Wes Bush

Product-led coach helping founders scale from 6 to 8-figures in product-led revenue. Author of the bestselling book, Product-Led Growth.

Over the last 8 years, I’ve worked hands-on with 400+ SaaS companies, helping them unlock $1B+ in self-serve revenue through Product-Led Growth (PLG).

Yet, right now, the failure rate for product-led companies is still far too high.

I’m on a mission to change that because I believe the world needs more product-led companies where you can try before you buy. 

This approach builds trust faster than any sales pitch ever could—after all, 97% of buyers prefer it. But, let’s be real, PLG isn’t easy.

That’s why I’m here to help in three ways:

➡️ Is PLG is right for you?

I wrote the bestselling book, Product-Led Growth: How to Build a Product That Sells Itself, to help you determine if PLG is the right strategy for your business. 

You can read it for free at ProductLed.com/Book—my treat!

➡️ What’s the best approach to scale up PLG?

After two years of research and working with hundreds of companies, I discovered the 9 essential elements that separate PLG success stories from the rest. 

I break it all down in The Product-Led Playbook.

You can grab a copy at ProductLed.com/Playbook, or watch my free masterclass to see the entire process in action: ProductLed.com/Masterclass

➡️ Ready to scale up?

If you’re ready to scale and need hands-on help, our ProductLed Implementers are here. They aren't consultants—they are experienced PLG operators who want to roll up their sleeves and work alongside your team to help you address your biggest growth bottleneck, whether that's getting more users to sign up, upgrade, or get to value.

Since we only work with a handful of clients at a time and guarantee growth, you must apply to work with us at ProductLed.com

Let’s turn your product into a growth engine and scale your business the product-led way. 🚀

CEO & Founder

We help you build a successful product-led business.

Start with our free ProductLed Masterclass 👉 productled.com

There’s ZERO chance companies like Cursor, Lovable or any AI-native SaaS can scale at this lightning pace without PLG.

You can’t scale with AI alone. 

You need a strong product-led motion to power it.

Without a self-serve product experience and rapid time-to-value, these companies wouldn't be able to hit the growth rates we're seeing.

To put it simply,

AI is the rocket. PLG is the fuel.

Let’s look at the numbers…

Both Cursor and Lovable hit $100M ARR in under a year with explosive, largely through self-serve growth.

Could any sales-led SaaS company scale to $100M in under a year? Even with an elite outbound team?

No chance.

This kind of growth isn't possible without a product users can adopt immediately, a frictionless self-serve experience, and organic expansion loops.

AI removes friction from the product experience through faster workflows, better outputs, more intuitive interfaces. But PLG removes friction from everything else: onboarding, adoption, expansion, and monetization.

You need both.

AI-native companies that build without a PLG motion will hit the same growth ceiling that every other sales-led SaaS has hit. They'll need more reps, longer sales cycles, and heavier implementation.

All the old problems that PLG was designed to solve.

AI creates the capability.

PLG creates the velocity.

#1 PLG Partner | We Scale (and Sometimes Buy) SaaS Businesses | $1B+ Self-Serve Revenue Generated For Our Clients

Founder @ Flow

Most SaaS companies don’t lose customers because of product. They never make it there in the first place because of crappy onboarding.

I’ve led marketing & growth at five SaaS scale-ups, and advised many more. Wherever I went, I saw the same pattern repeating itself: founders spending millions to acquire users, only to lose them in the first few clicks.

In 2022, I founded Flow to help B2B SaaS companies fix their onboarding gap, and turn trial users into loyal subscribers. Basically, my job is to speed-run users as quickly as possible to their first “aha” moment: that’s what really makes them stick.

Here’s how we do it:
- First we’re uncovering how users really experience your product (and where they drop off).
- Then we’re pinpointing onboarding friction that kills activation and conversions.
- Based on that, we build personalized onboarding flows across in-app, email, and beyond, using scalable low-code solutions.

Acquisition is expensive, retention is priceless - and onboarding is the bridge between the two. Our clients see faster activation, higher subscription rates, and less cancellations. They get users that stay, succeed, and become advocates.

If you’re leading a SaaS company and want your users to stick, I’d love to connect.

Jamie McDermott

A $5M ARR SaaS company I spoke with had almost no user analytics.

Let that sink in. Millions in revenue, but critical product decisions were being made in the dark.

This isn't a rare exception; it's a widespread problem. Teams are drowning in data but starving for insight because they don't track the right events, or worse, don't trust the data they have.

