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

We asked 60,000 people: “who’s the best PLG operator you know?” 

and we researched who are (or were) behind the world’s best PLG companies (think early-days Slack, Notion, Miro, Etc.). 

Here are the results (2026 world rankings): 

#1 - Elena Verna
#2 - Giancarlo 'GC' Lionetti
#3 - Merci Victoria Grace
#4 - Melissa Tan
#5 - Wes Bush
#6 - Lauryn Motamedi
#7 - Laura Schaffer
#8 - Casey Winters
#9 - Jacob Bank
#10 - Kieran Flanagan
#11 - Leah Tharin
#12 - Ben Williams
#13 - Salvador Torres
#14 - Anton Osika
#15 - Carrie McMahon
#16 - Patrick Campbell
#17 - Esben Friis-Jensen
#18 - Ramli John
#19 - Bryan Ng
#20 - Kyle Parrish
#21 - Melissa Ross
#22 - Josh Sookman
#23 - Tommy Fink
#24 - Henrique Cruz
#25 - Casey Hill
#26 - Hila Qu 曲卉
#27 - David Barron
#28 - Mario Araujo
#29 - Kyle Poyar
#30 - Brian Balfour
#31 - Kate Syuma
#32 - Shaun Clowes
#33 - Meghan Gill
#34 - Michael T.
#35 - Shuo Wang
#36 - Eitan Helman
#37 - Raaz Herzberg
#38 - Shane Murphy-Reuter
#39 - Hiten Shah
#40 - Sam Crowell Richard
#41 - Jon Noronha
#42 - Etgar Bonar
#43 - Yaakov Carno
#44 - Aggelos Mouzakitis
#45 - Andrew Capland
#46 - Adam Fishman
#47 - Ravi Mehta
#48 - Jiaona "JZ" Zhang
#49 - Albert Cheng
#50 - Maor Shlomo
#51 - Francois Bondiguel
#52 - Sian Townsend
#53 - Brian de Haaff
#54 - Jules Walter
#55 - Amol Avasare
#56 - Arik Marmorstein
#57 - Dave Boyce
#58 - Sean Ellis
#59 - Rachel Hepworth
#60 - Jessica Gilmartin
#61 - Aaron Cort
#62 - Adam Robinson
#63 - Jason Fried
#64 - Alex Turnbull
#65 - Yasser Elsaid
#66 - Guillaume Moubeche
#67 - Nicolae Rusan
#68 - David Okuniev
#69 - Jan Oberhauser
#70 - Karim Atiyeh
#71 - Mickey Alon
#72 - David Barrett
#73 - Gary Brewer
#74 - James Hawkins
#75 - Nils Schneider
#76 - Daryna Kulya
#77 - Kurt Mackey
#78 - Koen Bok
#79 - Drew Banin
#80 - Patrick Thompson
#81 - Chris Bach
#82 - Melissa Kwan
#83 - John Foreman
#84 - Ryan Singer
#85 - Krithika Shankarraman
#86 - Pedro Magriço
#87 - Nick Chong
#88 - Harley Finkelstein
#89 - Hugh Molotsi
#90 - Ilan Rabinovitch
#91 - Jim Gochee
#92 - Neil Rahilly
#93 - Dylan Fox
#94 - Steffen Tjerrild
#95 - Ben Edelstein
#96 - Mauricio Idarraga
#97 - Carina Fonseca
#98 - Nick Rico
#99 - Fredo Tan
#100 - Rodrigo Fernandez
#101 - Justin Gallagher
#102 - Adam Jarczyn

Couldn’t tag everyone on this post. In the comments! 

Who do you know that’s not on this list, but should be? 

Let me know below 👇

Genspark AI reached $155M ARR in 10 months but I still got stuck getting to  value when I onboarded.

Here’s my full teardown of their PLG motion, and what I would change to get to $1B if I was in charge of self-serve growth 👇

DM me to get the full 10-minute Loom of me onboarding and giving feedback.

Oh, and Wen S. is coming on the pod. Stay tuned.

Reverse-engineering AI companies hitting $100M ARR ≤ 12 months

Genspark AI - PLG Teardown

Right now, founders have two choices.

One, they can pretend like they're living under a rock with their product, even if they have strong product-market fit right now. Or two, they can realize that product-market fit evolves faster than ever before with AI.

Let’s say you’re running a $45M business.

