Root-Causing a 25% Drop in Notion's New Free-Plan Accounts
Company: Notion
Role: Product Manager
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Other
Free sign-ups on Notion are down 25%. How would you work out what caused the drop?
```hint Find where the drop lives
Before brainstorming causes, make sure the number is real, then narrow down which step of the sign-up path and which kind of new user account for the missing quarter.
```
### Clarifying Questions
- What period does the 25% cover, and against what baseline: the previous week, the same period last year, or a forecast?
- Did the drop appear overnight or build gradually over several weeks?
- Does a free sign-up mean any newly created account, or only one that finishes onboarding and creates a workspace?
- Have paid-plan, trial or team sign-ups moved too, or only free ones?
### What a Strong Answer Covers
- Validating the metric first: its definition, the tracking behind it and a seasonally fair baseline
- Locating the drop by funnel step and by segment, such as acquisition channel, region, platform, sign-in method and user type
- Checking internal causes (releases, sign-up flow or plan changes, outages, marketing spend, website changes) before external ones (seasonality, competitors, search engine changes)
- A ranked list of hypotheses, each paired with the data that would confirm or rule it out
- Judging the impact on activated and paying users, and the next actions and monitoring
### Follow-up Questions
- The drop turns out to be almost entirely organic search traffic to the website. What do you check next?
- Sign-ups fell 25% but new weekly active users barely moved. Is this still a problem?
- How would you tell a competitor's launch apart from the effect of a change Notion shipped the same week?
Overview: A metric-diagnosis interview question about a 25% fall in free sign-ups on Notion. It tests whether a product manager validates the data first, breaks the sign-up funnel down by step and segment, separates internal from external causes, and ranks hypotheses with the checks that would confirm each one.