Exit surveys are instrumental in understanding why customers cancel. These two questions will ensure you get actionable feedback.
We studied exit surveys from top SaaS products and discovered two essential questions:
What’s great about these questions is they help you understand churn at two levels.
The first question is easy for customers to answer and provides a high-level overview suitable for aggregate analysis.
The second question allows for more personal responses from customers. Not everyone will respond, but the answers you do get can be golden.
Let’s take a look at how to implement these questions in your exit survey.
How should you conduct your exit survey?
Follow-up surveys see low response rates (~8%). Phone calls get great results but are time consuming. To maximize feedback with the least amount of effort, integrate your survey into your cancellation flow.
As stated above, this question should provide a multiple-choice list of answers to make it painless for customers to answer.
Based on our analysis, the most common options are, in order of frequency:
Use these as a starting point. When selecting options, strive for completeness but balance this against overwhelming your customer. Too many options may be frustrating. The exit surveys that we analyzed had an average of six options.
A majority of the surveys we reviewed included an "Other" option, but there are pros and cons to doing so.
The main benefit is that it reduces noise in your data. If none of the other options matches the reason a customer is leaving, whatever choice they pick will reduce the accuracy of your data.
On the flip side, you don't gain meaningful insight from this answer, and some users may opt for "Other" because they didn't want to spend the time to think more deeply about their real reasons for leaving.
TIP: Enable "Other, please specify" in ProsperStack from the flow editor.
People may favor the first few options in your "reason for leaving" question.
Consider randomizing the order to reduce the effect of this bias.
TIP: You can enable option randomization in ProsperStack from the flow editor.
Reason for leaving data has many uses, including:
Correlate reasons for leaving to lost MRR to prioritize improvements.
Launch win-back campaigns segmented by reason for leaving.
Offer incentives to stay based on answers. For example, if the customer says the product is too expensive, offer a discount.
This question asks for open-ended feedback, which allows customers to better convey attitude and feelings.
You’ll find those that answer this question offer more insights and motivations than you might have anticipated.
If you see recurring feedback to this question, you may want to add it to your predefined options.
When you combine these two questions, you get the perfect blend of quantitative and qualitative data.
Criticism isn’t always easy to take, but truly listening to your customers' answers will help you improve.