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.

A Practical Dashboard Standard for $2M–$10M B2B SaaS

Yo, I'm Matt Mike 👋

(yes, Mike is my actual last name).

My career path has been far from linear. Here are the cliff notes (that's still a thing, right?)

2015: graduated with an English degree
2016: became a teacher
2017: became a dean of students
2019: left education for B2B sales
2019: hated sales. took a pay cut to become an operations analyst
2021: got promoted to operations supervisor

2022 and onward: became a business analyst (FIRST DATA JOB). Started documenting the journey on social media where I now have a combined following of 100,000+ tech professionals. I've been through a few different data roles with progressive complexity and now do BI consulting while continuing to help others progress their tech careers through content.

Because of my background, I have a passion for helping people with non-technical backgrounds break into tech and advance their careers. My technical passion is business intelligence analytics.

🤝🏻 Brands: mjomike@gmail.com
🎥 YouTube: @mattmike
📩 Newsletter: https://thdatapoint.substack.com/

Matt Mike

Not 1, not 2, but 3 hernia’s repaired.

Had surgery the other day. 

Recovery has been brutal but I’m so glad to finally get this done. These hernias have been a major impairment to physical activity and a daily discomfort.

Super grateful to my wife who’s been taking care of me, the kids, and everything else while I hobble around like an old man.

Day 3 of a 6-8 week recovery✌🏻

Business Intelligence Developer 🤘 | BI & Analytics Consultant | YouTube @ Matt Mike | Helping non-tech professionals break into data and make $30k+ more with the Data Career Makers community

No alternative text description for this image

I've applied to 1,000s of jobs in my career.

Most led nowhere.

But the problem wasn't my resume or skills.

The problem was treating job hunting like a numbers game.

(the spray and pray method).

Applying to 50 jobs a week → exhausting.
Applying to 5 targeted opportunities → strategic.

Strategic job hunting = better interviews, faster offers.

Here's how I'd approach the job hunt in 2026 if I had to start over:

1. Build relationships before you need them

Most people wait until they're desperate to start networking. 

They send cold messages, ask strangers for referrals, and wonder why nobody responds.

This is backwards.

Instead I'd spend 30 minutes a day engaging with people in my target companies.

Comment on their posts, share their content, add genuine value.

When you build relationships first, opportunities come to you.

You don't need to beg for referrals when people already know your name.

2. Post content that showcases your work

Resumes can get lost or ignored.

LinkedIn posts are living proof of what you can do.

I'd post 3x a week about projects I'm working on, problems I've solved, tools I'm learning.

Not generic advice. Actual work.

This does two things: 1) it proves you know your stuff and 2) it makes you visible to hiring managers who are scrolling LinkedIn looking for talent.

3. Apply like you mean it

I'd rather spend 20 minutes on one application than 10 minutes on twenty.

For each role I'd research the company, customize my resume to match their exact needs, and write a cover letter that shows the value I bring.

Then I'd find the hiring manager on LinkedIn and send a short message explaining why I'm interested.

Most people won't do this because it takes effort.

But that's why it works.

tl;dr:

1. Network before you need it. 
2. Prove your skills publicly.
3. Apply with intention.

ps - got a vid on this topic publishing soon. check out my channel so you don't miss it: https://lnkd.in/dpMCPTmH

Career growth is not always linear.

I've switched jobs and changed careers more than most.
I've even taken steps back at times.

But every shift always moved me forward in the long run.

To better pay.
To a better role.
To a better field (for me).

You can feel lost when a job no longer feels right.

Or when you're let go.
Or you're burnt out

But sometimes you have to take necessary shifts.

And those shifts aren't bad.
Staying stuck in a bad place is.

So embrace the checkered past.

Or the shifting target.
Or the challenging circumstance

Those steps are necessary.

You're just on your way somewhere better.

Had a great time at our low-key Phoenix, AZ happy hour last night!

Awesome turnout. Got to meet some great people!

It was also my first time meeting in person a few people that I've known from LinkedIn for quite some time now.

Andrew Madson 
Madison Schott 
Monica Kay Royal (won't let me tag you for some reason???)

We're thinking of doing these quarterly. 

If you're in Phoenix and missed this one, hope you can make it to the next one!

___
PS - still recovering from my hernia surgery but I couldn't miss this. Really pushed myself to be there. Couldn't stay long due to the pain, but glad I made it :)

A lot happened for me in 2025.

I've talked about bits and pieces of it here on LinkedIn, but I just posted a full video about it for anyone interested.

I like doing these yearly check-in type videos.

It's just nice to process everything out loud.

https://lnkd.in/g8i8PDAe

PS - thanks to everyone for the well wishes on my recovery from surgery. Today is day 5 and I'm getting a little bit stronger each day :)

Open video: Data Analyst Year In the Life: 2 Moves, Lost My Dream Tech Job, and What I'm Changing in 2026 on youtu.be

Data Analyst Year In the Life: 2 Moves, Lost My Dream Tech Job, and What I'm Changing in 2026

There's a lot of talk about data and AI.

And I hear most from people outside of the data space about what will happen to technical jobs.

So, in this video I share my boots-on-the-ground take on the situation. What I'm seeing, researching, and hearing from my many peers around and above me in the data and AI space.

https://lnkd.in/gdmDtEJb

___
PS - getting back to a regular schedule with uploads. My goal for 2026 is actually to increase volume to 2 uploads per week. We'll see if I can manage that lol

Open video: Will AI Replace Data Analysts in the Next 10 Years? on youtu.be

Will AI Replace Data Analysts in the Next 10 Years?

You don't have to sound like an idiot anymore.



Check out Count here:
https://lnkd.in/gKFDZJgN

#countpartner

Some people call pie charts bad.

It's like the "Is a hotdog a sandwich?" debate of data viz.

But I think it completely depends on the context.

There's nothing wrong with pie charts inherently.

Comparing 2 values against each other is a great use case.

The problem shows up when you have too many values.

Too difficult to interpret quickly. 
Data labels get smushed together.

Can you see the data clearly?

The second they start getting smushed, swap the visual.

(rule of thumb is 4-5 values, but it depends)

Especially when your dashboard is already full of bar and column charts.

So if you're avoiding pie charts because someone told you they're bad:

1. Ask yourself how many values you're showing
2. Consider if variety would help your dashboard
3. Check if the data labels are readable
4. Then decide

Context matters.

Which camp are you in on this?

___
PS - I just started a community for people breaking into data careers. Check it out here (launch pricing still active): https://lnkd.in/gjY7-wyJ

The data job market looks different this year.

More data jobs than ever before, but also more saturated.

As someone who was laid off and on the job hunt again mid-2025, I have some thoughts on how I'd do it all again 2026. Especially if I was starting from scratch.

In this video, I cover those thoughts.

https://lnkd.in/gvPJxsbq

Open video: The EASIEST Way To Become a Data Analyst in 2026 (skills + portfolio + job search) on youtu.be

The EASIEST Way To Become a Data Analyst in 2026 (skills + portfolio + job search)

I just created a FREE tier for my community.

It gives you access to all community chats as well as a few helpful resources.

I don't know how long I'm going to keep a free tier. Might be a week, might be forever. But once you're in, you're in forever, even if I close the free tier later on.

Interested? Check out the Data Career Makers community here:

https://lnkd.in/gHdhtf9v

✌️

ps - the community has only been open for a week. There's lots of great stuff there already, but I have lots of plans for building this out and creating a ton more value.

Curious...

...also, feel free to leave suggestions in the comments if you have a different answer than in the poll :)

___
ps - i got one of these. we're steadily growing! you can check it out here: https://lnkd.in/gjY7-wyJ

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