language about changing pricing models and about possible outcome- or task-based pricing. On the advisory side, they summarize nine months advising more than 20 Series A to D software and AI founders and recommend running a monthly extraction over call recordings to spot shifts in pricing and customer value.
The Anthropic analysis treats pricing instability as new enough to be a live risk for a company of that size, where the earlier advice framed the same six-month decay as a founder planning problem.
Fix the pricing you already have before switching to usage- or outcome-based models
Kyle Poyar argues that usage- and outcome-based pricing has become fashionable — investors now push portfolio companies to "get in the token path" — but that it carries real costs: harder forecasting, weaker predictability, and sales compensation headaches.
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Hybrid pricing gets too complicated to explain, and seat pricing limits expansion revenue. The advice is to start with smaller changes to pricing and enablement, and to treat credit and token pricing as heading toward commoditization as buyers swing toward cost optimization and ROI.
They compare pricing models on the market: Anthropic's mix is roughly 80% consumption revenue against 20% subscriptions, with enterprise customers still carrying minimum spend commitments and annual or multi-year terms; OpenAI has tested outcome-based pricing with select enterprise customers; and Cognition introduced a guarantee to fund up to $10 million of usage until AI delivers real engineering value.
Pricing is a positioning exercise, not just a number
A repeated claim across the pricing material is that pricing tells a story about who a product is for and why it beats the alternative, so pricing choices are also messaging choices.
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That framing leaves an open question Kyle Poyar returns to: whether customers want to pay for intelligence or for the work that intelligence delivers.
They describe Anthropic's "pay-for-intelligence" label as clever positioning, and examine how the company measures itself with run-rate revenue — trailing 28-day consumption times 13, plus monthly subscription fees times 12 — a window short enough to swing with holidays and vacation periods.
Work at one end of the barbell: exceptional relationships or exceptional AI, because the middle stalls
The summary line Kyle Poyar repeats across the channel research is that there are two ways to win — being exceptional at relationships and being exceptional at AI — and that the space in between is where companies get stuck.
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The tiering follows from that: relationship-heavy motions and AI search sit at the top, while generic automation sits at the bottom.
The 2026 channel scorecard, produced with Maja Voje from a survey of 300 B2B leaders and mapped on a popularity-versus-impact grid, puts network and introductions, intimate events such as executive dinners, and AI search (AEO) in the top tier. PR and agentic campaigns, meaning AI SDRs, fall to the bottom, with cold outreach and cold calling in the tier above them.
The best channel depends on company size, so no single ranking applies to everyone
Kyle Poyar argues that channel advice has to be read against company stage, ARR, and deal size, which is why the report splits its data rather than publishing one leaderboard.
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A channel that leads for a small company can be the wrong bet at scale, and vice versa.
Network and introductions stay a top channel only up to about $50 million ARR.
Digital ads were the most popular channel among companies above $50 million ARR, rising from third to first over a year, with AI-native companies shifting budget from Google toward Meta.
Founder LinkedIn posting works best below $50 million ARR, newsletters and editorial content suit $5,000 to $50,000 ACVs, and large conferences dipped year over year.
Signals are widely used but shallow; combine first-party data and let agents stack them
Kyle Poyar treats signal-based outreach as the buzziest term in GTM while pointing out that teams act on a narrow set of signals.
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The most common are content engagement, website visits, and product usage; third-party signals such as champion job moves, hiring activity, leadership changes, company news, and technology changes lag well behind, even though a stack refresh can be the clearest sign a company is buying. Their conclusion is that agents suit scanning target lists for stacked signals and suggesting plays, and that the most defensible plays combine data only you have with outside data about when and why to reach out.
The champion-tracking play published with Clay, carrying a partner hashtag, starts from known champions, executive buyers, and power users on closed-won accounts in the CRM, has an agent monitor them continuously, flags a job change, then deliberately waits 30 days or until a job requisition appears on the person's new team.
Tier-one contacts go to a rep for outreach across phone, LinkedIn, and email over 7 to 10 days; tier-two contacts are automated.
Other starter plays they name are reactivating closed-lost deals after leadership or technology changes, de-anonymizing visitors to high-value pages and targeting their buying groups with ads, and converting product users into enterprise pipeline.
Across the year the gap they emphasize shifts from which signals teams use to who should act on them, with AI agents proposed as the mechanism for spotting several signals stacking on one account.
For AI products, churn is a see-you-later rather than a goodbye
Kyle Poyar reports that about 10% of churners at AI-native companies come back within 12 months, and half of those returns happen within 60 days of cancelling.
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The implication is that retention work should be designed around return: audit the cancellation flow for dark patterns that could close the door, run win-back sequences at day 1, 30, and 60, use intent signals for reactivation rather than only acquisition, and make returning one click by preserving the customer's workspace, data, settings, and integrations.
The figures come from ChartMogul, where Kyle Poyar has been an analyst-in-residence, using aggregated data from 8.9 million customer purchases across 3,990 private software and AI companies. They compare the pattern to their own return to apps like Lovable, and link a fuller report covering seat and plan upgrades.
