Michel Brok 🎯

Tracking Architects

Tracking Architects empowers eCommerce and funnel website owners to maximize revenue from their marketing efforts through advanced server-side conversion tracking and data analytics.

Eigenaar

Team6

Team6 helps FMCG and retail businesses to improve business performance with data. Our focus is to make strategies work by bringing ways of working, data and technology together.

Founder

A.S. Watson Group

Helping the marketing team to use data to 1) make better decisions in target audiences, offerings and content and 2) increase relevancy and therefore increase customer lifetime value. 

Results:

- Created and implemented the CRM Data Strategy
- Implemented cross-functional CRM data team
- Implemented the CRM data-driven process
- Implemented algorithms for optimizing promos

Data Lead CRM a.i.

Danone

Leading 2nd Digital Transformation wave of the Dutch CBU for all Danone brands (dairy, plant based, medical & baby). Build the data foundation to take better decisions and actions to drive business value for the CBU.  

* Developed the data strategy and roadmap together with senior management
* Build the cross-functional data team overseeing data analytics, data science, architecture and platform
* Managed the local data platform and architecture (Azure) implementation
* Managed the integration of all digital channels in Azure data lake
* Delivered 3 use cases: customer 360 together with CDP, Marketing Mix Modeling & MROI (causal attribution)

Head of Data

Leading the Digital Transformation for the Benelux BU with focus on improved customer experience. 

* Building the digital environment and BU digital capabilities
* Transforming marketing strategy and operating model
* Shape and build the marketing technology stack, integrate within marketing operations
* Delivering and activation of digital products & services
* Leading design, experience, digital product & engineering teams

Head of Digital

E.ON

Responsible for e-commerce and digital marketing for the residential, SME market and large enterprises.

* Development and implementation of the digital transformation roadmap for the Benelux cluster
* Development and execution of the digital marketing & e-commerce strategy to drive brand awareness, customer acquisition, retention and NPS 
* Marketing technology: implementation of the Adobe CMS and migration existing digital platform, implementation of the customer self-service portal and connection between digital platform and SAP
* Management and optimization of traffic channels  SEA, SEO, affiliates, retargeting campaigns, display advertising and online partners
* Management and optimization of webconversion with A/B testing, data analytics and UX-optimization
* Implementation of the E.ON self service portal to increase self service and drive NPS and decrease costs
* Implemented Lean wow and performance driven mindset
* Managing and coaching multi-disciplinary online team (4 fte)
* Operational excellence day-2-day optimization working method

Team Manager Online Marketing

Essent

Responsible for online sales and lead generation for residential and SME market.

	Defined and implemented annual online sales plan, defined targets, budgets and weekly sales forecast
	Accelerated performance based sales & lead generation by optimize traffic sources (display advertising, SEA, SEO, affiliates) and CRO for Essent.nl. Managed referral and price comparison websites
	Implemented marketing campaigns ATL/BTL in online channels in collaboration with marketing and sales department 
	P&L responsible for digital sales

Digital Marketing Manager

Tribal

Helping clients driving business growth with developing and executing online marketing strategy focussed on increasing website traffic and conversion optimization.   

	Development and implementation of new online advertising campaigns to increase numbers of leads and / or sales
	Managed and optimized existing SEA and SEO campaigns
	Aligned projects with usability and web analytics experts 
	Evaluated campaigns by analysis with Google Analytics
	Reporting to customers and team lead

Online Marketing Consultant

Lensvelt Medical

Improving company awareness and developing customer service proposition to support customer acquisition and relationships.


	Development and implementation operational marketing plan
	Coordinated and implemented marketing activities such as product / price promotions, trade fairs, managed and implemented online advertising campaigns, website optimization and e-mail marketing
	development of services products and related concepts and responsible for activation via website, sales channel and fairs

Marketing Specialist

Marketing Automation & Data Expert | Helping retail & CPG to drive customer engagement at scale.

Business & Agency Owners – Listen Up:

The #1 reason your ad campaigns hit a wall?

INACCURATE DATA.

It’s the frustration holding back ambitious advertisers like you — those who are ready to scale but can’t break through.

At this stage, you’re trying to lower ad costs and increase value. But if the data you rely on is off, making the right decisions becomes nearly impossible.

Here’s the real issue:

Inaccurate data doesn’t just impact your decisions — it also sabotages the advertising algorithm.

The better your data, the better the algorithm can identify your best customers.