Growth is steady.
Churn is manageable.
Customers are happy.

On paper, everything looks solid.

But AI is compressing time.

If someone enters your category and delivers the same outcome in a fraction of the time, the equation changes fast.

The issue is → is your product still the fastest path to value?

That’s where the hard decision shows up.

Do you keep optimizing the current product?

Or do you build the version that makes your current product feel slow?

I’ll be direct: You should build the version that replaces you.

Design the AI-native experience that gets users to value dramatically faster.

Because if you don’t, someone else will.

And when they do, growth shifts quickly.

You’ll notice churn creeping up.
You’ll run experiments.
You’ll tweak onboarding.
You’ll adjust pricing.

But if the core workflow is slower, optimization won’t save you.

So the choice becomes simple.

Ultimately, these are the two choices you have to make:

1. Adapt or die: You must decide to disrupt yourself.
2. Be disrupted: Continue as you are and face the consequences.

That’s the decision.

I’m going to be blunt.

This was the best interview we’ve ever recorded.

Because Wen S. (COO + co-founder of Genspark AI) doesn’t talk in startup clichés.

He explains, in plain language, how a 50-person team hit $100M ARR in 9 months, then $155M ARR by month 10… with almost no marketing until after $100M.

Here are the ideas I can’t stop thinking about.

1) People want the job done. Period.

Wen said something that reframed the whole category for me:

People look for information because they need to finish something.

That’s why Genspark shifted the goal from “answer questions” to “finish work.”

2) Their “secret sauce” is boring, but effective: output quality.

Genspark put 99% of their energy into one thing: make the output so good you can ship it.

Work you can use right away.

That obsession is what made word-of-mouth do the heavy lifting early.

3) They refused to spend on marketing.

Most startups pour fuel on distribution early.

Genspark avoided ads on purpose.

Only after they crossed $100M ARR did they say: “Okay. This must be real. It’s time.”

4) They made a Super Bowl ad in 10 days (10x’d growth).

Yes, they ran a Super Bowl spot.

But the part that matters is they made it happen in ~10 days.

Script and creative generated using Genspark.
Shot fast.
Shipped fast.

Traffic jumped 10x overnight.

5) “Focus on one thing” is becoming bad advice.

In the old world, building multiple products meant multiplying teams and coordination.

In the AI-native world, you can reuse the same context across outputs.

People don’t want 12 tabs and 8 subscriptions. They want one place where context carries across everything.

6) How 50 people ship like 500.

Wen shared that 90%+ of their code is written by AI.

Instead of a classic org chart (frontend team, backend team, DevOps, design), they built a platform and kept ownership tight.

7) Why AI companies are hitting warp speed growth.

Adoption comes from two directions at once:

Bottom-up: individuals try it and get value immediately.
Top-down: leadership feels urgency and formalizes adoption.

If you aren't growing at warp speed, attend WARP Week from March 2nd to March 7th.

Save your spot: https://lnkd.in/gQfq4hYd

8) The real proof is revenue.

A consultant who used to spend weeks coordinating research and building decks now pays $25/month, gets the grunt work done in days, keeps more margin, and serves 5–6x more clients.

9) Their only advice to founders: obsess over the product.

If you have a great product, people will notice.

Stay paranoid. Keep shipping. Keep raising the quality bar.

That’s the game.

👉 Listen or watch the episode:
https://lnkd.in/geRJEhTk

“60 seconds to value? That’s impossible for my product.”

I hear this every time I talk about WARP.

Here’s what I tell them:

Cursor writes complex code in seconds.

Midjourney creates complex art in seconds.

Lovable builds entire applications in seconds.

These aren’t simple products. The difference is who does the work.

Old way: “You do the work and get X result.”

New way: “Tell me what you want done. Boom, it’s done.”

Even if you can’t hit 60 seconds today, what if you went from 3 days to 5 minutes?

That’s still a massive moat. And the window to capture it is now, while users are still actively trying new tools.

Wait until everyone has settled on their defaults and the cost of winning that same user goes up 10x.

That’s what we’re building in WARP Week.

Starts Monday. Link in comments.

I spoke with a $50M ARR founder yesterday.

He said something I haven’t stopped thinking about:

“We have product-market fit right now. But that’s PMF pre-AI.”

Let that sink in.

Most users aren’t deeply loyal.

They’re accepting the friction because there hasn’t been a dramatically better option.

