Exit-surveys

An exit survey is a short survey at the moment of cancellation or leaving: why are you leaving, what did not suit you, what could have retained you. The goal is to collect real churn reasons, see patterns and improve the product/service, reducing future churn. Honestly about 'not a barrier at the exit', this is critical: an exit survey must NOT hinder cancellation. Unsubscription/cancellation stays easy, and the survey is strictly optional and short. Turning the survey into an obstacle ('answer the questions to unsubscribe', mandatory fields, multi-step 'retention' flows) is a dark pattern that angers an already-leaving customer and leaves a very bad impression. We make the survey a respectful addition to easy leaving, not a gate. Honestly about answer bias: exit-survey data are biased — many leavers simply do not answer (they no longer care), and those who answer often name a surface reason ('expensive') instead of the real one. It is a valuable but incomplete signal — treat it as hypotheses, not exact statistics. Honestly about small samples: on a small number of answers it is easy to draw a wrong conclusion — a couple of reasons ≠ the main churn driver. Honestly about 'survey ≠ improvement': an exit survey itself changes nothing. The value is in reason analysis and ACTIONS (fixing what people leave over). Collecting reasons 'for a report' without reaction is useless. Honestly about the link: exit surveys provide reasons for win-back (985) and churn prevention (churn 1000) — they are input for those, not separate magic. Honestly about the effect: it helps understand real reasons for leaving and improve the product, but it is not a guarantee of reducing churn — changes decide everything. Honestly about access: a cancellation/leaving point and a survey channel are needed. An important boundary: this is exit surveys (reasons for leaving); win-back of those who left — 985; the survey approach for active ones — 996; churn-prediction — 1000. Picture this: instead of 'customers leave silently' — understanding real reasons for leaving without barriers at the exit. The base price starts from 25,000 ₽ (depends on channels and integration).

• Customers leave silently — churn reasons are unknown.
• No data on what exactly to fix so people leave less.
• A past exit survey hindered cancellation and angered leavers.
• Reasons are collected 'for a report' but not acted on.

• Setting up a short optional exit survey (no barriers at the exit)
• Easy cancellation stays easy (an explicit rejection of dark patterns)
• Analysis of reasons for leaving and pattern identification
• An action cycle for reasons (survey → analysis → fixes)
• Honest boundaries (the survey not a barrier; answer bias; survey ≠ improvement)
• A link with win-back (985) and churn-prediction (1000)
• Accounting for small samples in conclusions
• Handover and review with you

• Understanding the real reasons customers leave
• Data for fixes and for win-back/churn prevention
• Respectful leaving without barriers (easy cancellation)
• Honest boundaries (answer bias; survey ≠ improvement; no guarantee)

• We set up a short optional survey at the cancellation point
• We analyze reasons and patterns (accounting for bias)
• We build an action cycle, honestly set boundaries with you

• Can we require answering the survey to unsubscribe?

  No, categorically, honestly: an exit survey must not hinder leaving. Cancellation stays easy, and the survey is strictly optional and short. Mandatory fields, multi-step 'retention' flows and 'answer to unsubscribe' are a dark pattern that angers an already-leaving customer and leaves a very bad impression of the brand. We make the survey a respectful addition to easy leaving, not a gate at the exit.

• Can exit-survey data be fully trusted?

  As a signal — yes, as exact statistics — no, honestly. Answers are biased: many leavers simply do not answer (they no longer care), and those who answer often name a surface reason ('expensive') instead of the real one. Plus on a small sample it is easy to draw a wrong conclusion. We treat reasons as hypotheses to verify and act on, not as an exact picture of churn.

• Will collecting reasons for leaving reduce churn?

  Not by itself, honestly: an exit survey changes nothing without ACTIONS. The value is in reason analysis and fixing what people leave over. Collecting reasons 'for a report' without reaction is useless. Plus exit surveys are input for win-back (985) and churn prevention (1000), not separate magic. Changes based on reasons reduce churn, not the fact of a survey — we build exactly that action cycle.