But getting accurate data and conversion tracking right is easier said than done.

That’s where the Data-Driven Scaling Formula comes in — putting accurate conversion tracking at the core of your strategy.

The Data-Driven Scaling Formula empowers ambitious business owners like you to scale faster by leveraging the right data at the right time.

The formula is made up of three key parts:

	1.	Enhanced Performance Tracking: Best-in-class server-side tracking combined with smart data usage throughout the entire customer journey. This ensures both you and the advertising algorithm are making better decisions and taking smarter actions.

	2.	Precision Algorithm Training: Fueling your advertising algorithm with high-quality data to significantly improve targeting. Now, you’re only spending money on customers who bring real value.

	3.	Transform Data into Growth: Gain control over your business’s growth by understanding what works — and what doesn’t — in both marketing and sales.

Curious about how we’ve helped others scale smarter?

Send me a DM, and let’s chat!

-----

Hi, I’m Michel – The Conversion Tracking Guy.

With over 18 years in Digital Marketing, I’ve witnessed firsthand how advertising platforms and marketing systems are becoming increasingly data-dependent. Yet, proper conversion tracking and data architecture are often overlooked because they seem complex or costly.

I’ve helped over 250 business owners unlock the full potential of their marketing with server-side tracking and analytics. In almost every case, the results were clear: a significant boost in performance.

Let’s talk about how accurate data can transform your business.

Co-Founder

AldrichX is a data-driven marketing agency that helps 6+ figure fashion eCommerce brands to grow their business whilst they can keep focussing on building their brands.

Ecom subscription sellers: 

Stop wasting your Meta Ads budget on returning customers.

Such an easy fix, yet almost nobody does it.

Every major Ecom platform already gives you the parameter you need, you just have to plug it into your tracking setup.

Once you tell Meta who’s new vs returning, everything changes:

- Cleaner attribution
- Less wasted spend
- Better audience signals

More budget going to actual new customers

Meta can’t optimize for what you don’t tell it, give it the right data, and it will find the right people.

Want help setting it up? 

You know where to find me ;)

Michel Brok

I train your ad algorithms to find your best buyers. Accurate conversion tracking + smarter buying signals = higher ROAS.

You’re launching the Black Friday campaign with sweaty palms…
…and your developer just deleted the tracking code 😭

Always check  tracking first before launching  new campaigns:

1. For Meta, use the Meta Pixel helper tool
2. Google Ads, check the Google Tag Assistent

Still not sure if everything is working?

DM me😀

Shopify Analytics sucks.
Tracking breaks.
And “Direct” suddenly looks like your best-performing channel.

But here’s the thing, it’s not Shopify’s fault, it’s Consent Mode.

When a user doesn’t accept cookies, Shopify simply stops tracking.

No pageviews.
No addtocarts.
No purchases.
No channel.

Which means your data becomes… well, kind of useless.

Another place where tracking seems broken 🤯

So what are your options?

1️⃣ GA4 server-side setup with Consent Mode
2️⃣ Triple Whale

Both have their pros and cons, ut they’ll give you a much clearer picture of what’s really happening, even when users don’t consent.

What are you using right now to close this gap?

Helping agencies deliver better client results — with accurate tracking, stronger algorithm signals, and actionable ad dashboards

People don’t want to spend a dime on conversion tracking.
But they’re happy to invest in “algorithm training.”

Most advertisers still think tracking is just a fix.

It’s not, it’s the foundation for growth.

Better tracking doesn’t just lead to better decisions....
it sends better signals to the algorithm about who buys and who doesn’t.

Imagine being able to tell Meta or Google exactly who to target, that’s what accurate tracking really does.

Curious how accurate your tracking really is.
You know where to find me. 😉

“Our Google Ads spend doubled… but sales didn’t.”

Not funny when you’re managing a €600K budget.

Turns out, Google was seeing fake purchases.
So it kept spending like crazy because performance looked great.

What happened?
After a website update, purchase events started firing twice.

The algorithm thought it was crushing it.

That’s why you always audit your tracking after any major change:

- Review tracking codes
- Test if purchases fire correctly
- Monitor data closely the first few days

Nothing’s more painful than spending big…
and realizing you’ve been optimizing on fake results.

Proud that TrackingArchitects is one of Stape’s Top Partners.
And it’s more than just a badge.