Without product-messaging fit you will never have product-market fit
Kyle Poyar complains that every homepage sounds the same and that AI has made already boring positioning worse.
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Their recommended fix is to hold the company's context in one place — an AI project containing call transcripts, customer stories, sales objections, competitive alternatives, the reason for repositioning, the language to move away from, and the company's voice — then layer trusted positioning frameworks with your own notes on top, produce two foundational documents covering value drivers and language, write the homepage first, test it on real people, get a fresh outside opinion, and roll the new positioning out everywhere.
The case study is Melissa Kwan, co-founder of eWebinar, who spent five months repositioning the company.
Time on the website rose 50% right away, sales objections fell, and eWebinar closed a first enterprise deal at $40,000 per year.
Kwan sent her COO to a conference to test the messaging on real prospects, and Carole Boutet recommended a better tagline and other changes.
Kyle Poyar names April Dunford's Obviously Awesome and Fletch by Anthony and Rob as the frameworks to start from, and notes a newsletter sponsor.
Brand partnerships are now the economics behind independent B2B research and creators
Kyle Poyar argues that B2B creators are niche practitioners whose platforms are newsletters, LinkedIn, and communities, and that brands should diversify across them rather than concentrate spend.
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Newsletters come out ahead because people actually read them, the ad arrives in the creator's voice, and no algorithm sits in the way.
The price of a collaboration scales with audience size, landing the first deal is easy, and renewals are where most creators and brands go wrong.
The audience conditions for good results are ICP fit, an engaged audience that actually sees the ad, and a compelling offer, with webinars and content working well; creators typically land in brand marketing and expand in growth marketing.
Kyle Poyar reports that brand partnerships drove 55% of revenue over the past 12 months and became the biggest line in a seven-figure solo business, which they say they never planned. Writing with Tony Varghese and Luke MccGwire of beehiiv, whose ad network has paid writers $37 million, they give price bands: under 2,500 subscribers is too early for real ad revenue, 2,500 to 10,000 suits programmatic ads bought across many creators, 10,000 to 40,000 supports direct sales or agencies at $1,000 to $5,000 per collaboration, and 40,000-plus reaches $5,000 to $15,000 per collaboration and $20,000 to $100,000 per month, often sold out three or more months ahead.
The same posture shows up in how the research is funded: the State of B2B GTM report and summit are released free with named presenting, performance, data, and silver partners.
This is the fastest way to see what Kyle Poyar is best known for: turning a survey of 300 B2B software and AI companies into a decision tool rather than a list.
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Start here if you want to know which channels are producing pipeline now and where the ranking shifts with company size.
Kyle Poyar and Maja Voje surveyed 300 B2B leaders and placed each channel on a popularity-versus-impact grid.
Network and introductions sit in the top tier but stop being a leading channel above $50M ARR; intimate events like executive dinners stay high-ROI; AI search (AEO) had the largest year-over-year growth.
Signal-based outbound, SEO, and founder LinkedIn posting fill the second tier, with founder posting best below $50M ARR.
Cold email and cold calling fall to the third tier, and PR and agentic campaigns (AI SDRs) sit at the bottom.
The post closes on the idea that relationship-led and AI-led motions both work, and the middle ground is where companies stall.
For brands planning a campaign
A sponsored update to the same survey is a strong collaboration shape: the product appears inside the signal-based workflow the data already ranks highly, and deal-size or ARR splits give the audience a reason to read the sponsor's version.
If you want the source behind the signal-based outbound talk, this is it.
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It answers which buying signals teams act on today, and it shows the gap between what is common and what is still underused.
Asked which signals they act on, respondents mostly named content engagement (52%), website visits (42%), and product usage (40%).
Third-party signals lag: social activity (30%), champion job moves (28%), hiring activity (25%), leadership changes (24%), company news and events (17%), and technology changes (14%), even though a stack refresh can be the clearest sign a company is buying.
Kyle Poyar draws three conclusions: AI agents are well suited to scanning target lists for stacked signals and suggesting plays; the most defensible plays combine first-party data (customers, champions, product usage) with third-party data; and four starter plays are champion job-change tracking, reactivating closed-lost deals after leadership or tech changes, de-anonymizing high-value page visitors and targeting their buying groups with ads, and converting product users into enterprise pipeline.
For brands planning a campaign
This is the natural anchor for a sponsored research or playbook collaboration: the brief's product can be shown at the agent step that scans and stacks signals, with the survey data supplying the credibility and the four starter plays supplying the demo workflow.
This is a worked example of signal-based outbound, from a practitioner who both advises and runs these motions.
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Read it if you want to see what 'signal-based' means in practice rather than as a slogan.
The post contrasts two versions of champion tracking.
The old version: see a job-change announcement on LinkedIn, immediately ask for a meeting, keep chasing for a week, give up.
The better version: always-on automated monitoring, with sequencing that deliberately waits.