If someone builds a tool that delivers the same outcome in 60 seconds instead of 30 minutes, switching becomes obvious.

And here’s the part founders don’t like to admit:

That company is being built right now.

Today.

Very likely by someone who understands your category inside out.

I’ve been studying what I call WARP speed companies.

The ones going from zero to $100M ARR in under 12 months.

They share a pattern.

Zero friction to value.

Users reach their first meaningful outcome in 60 seconds or less.

That’s the new bar for product-market fit in the AI era.

The question is no longer “Do people want this?”

It’s “How fast can they experience the outcome?”

Because speed to value is becoming the moat.

So the real question is simple.

If AI is going to compress your workflow, will you be the one compressing it?

Or will someone else?

10 months ago, Wen S. launched Genspark.

Today, it’s at $155M ARR with ~50 people.

For the first time, he shared exactly how they did it:

1. They didn’t build a better chatbot.

They rebuilt “work.”

Instead of answering questions, Genspark focuses on finishing tasks: decks, models, briefs, decisions.

2. They let individuals pull the product in.

Adoption started bottom-up.

Employees used it because it was immediately useful. Then leadership stepped in to formalize it.

3. They refused to spend on marketing until after $100M ARR.

No big ad budgets.

No artificial fuel.

If it grew, it had to be because the product earned it.

4. They made a Super Bowl ad in 10 days.

After product-market fit was obvious, they took a high-leverage swing.

Traffic jumped 10x overnight.

5. They built a 50-person team that ships like 500.

Over 90% of their code is AI-written.

Weekly releases.

70+ models orchestrated under the hood.

As Wen said, the entire team’s obsession is output quality.

Not features!

The formula is clear → Get users to real value fast. Make the output so good they can ship it. Keep raising the bar every week.

Individuals adopt.

Companies follow.

Growth compounds.

That’s what AI-era product-market fit looks like.

🎧 Listen to the full breakdown: https://lnkd.in/geRJEhTk

Growing MRR of B2B SaaS companies via affiliate marketing | Growth Manager @ Reditus | T500 | Reforge '24 🤘

Hi there, welcome to my profile!

Currently building Signalbase, a real-time signal provider helping GTM and RevOps teams be the first to reach out when a signal occurs.

Because let’s face it, creating firmographic-first lists and hoping for intent later simply doesn’t work anymore. Prospecting isn’t a filtering exercise as 95% of your market is not ready to buy, but signals can help you see who is about to be.

We help teams spot real intent signals before anyone else does and plug those signals straight into your existing GTM stack, so your workflows trigger when the market’s ready, not when it’s too late.

You will want to use Signalbase if: 

1. You want a healthy pipeline with active companies
2. You seek verified signals to feed your GTM workflows
3. You don't have time to learn Clay or the money to hire someone to do it for you

Ready to discover some accounts with real-time intent? 

Give Signalbase a try, no card needed!

Talking about signal-first GTM and data which you will use to feed your workflows with

Georgi Furnadzhiev

Clay just increased their pricing 🤷‍♂️ 

The most important thing that you need to know? 

👉 HTTP API costs jumped 0→ $0.03 each (imagine that table run)
👉 You need to pay extra if you want to use their signals 

For a detailed breakdown you can check their pricing, but now we need to address something BIGGER that's happening! 

When a platform taxes data access & nudges users toward their "actions", which is their new feature...the implicit message reads that data matters less & what you do with it matters more.

I disagree + contact data gets cheap, not signals 😉 (Thanks for the question Wesley & Spencer for pushing me to share my thoughts.)

To put it simply, garbage in = garbage out 

History simply shows that your data is only valuable when it's contextualized and verified, as there is simply so much noise out there. 

In fact, that's the reason why to every raw signal source inside Signalbase we run additional enrichments to meet at least 80% accuracy threshold.

So big updates or not, don't lose control over your data quality 

P.S to address another question which destroyed my DMs - If you are looking for an alternative check (in no particular order) 👉 Databar.ai, Baseloop, Freckle.io, Floqer, Cargo 🧱, Sendr, Starnus, nRev, Extruct AI, BitScale

API for real-time signals at scale | CEO @Signalbase

Building Signalbase in public to $1M ARR

👇 Here are a few lessons from this week 👇 

1. Founders should not automate everything, at least not so early in their journey! 

Yes, I said it as perhaps too many of us think about designing shiny GTM systems rather than doing what's needed for you to survive today

While everyone talks about automation, I’m still sending ~200 messages manually and doing support 24/7 as I need to feel the friction to get better with every single day 

I need to see where people hesitate, what objections repeat and what wording makes someone reply on a Sunday afternoon and jump on a call to evaluate us.