Because my clients now know:

> I’ve done more than enough tracking implementations to handle any setup
> They can rely on an extra pair of expert eyes when accuracy matters most
> I follow a structured process to deliver the highest quality

It’s always great to be recognized, 
but even better when it helps my clients scale with confidence.

How’s your tracking going? 👀

70% of your Google Ads leads are spam.
Real problem? You keep feeding Google… spam data.

So Google thinks those fake leads are exactly what you want, it finds you more of them.

Meanwhile, the good leads?
Google has no idea what they look like.

Here’s the fix:

- Mark qualified leads in your CRM
- Setup offline conversion tracking 
- Activate Enhanced Conversions
- Gather data in Google Ads 

Make the switch when everything looks good and feed Google with signals from high quality leads. 

Better signals = better leads

Still getting mad when I see this. 

You're spending 100k monthly on Ads and using a free tracking plugin 🤯 

Audited an e-commerce brand this week.
Meta was their ONLY growth channel.
Big budget. Big ambitions.

But they were only sending 60-70% of their data back to Meta.

Why?

The Facebook app in Shopify was not tracking all data. 

And then they wondered why:

> ROAS was unstable
> Scaling didn’t work
> Meta was “inconsistent”

The algorithm can’t optimize on blind spots (and it's getting worse).

So we fixed it:

+ Implemented a real data layer
+ Added server-side tracking
+ Passed email, phone, location
+ Captured click IDs

Result? 20-30% more conversions. Instantly.

DON’T save on tracking please 🙏

Meta and Google Ads numbers seem off… and you’ve already tried everything:

- Free plugins
- Agency experts
- YouTube tutorials
- Cheap freelancers
- In-house developers
- A fresh Google Tag Manager setup

But still, after 6 months you’re staring at numbers that make zero sense whilst your competitor absolutely crushing it.

Let's end this frustration once and for all.

Hire a tracking expert or agency, ask them:

1. How many times the've done the setup you need
2. How they measure accuracy and how to optimize for
3. If they have a 'second-pair-of-eyes' mechanism
4. What their monitoring process is

Time to stop doubting and start scaling with confidence.

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.

What once felt simple and under control, now runs on many moving parts...

Marketing channels are disconnected from sales, LTV:CAC ratio is a rough guess, and your churn data is a month old.

‍The data to make sense of it all is scattered across Stripe, Hubspot, and product analytics, leaving your team to manually piece it together.

The result?

A collection of outdated reports that no one fully uses.

You’ve tried to fix it, asking people to update spreadsheets, buying new tools, maybe even hiring a specialist. But nothing sticks. Your own engineers are brilliant, but they’re busy building the product customers pay for.

In your mind, it’s simple: you just want accurate numbers so you can stop second-guessing and make the right calls.

At this stage, you face a choice.

You can continue guessing which free users will convert and which sales activities actually close deals, all while your teams debate why customers churn.

Or, you can choose a path to regaining control. The path where you:

- Increase conversion rates from trial to paid users.
- Attract customers who pay more and stay longer.
- Eliminate data debates between your teams.
- Truly understand why churn happens.
- Slash the time it takes to close deals.

We build the system that delivers these results, turning your scattered data into efficient, repeatable ARR growth.

The first step is a conversation. During a 30-minute call, we talk through your situation and what you're hoping to achieve. We'll be honest about whether we're the right fit to help. Our promise: you'll walk away with a fresh perspective, no strings attached.

Check our website for more info: www.datadrilldown.com

Thomas Varekamp

Landed in Bali last week. 

Mixed feelings on this place so far.

What I like:

I found a spot called Omni, a combined co-working, wellness, and gym.

It's basically a hub to get tons of work done with no distractions:

- solid gym
- top-notch service.
- great, healthy food.
- great co-working space.

Everyone is limited by time and energy. This place lets you really maximize both by having everything in one spot.

Also, prices are about 50% cheaper than in The Netherlands. Big arbitrage.

So, here’s what I don't like about Bali (so far):

1. The traffic is crazy. You literally cannot walk here. No pedestrian paths, just cars and tons of scooters.

2. Weird inequality. The moment you step outside of your nice co-working space, you see run-down buildings, broken roads, and trash. 

People that have been in Bali, any recommendations?

This weekend I’m going to explore the Gili Islands, excited for that one!

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

This is Mex, a Dutch entrepreneur I met here in Bangkok.