Without reliable metrics, you can't find your bottlenecks. You can't measure feature impact. You can't confidently build a roadmap.

𝗧𝗵𝗲 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗱𝗮𝘁𝗮 𝗰𝗵𝗮𝗼𝘀 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗮 𝗺𝗲𝘀𝘀𝘆 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱. 𝗜𝘁'𝘀 𝘀𝘁𝗮𝗹𝗹𝗲𝗱 𝗴𝗿𝗼𝘄𝘁𝗵.

To make your onboarding more valuable, do less for your customer.

It sounds counterintuitive. But doing everything for your customer isn't always a good thing.

In a recent client call, we mapped out their onboarding. It was thorough. The team handled everything: phone number setup, calendar configuration, contact list uploads. But I pointed out a hidden cost.

By automating these tasks 𝘧𝘰𝘳 the user, you're not just saving them time. You're potentially robbing them of their first 𝗮𝗵𝗮 𝗺𝗼𝗺𝗲𝗻𝘁.

That feeling of satisfaction when a user connects their own calendar and sees it sync perfectly? That's a powerful win. It builds confidence and momentum. When your team does it on the back end, the user misses that moment of discovery.

The takeaway is simple. Don't just build a product. Engineer the user's first success. Guide them to their own "aha moment" instead of claiming it for yourself.

That's how you turn a setup process into an activation engine.

Your perception of your onboarding is wrong.

We hear this from founders constantly: "Our onboarding is pretty simple. Most people get it." They believe it. But their customer support data tells a different story.

On a recent project, we analyzed thousands of support tickets for a client who felt their onboarding was straightforward. The data was screaming the opposite. Ticket after ticket mentioned confusion, frustration, and difficulty with the initial setup.

The founder's perception was based on anecdotal feedback. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝘄𝗮𝘀 𝗯𝘂𝗿𝗶𝗲𝗱 𝗶𝗻 𝘁𝗵𝗲𝗶𝗿 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘀𝘆𝘀𝘁𝗲𝗺.

This is a massive blind spot for SaaS companies. You can't rely on vibes or what you 𝘵𝘩𝘪𝘯𝘬 is happening. The unfiltered truth lives in the raw, unstructured data—your support chats, feedback surveys, and call transcripts.

That's where you find the real friction points killing your activation. Your customers are telling you exactly what's broken. You're just not listening in the right place.

Check out my thoughts on 'product tours'...



Thanks to the Chameleon team for letting me dig into their data.

You spent 3 weeks building the perfect product tour. 
Users spent 0.4 seconds dismissing it. 
Welcome to onboarding in 2025. 💀

Thanks to Jamie McDermott for putting together this great playbook 👇 
https://lnkd.in/dh7B62uk

The Hidden Metrics of Effective Product Tours | Chameleon

If your churn meetings feel like a game of hot potato, you’re not alone.

Too many leadership teams treat churn like a customer success problem. Easy target, right? But it's rarely just a CSM issue.

If your product is buggy, no amount of relationship-building will save you.

If you're selling to the wrong fit, no handoff deck fixes that.

If marketing promises things the product can't deliver, no QBR will make the disappointment go away.

And if your support is drowning in tickets, don’t expect a renewal, no matter how many check-ins you schedule.

Customer success can only patch so many holes. Most of the leaks start way upstream.

Retention is a mirror: it reflects every weakness in your funnel, your product, and your messaging.

If you want to move the needle, stop the blame game and start owning your slice of the problem. Product, sales, marketing, support, success - nobody gets a free pass.

Churn isn’t a department. It’s a symptom.

Treat the cause, not just the pain.

Stop prioritizing complex integrations. Find the most boring, repetitive task your user hates and automate it. That's your real product magic.

During a deep dive into a client's onboarding process, their Head of CS said something that cut through the noise:

"Automated workflows are definitely powerful with customers."

We'd been discussing complex EHR integrations and calendar setups. But her point was a reminder of what users 𝘵𝘳𝘶𝘭𝘺 value. It's not the technical connection itself. It's the magic of seeing a manual, time-consuming process simply disappear.

For their users, seeing a workflow trigger automatically based on an event in their system was the real "aha moment." It was the point where the product's value became tangible.

This is a critical lesson for prioritization.

Instead of getting lost in complex integrations, find the most painful manual task your user performs. Then, show them how your product makes it effortless. That's where you'll find the most powerful activation moments.

