Onboarding Friction Observation Log Template
Record what a new user actually attempts, where progress stops and what assistance changes the outcome before assigning causes to drop-off.
When to use this template
Use this when an onboarding dashboard shows unfinished setup but does not explain what happened in the user’s task.
Choose another approach when: You want to record private sessions without permission, assume every exit means disinterest, or treat facilitator-guided completion as independent success.
Gather these inputs
- A relevant voluntary participant and safe task context.
- The supported first-use journey and actual completion condition.
- An appropriate minimal observation record and permission boundaries.
Copy and adapt the template
Edit the text below and copy it into your own document. Edits stay in this browser field and are not submitted or saved by this page.
Worked example
Illustrative example, not a Crany customer result. Replace every example detail with facts you can verify.
In an illustrative session, a new designer reaches a checklist screen but does not create an item. Observation shows they are looking for an existing project imported from signup, while the product never imported anything. The log records that expectation and the actual empty state. After the facilitator explains the starting state, the designer continues. That completion is marked assisted. The team investigates orientation and expectation-setting instead of labeling the person unmotivated or claiming that a missing event proves the interface caused abandonment.
How to use it
- Define a safe realistic task and its observable completion condition.
- Record actions, system state and assistance separately from interpretation.
- Use the evidence to choose a targeted follow-up rather than assign a broad motive.
Check before using it
- A stopped session has no invented reason attached.
- Assisted and independent task completion remain distinct.
- Private project content is not captured unnecessarily.
What to measure
Compare concrete obstacles across relevant sessions and verify targeted changes in later observations. The log diagnoses task conditions; it does not estimate population-wide drop-off causes or retention effects.
Research and sources
Realistic task observation and context-sensitive help inform this original log. It is not a session-recording setup or permission to collect private user activity.
- NN/g: Turn User Goals into Task Scenarios for Usability Testing — checked 2026-10-23. Realistic actionable user tasks without interface clues for qualitative usability observation.
- NN/g: Onboarding Tutorials vs. Contextual Help — checked 2026-10-23. Task-relevant contextual help, dismissibility and avoiding unnecessary memorization or interruptions.
- Yale: User Interview Example Questions — checked 2026-10-23. Interview structure, current tasks, past experience, alternative workflows and discovery paths.
About Crany
Crany is an AI marketing co-founder in development for software founders and vibe coders, designed to strategize, execute approved marketing and improve based on results. This free resource is usable independently of the product. Join the public waitlist.