We bumped into each other at a club, and I instantly recognized the Dutch 🇳🇱.

A few days later we met for coffee, and that’s when he told me his story.

It all started years ago with Minecraft.

In Minecraft, you can create custom servers, basically private worlds with your own rules. 

Mex originally built one just for his friends, but after a while opened it to the public. The server was so good that people kept joining.

For the first 4 years it was purely a passion project. 

But as the community grew, Mex figured out how to turn this into a business.  

He began offering:

- custom game modes.
- memberships with extra privileges.
- custom skins for players to show off.

The model worked. The server grew steadily at around 20% per year. Then, 2 major events caused an explosion:

1. The pandemic
  
With everyone stuck at home, growth shot up to 100% year-over-year.
  
2. The Minecraft Movie
  
Its release brought in a whole new wave of players.

He scaled up, built a team, and hired an operator to manage the day-to-day.

After a while, he acquired another Minecraft server from a competitor (he told me they finalized the deal in a McDonald's lol)

Now he lives in Bangkok and runs the business remotely.

This is why I love talking to other entrepreneurs. 

You find out about businesses you didn’t even know were a thing.

A dashboard full of metrics means nothing if no one knows what they mean.

At many B2B SaaS companies we work with, this is common:

→ data is stored in some spreadsheets.
→ definitions are not 100% clear.
→ people don’t use the data.

The result: another data projects fails.

We solve this by creating a Metrics Dictionary.

It’s a simple Google Sheets that makes sure we all know what each metric means.

(this makes working with data a lot easier) 

Here’s what we include:

1. unit → what it's measured in
2. filters → how to slice the data
3. calculation → how it's calculated
4. department → who cares / uses it
5. metric owner →who is accountable
6. refresh rate → how often it updates
7. description → what the metric means
8. data source →where the data comes from

I included the template we use in the comments.

Copy it, tweak it, use it.

Good luck!

I'm launching a Youtube channel.

In the last 3 years, I’ve helped 20+ B2B SaaS companies build their data systems and create content about it.

Linkedin is great, but it's hard to show how to actually fix a broken ARR calculation in a 60-second clip.

Youtube allows me to go much deeper.

The goal is the same: help B2B SaaS companies regain control by turning their data into direction.

Topics:

- how to use data for ARR growth.
- how to align your team using data.
- how to operationalize B2B SaaS metrics.
- how to analyze your B2B SaaS business.

Basically everything a B2B SaaS leader needs to build a data-driven business.

The first video is live: https://lnkd.in/egPNPSs5

I show the exact data intelligence system we set up for most of our clients.

The plan: upload every week.

Check it out and let me know what you think!

If you can only build 1 dashboard for your B2B SaaS, this is the one I recommend.

Most SaaS companies I work with don’t have a single, reliable view of their performance that can be easily shared with investors, their board, or their team. 

Instead, the data lives in large, complex spreadsheets that are hard to maintain and often already outdated by the time someone opens them.

For companies that want something better, I recommend the dashboard I show in this video. 

It includes:

- automated data pulls.
- clear visualizations of all metrics.
- comparisons and trends to understand progress.

Leading to:

- smoother investor and board reporting.
- faster and more confident decision-making.
- better team alignment around performance.

Great tool for SaaS companies that want to build a data-driven culture.

10 dashboards we’ve built for GTM teams to fix deal pipelines, missed targets, and slow leads.

Over the past few years, we’ve built many custom dashboards for B2B SaaS companies in the $2M–$10M ARR range. 

Below are 10 dashboards we have built for marketing & sales teams to make better decisions:

1. Deals Pipeline
2. Lead Lifecycle
3. Sales Rep Overview
4. Sales Funnel
5. Campaign Performance
6. Sales Overview
7. Target Account Overview
8. Advertisement Performance
9. Website Insights
10. Lead Journey

Scroll to see what each dashboard looks like ↓

Marketing__Sales_Dashboard_Showcase

I fixed a $3.2M ARR B2B SaaS's broken data system

(here’s how)

There is a dangerous transition for B2B SaaS companies around $2M ARR.

In the early days, data is a "favor."

You ask an engineer to pull a quick CSV. They write some code. You get the data.

But as the business grows, that method breaks:

- volume gets bigger.
- questions get harder.
- data is more scattered.

You move from needing a quick export to needing insights on daily basis.

And the engineer who used to run those scripts?

- they are not specialized in analytics.
- they are busy building the product.
- or worse: they left the company.