Here's our 3-step process for finding the biggest bottlenecks in any SaaS product.

You just need a system to find them.

We call it finding the bottleneck. Instead of guessing, we analyze everything to get a complete picture of the user journey.

Our process is simple but rigorous:

🔍 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝗤𝘂𝗮𝗹𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗗𝗮𝘁𝗮: We plug into customer support tickets, online reviews, and feedback surveys to understand user frustration in their own words.

📊 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗗𝗮𝘁𝗮: We connect to tools like Amplitude and Mixpanel to pinpoint exactly where users drop off in the onboarding flow.

💡 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝘁𝗵𝗲 𝗗𝗼𝘁𝘀: We combine both data sets to form a clear hypothesis. 𝘞𝘩𝘺 are users getting stuck, and what's the highest-impact fix?

𝗧𝗵𝗶𝘀 𝗶𝘀𝗻'𝘁 𝗮𝗯𝗼𝘂𝘁 𝗰𝗵𝗮𝘀𝗶𝗻𝗴 𝘀𝗵𝗶𝗻𝘆 𝗼𝗯𝗷𝗲𝗰𝘁𝘀. 𝗜𝘁'𝘀 𝗮𝗯𝗼𝘂𝘁 𝗮 𝗿𝗲𝗽𝗲𝗮𝘁𝗮𝗯𝗹𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 𝗳𝗼𝗿 𝘁𝘂𝗿𝗻𝗶𝗻𝗴 𝘂𝘀𝗲𝗿 𝗳𝗿𝗶𝗰𝘁𝗶𝗼𝗻 𝗶𝗻𝘁𝗼 𝗺𝗲𝗮𝘀𝘂𝗿𝗮𝗯𝗹𝗲 𝗴𝗿𝗼𝘄𝘁𝗵.

Sales Navigator

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🔥 66-67% of growth experiments fail at companies like Microsoft.

But it's not the ideas that suck.

I've audited 200+ failed experiments across SaaS companies. The pattern is always the same:

𝗧𝗵𝗲 𝗦𝗶𝗹𝗲𝗻𝘁 𝗞𝗶𝗹𝗹𝗲𝗿𝘀:
• No clear success criteria defined upfront
• Missing activation event definitions
• Zero interpretation rules for edge cases
• No timeline boundaries for decision-making

𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗼𝗿𝗸𝘀:

✅ 𝗛𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗶𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: "If we change X, then Y metric will improve by Z% because [user behavior assumption]"

✅ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗧𝗵𝗿𝗲𝘀𝗵𝗼𝗹𝗱𝘀: Define minimum detectable effect BEFORE you start

✅ 𝗔𝗰𝘁𝗶𝘃𝗮𝘁𝗶𝗼𝗻 𝗟𝗶𝗻𝗸𝗮𝗴𝗲: Connect every test to your core activation events

✅ 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗥𝘂𝗹𝗲𝘀: Pre-commit to what constitutes success, failure, and inconclusive

The companies that nail this? They turn experiments into predictable growth engines.

The ones that don't? They waste months on "promising" tests that lead nowhere.

𝗧𝗵𝗲 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Great ideas without decision frameworks are just expensive guesses.

What's your biggest experimentation blind spot? Drop it below 👇

Raw data doesn't drive decisions. Structure does. If your user research ends in a Word doc, you've failed.

You just finished 20 user interviews. Now what?

You're left with a mountain of transcripts and raw insights. This is a classic bottleneck. The research is done, but turning it into a clear, actionable plan that gets the whole team aligned is a project in itself.

Instead of writing a 50-page report no one will read, we translate research directly into visual frameworks. Here's the simple process we're using for a client right now:

- 𝗠𝗮𝗽 𝘁𝗵𝗲 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗝𝗼𝘂𝗿𝗻𝗲𝘆: Create a simple, visual map of the user's experience from awareness to activation.

- 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗝𝗼𝗯𝘀 𝘁𝗼 𝗯𝗲 𝗗𝗼𝗻𝗲: For each stage, pull out the core JTBD from your research. What is the user 𝘳𝘦𝘢𝘭𝘭𝘺 trying to accomplish?

- 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝘄𝗶𝘁𝗵 𝗮 𝗠𝗼𝗱𝗲𝗹: Use a framework like the Kano Model to categorize features into must-haves, performance-based, and delighters.

The output isn't a static document. It's a living FigJam board that becomes the foundation for the project, sparking conversation and driving the roadmap.

Stop writing reports. Start building shared understanding.

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The Battle

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