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!

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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.

Tenet Healthcare

AI Product Director

Trilliant Health

Developed machine learning models to predict various data points in our claims and provider datasets. My role among them was:

• working with Health Plan Price Transparency (HPPT) data to develop a proprietary Rate and Quality Score for payers and providers to enable users to identify who the high-quality *and* affordable providers are
• using machine learning to predict providers' taxonomy classification to enhance our Provider Directory product using claims and NPPES features
• using claims data to infer patients' Primary Service Area (PSA) to enhance many of our products - like our Demand Forecast, Provider Directory, and Network Explorer reaching a ~47% increase in classification accuracy

Data Scientist IV

Unum

• Developed and implemented the company’s first ever AI Governance Framework, aligning AI with enterprise compliance goals and ensuring bias mitigation, model transparency, and reproducibility
• Led the zero-to-one vision, strategy, roadmap, and execution of NLP and AI projects, building scalable AI products across different functional domains while ensuring executive buy-in
• Consistently lead user interviews to discover common pains, needs, and friction points to better inform AI projects

Principal AI Product Manager

• Lead zero-to-one AI projects through Product Discovery, Delivery, and Iteration, while using best Build-Measure-Learn practices
• Orchestrated the cross-functional launch of a scalable NLP-as-a-Service platform (backed by LLMs and GenAI) to address document classification, semantic matching, entity extraction, and summarization leading to a 54% increase over baseline models, a 73% average time savings of common manual processes which drove an annual cost savings of $2.5M
• Championed quick experimentation and iteration on AI initiatives, leading to quicker development and release cycles
• Drove executive buy-in of AI products through heavily-researched operational usability, engineering feasibility, and business viability analyses

Senior Data Scientist / AI Product Manager

Nashville Software School

Data Science Instructor - Assistant (One Cohort)

The General®

•     Led end-to-end 0-1 product development and data science execution across multiple Claims-focused ML initiatives, managing roadmaps, feature definitions, and integration with core systems
•     Identified and prioritized high-impact ML use cases in collaboration with cross-functional stakeholders, translating business needs into scalable predictive models
•     Mentored and coached junior data scientists while also setting standards for model development, engineering best practices, and product delivery
•     Designed, developed, and deployed Silhouette, an internal ML infrastructure tool that automates cloud-based environment setup (AWS), version control (DVC/S3, Git/Bitbucket), and reproducible ML workflows (Pipenv, Cookiecutter)
•     Scaled internal tooling and drove cross-team adoption of Silhouette, reducing friction in deployment and improving reproducibility across ML projects

Lead Data Scientist

•     Shaped data science team vision, product strategy, and foundational infrastructure - establishing the team’s first tech stack, creating its first public-facing AI blog, and launching its first internship program
•     Led zero-to-one development of NLP product using claim notes (Word2Vec, LDA Topic Modeling, Concept Mining) to predict attorney involvement, delivering $2.3M in business savings
•     Built and trained a deep learning model (PyTorch) to classify vehicle damage from claim images, enhancing adjuster workflows
•     Used OCR to extract structured text from scanned claim documents to identify and surface specific types of claim denials
•     Developed a REST API web app to support labeling workflows, enabling scalable image annotation for model training
•     Owned product lifecycle and modeling for a total-loss vehicle prediction system, driving $2.5M in annual cost savings

Data Scientist II

• Perform various natural language processing tasks (R/tidytext, Python/gensim), including sentiment analysis, topic modeling, and Word2Vec/Doc2Vec
• Build a nation-wide price elasticity model using a Mixed Effects/Hierarchical Logistic Regression algorithm (with cross classified and nested random effects) to predict demand for a product at various pricing structures (R, Julia)
• Predict a claim's route by converting claim notes to Word2Vec word embeddings and feeding those word vectors into machine learning models for multi-class prediction (Python/Gensim/Scikit-learn)
• Build an interactive geo-spatial smoothing app (Python/Flask, PostGIS, Leaflet.js) for various key performance indicators using AWS S3 as the data store
• Collaboratively design and implement statistical techniques and machine learning models with team members and department heads
• Create pipeline to transfer data from SQL Server database on local server to PostgreSQL database on AWS EC2 instances
• Assist the data science team in transitioning from local servers to cloud computing on AWS
• Architect and implement RESTful APIs (Python/Flask, Celery, Redis, SQL) that expose various statistical models for consumption

Data Scientist I

Perception Health (Acquired by Huron)

•	Built machine learning models (Python) that used lab data to predict if a patient would be admitted or not and visualized results using an ROC curve and confusion matrix
•	Worked alongside Perception Health's Principal Data Scientist to analyze physicians’ referral patterns and consult hospitals on how to best reduce out-of-network referrals
•	Used GIS (PostGIS, Leaflet.js) techniques to visualize healthcare trends geographically
•	Lead production on Perception Health's flagship product since March 2015 to the present
•	Built customizable, interactive dashboards (Leaflet.js, D3.js, Crossfilter.js) into the primary platform
•	Optimized SQL queries and data preparation for faster graph rendering and page-load times
•	Utilized Agile methodologies (JIRA) to organize releases while ramping up features
•	Worked with the lead architect to optimize SQL scripts across the primary product's platform
•	Converted the platform to a RESTful API for more efficiency and to decouple the server-side code from the client side templates
•	Designed and developed an internal SQL application (Python, Flask) for non-programmers to easily upload data into a database, making repetitive communication with the database faster and more memory efficient

Software Engineer Project Lead

Perception Health

• Built machine learning models (Python, scikit-learn) that used lab data to predict if a patient would be admitted or not and visualized results using an ROC curve and confusion matrix
• Worked alongside Perception Health's Principal Data Scientist to analyze physicians’ referral patterns and consult hospitals on how to best reduce out-of-network referrals

Data Scientist / Software Engineer

Relode, LLC

• Designed and wrote programs that efficiently scraped useful data from various websites using Python and created web applications to be used internally by Relode sales representatives to access this data.
• Uploaded and maintained captured data in a MySQL database.
• Wrote Python scripts that reformated and correctly structured raw, unstructured data.

Software Developer (Contractor)

Digital Reasoning

• Parsed corrupted XML files in Python using ElementTree and Regular Expressions in order to pin point the corruption
• Designed and wrote programs that efficiently cleaned and structured the corrupt data in order to increase the accuracy rate of the firm’s predictive models

Checkd.in

• Employed web-parsing techniques to convert unstructured, raw data into a workable format to perform statistical analyses
• Utilized Facebook's Social Graph API to scrape useful data
• Designed and wrote programs that parsed and statistically analyzed Facebook data using Python

Software Developer (Intern)

Building data products @ Gridsearch | Principal DS @ Trilliant Health

I partner with businesses to bring data and AI-centric products and features to market. 

I also build machine-learning apps with and for my sons. Currently, I’m building a Natural Language Understanding app I call LADNER (Locating Assignments and Dates using Named Entity Recognition) that locates homework assignments and due dates on his teachers’ websites and emails, and then automatically adds them to my Trello calendar daily so we don’t miss homework assignments or quizzes. 

Before that, I built a machine-learning app called Achoo that predicted my son's inhaler usage using air quality, weather, and allergen data.

In my career and hobbies, I build machine learning and data-centric software that makes life easier.

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