This creates a massive bottleneck.

And was exactly the case for a $3.2M ARR B2B SaaS I worked with last year. 

The CEO was waiting days for basic insights, and the data pipelines were impossible to maintain.

You can’t lead a company if your data is outdated or incorrect.

I just uploaded a video of how I completely overhauled the data infrastructure for a $3.2M ARR B2B SaaS.

In my new video on Youtube, I break down:

- the specific 15 dashboards I built.
- how I reduced data processing time by 98%. 
- how I aligned the teams on the right metrics. 
- how to drill from ARR to customer details in 2 clicks.

Check it here: https://lnkd.in/eAEps9T7

Our 5-dashboard system that gives B2B SaaS teams 80% of the insights they need.

Many B2B SaaS use data in:

1. spreadsheets
2. some pdf slides
3. a handful of dashboards

But this spread-out approach makes it hard to pinpoint exactly what’s driving growth, or what’s causing churn.

We fix this by building a 5-dashboard system.

It's designed for one purpose: give you complete visibility across everything that leads to ARR:

1. The ‘What’ (Management Overview)

Your high-level Command Center. It's the executive summary of all your key subscription metrics

2. The ‘Why’ (Revenue Overview)

The deep dive on your revenue. The ARR waterfall chart is the most important part. It shows you precisely what's driving ARR change.

3. & 4. The ‘Where’ (Country and Industry Overview)

This is how you validate your GTM strategy. You drill down into a specific segment and see its exact performance.

5. The ‘Who’ (Account View)

The 360-degree view of a single customer. You see their entire MRR history , sales activity, health, and user activity, all in one place.

You can drill down from your top-level ARR number... to the 'Agriculture' industry that's underperforming... all the way down to the specific customer who left.

Leading to:

→ more confident decisions. 
→ better team collaboration.
→ fewer data discussions. 

I put these 5 dashboards in the document below.

Check 'em ↓

The 5 dashboards that cover 80% of the insights (B2B SaaS)

97% reduction in data processing time (and unlocking company-wide insights)

LegionellaDossier was struggling with their data:

- reports took 6 hours to refresh.
- finance had no up-to-date numbers.
- management couldn’t trust the dashboards.

So we came in and rebuilt their everything from the ground up:

→ set up BigQuery.
→ automated data collection.
→ simplified the data models.
→ created clean datasets for analysis
→ built dashboards for finance, sales, CS.

The result:

→ faster reports for the board.
→ 97% faster data processing.
→ company-wide performance insights.

Check the full case below ↓

How we helped LegionellaDossier regain control 

Everyone says: “Focus on your Ideal Customer Profile (ICP)”

But is your Ideal Customer Profile backed by data? 

Leading SaaS companies don’t guess, they segment customers, measure performance, and let the data tell who their best customers really are.

We use 3 core metrics in our analyses:

1. Customer Lifetime Value (CLV): How much revenue has each group generated?

2. Net Revenue Retention (NRR): How well do they expand and stick around?

3. Churn: How quickly do they leave?

I ran this analysis for a $7M B2B SaaS client the other day and found a group of customers with:

- 3x higher CLV
- 30% higher revenue retention
- 10% less churn

…versus the rest.

Combine this with customer acquisition costs, and you get a deep profile of what a good customer actually looks like.

The outcome:

- marketing knows who to attract.
- product knows who to build for.
- sales knows who to prioritize.

Instead of trying to serve everyone, you can double down on the customers that are the best for your business.

It took levelworks 12 hours every month just to get accurate insights.

(this is Tim from levelworks, check out the video 👇)

This is a classic scaling problem: the most important data lives in manually updated spreadsheets. 

It’s hard to grow when you’re spending all your time just trying to get basic numbers right.

We stepped in and built them a real data foundation.

The result? 

In Tim’s words: “It basically saves us 2 to 3 hours a week.”

More importantly, the team’s conversations are now deeper, more strategic, and lead to higher-quality decisions.

And that’s the point: not pretty charts, but time saved and better decision-making.

Better data → better decisions → better business.

Ecochain was struggling with a loss of control.

This is a classic growth problem: their most important data was not readily available.

It’s hard to lead a company when you don’t have a clear picture of what's happening.

We stepped in and built the dashboards + data infrastructure they needed.

The result?

As the CEO Frans-Willem put it:

"The moment I realized it was working was when we could compare the previous results with the current results and see the trends."

