Exit surveys are not the most exciting task that you have to deal with when you are running a business, but they are essential to understanding what you may want to improve in your business.
Departing customers take the time to give us their honest feedback and the reason they leave our service. We at DNSimple want to listen to those comments and figure out what we can do to improve our offerings. We make a point to put our customers first, so exit surveys are something that we take seriously. We are aware of the importance and value of the information we gather. Exit surveys act like a temperature gauge.
Collection and clean-up
First, we collect our exit survey answers over a period of time (right now we look at the last 12 months of exit surveys). With that list in hand, we start what I call the clean-up phase. The clean-up phase involves reading through all the exit survey answers we collected, removing the ones that are gibberish or otherwise useless. With a "clean" list we read each answer.
At first glance, I found that in our case people were really kind: over half of the answers had a positive remark. Even though those customers were leaving us, they took the time to explain why; and sometimes it's not for a reason you might think. Some had to leave because they sold their business or for other reasons that were out of their control. Sadly some went out of business. Others closed accounts to consolidate multiple accounts into a single account. Some even apologized for closing their account!
After the first quick read through, it is time to read again and analyze all the answers more throughly, trying to connect them to each other or to find a trend. We do this by sorting all of the answers into categories.
Sorting the answers into categories is a long and slow process. You have to read all the answers again and find a way to tie them together.
I decided to work through this using Google spreadsheets. I set up the first column with the response and then one column for each major category. I marked each category with a X when the text was in that category. I added new categories as necessary. I also put a exclamation point next to responses that were interesting, and a question mark when it was difficult to understand what the customer what trying to say or determine the feature they wanted us to implement.
Once the categories are in place we have to apply number to be able to determine the pertinence of the responses. If only one person complaining about something, it is not the same impact and value that if there is a majority of people complaining. Even so, you still have to be aware and attentive to the one good suggestion.
We have to be able to determine what matters enough to our customers to justify canceling their account with us and going elsewhere. It could be because we are missing a functionality, or because there is a misunderstanding in our way to explain a feature. The exit survey helps by opening discussions amongst the team and leading us to questions we should ask ourselves about how our service works.
Sharing with the team
After the work is done on the data, it's time to share with the rest of the team. The raw data is available to the team, linked from our wiki, but we also have a summary along with an overview of the reasons why some of our customers left available as well. The team then can review, react, and comment on the customer feedback.
The exit survey is a way to realize our weaknesses and our strengths, and to understand if we are on the correct path with the way we treat our customers. What I realized is that the next time I am given an opportunity to fill in an exit survey, I will take the time to give my honest feedback because there's a good chance that someone will read it and will value the opinion I am giving to make their business better.