The steps are to identify known champions, executive buyers, and power users on closed-won accounts from the CRM; have an agent monitor them continuously; flag a job-change signal; wait 30 days or until a job requisition appears on the person's new team; then send tier-one contacts to a rep for outreach across phone, LinkedIn connection, email, and LinkedIn message over 7-10 days, and automate tier-two contacts.
Kyle Poyar adds that messages land better when they reference exact usage data or past interactions, and that the play can extend to contacts who knew the product at their old company.
The post carries a partner hashtag for Clay.
For brands planning a campaign
The structure is reusable as a sponsored playbook: a named workflow, numbered steps, and a deliberate reason for each step, with the sponsor's product placed at the monitoring and signal-detection step rather than bolted on at the end.
This answers the budget question directly: what B2B creator sponsorships cost and where they work.
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It is unusual because the numbers come from the creator's own revenue and from an ad network's payout data.
Kyle Poyar states that brand partnerships drove 55% of revenue over the past 12 months and are now the largest line in a seven-figure solo business.
The post, written with Tony Varghese and Luke MccGwire of beehiiv, whose ad network has paid writers $37M, reports that B2B brands pay creators $1-15k per collaboration and that landing the first deal is easier than renewing.
It argues B2B creators are niche practitioners whose platforms are newsletters, LinkedIn, and communities; that newsletters are the best channel because readers actually read them and the ad arrives in the creator's voice; and it gives price bands by audience size: under 2,500 subscribers is too early for real ad revenue, 2,500-10k suits programmatic ads, 10k-40k supports direct sales or agencies at $1-5k per collaboration, and 40k+ reaches $5-15k per collaboration and $20-100k per month, often sold out three or more months ahead.
It names the conditions for best results: ICP fit, an engaged audience that sees the ad, and a compelling offer, with webinars and content working well.
For brands planning a campaign
This is the clearest evidence that Kyle Poyar takes brand work and reports on its economics openly, which makes a sponsored research or playbook collaboration a natural fit for a growth tooling vendor rather than an intrusion.
Start here if you care about pricing rather than channel strategy.
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It shows the practical side of Kyle Poyar's work: five pieces of advice grounded in named companies and a repeated client pattern.
Kyle Poyar writes that in nine months he advised 20+ Series A-D software and AI founders on pricing and monetization, and gives five Q4 recommendations.
Revisit pricing every six months rather than every 18, because Salesforce is on its fifth AI pricing model in under two years.
Build a system for fresh data, using call recordings as the real-time source, extracting themes with a Claude skill run monthly, and watching for changes.
Fix current pricing before pivoting to usage- or outcome-based models, which bring forecasting, predictability, and sales-comp problems, while hybrid pricing gets too complicated to explain and seat pricing limits expansion.
Treat credit and token pricing as heading toward commoditization.
And track whether bleeding-edge pricing experiments actually work.
Pricing, they argue, is ultimately a positioning exercise about who the product is for and why it beats the alternative.
The post also promotes After Tokens 2026 in San Francisco on November 10, hosted by Stigg.
For brands planning a campaign
A pricing or monetization vendor gets a concrete, credible hook: the monthly call-recording analysis and the six-month revisit cadence are both sponsor-able workflow steps with measurable outputs.
This shows the analytical register Kyle Poyar uses outside the newsletter: picking the least-covered part of a widely discussed document and explaining why it matters.
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Read it if you want evidence of close reading rather than summary.
Kyle Poyar highlights the part of Anthropic's S-1 filing least discussed: pricing gets its own risk factor.
Four points follow.
The filing says pricing models may change, and the post notes Anthropic overhauled enterprise pricing this year, lowering per-seat prices toward usage-based API rates and testing Claude Code on the Max plan only, which drew backlash; pricing models that used to last 18-24 months can now go stale within six.
The filing mentions possible alternative pricing such as outcome- or task-based models, which fits a shift from tokenmaxxing to ROImaxxing, with OpenAI testing outcome-based pricing and Cognition offering a productivity guarantee funding up to $10 million of usage.
Consumption revenue is about 80% of Anthropic's total against 20% from subscriptions, described as a pay-for-intelligence model, leaving open the question of whether customers pay for intelligence or the work it delivers.
Finally, ARR is recalculated as run-rate revenue from trailing 28-day consumption times 13 plus monthly subscription fees times 12, a short window that will swing with holidays and vacations.
For brands planning a campaign
For a SaaS metrics or finance-sponsoring brand, this demonstrates the kind of topic Kyle Poyar will analyze in depth, and the fair-value accounting angle is an easy sponsored-research extension.
Read this to see how Kyle Poyar turns a private client conversation into a repeatable method.
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It is the clearest example of the teaching format the profile describes.
The post opens with a complaint about identical homepages and AI making positioning worse, then reports on Melissa Kwan, co-founder of eWebinar, who spent five months repositioning the whole company.
Results so far: time on the website up 50% immediately, fewer sales objections, and a first enterprise deal at $40k per year.
