.02 Data
You have data. You're missing decisions.
Data analytics for startups: I help you define the digital product metrics that matter, set up your startup's KPIs, and create a culture where data guides decisions.
The problem
Data without action
You have Google Analytics, Mixpanel, Amplitude, Metabase... and ten dashboards nobody looks at. The data is there, but data-driven decision making doesn't happen: decisions are still made by intuition.
There's no consensus on what metrics a startup should measure. Each team member looks at different numbers, and nobody knows if the product is doing well or poorly.
When someone asks "how was the launch?", the answer is "seems like it went well" instead of concrete data.
Signs you need help
- You have analytics tools but nobody uses them regularly
- You don't know if a feature was successful after launching it
- Each stakeholder has their own definition of success
- Tracking is broken or incomplete and nobody fixes it
- Decisions are based on opinions, not evidence
The solution
How we work
It's not about having more data, but having the right data and knowing what to do with it.
Metrics definition
We identify the north star metric that aligns the entire team, and the secondary metrics that support it.
- • North star metric and metrics tree
- • KPIs by area (growth, engagement, retention)
- • Success criteria for experiments
Startup analytics setup
We set up the necessary tracking (and only the necessary) to measure your digital product with reliable and actionable data.
- • Current tracking audit
- • Events and properties plan
- • Operational dashboards (not decorative)
Data-driven culture
We create rituals and processes so that data is used day-to-day, not just in presentations.
- • Weekly metrics reviews
- • Experimentation process
- • Learning documentation
What you get
📊 Guide: Metrics for Startups
What metrics a startup should measure, how to define digital product KPIs, and north star metric examples.
Download guideComing soon
Metrics clarity
The whole team knows what number matters and why. No more discussions about what to look at.
Tracking that works
Events configured correctly, without duplicate data or gaps. Data you can trust.
Faster decisions
When data is clear, decisions are made in minutes, not in 2-hour meetings.
Experimentation culture
A process to test ideas, measure results, and learn from each launch.
When it fits
- ✓You have a product in production — with real users generating data you can analyze.
- ✓You want to grow with foundation — not just "move fast", but learn from each action.
- ✓The team is willing to change — adopt new data-based processes and rituals.
When it doesn't fit
- ✗You want pretty dashboards — this is for making decisions, not for impressing investors.
- ✗You don't have users yet — without user data, there's not much to analyze.
- ✗You're looking for ML/AI magic — this is practical analytics, not sophisticated predictive models.
Want to make better decisions?
Let's talk about your current data situation and see how to improve it.
