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How to measure and improve customer retention using qualitative data
Traditional metrics like customer retention rate (CRR) and customer lifetime value (CLTV) are good to know, but they don't tell you the whole story of customer churn. To really make a difference in your retention rate, you need to know why customers stop using your product—and how you can get them to stick with it.
Last updated15 Sep 2021
So, how do you do that?
With a combination of traditional web analytics data and user behavior insights.
In this article we'll show you how to uncover insights about where, why, and how your customers churn. We cover:
What is customer churn?
Customer churn is the loss of customers (those that stopped using your product) during a time frame.
Calculate customer churn rate by dividing the number of customers lost during a time frame by the number of customers you had at the start of that time frame.
For example, let’s say you had 1000 customers at the beginning of a quarter, but at the end of the quarter you had 950 customers (50 customers churned). Your customer churn rate was:
50 / 1000 = 5%
Understanding customer churn rate can help you set goals to improve customer retention.
What is customer retention?
Customer retention is the ability to keep customers using your product or service. Customer retention is a common KPI that suggests that your product remains
for your customers over a period of time. That is, your product continues to serve its purpose for your users.
Why measure customer retention?
Measuring customer retention helps you predict
customer lifetime value (CLTV)
by indicating how long customer cohorts are likely to stay with you and how much profit those customers will bring your company, on average.
Most importantly, measuring customer retention helps you provide better services and products by prioritizing your business growth around the happiness of your current customers.
3 ways to measure customer retention
To improve customer retention, start by tracking metrics that will help you understand your current retention rate.
Here are three important customer retention metrics:
1. Customer retention rate (CRR)
Customer retention rate (CRR) measures the number of customers who stay with your business in a time frame. CRR is the inversion of customer churn rate (more on this metric later).
Understanding CRR can help you
safely assign budgets
identify when to increase retention efforts
identify when to run a retention campaign
Customer retention rate = (Number of active customers at the end of a time frame / total number of active customers at the beginning of that time frame) × 100
For example, let’s say at the end of a quarter you had 120 active customers, but you started the quarter with 150 customers. Your customer retention rate would be:
(120 / 150) x 100 = 80%
2. Annual churn rate
Annual churn rate is the percentage loss of customers—or revenue—per year.
Running a yearly analysis of your customer and revenue churn will help you understand your profit and loss (P&L) throughout the (fiscal) year. Tracking annual churn rate can also help you get buy-in to prioritize customer retention.
Annual customer churn rate = (Number of lost customers during 12 months / total number of customers at beginning of 12 months) x 100
Annual revenue churn rate = (Total lost revenue during 12 months / total expected end-of-year revenue) x 100
For example, if you started the year with 300 customers with a collective annual contract value (ACV) of $7900, and 40 of those customers churned with a collective ACV of $2280, your annual churn rates would be:
(40 / 300) x 100 = 13% annual customer churn rate
(2,280 / 7,900) x 100 = 28% annual revenue churn rate
💡 Pro tip: you can predict annual churn rates even if you don’t have the data to measure an entire year. Just measure a month using the same equation, and apply the churn rate percentage to the year.
But keep in mind that these are predictions and estimates. Many factors affect churn—like seasonality, campaigns, competition, and economies—so take predictions with a grain of salt.
3. Cohort customer churn rate
Cohort customer churn rate is the loss of customers within a specific group compared to another variant group or groups. It might look something like this:
Your cohort customer churn rate helps analyze the effectiveness of your retention methods.
💡 Pro tip: keep your cohort customer churn analysis within the same date range to eliminate external variants that may affect churn, like seasonality or competitors' campaigns.
How product teams can use cohort churn rates to inform product tests
In the cohort example above, you could exchange the date column for UI or UX variants for each cohort.
For example, you could give Cohort A a 3-step in-app product tour and Cohort B a 5-step product tour. In this case, the experience you're testing is whether a 3-step product tour retains more customers than a 5-step tour:
Split customers into cohorts depending on variants
Measure the churn rate of all cohorts across the same time span
Compare data to suggest which method retained more customers
Try to change only one variant per cohort so you can more easily identify why more customers churn between one group and the other(s).
Also, keep in mind that you can test a variant in as many different ways as you want to. Taking our example, it could look like this:
Cohort A: 3-step product tour
Cohort B: 5-step product tour
Cohort C: 6-step product tour
Continue to A/B test changes in UI or UX to see which change(s) give you the best retention rates. Once you’ve landed a positive result, continue to micro-test changes within it, and keep fighting churn.