Kyle Poyar lays out seven steps to copy: build an AI project holding everything about the company and its customers (call transcripts, customer stories, objections, alternatives, the reason for repositioning, language to avoid, voice); add trusted positioning frameworks with your own notes, naming April Dunford's Obviously Awesome and Fletch by Anthony and Rob; produce two foundational documents, a top-10 value driver list and a positioning and language guide; write the homepage first; test it on real people, as Melissa Kwan did by sending her COO to a conference; get an outside expert, in this case Carole Boutet, who recommended a better tagline; and roll the new positioning out everywhere.
It closes on 'without product-messaging fit, you'll never have product-market fit.' The post notes a sponsor for the newsletter issue.
For brands planning a campaign
Workshops, template packs, and tools for building a company 'AI brain' are an obvious sponsored format here, and the before-and-after metrics give a sponsor a measurable promise.
This answers a retention question with data rather than opinion: whether cancelled AI customers return, and how fast.
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Read it if you want to see how Kyle Poyar uses a data partner's dataset.
Kyle Poyar reports, from work as an analyst-in-residence at ChartMogul, that about 10% of churners at AI-native companies return within 12 months, and half of those come back within 60 days of cancelling.
The dataset is aggregated from 8.9 million customer purchases across 3,990 private software and AI companies.
Four actions follow: audit the cancellation flow for dark patterns that could close the door on reactivation; run win-back campaigns with a sequence at day 1, 30, and 60 after cancellation; use intent signals such as website visits, reopened emails, new teammates, and activity in a connected integration for reactivation rather than only acquisition; and make returning one click by preserving the workspace, data, settings, and integrations.
The post links the full report for more on seat and plan upgrades.
For brands planning a campaign
Retention and lifecycle tooling vendors get a defensible data hook: the 10% return figure and the 60-day window are concrete enough to anchor a sponsored report or benchmark.
Pricing strategy and monetization for software and AI2
Founder-led sales, events, and GTM community2
Retention and win-back for AI products1
Positioning and messaging1
Creator brand partnerships and newsletter economics1
Pricing strategy and monetization for software and AI
Kyle Poyar advises Series A-D software and AI founders on pricing and monetization.
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Poyar says pricing used to be revisited every 18 months but can now be outdated within six months, points to Salesforce being on its fifth AI pricing model in under two years, and recommends a monthly system to extract pricing themes from call recordings.
A separate post analyzes Anthropic's S-1 pricing risk factor, including usage-based pricing, outcome-based pricing, and consumption revenue.
Poyar warns usage- and outcome-based pricing creates forecasting, predictability, and sales-comp headaches, and that hybrid pricing can become too complicated to explain.
Poyar recommends building a Claude skill to extract themes from call recordings once per month and looking for deltas; fix current pricing before pivoting entirely.
Poyar notes credit and token pricing is on a path toward commoditization and that smaller changes to pricing and enablement can go a long way.
For brands planning a campaign
A growth tooling company could sponsor pricing or monetization research using Poyar's survey and analysis format, or a playbook showing how its product surfaces pricing signals from customer conversations.
Poyar co-produces the State of B2B GTM report with Maja Voje, based on a survey of 300 B2B software and AI companies.
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The 2026 report ranks channels on popularity and impact: S-tier network and intros, intimate events, and AI search or AEO; A-tier signal-based outbound, SEO, and founder LinkedIn posting; C-tier cold outreach, cold calling, and B2B creators; F-tier PR and AI SDRs. Poyar says teams are betting on AEO, signal-based outreach, intimate events, and LinkedIn posting for 2027.
Poyar surveys 300 B2B leaders, maps channels on a two-by-two, splits data by deal size and ARR, and releases the report free with partners.
For brands planning a campaign
A brand can sponsor the research or a channel-specific cut, or use the report format to position its product in a buyer's annual planning.
Poyar argues signals tell who is ready to buy, when to reach them, and how to persuade them.
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Poyar reports that GTM teams act most on content engagement at 52%, website visits at 42%, and product usage at 40%, with less maturity around social activity, champion movements, hiring, leadership changes, company news, and tech changes.
Poyar recommends combining first-party data with third-party signals.
A Clay champion-tracking play identifies known champions on closed-won accounts via CRM, monitors with Clay Audiences, flags job changes, waits 30 days or until a new job req is posted, then sequences outreach across phone, LinkedIn, and email.
Use CRM first-party data, Clay Audiences, and automated monitoring; for Tier 1 audiences send to a rep, and for Tier 2 automate outreach.
For brands planning a campaign
A signal-based outbound product could sponsor a concrete playbook or workflow demo that follows this structure, showing the product inside a champion-tracking or signal-stacking motion.
Poyar reports AEO had the biggest year-over-year increase in adoption of any channel tested.
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Digital ads were the most popular channel among companies above $50 million ARR, with AI-natives shifting budget from Google toward Meta. Poyar says AI Overviews squeeze Google inventory, branded search is still important, and ChatGPT ads had only 3% current adoption but 39% of B2B companies plan to try them in 2027.
