Reading first-session friction from sparse events
When early-journey tracking is incomplete, you can still reconstruct hesitation patterns without inventing precision you do not have.
Sparse instrumentation is common in young products. That does not mean you must wait for a perfect schema before talking about onboarding quality.
Begin with what exists: time-to-first-key-action, permission grant rates, and exits from setup screens. Pair those with five structured user interviews focused only on the first session. Qualitative notes fill gaps that events cannot yet see.
Document every assumption you make. If you estimate that a blank state causes drop-off, mark it as a hypothesis and schedule the two events needed to confirm or retire it in the next sprint.
Teams that treat incomplete data as temporary scaffolding move faster than teams that wait for a pristine warehouse before asking why new users leave.