Marcin Żmigrodzki — Independent
Metodyka projektu discovery
September 20, 2024
15:15
Evidence-Based Management
🇵🇱 Polish
Evidence-Based Management
North Star metric, or how analytics can get your team to align and cooperate
About
When done right, analytics translates your strategy into simple and actionable metrics. Thanks to this, your teams can use them to focus their effort to achieve the biggest impact possible by working on clearly defined, shared goals. In this presentation, you'll learn about the best ways to get there and typical traps and problems to watch out for. Special focus will be given to the North Star metric: the single product metric that, if you can find it, can coordinate and align the efforts of everyone in the product.
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From the recording
Talk in brief
A rigorous argument for using product analytics to create shared knowledge, not to distribute raw data or replace strategy. The talk warns against unrestricted data democratization, separate success metrics for every team, and libraries of dashboards that generate cost, noise, and metric gaming. Better foundations include a searchable knowledge repository, clear metric definitions, skilled analysts who communicate results, and deliberate presentation of findings. Only then should a team consider a North Star metric: one simple, actionable, effectively unbounded measure of customer value. A detailed Base CRM case shows how an obscure usage metric aligned teams around the wrong behavior and consumed a year of effort without improving what customers actually wanted.
Key takeaways
- 01
Turn data into knowledge before distributing it
Raw access creates cost and conflicting interpretation unless specialists transform evidence into conclusions people can use.
Watch from 0:00 - 02
Do not substitute metrics for strategy
Analytics can express and test a direction, but financial targets and abundant data do not explain how a product will win.
Watch from 2:00 - 03
Share insights instead of dashboard inventory
Searchable conclusions spread learning, while automated reports accumulate maintenance and allow selective arguments from noisy data.
Watch from 10:01 - 04
Make analysts responsible for explanation
The person who develops an analysis is best placed to present its reasoning, surface errors, and help decision-makers apply it.
Watch from 14:02 - 05
Measure customer value, not internal habit
A North Star must describe why customers choose the product and remain understandable and influenceable across the organization.
Watch from 20:00
Read edited transcript highlights
These concise notes were edited from automatic captions and checked against the talk structure. They are not a verbatim transcript.
Stored information is a cost until interpreted
Data requires systems, maintenance, transformation, and human attention. It does not contain a mechanism that automatically converts volume into business value. The return appears only when someone builds trustworthy knowledge from it and that knowledge changes a decision. Product analytics should therefore focus on understanding behavior and communicating conclusions rather than celebrating how much information is available.
Watch from 0:00Local metrics can produce global conflict
Giving each team its own success measure appears to create accountability, but it also creates a set of competing games. People learn how to improve the number that evaluates them, sometimes by exploiting its definition rather than improving the product. A manager is then left reconciling teams whose incentives point in different directions, which is the opposite of alignment.
Watch from 6:01The repository should preserve conclusions
Every analysis does not need to become a permanent dashboard. Dashboards are software that require maintenance, create noise, and can be cherry-picked once their number grows. A more useful repository records the question, reasoning, conclusion, and context in searchable form. That allows one insight to support later investigations without forcing everyone to operate analytical tooling.
Watch from 10:01A North Star is a high score with consequences
People naturally look for ways to influence any metric placed in front of them. When the shared measure reflects real customer value, improving the score requires improving the underlying product reality. When it is chosen poorly, the same energy drives coordinated work in the wrong direction. Having no North Star is therefore safer than installing a misleading one.
Watch from 18:02Base CRM measured usage instead of success
The selected metric described the share of paid users who opened the software on a given day. It was difficult to explain, hard for teams to influence, and centered the company’s desire for habitual use rather than the customer’s desire to close sales. A specialist growth team spent months trying to move a behavior that the product interface alone could not meaningfully change.
Watch from 34:01Explore WaysConf 2026