Quantitative metrics (numerical metrics like the ones we've listed here) help highlight issues and opportunities, but they're limited: you still don’t know what the user wants.
To make data-driven changes that are user-centric, you need to combine your traditional (quantitative) analytics data with user behavior (qualitative) insights:
3 ways to use behavior insights to improve customer retention
Quantitative research is a proactive approach to retaining customers. Qualitative and user behavior research methods can be reactive efforts of your quantitative results—or stand-alone proactive initiatives. They can help you discover:
How customers experience and interact with your site or app
What’s going wrong (why customers are churning)
What’s working well (why customers stick around)
and then either improve, replicate, or enhance your findings.
Behavior analytics tools let you gather firsthand insights into user behavior, revealing what users like and dislike, their friction points, and issues or blockers that cause them to leave—like unclear directions, confusing UI and navigation, or UX issues like broken elements or website bugs.
Here are three ways to use behavior insights to answer the question that really needs answering:
Why do customers leave, and how can I get them to stay?
1. Understand individual user actions with session recordings
Session recordings (or session replays) are replays of how individual users interact with and experience your site or product.
Recordings can help you understand a user's actions before they churn—which can help you identify why they churn by revealing specific issues or blockers they experience with your product, like:
Poor user interface
Disengaging product tour
A bug or broken feature
🔥 If you're using Hotjar
Use recordings filters to analyze session recordings that include a specific exit URL to find out how users behave and interact with your site in the moments before they exit. This research can help you identify or confirm a hypothesis for customer churn.
See if users are collectively experiencing the same issues—which could be indicated by rage clicks or u-turns, for example—that are pushing them away from your product.
Once you’ve identified a collective poor experience, you can take steps to fix it and improve UX for your customers (and increase customer retention for your business).
2. Give your users a voice with on-site surveys
On-site surveys let you ask users direct questions and give you voice of the customer (VoC) feedback about the user experience.
To conduct an online survey that clues you into customer churn and retention, keep in mind:
Your survey goal is to understand why users are churning (so you can address and fix issues they experience), or to learn what's working (so you can replicate or enhance it)
Your survey questions should be directly related to your survey goal
You should ask your questions at the appropriate time: either after customers leave, or after they complete a desired action within your product
As you analyze your survey data, you might learn about UX issues you hadn't identified before—like a broken button, slow loading times, or confusing UI and navigation—that are causing a poor user experience.
🔥 If you're using Hotjar
Use Hotjar Surveys proactively and reactively:
Implement reactive surveys when you see abnormal customer churn to understand what’s going wrong for the user (and then take steps to improve it for them).
Long-term proactive surveys can highlight how a particular section of your product provides consistent value to your users and can spark ideas about replicating or enhancing the positive user experience.
3. Get instant visual feedback from your users
User feedback is qualitative customer data about a customer's likes, dislikes, or indifferences. User feedback tells you what features or elements of your product are working, and what’s causing friction for your users (which ultimately leads them to stop using your product).
For example, if you’re testing changes to your product, you can give users the option to leave feedback about specific elements or sections on each page. User feedback helps you combat churn because you get to know what’s working and what’s not.
🔥 If you're using Hotjar
If you’re using Hotjar to collect user feedback, use the Incoming Feedback widget to pinpoint the exact moment in the customer journey that convinces customers to churn (or to stay).
The Incoming Feedback widget combines quantitative and qualitative information into one data set:
users can select broken or problematic elements on the page to indicate exactly where things are going wrong
a Likert scale lets users rate how they feel about their experience on the page or within the product flow, adding context to the elements they highlight
Placing the Incoming Feedback widget throughout the user journey gives you a glimpse into the user experience and an opportunity to hear, in the customer's own words, how the experience is making them feel.
The insights from Incoming Feedback not only suggest what needs to be fixed to stop churn, but will also help you understand how much of a priority the fix might be to improving UX.
Time to combine data for better customer retention
When you elevate your retention strategy by adopting a dual-analytics mindset using quantitative and qualitative data, you can learn:
How customers are experiencing and interacting with your site or app
Where things are going wrong (why customers are churning)
Where things are all right (why customers stick around)
Unite your data and use retention metrics to understand (and improve) the user experience—to keep customers around for the long run.
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