They now have the ability to show the results in a better way to the board and can see where they really have the challenges... and to get it resolved.

And that’s the point of data: not dashboards or nice charts. 

But improved understanding, control, and ultimately, better decisions.

The reason you have 20+ unused dashboards? Big chance you skipped some steps.

Here’s what happens:

- you needs insights. 
- you buy a BI tool. 
- you tell an engineer to "build dashboards"

A month later, there are 20+ outdated reports nobody uses.

If this is the case, you probably skipped some foundational work.

Here's the full 5-step system we use to build useful & accurate dashboards 👇

1. Choose metrics

Answer:

- what are your goals? 
- what KPIs track it?
- what are the metrics driving the KPIs? 

This helps to focus on the essentials. 

2. Create a metrics dictionary 

- write down what "ARR" means. 
- what's the calculation? 
- what's the data source? 

This document ends discussions about data. 

3. Extract, Transform & Load (ETL)  

This is the "lean" data stack we recommend for almost everyone:

- extraction: Fivetran / Airbyte / Weld
- warehouse: BigQuery
- transformation: Dataform
- visualization: Looker Studio

You don't need big, complex stack. This setup is cheap, scalable, and powerful.

4. Build dashboards 

- take your metrics dictionary
- start building charts for the metrics
- ask feedback from users

5. Integrate in daily work 

Data means nothing if no trust it.

- give every metric an owner.
- use the dashboard in your meetings.
- review your metrics definitions every quarter.

This is how you go from random dashboards to a data intelligence system that helps everyone.

Here's how Ecochain finally got insights they can trust.

Ecochain helps businesses measure their environmental impact.

After setting ambitious growth targets, they faced challenges with data:

→ data scattered across different systems.
→ arguing about which numbers were right.
→ manually exporting data for every report.

You can't grow efficiently when you don’t have the right insights.

So we build their data foundation:

1. Start with a workshop (not a dashboard)

We aligned their teams on the right metrics to track (Trial Users, Conversion Rate, Churn).

2. Automated the data flow

We connected all their key tools (Stripe, Mixpanel, HubSpot) into a central data warehouse. 

This stopped manual exports.

3. Built dashboards

Once the foundation was set up, we built the dashboards. 

Now the data is updated every day and easy to work with.

The result?

→ teams aligned on one set of numbers.
→ faster access to custom data insights.
→ hours saved every week.

Check out the full case study 👇

Case Study Ecochain

We recently built a data intelligence system for Expandi, a LinkedIn automation platform doing $10M ARR.

The challenge: 

They had BigQuery and dashboards, but teams were misaligned, with no central place to find all data insights.

We started with a workshop to agree on the top priorities.

Then we rebuilt their data foundations from the ground up:

→ enhanced customer data (30% to 90% coverage).
→ connected user behavior to company metrics.
→ implemented data checks with Slack alerts.
→ cleaned and centralized all data sources.
→ built dedicated datasets for the teams.
→ deployed 10 production dashboards.

The result: 

1. hours saved to focus on strategy instead of data.
2. better alignment between teams.
3. more efficient meetings.

Very happy how this one turned out.

Check the full case study below ↓

Case Study Expandi ($10M ARR)

Here’s why churn might not be your fault (and what to do next).

Many SaaS leaders I speak worry over churn.

They have a strong product, a good ICP, been in the game for some time.

The problem: customers still leave after a few months.

After reviewing dozens of SaaS companies, I’ve learned that the issue isn’t always the product. 

Sometimes, it’s simply human behavior.

Consider gym memberships. Natural annual churn is 30-50%.

The gym can be beautiful, fully-equipped, and well-staffed. People still cancel.

Not because the gym is bad, but because they won’t sustain the effort that's needed.

SaaS is similar.

If your product requires user effort (complex setup, daily input, team adoption), some churn is unavoidable. 

No matter how good your retention tactics are.

So what?

You need to benchmark your numbers.

Find out what "normal" churn looks like for a similar product.

This is how you know if your churn is something you can fix, or just the cost of doing business.

So, how do you find those benchmarks?

This is a good job for AI.

1. Copy the prompt in the image below 👇
2. Fill in the placeholders.
3. Run it in Gemini Deep Research.
 
(always check the sources it gives you)

Don't lower churn because you think it's high. 

Benchmark first, then take action.

taplio

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The Battle

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