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

Six years ago, PLG was a choice.
Today, it is table stakes.

Recently, Brex published a list of the 50 fastest-growing software companies.
ALL of them have a PLG motion.

If you want to win in the SMB or Mid-Market space, you cannot survive without PLG in 2026.

What separates the winners is not whether they have PLG.
It is how strong their PLG motion is.

The best PLG motions showcase value in minutes and expand rapidly without adding headcount. Weak PLG motions get stuck in linear growth.

That is what I help founders fix 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

Signed up for 100+ SaaS products in the last 6 months. These are the 8 best examples of AI onboarding I’ve seen this year. Not hype, real AI used to onboard users in seconds.

Took a few hours to put the onboarding flows on a Figma board, with some notes covering exactly how these companies use AI to get users to value faster.

Here’s how they are using AI to cut time-to-value down to seconds 👇

1. Relay.app (Context > Content) 
Instead of asking 20 questions, Relay asks for your LinkedIn URL. The AI scans your profile and auto-configures your agents and workspace instantly.

2. Gamma (Execution > Guidance) 
Gamma doesn't teach you how to use the editor. It asks for a topic and generates a full slide deck for you in seconds. No more relying on "empty states."

3. Figma (Just-in-Time Education) 
Figma analyzes your behavior in the canvas. If you get stuck or pause too long, the AI suggests the specific plugin or feature you need right in that moment.

4. Zapier (Outcome > Templates) 
Templates have taken a back seat. Now, a Copilot ingests your desired outcome and builds the workflow for you. It uses your initial app selections to predict exactly which prompts you need first.

5. Notion (Conversational Setup) 
They replaced the static "welcome wizard" with an active AI chat. It uses natural language to configure your workspace behind the scenes.

6. Miro (Zero-Click Canvas) 
The first screen is a chatbot asking, "What are we working on?". It builds the board structure for you before you even learn the UI.

7. n8n (Teaching by Showing) 
The "Try an AI Workflow" option demonstrates a working example first, teaching you how to interact with the agent while giving you a feeling of immediate progress.

8. Instantly.ai (Embedded Support) 
While the main tour is traditional (tooltips), the real power is hidden inside. As you navigate, AI agents surface to handle complex setup tasks, proving you don't need to be "AI-Native" to be effective.

Onboarding is evolving.

→ From: Teaching users how to use your interface.
→ To: Teaching AI what the user wants to do.

Think I’m exaggerating? Watch your growth rate when competitors can activate users in seconds, while you do it in minutes.

I compiled screenshots of all 8 flows into a Figma Board so you can see exactly how they work. I’m also covering how to do AI onboarding in a live workshop with Mickey Alon next week (Jan 28).

Comment "AI Onboarding" below and I'll send you the link for both. 👇

#1 PLG Consultancy | 434+ clients, $1B+ self-serve revenue

AI is messing with SaaS Conversion Benchmarks across the board. It’s time to reset expectations.

We’re teaming up with Kyle Poyar @ Growth Unhinged and ChartMogul to build the 2026 SaaS Conversion Benchmarks.

There’s too much anecdotal advice, and not enough hard data.

We want to know what is actually happening with trials and conversion right now. From real SaaS companies.

Please help us aggregate the largest dataset on free-to-paid conversion rates so we can stop guessing what great looks like for SaaS products.

It takes 4 minutes.
It is fully anonymous.

We publish the aggregate results in February.

You can contribute here: https://lnkd.in/ed2VjKGz

THANK YOU for your support 🙏

Founder @ Drilldown | Custom-designed business dashboards for B2B SaaS that deliver insights in one click, eliminating the need for complex spreadsheets in just 60 days.

We help B2B SaaS teams build an owned data system - so metrics align across the organization and growth decisions are based on evidence.

This might resonate:

As B2B SaaS companies scale, it becomes harder to understand on where growth comes from and what to do next.

Most teams already have dashboards, data integrations, and the technical ability to build new ones. 

Yet they still struggle to agree on what metrics mean, explain drivers of revenue, or produce reliable forecasts.

What you need is one set of accurate, explainable numbers that your team can rely on.

