Growth Unhinged

New data from 6,525 SaaS startups: It’s easier to get into Harvard or Stanford than it is to reach $25 million ARR within 10 years. Let that sink in. I'm pumped to announce that I've partnered up with ChartMogul as their Analyst-in-Residence (fancy title, huh?), which means I get to dig into their 🔥 dataset on subscription metrics going back 10+ years & share it with you. What I found: - Almost half of software startups do eventually make it to $1 million ARR after they’ve started monetizing -- if they’re willing to stick around.* - One-in-five make it to $5 million ARR. - One-in-ten make it to $10 million ARR. Yet just one out of every fifty startups makes it to $25 million ARR within 10 years. The odds of doing this (2.3%) are lower than getting accepted into Harvard or Stanford (3.6% acceptance rate). If you’ve done it, I hope you take a moment to celebrate. 97.7% of your peers didn’t get this far. (And that doesn’t even factor in the scores of startups that never start monetizing a product in the first place!) *Worth mentioning is that this data is based on a 10-year period, meaning it looks at companies that launched & started monetizing in 2016 or earlier. The full report will include data on more recent cohorts! --- We're wrapping up our first deep dive report called "The odds of making it". Subscribe to Growth Unhinged if you want to be the first to see it next week: https://lnkd.in/exTbjKaM So excited to partner with Nick Franklin, Sara Archer, Thomas Anastaselos & the whole ChartMogul crew! It's rare to find folks who like to geek out about SaaS metrics as much as I do 😁

ChatGPT just hit 800 million weekly active users, up from 500 million in March. AI discovery is the fastest-growing channel to reach your customers. But more than that, it forces us to rethink buyer journeys for AI discovery. The team at Docebo told me AI discovery now accounts for 12.7% of their high-intent leads, up 429% (!) from last year. They're doing this with one dedicated team member (Valeriia) plus an assist from AI tools like AirOps & XFunnel. Here's the thing: ChatGPT leads don't look like SEO or referral leads. They show up ready to buy, either going to your website directly (*after* they've made a decision) or searching for your brand on Google. Branded search now accounts for 85% (!) of Docebo's search traffic -- meaning 85% who come from Google already know about the company. ▶️ The old buyer journey: Problem awareness > feature research > vendor comparison > brand selection. ▶️ The new buyer journey: AI-assisted research > network validation > direct brand search > selection. Read more in Growth Unhinged about what this means & how to get more pipeline from AI search: https://lnkd.in/ee2wKTbR The TL;DR: 1. Measure your AI search performance through self-reported attribution, branded search traffic, and share-of-voice in AI queries. 2. Late-funnel SEO is the foundation for great answer engine optimization (AEO). 3. The dirty work of AEO has to get done: updating, formatting, and structuring content for LLMs. 4. You can see tangible AEO results with a modern tech stack. #aeo #ai #seo

Introducing my first podcast: Mostly Growth! 🎧 Mostly Growth is the (mostly) serious podcast for anyone who cares about startup growth. Like a good millennial, I listen to *a lot* of podcasts. But I struggle to find business podcasts that are both insightful and entertaining. Too many are run-of-the-mill interviews with a rotating cast of the same dozen guests repeating their talking points. The Mostly Growth pod is here to change that. It’s myself, my favorite CFO CJ Gustafson (from Mostly Metrics), and producer Ben Hillman unpacking the most interesting happenings in tech and startups. A taste of what we jammed on this week: ➡️ Is T2D3 dead? ➡️ SEO's collapse and AEO's rise ➡️ Y-axis crimes of mass proportions (👀 Ramp) ➡️ The brutal job market for new grads ➡️ Hospital bed Linkedin photos ➡️ The story of Bob's Barricades (and his curious pricing model) You can check it out on YouTube, Apple, or Spotify (links below). Your support would mean the world to us and convince the algorithms we’re legit. Hope you enjoy it 🙏🙏 - KP --- 🎧 Listen on Apple: https://lnkd.in/ehPCnsHE 🎧 Listen on Spotify: https://lnkd.in/eirHMj8E 📺 Watch on YouTube: https://lnkd.in/eBTKrCUW