Poyar draws on the 300-company survey and commentary from Keith Putnam-Delaney of Primer.
Poyar notes AI answers have not eaten into branded search terms as much yet.
For brands planning a campaign
A brand can sponsor an AEO or paid-media benchmark, or a playbook on testing ChatGPT ads and branded search before budgets shift.
Poyar reports AI-natives see 10% of churners return within 12 months, and half of win-backs happen within 60 days of cancellation.
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The data comes from ChartMogul, where Poyar has been an Analyst-in-Residence, covering 8.9 million customer purchases across 3,990 private software and AI companies. Poyar recommends auditing cancellation flows for dark patterns, running win-back sequences at day 1, 30, and 60, bringing intent signals into reactivation, and making reactivation one click.
Poyar uses aggregated ChartMogul data and recommends lifecycle email, retargeting, offers, and preserved workspace, data, settings, and integrations.
For brands planning a campaign
A retention or customer-success tool could sponsor research or a win-back playbook that uses Poyar's data-led format and product workflow.
Poyar criticizes homepages that sound the same and says AI has made boring positioning worse.
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Poyar profiles Melissa Kwan's repositioning of eWebinar over five months: time on site rose 50%, sales objections fell, and eWebinar closed a first enterprise deal at $40k per year. Poyar's recommended process includes an AI project with call transcripts, customer stories, objections, competitive alternatives, and voice; trusted positioning frameworks; two foundational documents; writing the homepage first; testing on real people; getting an outside expert; and rolling out everywhere.
Use an AI project as a positioning brain, draft with AI but review, test homepage messaging on real prospects, and bring in an outside expert.
For brands planning a campaign
A positioning or messaging product could sponsor a playbook or case study that shows the product as the AI brain or testing layer in this workflow.
Creator brand partnerships and newsletter economics
Poyar says brand partnerships drove 55% of revenue over 12 months and became the biggest line in a seven-figure solo business.
Read more
Poyar and beehiiv report B2B brands pay creators $1-15k per collaboration; newsletters are the best B2B creator channel; pricing scales with audience size; and the best results combine ICP fit, an engaged audience, and a compelling offer. Poyar advises brands to diversify their creator mix and says creators land in brand marketing and expand in growth marketing.
Poyar worked with Tony Varghese and Luke MccGwire at beehiiv, whose Ad Network has paid writers $37M.
Under 2,500 subscribers is too early for real ad revenue; 2,500-10k suits programmatic ads; 10k-40k fits direct sales or agencies at $1-5k per collaboration; 40k+ can command $5-15k per collaboration.
For brands planning a campaign
A brand can use Poyar's own newsletter as a partnership channel or sponsor a creator-partnership benchmark.
Poyar and Maja Voje host a free online summit for the State of B2B GTM report with 15 speakers from Lovable, Clay, Vercel, Granola, SpaceXAI, and other companies.
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Sessions cover founder-led sales, data science for GTM, RevOps and GTM engineering, paid, and marketing. Poyar also promotes After Tokens 2026 in San Francisco on November 10, hosted by Stigg, with speakers from OpenRouter, OpenAI, Clay, Databricks, and Temporal.
Poyar uses co-hosted summits and in-person events to distribute research and convene GTM leaders.
For brands planning a campaign
A brand can sponsor an event, a field report, or a speaking slot connected to Poyar's research audience.
Kyle Poyar's own posts document one business he owns — Growth Unhinged — and an open commercial layer around it: a sponsored newsletter issue, a paid-partnership post for Clay, and a 2026 GTM research report he co-produced with named presenting, data, performance, and silver partners.
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He also states an Analyst-in-Residence role at ChartMogul and a content collaboration with beehiiv's ad-network team, and he is listed as a speaker at an event hosted by Stigg. Poyar says brand partnerships supplied 55% of his revenue over the past year and are now the largest line in a seven-figure solo business, but the reviewed posts do not name those sponsors beyond the relationships listed here.
Growth Unhinged
Owned business
Poyar is the founder of Growth Unhinged, the pricing and growth newsletter he promotes across the reviewed posts.
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He describes a readership of 90k+ subscribers, and says brand partnerships are now the biggest line in his seven-figure solo business.
Poyar publishes AI-native GTM plays built on Clay, including a champion-tracking workflow that watches closed-won accounts for job changes and sequences outreach by tier.
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The post carries a partner hashtag disclosing the relationship.
Poyar says he teamed up with Tony Varghese and Luke MccGwire from beehiiv, whose ad network has paid writers $37M, to write a deep dive on B2B creator brand partnerships and what makes renewals work.
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The posts state the collaboration but not its commercial terms.
Original disclosure
I teamed up with Tony Varghese & Luke MccGwire from beehiiv since they see the brand partner sides I don't.
Salesforge.ai is listed as a silver partner of the 2026 State of B2B GTM report, and its CEO Frank Sondors appears in the report's RevOps and GTM engineering session.