Our work focuses on the data system underneath dashboards: the definitions, structure, and logic that determine whether analytics can support decision-making at scale.

If you’re trying to make decisions based on data but the numbers don’t line up, this explains why: https://thomasvarekamp.substack.com/p/you-have-dashboards-why-are-decisions

Thomas Varekamp

2025 in a nutshell (the good, the neutral and the bad):

The bad:

- marketing & positioning is still a challenge.
- life was very unbalanced → more stress.
- wasted a ton of money (but learned a lot).

The neutral:

- moved to Amsterdam (for a couple of months).
- got a bigger office (which we closed down).
- updated our website (like 20+ times).

The good:

- helped 11 companies with data & analytics.
- revenue grew by +30%.
- hired first full-time employee.
- got clearer on what I want from life.
- grew as a person (I feel more peaceful).

All in all, 2025 was a good year. But my goal is to make 2026 even better.

So this is what we will be doing in 2026:

Change 1: we’re becoming remote-first.

I want to travel more and have more control over my time. Everyone that works for Drilldown can work wherever they want.

Change 2: a new offer.

A recurring theme from clients was how much they valued that their teams could own and maintain the systems after we were done.

Our new offer is much more focused on transferring knowledge, not creating dependency.

Change 3: make things simpler.

From now on we're only going to focus on:

- 1 client profile: B2B SaaS leaders >$1M+ ARR.
- 1 outcome: helping you see what’s driving ARR.

I genuinely feel the right foundations are in place to make 2026 our best year ever, both personally and professionally.

Huge thanks to everyone we worked with in 2025.

Hope to build more together next year!

Best,
Thomas

ps. here’s a photo from my first surfing lesson, a fitting way to wrap up a year of trying new things, failing, and learning :)

Drilldown | Helping B2B SaaS leaders regain control by turning data into direction.

I spent €20,000 building a data platform. This year, I’m shutting it down.

Most of our clients use Dutch software to run their business.

To build great dashboards, we need to pull this data out of the tools.

The common data extraction tools do not support these sources. 

So I decided to build our own extraction tool called the Drilldown Extraction Hub: 

- fixed price.
- unlimited data.
- custom support.

On paper, it made sense. 

We onboarded a few customers and within a short time it was doing around €400 MRR. But then sucky part started.

Connectors started breaking, APIs changed, edge cases appeared…

Everything required constant custom work.

Problem #1: data extraction is not an easy one-time build. You need permanent maintenance.

Problem #2: Instead of fully focusing on what we are actually good at (analytics for B2B SaaS), I was now splitting attention between client work and engineering work. 

Not good.

By the end of last year, I made the call to stop. 

We still support existing customers, but for new clients we use existing tools.

My big lesson: focus is extremely important. Especially in the stages we’re at (~€220k revenue / year).

Keep building!

Most people know HeyReach.io as the LinkedIn tool that sprinted to $10M ARR in 29 months. Few know the real story of how they started.

- before the 2,900 monthly trial signups.
- before the 4,000+ paying customers.
- before the 8-figure revenue.

---

The founders actually began their journey in Macedonia, an place they described as "prehistoric" for startups.

Their first venture, Howitzer, burned through $500k as they fell into the "White Knight" trap: trying to hire expensive managers to fix their problems.

It didn't work. 

So they decided to build a product where they owned the growth. 

That was v0 of HeyReach.io.

---

In 2023, with only 3 months of cash left, they negotiated a life-saving AppSumo deal at 2:00 AM in a club.

That cash injection allowed them to answer the question:

“𝘏𝘰𝘸 𝘥𝘰 𝘺𝘰𝘶 𝘴𝘤𝘢𝘭𝘦 𝘰𝘶𝘵𝘳𝘦𝘢𝘤𝘩 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 𝘳𝘦𝘭𝘺𝘪𝘯𝘨 𝘰𝘯 𝘱𝘢𝘪𝘥 𝘢𝘥𝘴?”

They positioned themselves as the LinkedIn layer of the modern sales stack (Clay + Smartlead + HeyReach). 

They exploded.

Between 2023 and 2025 they saw:

→ 10-15% Month-over-Month growth.
→ A surge to 2,900+ free trials per month.