GTM is changing so quickly, it feels impossible to keep up. Here's a handy, 100% serious glossary to stay in-the-know ⤵ What did I miss? --- PS: If you 😍 GTM, please take the 7-minute 2025 State of GTM survey from yours truly & Maja Voje. Pitch in here: https://lnkd.in/ecdQAyFJ #gtm #marketing #startups #satire

The ability to build & manage AI agents is quickly becoming a core skill for everyone. Here are 5 of my favorite marketing use cases for AI agents -- with templates ⤵️ 1️⃣ Lead scoring & qualification Lead scoring is part art, part science. You want to enrich fields via 3rd party data, but also bring in form data & some human(like) judgement. Turns out AI agents are great at this -- and you can add a human-in-the-loop escalation via Slack when the classification isn't clear. See the workflow here: https://lnkd.in/eeDrZrdv 2️⃣ Lifecycle emails Traditional lifecycle emails are pretty mid (did I say that right?!). But AI agents can track new customers, analyze interesting ones & then automatically draft personalized emails suggesting next steps. See the workflow here: https://lnkd.in/eeDrZrdv 3️⃣ Competitor tracking Everyone is racing to write comparative content for AI search. This content needs accurate, real-time info on competitors including features, pricing info, reviews & more (otherwise you'll get penalized). Turns out that AI is pretty great at scraping text and sending alerts when there are significant updates. See the workflow here: https://lnkd.in/eeDrZrdv 4️⃣ Content research You need to stay on track with what's trending with your audience & key influencers in your space. But nobody has time to monitor dozens of LinkedIn profiles & Substacks. You can get an AI agent to do the research for you & write a report on the top-performing themes. See the workflow here: https://lnkd.in/eeDrZrdv 5️⃣ LinkedIn coaching AI models have spiky intelligence. While they struggle with things that seem easy, they're surprisingly brilliant at things like analysis & coaching. You can create your own PhD-level coach to improve your LinkedIn game with tips on what's going well & what to change. See the workflow here: https://lnkd.in/eeDrZrdv --- Shoutout to Jacob Bank from Relay.app for sharing his 🔥insights. If you've found other cool use cases for AI agents, please share them in the comments (I'm working on a new piece for Growth Unhinged). #ai #marketing #aiagents

What is the future of GTM motions? AI will take over the repetitive, derivative busywork. Humans will own trust, creativity, and relationships. That was the core of my conversations with Emily Kramer (ex-Asana, now MKT1) and Jacob Bank (ex-Google, now Relay app) in September. Jacob explained how Relay’s GTM is entirely education-driven: show people what’s possible with AI, inspire them, and make it easier to use. He is betting on founder-led growth. 0 people working in marketing. It is all him and AI agents. Emily added: When AI floods the market with generic marketing plans, the most creative marketing will win again - just like in the Mad Men era. WoW 🥃 We agreed on 3 shifts already happening: 1️⃣ Paid channels (Google, LinkedIn, Meta) are too expensive for bootstrapped startups. 2️⃣ People don’t buy from feature checklists - they buy from trusted messengers and signals of credibility. 3️⃣ GTM motions are moving toward relationship-driven, zero-click transactions where the product may not even be used by a human. But my goal is to get even more insights into the state of GTM in 2025. That's why Kyle Poyar (Growth Unhinged) and I have joined forces to prepare a survey - so we can share the most up-to-date data with you next month. 🙏 Please fill in our survey here: https://lnkd.in/d3WEpynF Thanks for your support!