Passionfroot is listed as a silver partner of the 2026 State of B2B GTM report, and its CEO Jennifer Phan appears in the founder-led sales field reports.
Civic Technologies is listed as a silver partner of the 2026 State of B2B GTM report, and its chief growth officer Brad Webb appears in the founder-led sales field reports.
Stigg hosts After Tokens 2026 in San Francisco on November 10, and Poyar says he will speak there alongside named speakers from OpenRouter, OpenAI, Clay, Databricks, and Temporal.
Kyle Poyar writes about B2B go-to-market with a focus on pricing, annual channel research, and signal-based outreach.
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A reader can start with the State of B2B GTM research for the broad view of what channels and signals teams report using, then move to the pricing posts for a close look at how software and AI companies are changing how they charge.
The AI-native GTM plays and retention posts show how Kyle Poyar turns research into specific workflows, while the positioning and creator-partnership posts cover messaging and the business model behind independent B2B research.
The work is data-led, often built from surveys or aggregated platform data, and it usually ends with a practical set of steps.
Rami Zwebti writes about AI-era go-to-market, distribution, and the Clay and Lusha data layer used to find accounts and time outreach.
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That overlaps with Kyle Poyar's work on signal-based outreach, AI-native GTM plays, and the argument that distribution and timing decide which AI companies win.
Rami Zwebti's posts lean more toward agent reliability, permissions, and vendor integration announcements, while Kyle Poyar's work includes original survey research, pricing analysis, and creator-business economics.
Yaniv Mazor builds and writes about end-to-end go-to-market systems: paid acquisition, the signal layer, routing, outbound, and attribution.
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Kyle Poyar covers similar ground in the signal-based outbound and AI-native GTM posts, especially the idea that the best plays combine first-party data with outside signals.
Yaniv Mazor writes from an agency and systems-engineering perspective, often about attribution and CRM connections, while Kyle Poyar writes more as a researcher and analyst using surveys, platform data, and public documents.
Michael Nisbet writes about enterprise sales craft, deal loss, champion management, and the gap between activity and results.
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That connects to Kyle Poyar's coverage of outbound, signals, and the relationship end of the GTM barbell.
Michael Nisbet is a reflective sales practitioner focused on deal psychology and loss reviews, while Kyle Poyar is a research-led analyst focused on channel data, pricing, and AI-native GTM plays.
Placement decision: Kyle Poyar is a credible test for a sponsored research or playbook collaboration aimed at B2B SaaS growth and GTM leaders, especially for signal-based outbound and AI-native GTM workflows.
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The evidence shows reach and topical fit: their LinkedIn account snapshot records about 115,553 followers as of 8 October 2026, and a post describes Growth Unhinged as reaching 90k+ subscribers.
Their posts consistently address growth, GTM, pricing, and AI-native selling for B2B software and AI companies.
The State of B2B GTM research they run with Maja Voje asks 300 B2B teams and leaders about channel and signal priorities, which indicates the work is built for that operator audience.
The gap is composition: the supplied material does not measure the audience by job title, seniority, employer, industry, geography, or company size.
Before buying, request a recent audience survey or approved LinkedIn follower demographics showing the share of growth, GTM, RevOps, founder, and marketing leaders, plus company size and region, and ask for recent performance on signal-based outbound, AI-native GTM, and pricing posts or newsletter placements.
Treat the 300-respondent surveys as evidence of the research audience Kyle Poyar can convene, not as a demographic breakdown of their followers.
Growth Unhinged newsletter subscribers
90k+
Kyle Poyar, LinkedIn post · 2026-10-08
State of B2B GTM survey respondents
300 B2B teams/leaders
Kyle Poyar and Maja Voje, State of B2B GTM research · 2026-10-01
Kyle Poyar's documented partnership activity centers on Growth Unhinged, the newsletter and research brand Kyle Poyar runs, and on paid placement inside B2B go-to-market research.
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The clearest first-person figure is Kyle Poyar's own disclosure that brand partnerships drove 55% of revenue over a 12-month period, described as the biggest line in a seven-figure solo business.
The disclosed collaborations are of two main kinds: newsletter sponsorships read inside Growth Unhinged, and named partner roles in the annual State of B2B GTM research report and its launch event.
Kyle Poyar also publishes vendor play content, such as an AI-native champion-tracking play built in Clay, marked with the #claypartner hashtag; the hashtag alone does not establish paid terms, and no rate was stated for that work.
Kyle Poyar describes the B2B creator deal range as $1,000 to $15,000 per collaboration and prices newsletter placements by subscriber count: 2,500 to 10,000 subscribers suits programmatic buys across many creators, 10,000 to 40,000 suits direct sales at roughly $1,000 to $5,000 per collaboration, and 40,000-plus supports $5,000 to $15,000 per collaboration at $20,000 to $100,000 per month, booked three or more months ahead.
No official media kit, sponsor page, or published rate card appears in the reviewed material, so inquiry routing is unverified.
