Do you fully understand why your customers cancel your service? Not when or how, but why?
Using time-based cancellation data to perform churn and cohort analysis will show you when they leave (and allow you to surmise why), but this alone can’t tell you the real reasons behind it.
“So I know my customers have a higher propensity to leave in the first month – if I only I knew why.”
To really understand why your customers are leaving, you need to go deeper.
In this post I will look at three way you can find out why your customers cancel:
- Post-cancellation survey
- Identifying on-site friction points
- What separates successful and churning customers
Don’t be afraid to ask – Post-cancellation survey
It may seem counter-intuitive to expect customers who cancel your service to answer some questions, but you’d be surprised how many will.
Set up an automated email (fired upon cancellation) that links to a very short survey, asking why they left, would they use you again and the opportunity to leave open feedback.
I have used this method myself, and got some great insights.
For example, I found:
- They found getting set up difficult – Our onboarding upon initial login was not good enough, and we needed to hand hold a lot more when customers tried to use the service for the first time.
- We were forcing them to contact support for basic questions – Our support database had out of date content and it was difficult to navigate.
- We assumed customers would find products themselves if they needed them – Customers did not know about some key add-ons we sold.
- It wasn’t all negative! – Half of the customers who cancelled did so because they didn’t need the product anymore. In fact they had a positive view of us, and would use us again. The way we would remarket to that group instantly changed.
Here is an example survey you can use.
The aim is to get as much information as you can, in as few questions as possible.
Don’t let yourself fall in to the trap of asking these questions and not using the information. Over time, as new projects grab everyone’s attention and energy, this is a real danger. The best way to prevent this, is to automate and formalise as much of the process as possible.
Ask > Collect > Catalogue > Store > Analyse > Act > Measure
There are six stages to using customer feedback to inform your product and brand marketing:
- Collecting – Collection of the data (dealt with above)
- Cataloguing – Putting the data into distinct groups
- Storing – Where the feedback is stored to be retrieved
- Analysing – The ability to analyse volume, trends and value
- Acting – Putting the ideas into practice
- Measuring – Are the changes having a positive impact?
The way you structure your questions will have a huge impact on your ability to store the feedback and act on it. Closed questions and selectors make it easier to identify trends.
I would recommend bringing all the data into one single database/GUI, all linked to your customer accounts. This data can be used by the your customer services, sales and marketing team for their specific needs.
- Using their characteristics: Market segments and persona data
- Transactional behaviour: Customer segmentation
- Their brand sentiment: Net Promoter Score
- Value of that segment: No. customer accounts, Monthly Recurring Revenue, Life Time Value
Combining this data will allow you to tailor the messages you send, as well as track a customer’s metrics over time – including reactivations.
This also reduces the number of irrelevant emails going to those who have negative brand sentiment, and are unlikely to buy.
There is nothing worse than spending time giving feedback, only to feel like it has disappeared into a black hole.
Use the positive changes you make to customers’ products and services to curate positive brand sentiment, reactivate churned customers (“You spoke, we listened, we acted. Come back!”)
Identify the specific points of friction, not just the general page
Are there areas of your website/control panel that people find difficult to use?
Google Analytics will be able to tell you how long people stay on a page, and which pages see the most significant page exits, but it won’t be able to tell you why.
For this you will need to be able to report on how customers interact with a page’s components.
You can quickly and easily set-up heatmaps, funnel visualisation, user recordings and more using www.hotjar.com.
Here is an example of their visitor recording…
How many of your customers are finding and clicking on the page’s primary action points?
I have used the free plan on a personal website and the data is a gold mine. It is also a very simple copy and paste job to get set-up.
What differentiates successful customers and churners?
The first month is traditionally the most critical for any SaaS product. Based on a multitude of public case studies/blog posts (and my own experiences), this is when customers are most likely to churn.
Your challenge is to give customers with the right tools, signposts and motivation to successfully use your product.
The first step is to identify the most important quick wins that customers who stay long-term perform, compared to those who leave. This is the ‘why’.
Generally this tends to be the “Aha!” moments – those moments that tip the customer over from a passive user to an active user.
To use my own personal experiences, with MailChimp it was:
- When I saw the first subscriber appear in my mailing list
- When I successfully sent out my first newsletter and saw the stats rolling in
You’ll notice there were two moments.
In some cases you may have one moment, and in others you may have multiple moments – there is no set rule.
If we assume my MailChimp subscriber moment is what divides customers who renew and customers who cancel, I would…
- Focus my efforts on educating people how to add a subscription form to their website, and import any existing mailing lists.
- Include a progress bar/ list in the control panel that includes this as one of the key steps to tick off.
- Set up an automated email to accounts that haven’t added a subscriber within x days (where ‘x’ is the average number of days it takes a renewing customer to add their first subscriber).