Fyxer was a sleepy virtual EA firm from 2016-2022. Then they pivoted to AI, aspiring to be Cursor for email. And growth has since *exploded* — from $1 to $17M ARR in the last 8 months. Some quick stats on Fyxer AI: 👉 Founded & run by two brothers, Archie and Richard. 👉 Raised a $10M Series A led by Harry at 20VC with backing from Marc Benioff & Lenny. Then raised a $30M Series B led by Madrona only 6 months later. 👉 This is real ARR -- 90% of paying users stick around >3 months & net revenue retention (NRR) is 150%+ in most cohorts (🤯). Today's Growth Unhinged unpacks how they did it. Read the story here: https://lnkd.in/ejF7Vxte Fyxer's consumer to enterprise AI expansion playbook in 5 steps: Step 1: Make the product dead simple for everyday people. The onboarding process feels almost non-existent; once you’ve integrated your calendar, it's essentially ready to go. There are no complicated shortcuts. But you can easily adapt it to your preferences by toggling a slider or adding a few extra sentences to the style prompt. Step 2: Turn to influencers to get initial traction. From zero to $1M ARR, Fyxer’s biggest growth lever was definitively non-sexy. It was Archie sliding into DMs and begging people to post on LinkedIn. Each influencer post attracted about 20-30 new signups. (Btw, there wasn’t much correlation between an influencer’s size and their impact.) Step 3: Go big with consumer performance marketing. Performance marketing now drives about half of Fyxer’s new growth. Their ad cadence is relentless. Two-week sprints, 200+ ads live at any given moment, 100-150 new creative variations every sprint. This is powered by (lots) of AI tools incl. ChatGPT, Claude, ReelFarm, Arcads AI, ElevenLabs, HeyGen, Synthesia, Motion & Getdot.ai. Step 4: Refine GTM around business users and enterprise expansion. Work email signups are worth 10x more than personal emails. The top KPI for performance marketing: cost-per-work-email. Step 5: Continuously improve AI and reactivate users along the way. One of the biggest reasons why initial Fyxer signups didn’t convert was that the AI wasn’t quite good enough yet. The next unlock is re-activating these users. They're doing it with trial re-starts & a human-seeming email “from” a founder (Archie in particular). Hope you find this useful 🙏 --- Today's newsletter is supported by Metronome. They're running a 🔥 webinar on how Snowflake built their Monetization Operating Model (link in comments). #ai #genai #startup

What's the right go-to-market (GTM) motion for your product? ⤵️ When you look at a table like this (from the brilliant Maja Voje), GTM looks pretty straightforward. There are 7 main types of motions. You just need to figure out what's best for your product & scale it. The reality is that GTM in 2025 is a bit of a 🗑️🔥. The tried-and-true channels don't work like before (👋 blogs, SEO, outbound emails). New channels aren't totally proven or are hard to scale (👋 AEO). And now we're supposed to figure out how to do this & master AI at the same time (😭). I want to bring objective data to the conversation. Real insights from real tech companies. And real nerds crunching the numbers (that's me!). 🚨 Introducing the first annual State of GTM survey, a collab between Growth Unhinged and Go-To-Market Strategist! Please take the survey here: https://lnkd.in/ecdQAyFJ The survey is ~7 mins according to Typeform. All data will be anonymized & reported on an aggregate level. And results will come out in October. THANK YOU for your support!! 🙏🙏 - Kyle & Maja #gtm #marketing #ai

Your mini-MBA: Master AI Monetization ⤵️ I've never seen monetization change as quickly as it's changing right now. There's a real shift from charging for *access* to charging for *work delivered* by a combination of software & AI. Here's your crash course to keep up -- and you can complete it over the weekend. 101 Level: Learn how AI is changing monetization models - Learn how to apply it: https://lnkd.in/ea5eTrVD 201 Level: Explore new benchmarks on AI monetization - The data comes from 240+ software and AI companies - Learn how to apply it: https://lnkd.in/ePsQJT6X 301 Level: Build an AI credit model - Example: Clay - Learn how to apply it: https://lnkd.in/edDCXget 401 Level: Apply a framework for AI agent pricing - Example: Harvey - Learn how to apply it: https://lnkd.in/ed8g68wh Case A: Outcome-based pricing - Example: Intercom - Learn how to apply it: https://lnkd.in/ezrHeUeJ Case B: Credit-based pricing - Example: Replit - Learn how to apply it: https://lnkd.in/eWauyG_A Hope it's more fun than a real MBA ✨ #ai #pricing #aimonetization