This section covers only the partnership formats and terms the reviewed posts actually show; it does not confirm availability, current pricing, or that Kyle Poyar accepts any particular deal.
Growth Unhinged newsletter sponsorship
Buyer requirement
Plan for an in-newsletter placement written in Kyle Poyar's own voice, with no algorithm between the ad and the reader.
Growth Unhinged is described as reaching 90,000-plus subscribers on a weekly cadence.
Expect pricing to scale with audience size, using the disclosed creator tiers: 10,000 to 40,000 subscribers at roughly $1,000 to $5,000 per collaboration, and 40,000-plus at $5,000 to $15,000 per collaboration.
Budget lead time: the largest audience band is described as sold out three or more months ahead.
Sponsored research and report partnership
Buyer requirement
Bring budget and data to co-fund a named research report rather than a single post.
The State of B2B GTM report credits partners by role: a presenting partner that also built the report site, an exclusive data partner, an exclusive performance partner, and silver partners.
Buyer planning needs to cover survey distribution, data contribution, and a public partner credit, plus a launch moment such as the free online summit with an external speaker line-up.
Event and webinar co-production
Buyer requirement
Fund or host a live moment where Kyle Poyar speaks and the brand is attached to the session.
Reviewed examples include a hosted conference invite push for After Tokens 2026 and an on-demand webinar about what AI agents think about pricing, recorded with a sponsor.
The buyer supplies the event or webinar platform, a compatible audience, and a registration route; expect the promotion to run through Kyle Poyar's own newsletter and LinkedIn posts.
Vendor play content and put-your-product-in-a-workflow pieces
Buyer requirement
Expect a documented, repeatable GTM workflow that uses the buyer's tool step by step, written for practitioners rather than as an ad.
The reviewed example walks through champion tracking in Clay, including audience monitoring, job-change signals, wait timing, and tiered outreach.
Note that a partner hashtag on such a post does not by itself establish paid terms, so any commercial arrangement must be set explicitly in the brief.
Brief: a B2B SaaS growth tooling company wants to reach growth and GTM leaders with practical, signal-based outbound plays, through a sponsored research or playbook collaboration that puts its product inside a concrete AI-native workflow.
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Decision: yes.
Kyle Poyar is a strong fit for this brief for four reasons that come from the reviewed work rather than from reach alone.
First, the topic is the center of Poyar's current research.
The 2026 State of B2B GTM report, run with Maja Voje across 300 B2B software and AI companies, puts signal-based outbound in its second tier and names it as one of the channels teams are betting on for 2027, and a companion post reports which signals teams actually act on: content engagement (52%), website visits (42%), product usage (40%), with champion job moves (28%), hiring (25%), leadership changes (24%) and technology changes (14%) far less used.
That gap between common and underused signals is a ready-made argument for a tooling sponsor.
Second, Poyar already publishes the exact format this brief needs.
The Clay champion-tracking post walks through CRM audience building, continuous monitoring, a job-change flag, a deliberate 30-day or job-requisition wait, and tiered outreach across phone, LinkedIn and email over 7-10 days, with the partner product sitting at the monitoring and signal-detection step rather than bolted on at the end.
A sponsor can buy that structure rather than invent it.
Third, the audience is the buyer.
Growth Unhinged is described as reaching 90,000-plus subscribers, the survey convenes 300 B2B leaders, and the LinkedIn account carried 115,553 followers as of 8 October 2026.
Fourth, the commercial formats already exist: paid placement read in Poyar's own voice inside the newsletter, a named partner role in the State of B2B GTM report and its launch summit, event or webinar co-production, and vendor play content.
Two conditions belong in the brief.
The strongest signal-based material sits with early-stage audiences: network and introductions stop being a top channel above $50M ARR and founder LinkedIn posting works best below that line, so a sponsor chasing enterprise accounts should expect the data to push toward intimate events and AEO instead.
And the supplied evidence contains no audience demographics by job title, seniority, company size or region, so the buyer should request a recent audience survey before committing budget.
When to choose a specialist
Brief: an AI SDR vendor wants a high-volume cold outreach programme, buying a set number of sponsored posts that carry a 'book a meeting' offer, with payment tied to meetings booked, and asks Poyar to argue that automated cold email beats every other channel.
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Decision: no.
The problem is not reach or topic adjacency, it is that the requested message contradicts what Poyar has already published to exactly this audience.
The 2026 GTM channel scorecard places cold outreach by email and LinkedIn in the third tier, cold calling near the bottom, and agentic campaigns, explicitly AI SDRs, in the bottom tier alongside PR.
A campaign that asks this creator to argue the opposite of their own current research damages the sponsor: the audience came for survey-backed judgments about which channels work, and a paid post that reverses one of those judgments reads as advertising that the creator does not believe.
The requested deal shape conflicts as well.
The champion-tracking play states that automation does not have to mean spray-and-pray AI slop but can be precise, first-party, signal-based targeting, which is the opposite of a volume cold-email programme paid per meeting.