Honestly, why even worry about scaling something which may not even exist down the line???? 

By far the hardest part is also to remember that your journey is not "theirs" :) So focus on your own resources and timeline

2. Don't underestimate the importance of resource allocation

If you wait for something to address the bottlenecks within your business, you are a dead man walking

I learned to challenge what's currently in place, as only then can you experiment and move the needle with learnings.

Guess what? We set an experiment exactly 22 days ago, and that thing starts to slowly pay off, shaping the slightly different direction of the company.

Many VCs claim that speed is key, but perhaps we need to talk more about the speed of gaining new learnings and iterating upon them.

Radical choices always seem to be the hardest right now, but they can save you in the long run.

3. Learn from others ahead of you 

A few weeks back, I spoke to another founder of a data product and what he simply said saved me 4 years of struggling. 

Because finding PMF and that repeatable use case is not an easy job, but we are getting closer with every passing day.

Right now, we are still in a state where we get destroyed by feedback and at times, it actually feels shameful to be in the call.

Yet that exact same feeling means that people care about what you are building and the direction that you are heading to!

Shall we take a realistic look at the situation? 

The roadmap is clear, the vision is clear, the pipeline for high ACV deals looks good...

We just need to keep on hustling and showing up just like the live pre-verified data in our dashboard 😉 

That's it for today, looking forward to crushing the new week!

Time to ditch the old databases with stale data and find the real movement so you can be the first to reach out.

👉 try Signalbase

Wrapping up month 4 of building Signalbase in public to 1M MRR

Trust me, this one got the best of me...

Believe it or not, everything that we did in the past suddenly stopped working and we got stuck BIG TIME.

It felt like it just didn't click, no matter how hard we tried. (the nightmare of every founder)

Luckily, we remained hungry for learnings and the market showed us a new direction, which made us finally discover that sweet repeatable use case.

I remember talking to Iron Brands and Adriaan van Rossum about it at the beginning of the month: 

"I am dedicating the entire month to exploring that ICP" and it worked as I had a record of 6 high ACV calls in one day. Pipeline is growing nicely at the moment too! 

We also managed to bring life back to our biggest deal that we lost back in December (The very optimistic me thought we could close it in 2 weeks of building 🤣) 

All while still getting a few customers a day via the PLG motion, which we were also improving in the meantime, on top of training our own LLM models, as signal verification ain't a joke! 

2 few things that I am extremely proud of 🧡

👉 Shipping the biggest quality update within our 3-step verification process
👉 Making our first full-time hire 

March will be huge, let's survive!

Month 5 of building Signalbase in public to $1M MRR 

Weekly product update 👉  We shipped A LOT of code over the past 4 days 

🧡 Core scraping and validation process upgrades
🧡 Taking the first step towards signal stacking 
🧡 Shipped the beta for the hiring signal
🧡 Introduced new filters for the job changes
🧡 Rebuild completely the M&A signal
🧡 Introduced a self-sustaining investor and company databases

Now that's what I call building a sick product! 

Extremely proud of the boys Tadas Gedgaudas & Adriaan van Rossum for pushing the limits and keep on questioning what's possible 👏 

If you are tired of feeding your systems with stale accounts, this is your sign to refresh them with signals sourced within a minute

STOP killing your SDRs right now.

If you're an in-house GTM exec betting on “AI replacing humans,” you might be slowing your own pipeline.

To prove you wrong, I had the absolute pleasure to take a deeper look inside Clay’s actual GTM engine with Everett Berry 🐐 

While everyone keeps shouting about “AI SDRs are replacing humans", the winning companies are surrounding their top performers with the most advanced automated systems

Here’s what’s cooking inside the episode👇

 🟧 How you should think about building your in-house GTME team
 🟧 Clay's 4 main signals that helped them to scale before being integrated within the platform
 🟧 The biggest mistake they made while scaling their signal engine
 🟧 Why data quality quietly kills most outbound teams

and of course a ton of nerdy battle-tested tips for the hands-on practitioners out there! 

