> For the complete documentation index, see [llms.txt](https://docs.zigpoll.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zigpoll.com/guides/how-to-reduce-churn-and-cancellations.md). # How to Reduce Churn and Cancellations A cancellation is the most informative moment in the customer lifecycle and the one most companies waste. The customer has already decided to leave, which means they have nothing to lose by telling you the truth — and for a few minutes, they're still reachable. A good cancellation survey does two jobs at once: it **saves a portion of the customers who take it**, and it **tells you what to fix** so the next cohort doesn't reach this page at all. *** ## Building the survey ### Question 1 — The reason Add a **Single Choice** question: **"What's the main reason you're cancelling?"** Write options that map to *different fixes*, not to different feelings: * It's too expensive * I'm not using it enough * I'm missing a feature I need * I had a bad experience with the product * I had a bad experience with support * I'm switching to another product * My needs changed Enable a dynamic **"Other"** option. Keep the list to seven or fewer — a long list on a cancellation page gets skipped. ### Question 2 — The detail Add a **Long Answer** question: **"What could we have done differently?"** Make it optional. A required text box at the moment someone is trying to leave feels like a hostage negotiation, and you'll get "asdf" instead of an answer. ### Question 3 — The save offer This is where [Question Logic](/questions/question-logic.md) earns its keep. Branch on the reason from Question 1: | They said | Do this | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Too expensive** | Show a [Promo Code question](/tutorials/adding-discount-codes-to-your-survey.md), or use the **Generate Reward** action on Shopify to issue a discount on the spot | | **Not using it enough** | Use a **Redirect To** action pointing at onboarding, a tutorial, or a booking link | | **Missing a feature** | Ask which feature, then offer to notify them when it ships — capture the email and push it to [Klaviyo](/integrations/klaviyo.md) | | **Bad support experience** | Route to a human immediately: create a [Zendesk](/integrations/zendesk.md) ticket or notify [Slack](/integrations/slack.md) with a Question Logic action | | **Switching to a competitor** | Ask which one with a **Short Answer** question. Competitive intelligence you cannot buy. | {% hint style="info" %} Don't offer a discount to everyone. A customer leaving because a feature is missing doesn't want 20% off — and offering it trains customers to threaten cancellation for a discount. Match the offer to the reason. {% endhint %} *** ## Where to run it * **On the cancellation flow itself** — Trigger the survey when a customer clicks cancel with a [Custom Survey Trigger](/tutorials/custom-trigger.md). This is the only placement that lets you save the customer. * **Email after cancellation** — For customers already gone. You lose the save opportunity but you still get the diagnosis, and the answers are often blunter. See [Email Zigpoll Surveys](/email-zigpoll-surveys.md). * **Before they churn** — The best cancellation survey is the one you never have to send. Target at-risk customers (declining usage, no orders in 60 days) with a check-in survey and catch the problem while it's still fixable. *** ## Reading the results Track the **reason mix over time**, not the raw counts. Total cancellations move with the size of your customer base, but the mix tells you whether you're fixing the right things. * **"Too expensive" dominates** → It's rarely price. It's usually value: the customer isn't seeing enough benefit to justify what they already agreed to pay. Look at whether the cancellers activated properly. * **"Not using it enough" dominates** → An onboarding and activation problem. The product never became a habit. * **"Missing a feature" dominates** → Read the specifics. If the same feature appears repeatedly, you've found a roadmap item — see [How to Prioritize Your Product Roadmap](/guides/how-to-prioritize-your-product-roadmap.md). * **"Bad experience" dominates** → Fix this first regardless of volume. These customers tell other people. Use Z-GPT Insights to summarize the open-ended responses into themes automatically, and sync everything to [Google Sheets](/tutorials/sync-survey-responses-to-google-sheets.md) so you can chart the mix month over month. *** ## Measuring the save rate Track how many people who *start* the cancellation survey don't complete the cancellation. That's your save rate, and it turns the survey from a research cost into a revenue line. If the save rate is near zero, your offers are mismatched to the reasons. If it's very high, you may be discounting customers who would have stayed anyway — tighten the conditions in your Question Logic. *** ## Related {% content-ref url="/pages/Cpctg3qiKtbrlvPfaYLD" %} [How to Measure Product-Market Fit](/guides/how-to-measure-product-market-fit.md) {% endcontent-ref %} {% content-ref url="/pages/hMalfN8WS1TbLwlzAixD" %} [How to Prioritize Your Product Roadmap](/guides/how-to-prioritize-your-product-roadmap.md) {% endcontent-ref %} {% content-ref url="/pages/N9NzutDsp4OwGHQ91Xz1" %} [Customer Effort Score (CES)](/tutorials/customer-effort-score.md) {% endcontent-ref %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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