Metrics that quietly disagree
Revenue on the dashboard does not match Stripe. "Active user" means three different things in three different queries.
Fractional Data & Analytics Lead for startups
Analytics you can trust, built at startup speed.
AI lets a small team ship dashboards, metrics and in-product analytics in days. Combine Analytics adds the senior data judgment that makes sure the numbers are right, and stay right as you grow, without hiring a full-time data lead.
The problem
Easy to build. Easy to get wrong.
AI tools can produce a dashboard in an afternoon. Whether the numbers are right, safe and ready to scale is a different question.
Customer data in the wrong place
Analytics inside your product without proper tenant isolation can show one customer another customer’s data. That is the kind of bug that ends deals.
Built for a hundred rows
Queries running live against production, pipelines nobody can re-run, and data costs that grow faster than revenue.
Decisions on numbers nobody checked
Founders, boards and investors steer by metrics that were generated quickly and never verified.
Services
From first metric to fully grown.
Three services that follow the way a startup's analytics grows. Start wherever you are today.
- 01 Start right.
Data & Analytics Seed
The first design and build of your analytics: internal numbers for founders and investors, analytics inside your product for your customers, or both.
What you get
- Agreed metric definitions and a tracking plan
- A data model and pipeline sized for your stage and budget
- First dashboards or embedded customer-facing analytics
- Documentation your team and your AI tools can build on
A good fit when
- You are about to add analytics and want it done right the first time
- Data is piling up and there is no single source of truth
- 02 Check what you have built.
Data & Analytics Review
A fixed-scope review of your existing setup for correctness, security and scalability, with clear, prioritised findings.
What you get
- A walkthrough of how data flows from source to screen
- Key metrics checked against your source systems
- Access and tenant-isolation review for customer-facing analytics
- Scalability and cost assessment
- A written report and a debrief call
A good fit when
- Your analytics was built fast, much of it by AI
- You are heading into fundraising or due diligence
- You are about to put analytics in front of customers
- 03 Keep it right as you grow.
Data & Analytics Care
A monthly arrangement that gives you a data lead on call: regular health checks of your setup and quick help when something breaks or you need something new.
What you get
- A monthly check-in and health check
- Priority response when numbers look off
- Review of changes made by your team or your AI tools
- New requests handled at an agreed hourly rate
A good fit when
- Analytics is live and matters to your business
- A full-time data hire is not justified yet
How it works
Simple, scoped, no surprises.
- 1
Intro call
A free 30-minute call about your product, your stage and your data.
- 2
Scoped proposal
A clear scope and a fixed price for Seed or Review, usually within a few days.
- 3
Delivery
Remote and async-friendly, working directly in your tools and repositories.
- 4
Care
Optional. Stay covered month to month once your analytics is live.
Who it is for
Startups that build fast and want to stay right.
Solo founders building with AI
You move fast with AI tools and need someone who knows where data goes wrong.
Small SaaS teams
You want to offer analytics to your users without building a data team first.
Pre-seed to Series A
Investors are asking for numbers, and they need to hold up.
About
Senior data judgment, without the full-time hire.
Combine Analytics is a consultancy for startups that need data and analytics leadership but not yet a full-time hire. It is run by Thomas Jauho, a data and AI leader with more than 10 years of experience building and leading analytics teams at global consumer brands and at McKinsey. Based in Copenhagen, working remotely with startups across Europe and beyond.
At McKinsey I was Chief Analytics Officer and COO of a predictive-analytics start-up, so I know the startup side from the inside. At IKEA I owned data and analytics for ikea.com and the IKEA app, more than 3 billion visits a year, with a simple rule: data foundations before dashboards. Today I lead advanced analytics and AI at a global consumer brand, where forecasting engines produce 1.5 million forecasts every week.
I start with the business problem, prefer proven methods over trends, and explain technical choices in plain language. I also build with AI coding agents every day, so you get senior judgment at startup speed.
- 10+ years leading data & AI
- Ex-IKEA
- Ex-McKinsey
- Start-up CAO & COO
- MSc Physics, DTU
FAQ
Questions founders ask.
What does “fractional” mean?
You get a senior data and analytics lead for the hours you actually need, on a project or monthly basis, instead of a full-time hire.
We already use AI to write our SQL and dashboards. Why do we need you?
AI is very good at writing queries. It is much less reliable at deciding what a metric should mean, how data should be modelled, or what breaks when ten customers become ten thousand. That judgment is what you get. I use AI heavily myself, so you keep the speed.
Which tools and stacks do you work with?
Mostly stack-agnostic: Postgres, BigQuery, Snowflake, DuckDB, dbt, product analytics tools and the usual BI and embedded-analytics options. The recommendation is always the smallest stack that does the job.
How is pricing set?
Seed and Review are scoped and priced as fixed projects after the intro call. Care is a monthly fee, with additional work at an agreed hourly rate.
Do you need access to our data?
Usually read-only access to the relevant systems. Happy to sign an NDA and a data processing agreement before anything is shared.
Do you work remotely?
Yes. Based in Denmark (CET), working in English, with calls scheduled to suit your time zone.
Contact
Tell us what you are building.
A few lines are enough. You will get a personal reply, usually within one working day, with a suggested time for a free 30-minute intro call.
Prefer email? hello@combine-analytics.com