If you're building a signal-based GTM engine, rethinking your SDR team, or wondering how automation should actually fit into your stack…this one’s for you

Don’t kill your SDRs yet, let’s get practical!

Finding recently hired execs across the world has never been easier 🤯 

We just shipped the new company country and city filters, which enable you to find the right people at the right time within the right location 

All of this is also available via API 👇  

Let's build your first signal-based list Signalbase

The friday shenanigans are here to stay, and so are your evergreen signals 🕺

Believe it or not, you do need them as every piece of context helps you narrow down your list, which also increases your probability of success

Let's take the fundraising signal as an example. Once an org secures their round, you can expect them to: 

👉 Invest in new features or optimise current ones (great if you are selling data) 

👉 Expand to market or simply add another location within the same country (great SEO & office management solutions)  

👉 Hire a new key exec or face more job changes (great starting signal for all vendors) 

and the list of hypotheses continues further, which helps you to layer an additional custom signal on top of your. 

Isn't it obvious that we all need to help the SDRs to talk only with people who have a budget right now? 

No need to spend 20K in complex enrichment chains, just build your first signal-based list under 2 minutes with pre-verified funding, M&A and job changes data at scale 

Happy Friday! Signalbase

Month 5 of Building Signalbase in public to $1M ARR

This time we will talk about GTM & the overall founder journey👇 

As a founder, you probably felt at least once that odd feeling in your chest that keeps you from breathing? 

Yep, that was me a few weeks ago while panicking about running out of cash. First thing we did? Put ALL of the money for product development meaning savings mode is activated.

Feeling lost about what to do next and how to take the company to the next level....I went back to all of the calls from November to identify patterns and something just clicked. 

If you go to our website, you will see that Signalbase slowly adopts a new look as a proper live data provider that acts like a refreshment layer on top of your datasets or agentic workflows

Over the past 2 weeks, we spoke with nearly every LinkedIn automation tool, AI SDR agent, AI GTM engineer, Clay alternative, and big GTM data provider.

The harsh truth about building a company?

We all read these great stories about going from 0 to 10M MRR in less than a year, but honestly none of that would happen if the market does not assist you (so yes there is luck involved) 

Right product, right time, right founder, right message

Another harsh truth? 

The moment your development stops, you are dead! 

You simply can't imagine how many alternatives and smaller competitors pop up on the market and most of them are born from one of the 500 WhatsApp groups out there!

We saw the saturation of tooling also this week as LinkedIn turned into a complete blood bath.

Here is the quote that made my week👇 

"Dude this is great!!! You don't know how much trouble Signalbase will save us with the signal sourcing. We need to get started as soon as possible" - a vendor who wants to feed our data into their product

Great, we hit the sweet spot! All we need to do is keep on showing up, keep on taking the feedback and the rest will follow. 

My role should also be to remember the bigger picture and know exactly our next 3 steps ahead.

Btw we have also reached a new revenue milestone and despite being small, I find it meaningful. 🧡 Because your team needs hope, a clear direction and an incredible amount of resilience along the way. 

There are a ton of other things, I won't be able to cover fully such as:

- Designing a repeatable sales process (I've seen it already 10 times so it's slowly becoming more repeatable)
- PLG experimentation (7-day free trials vs freemium) 
- Product updates such as server boosts and more AI magic to help you find the right leads
- Listing smaller chunks of our API here and there
- Answering Jack's question about how we use Signalbase (video is coming)
- Hyping further Francesco's sick agentic workflow (link below)
- Preparing myself for a few new speaking gigs while also working on the tweaks around our content strategy

That's all for now folks! ☕ 

Chat next week,
G

"The company has not made any official announcement regarding the funding."

I'm not kidding, this is the third time this month we've caught such news! And the best is that we can also showcase the source.

Now that's the whole point of using Signalbase 👇 

While the majority of GTM tooling goes on a monthly shopping spree to refresh their stale datasets, we will only display companies with real change!

- Funding rounds
- Job changes 
- M&A activity
- Hiring news

All captured, additionally enriched internally to find more data points and displayed in less than a minute when it’s publicly shared. 

Or in this case, even before that! 

Try Signalbase, you can be surprised 😉

You know that you are building a great product when one of the biggest GTM agencies hypes you up 🤝 Understory

Huge shoutout to Naufal Nugroho 🌲 and the rest of his team for supporting us since the second month of our journey! Deeply appreciating you folks, the product won't be the same without your feedback.