Then, data visibility became the bottleneck.

Stripe couldn't handle the complexity of their growth and caused internal chaos. 

The CEO would see $20k in "churn" and demand answers, while it was just failed payments that would be recovered the next day. 

As Ilija Stojkovski put it: 

"𝘞𝘦 𝘸𝘦𝘳𝘦 𝘭𝘪𝘬𝘦 𝘧𝘳𝘪𝘦𝘯𝘥𝘴 𝘩𝘢𝘷𝘪𝘯𝘨 𝘢 𝘤𝘩𝘢𝘵 𝘣𝘶𝘵 𝘥𝘪𝘴𝘤𝘶𝘴𝘴𝘪𝘯𝘨 𝘤𝘰𝘮𝘱𝘭𝘦𝘵𝘦𝘭𝘺 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵 𝘵𝘰𝘱𝘪𝘤𝘴. 𝘕𝘰 𝘰𝘯𝘦 𝘩𝘢𝘥 𝘵𝘩𝘦 𝘴𝘢𝘮𝘦 𝘴𝘰𝘶𝘳𝘤𝘦 𝘰𝘧 𝘵𝘳𝘶𝘵𝘩."

---

That's when we crossed paths and helped them at Drilldown to build a custom data infrastructure in just 4 weeks.

We moved them off generic dashboards and built a single source of truth.

In December 2025, HeyReach.io officially crossed $10M ARR.

They’ve proven that world-class tech companies can be built from anywhere.

My 8 unpopular opinions on B2B SaaS analytics in 2026:

1. CAC:LTV is mostly a vanity metric. It tells you where you stand, not what to fix.  Cool for VCs, useless for your team. 

2. Averages are your enemy. Segment your data to find your biggest growth levers.

3. Having 100% accurate numbers is overrated. Knowing trends over time and direction is more important.

4. If you are spending $5k/month on data tools before having product-market fit, you're being robbed.

5. Using "Free" open-source tools is EXPENSIVE. Buying a managed service is almost always cheaper than your hourly rate spent debugging.

6. Founders: if you're spending Saturdays fixing broken pipelines, that is a failure of prioritization. Your time is worth more than a Weld subscription.

7. AI writes great code, but it will never 100% understand your business. Humans must be responsible for insights.

8. Context > code. The hardest part of data is not technical. It's understanding how the business works.

Data analytics can have huge impact on your business, both positive and negative.

Good luck!

Currently digging in some B2B SaaS that used analytics to reach $1B+ valuation. Did you know this about Slack?

Slack began as an internal tool for a failing gaming company. 

When they analyzed the retention data, they found a specific “magic number”: 2,000 messages. 

Teams with fewer than 2,000 messages were likely to churn, but teams that crossed this had a 93% retention rate.

They engineered their entire onboarding and “freemium” limit around this metric. 

The free plan allows users to view 10,000 messages, giving teams enough space to blow past the 2,000-message “hook” before hitting a paywall.

This retention engineering helped Slack become the fastest-growing enterprise app in history, eventually acquired by Salesforce for $27.7 billion.

Crazy stuff

After building the same dashboards, data structures, and metrics 10+ times, I stopped rebuilding them from scratch.

I call this the SaaS intelligence system. 

It gives every SaaS company the things they should already have, but often don’t:

1. accurate, real-time ARR waterfalls everyone agrees on.
2. dashboards to go from revenue → accounts → users.
3. metric dictionaries so definitions don’t live in people’s heads.

That alone removes hours of manual work and discussions.

But the real benefit comes from what this foundation enables:

1. data enrichment → reach better users.
2. marketing attribution → acquire more of them.
3. customer health scoring → reduce churn.

It gives leadership and operators a reliable system to make decisions, without needing a big data team for maintenance.

The cool part: everything runs from the data warehouse.

That’s what the SaaS Intelligence System is: the core data setup most B2B SaaS teams end up rebuilding anyway.

I put together a short doc showing the 5 dashboards we recommend for $2M–$10M B2B SaaS teams. 

This is what that foundation looks like in practice.

taplio

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The Battle

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