True Intent Study

Real-time capture of user intent and abandonment reasons through exit surveys, revealing what users were actually trying to accomplish and why they did not complete their goal.

Process

Key Fields

Question it answers	Why are users leaving? What were they actually trying to do? What would make them stay and complete their task?
Participants & timing	200-500 abandonment survey responses · continuous collection · 2-4 weeks per analysis cycle
AI compatibility	AI analyzes survey text, clusters abandonment reasons, and identifies actionable vs. structural problems.
Output	Abandonment reason analysis, intent-to-action mapping, problem prioritization matrix, solution recommendations

Use when

Abandonment rate is high and the cause is unknown
True user intent needs to be captured in the moment, not recalled later
Quick feedback on a specific page or flow is needed

Skip when

Abandonment rate is already healthy and not a problem to investigate
Response rate is too low to yield actionable data

Common Mistakes

Asking "Why did you leave?" too broadly

Users give surface reasons (shipping too expensive) when the real reason is deeper (expected to see free shipping before reaching checkout). Ask "What were you trying to accomplish?" first.

Low response rate skewing findings

A 2% response rate from abandoners is heavily skewed toward people with strong opinions. Note the response rate; do not extrapolate as representative of all users.

Not categorizing solvable vs. structural problems

Someone abandons because delivery takes 2 weeks and you cannot offer 1-day shipping. Separate solvable problems (you can change) from structural ones (you cannot) and focus effort on solvable items.