The evidence also gives no basis for pricing or performance commitments: there is no media kit, sponsor page or published rate card, and the only rates disclosed are Poyar's own general creator benchmarks of roughly $1,000-$5,000 per collaboration at 10,000-40,000 subscribers and $5,000-$15,000 at 40,000-plus, with brand partnerships described as already accounting for 55% of Poyar's revenue.
A pay-per-meeting structure would be built on terms the reviewed material never confirms.
A cold-outreach vendor is not shut out permanently, but it should change the offer rather than the creator: fund a benchmark on where cold outreach still works, or a playbook on combining first-party signals with outbound, and accept the published ranking instead of buying a reversal of it.
A worked campaign example
Angle: sponsor the next signal study and attach a signal-stacking playbook, with the product shown at the agent step.
Shape it as a named partner position on the annual State of B2B GTM research, running alongside the free launch summit, rather than as a set of standalone posts.
Use the survey's own structure, which the existing report already proves out: ask the same 300-leader audience which signals they act on, keep the popularity-versus-impact grid, and add a cut split by deal size and ARR so the sponsor's version answers the question a reader actually has, which signals deserve budget at their company size.
Then deliver a companion playbook in the champion-tracking format: identify champions, executive buyers and power users on closed-won accounts from the CRM, monitor them continuously, flag a job change or a new requisition on the person's team, wait deliberately, and sequence tier-one contacts to a rep while automating tier-two.
The sponsor's product appears at the monitoring and signal-detection step, which is where the reviewed Clay play places its partner and where a signal tool has a genuine role.
Publishing targets: one or more newsletter issues in Poyar's own voice, a LinkedIn post carrying the key chart, and a summit session, with the workbook and the report cut hosted so readers can use them outside the article.
Give the playbook one measurable promise taken from the research, such as shifting spend from content-engagement and website-visit signals toward the underused champion-movement and hiring signals, and report back after launch.
What the sponsor buys is a specific, sourced argument that its product category deserves a line in a reader's 2027 plan, made by someone whose own data currently ranks the alternative cold-outreach approach lower.
Two honest limits to agree up front: the audience size bands Poyar publishes mean a 90,000-subscriber readership implies the top pricing tier and lead times of three months or more for the largest slots, and no verified audience demographic breakdown was supplied, so the sponsor should confirm the growth-leader share before scaling the buy.
Choose Yaniv Mazor if the campaign needs to show how signal-based outbound fits into a broader, measurable revenue system.
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In the reviewed post, Mazor describes connecting paid acquisition, signals, routing, outbound and attribution, then argues that teams should trace leads through to closed-won before deciding where to spend. That makes a better match for a sponsor whose product links data or channels across the GTM stack, rather than one centered on a specific champion-tracking play.
The example is about end-to-end systems and measurement, not a step-by-step workflow for identifying and sequencing former champions. Kyle Poyar’s Clay post gives the sponsor a more direct product-in-workflow demonstration: monitor known champions, wait for a relevant trigger, then tailor outreach.
Choose Rami Zwebti if the campaign’s main question is how to make AI agents safe and dependable once they can act across business systems.
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The reviewed post emphasizes least-privilege access, checkpoints, verification after consequential actions and recovery from stalled work. That would suit a sponsor selling agent controls or operational reliability, or a brief focused on the risks of automating GTM actions.
Those posts address agent reliability, not how to find the right account or buyer, choose a signal, or run an outbound sequence. For a growth-tooling sponsor that needs a concrete signal-based prospecting play, Poyar’s champion-tracking example is more directly aligned.
Choose Michael Nisbet if the campaign is aimed at enterprise sales teams and its central promise is helping sellers manage complex deals.
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His posts describe multi-threading, finding the economic buyer, recognizing silence as a warning sign and learning from losses. That gives a sponsor a human, deal-level angle on what happens after outreach creates an opportunity.
The reviewed examples focus on sales execution and deal retrospectives, not signal discovery or automated prospecting. Poyar’s work is the closer fit when the product needs to appear in a practical workflow that detects a buying signal and prompts relevant outreach.
This page draws on 11 full LinkedIn posts by Kyle Poyar, reviewed in October 2026, and a LinkedIn account snapshot observed on 8 October 2026.
The posts cover the 2026 State of B2B GTM survey research with Maja Voje, pricing analysis, signal-based outbound and a champion-tracking play, AI search and paid ads, retention and win-back, positioning, creator partnerships, and events.
The topics and similar-creators section also draws on two posts each from Rami Zwebti, Yaniv Mazor, and Michael Nisbet.
Not reviewed: the Growth Unhinged newsletter archive, the full State of B2B GTM report, webinar or event recordings, and any video or audio, so statements about those rest on the posts that describe them.
Brand relationships come from the reviewed posts; a partner hashtag is reported as written and does not establish payment.
Recent engagement
Across their last 9 LinkedIn posts, the median post got 173 reactions and 101 comments. Checked 2026-11-02.