These guys really know the new rules of the GTM game, so if you are building your signal-based engine from scratch, make sure to hit them up.

Signalbase is the biggest cheat code for 2026 when trying to be the first one to reach out to PE investors while hunting for M&A deals at scale. 😎 

Let's build your first signal-based list under 2 minutes 👇

Just because someone is wearing red underwear..doesn’t mean you should mention it.🤷‍♂️  

Yet that’s exactly how most teams use intent signals 

They see one trigger, maybe two, and immediately start reaching out like it’s a green light. The result? “Intent signals don’t work.”

But that's so far away from the truth as you simply don't know how to build your signal-based system  😉 

Come join me for the latest episode of My First Signal, where I had the absolute pleasure to sit with Bill (SalesCaptain) to understand what it actually takes to build a repeatable signal-based GTM engine

*I think this is a better intro than a Greek and a Bulgarian sitting in a room 🤣 *

Here’s what we actually broke down in the episode:
🟧 Why testing 1–2 signals is a guaranteed failure
🟧 A harsh reality check for all GTM executives 
🟧 Sales Captain's way of introducing a 3-layer signal funnel
🟧 The importance of the “language-market fit” concept most teams ignore

And of course, a little lesson for vendors to not be so explicit with their signals! 

If you're looking to build a signal-based GTM engine in 2026, this one might save you months of hitting your head against the wall

Let’s get practical!

What if most of your “intent signals”… are just an illusion?

Call me crazy, but indicating that a lead smiled at you should not be part of your CRM 🥴 (yes, history knows these examples) 

While building Signalbase, I kept seeing the same mistakes being repeated over and over again.

👉 Not using evergreen signals to craft the first versions of your lists
👉 Treating all market shifts with equal weight
👉 Jumping on every like or comment 

The result?  Burning out your SDRs while reaching out to the wrong people

Come join me on the 11th to discover even more mistakes and so many more hard learned lessons when sharing the stage with Zeynep (CompanyEnrich) 

We are about to go crazy with this one, make sure to register below!

CEO: Is this a real lead or not? 🤷‍♂️ 

Now that's a dangerous game to play and if you feel overwhelmed by all of the noise out there, this one is for you 👇 

Till this day, it's incredibly funny to see how the landscape pushes social engagement as the ultimate source of intent while completely missing out on the whole context per account 

The number of times history knows SDRs sitting in a room talking to someone who is eventually going to waste their time is honestly ridiculous. 

👉 That's why you are burning out your GTM team
👉 That's why you see such low response rates 

and that's why competitors are closing the right deals in front of your eyes!

Come get a grip on your signal-based GTM strategy at 5 PM CET today with our friends at CompanyEnrich (Zeynep Serra Avan)

Workflows, battle-tested insights and most importantly fun! As we are all done with the boring webinars out there 

Chat later!

Catching leaked news one time is miracle, but catching it twice is a system 🫡  

Once again before the press and any kind of official announcement. 

Signalbase is just getting scary good after the new verification & sourcing updates in place! 

While majority of GTM agencies and in-house teams swim in stale data, Signalbase only displays companies when real change is happening 👇

- Funding rounds
– Job changes 
– M&A activity
- Hiring (yes, we finally shipped it!)

+ we now have a fully self-sustaining or simply put growing investor database driven by the fundraising signal itself

All of this captured in less than a minute ago when it’s publicly shared (or according to this case way before that! 👀)

It's time to act first, not watch competitors close deals in front of you.

👉 Try the new Signalbase

Too many GTM teams undervalue how complex scraping signals really is.

They think: “Just scrape it.” or “Just pull it via API.” or “Just add another data source.”

When building Signalbase, I came to realise that scraping is maybe 20% of the problem. The other 80% is what breaks quietly in the background while your product keeps serving bad data to your users.

To actually make signals usable inside your GTM workflows, you need:

1️⃣ Continuous source monitoring across hundreds of sources 
2️⃣ Multi-layer verification so you're not passing recycled data downstream to your users 
3️⃣ Deduplication logic that doesn't collapse at scale 
4️⃣ Schema drift handling when sources change structure without warning 
5️⃣ Backfills and uptime guarantees your product can actually depend on 
6️⃣ An 80%+ accuracy threshold before a single signal reaches your platform

Without these verification and refreshment layers, you’re just automating scraped assumptions.

