Know exactly where your next $1 of marketing should go
We help growth-stage and enterprise brands build Marketing Mix Models and run experiments that drive confident budget decisions — without black-box attribution or vendor theatre.
who we help
brands who struggle with

Conflicting Attribution
Your paid channels each claim 140% of revenue. Attribution tools aren’t helpful at all. You’re stuck making budget decisions based on intuition.

opaque mmm vendors
MMM vendors pitch magic but deliver opaque models you can’t trust or explain. You need a tailored approach and someone who speaks ‘finance’ lingo.

no confidence in budget decisions
You’re pushed to cut budgets — but you can’t answer “what’s the least painful reduction?”. You need a repeatable way to reallocate budgets with confidence.

weak or inconsistent experiments
Experiments happen, but they’re underpowered, inconsistent, and ignored that are costing you money. You need a unified MMM + experimentation approach.

data that’s not model ready
Channel structures, promos, and tracking are too messy for reliable measurement, creating noise instead of insight. You need someone to clean the data and get it ready for the MMM.

pressure from finance
CFOs want clear justification for spend — but the current measurement setup can’t support the conversations.
How we work
four steps to smarter spending
01
Diagnose
We audit your data, experiments, and media structure to find what’s holding measurement back.
02
Model
We build transparent MMM and causal models tailored to your market, channel mix, and data reality.
03
Experiment
We design and run structured tests to validate and refine the models.
04
Reallocate
We help teams shift budgets, model scenarios, and forecast outcomes — with confidence.
READY?
2 DIFFERENT WAYS WE CAN HELP YOU
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meet the founder

GUI DIAZ-BERRIO
Founder, Pinemarsh. Data Scientist. Author. Teacher. Speaker.
Economist by training and at heart, Gui learned how to code at 6 and has been combining maths and code his whole career.
With over 15 years of experience in data analytics and marketing optimization he specialises in machine learning, econometrics, and Python for actionable insights, he focuses on cutting-edge Media Mix Modelling (MMM), Forecasting, and Experimentation.
Gui is particularly invested in demystifying data analytics for marketing, and his main focus is on increasing awareness, skills and critical thinking around data, marketing and statistics.
In 2024 he wrote “Data Analytics for Marketing“, by Packt.
He can be seen and heard in conferences, analytics meet-ups alike or his YouTube channel.

Data Analytics for Marketing Book
A practical guide to analyzing marketing data using Python
With so many types and sources of data, tools and techniques to shape data, from small to big data, not to mention AI, it can be difficult to navigate the world of data analytics.
In this book, Gui takes you through the nit and gritty of advanced data analytics for marketing using Python, in a simple and accessible manner.
brands we’ve worked with












testimonials
Why choose pinemarsh?
Deep Operator Experience
Built and deployed MMM/experimentation programs inside B2C, subscription, and retail brands.
Econometrics + Machine Learning + Paid Media Expertise
Not academics — practitioners who know how MMM must interface with campaign ops.
Speed and Transparency
Actionable insights in weeks, not nine-month waterfall projects.
Repeatable Playbooks
You keep the code, templates, model specs, and experiment playbooks.
Independent & Incentive-Aligned
No agency bias. No vendor lock-in. No dashboards to justify.
how to get started
01
Free Discovery Call
Understand your measurement gaps
02
Audit & Roadmap
3–4 weeks to produce a concrete plan
03
Build or Train
choose consulting or training based on your team