Audit intermediate Works with: Any AI

Survey Fatigue and Response Rate Improvement Audit

Before after Has example

Increase completion without hurting data quality.

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Improve completion and data quality in my survey. Audience and context: [AUDIENCE_AND_CONTEXT]. Survey tool and delivery channel: [TOOL_AND_CHANNEL]. Current response and completion rate, and where people drop off: [RESPONSE_DATA]. The current survey: [PASTE_SURVEY].

Return:
BEFORE: a summary of the survey as it is (number of questions, estimated minutes, number of open-ended questions, grids, required fields, order), then the invitation text with annotations in square brackets for each problem.
DIAGNOSIS: ranked causes of dropout (length, difficult early questions, matrix grids, vague purpose, privacy worries, mobile problems, timing).
AFTER: a revised invitation (under 90 words, with purpose, time needed, privacy statement, deadline), a revised question order, a list of questions to cut or merge (with reasons), reworded questions that were confusing, and a progress indicator plan.
TEST PLAN: how to pilot with 10 people, what to measure, and a plan for reminder timing.

Do not propose incentives that distort the answers without explaining the risk. Keep the survey under [TARGET_MINUTES] minutes.

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Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.

BEFORE: 34 questions, about 14 minutes, 3 matrix grids of 10 rows, 6 open text boxes, all required. Drop-off: 41% by question 12. Invitation: "Please complete our survey" [vague], no time estimate [problem].
AFTER invitation: "Help us improve the app in 4 minutes. 9 questions, anonymous, closes Friday. We'll share what we change."
Cut: 15 questions (nice to know), merged 3 grids into 1 of 5 rows, made 4 text boxes optional.
Reordered: easy multiple choice first, demographics last.
Pilot with 10 people; measure time and drop-off. Target: under 5 minutes, completion above 70 percent.

• response-rate
• fatigue