With proper verification, signals become reliable enough to drive outbound, enrichment, and routing.

Your GTM stack doesn’t need “more data.”
It needs a signal infrastructure beyond simple post engagement

Signalbase

Everyone is talking about signals, but not everyone understands how to leverage them to the fullest 👇 

I've been hammering on this recently, but social engagement signals can take you only so far as SDRs simply miss on the bigger picture 

To put it simply, does this company have any budget ?????

Because GTM is so much more complex than a simple like or comment which btw most of your buyers probably won't execute on as they know that they will be pitch slapped in seconds

Start feeding your platforms, custom Claude environments or workflows with evergreen signals to get the full company context 

👉 Signalbase

Most GTM teams destroy the mailboxes of their ICP right after a single signal lands in their workflow

Job changes. Website visits. G2 reviews. Then they wonder why nobody replies. 🤷‍♂️

The uncomfortable truth?

To make your message really stand out you need to find YOUR custom signal and use it as the ultimate competitive advantage. 

We are talking about that one signal that no competitor is tracking. The one tied directly to the pain only you can solve on top of a list full of already available context

That's exactly what we unpacked in Ep #8 of My First Signal with Kevin White  (Scrunch), representing one of the many seasoned marketing-led GTM leaders building signal-based engines out there!

Here's what we got into 👇

🟧 Why ABM ≠ signal-based GTM (and where teams keep getting this wrong) 🟧 How to find your bespoke signal through jobs-to-be-done research 
🟧 The intent spectrum framework — where to start so you're not overwhelmed 
🟧 Why personalization without relevance is just noise 
🟧 What "right person, right message, right time" actually looks like in practice

If you are a GTM exec lost in the journey of discovering their money-making signal sitting on top of their evergreen ones, then this one is for you 👇 

Let's get practical!

What if you could stop fighting all of the signals coming your way and build a predictable growth engine?

That's exactly what I'll be exploring live this Wednesday at 18:00 CET hosted by Ruadhán himself inside the Clay Club Europe.

Here are a few things we'll go deep on 👇 

→ What a predictable growth engine actually looks like 
→ How to layer real-time intent signals within every part of the sales process while killing it with your marketing efforts
→ A case study where this approach doubled the revenue of a multi-million dollar company 
→ Drilling down the agentic workflows of Francesco & Tanay

and sooo much more to experience when you join us!

Link in the comments 👇

3 signal-based prospecting use cases built from scratch
7 cost-effective ABM tactics that simply deliver
1 hour of battle-tested learnings

That's exactly what went down last week during our first webinar with Stefan Repin, destroying some of the biggest ABM myths out there

If you are an in-house GTM exec who looks for ways to move beyond the traditional spray and pray playbook, this one is for you! 

During the webinar, we also: 

🔶 Gaveaway 2 actionable playbooks covering insights from over 600 GTM practitioners 

🔶 Disclosed the copywriting formula to help your messages truly stand out 

🔶 Shared the secret sauce to the success of any signal-based GTM motion 

and lastly showcased how your marketing team can engineer its own signals to create a repeatable growth engine.

Want access to all of the materials and the recording? 

Comment and I will send you everything to help you build your signal-driven engine from scratch 👇

Want to know how all of the AI SDR agents or ChatGPTs for sales teams work? 

Here is what I learned after talking to 40 CEOs of different sales intelligence tooling in Q1👇 

They don’t actually track what’s happening in real time as their data refreshment process looks more like a monthly or weekly shopping spree.

The result for the end user like GTM teams? Making them blast massive campaigns and pray to catch intent by one way or another.

It reminds me a lot of a childhood game called "Broken Phone," as if only 1 person messes up or in that case data point, everything goes wrong.

So in short... AI SDRs buy static datasets with their contact data without any context from other niche API vendors with even more static data. 

What do these datasets tell you?

 👉 Who exists on the market (or at least on paper)
 👉 Where they are
 👉 What do they historically do

But the missing piece to all of these "recommendation" engines? 

 🔶 Who just got promoted or switched their role 
 🔶 Which teams got acquired
 🔶 Who just raised funding

Static data = risk of reaching out to the wrong person
Real movement = getting conversations that actually convert.

Because nobody should waste the time of their SDRs on accounts with no budget or movement behind them. 

Try Signalbase's API

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The Battle

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Georgi Furnadzhiev

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Wes Bush's LinkedIn Performance

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