Retention Analysis: The Ultimate Guide to Analyzing Customer Churn

Every company needs to analyze churn data to determine pain points in their services that lead to customer loss. If your company isn't already doing this, you're missing out on critical information about why your customers are leaving, where you're losing money, and much more.

Read on to learn more about churn analysis—and how it can improve your business in a number of ways.

What is churn analysis?

Churn analysis is the process of evaluating why your company loses customers. This evaluation helps companies find ways to reduce customer churn—also known as customer attrition—and increase retention.

Churn analysis should be used to improve your customer attrition rate. Successful companies have a maniacal focus on keeping existing customers, and using churn analysis to understand the reasons your customers leave will provide insights into making sure it doesn't happen again.

When you complete a churn analysis for your company, you can pinpoint several things, including:

• ​The strengths and weaknesses of your products or services
• ​Better ways and opportunities for customer communication
• ​Predicting and preventing future churn issues

The churn analysis process is highly beneficial for your company as well as your customers, and the insights you gain from doing one are invaluable for the future success of your business.

At the heart of effective churn analysis is structured, qualitative customer feedback. Companies that rely only on internal opinions or surface-level metrics are left guessing about why customers leave. Replacing that speculation with real customer input gives you a single source of truth across your customer success, product, marketing, and sales teams.

Why you need to analyze churn rates

When you are monitoring your churn rates, you're going to notice very quickly when those numbers change. If they are dropping, that's a good thing. If the numbers are rising, and quickly, you've got a problem, and that's cause for concern.

Instead of panicking about the rising numbers and making rash decisions, you can perform a churn analysis to determine where things are going wrong. Churn analysis gives you new insights into what your customers are thinking in terms of cancelation, including:

• ​Which customers cancel
• ​Why they cancel
• ​When they cancel
• ​Whether they could have been saved

Churn rate also plays a critical role in revenue growth and has an interesting relationship with your customer acquisition costs.

Customer acquisition cost

Customer acquisition cost (CAC) is the total cost related to acquiring a new customer. This includes the cost of all sales and marketing strategies that aim to attract new business.

CAC is usually significantly higher than a company’s costs to retain current customers. According to an HBR article, acquiring a new customer is anywhere from five to 25 times more expensive than retaining an existing one. This means that the more customers you lose, the more your company will have to spend to replace them with new customers.

Happy customers don’t churn. They also help with one of the best channels of sales and marketing—word of mouth. Increasing sales opportunities from word of mouth can be one of the best ways to reduce CAC, reduce sales cycles, increase win rate, and ultimately grow revenue.

Churn and retention research helps companies uncover the specific reasons their happiest customers stay loyal—so they can replicate that success across their customer base.

Analyze churn to reduce it

The more you know and understand about your churn rate, the more you can improve it. Companies need to know every area that is causing them to lose customers and create targeted action plans to address and prioritize the causes of customer churn. If you aren't analyzing your churn rate, you can't improve it to make your business better.

Capturing direct, candid feedback from both retained and churned customers helps you go beyond the numbers and uncover the root causes of attrition.

When to do churn analysis

Ideally, your company should have a steady pulse of your churn. This helps build a customer-centric culture and keeps sales revenue in the door. Although actually calculating your churn rate and analyzing its causes deeper tends to be done annually, this can also depend on what your average contract length looks like. For example, if your average contract length is six months, it would be most beneficial to conduct churn analysis every six months.

Another great time to do a churn analysis is a specific time period after you've introduced a new product or service. You can get valuable insight into whether these new offerings are performing well, if they are stagnating, or if they are losing you customers.

Churn analysis also becomes a hot topic inside of a company when a high-profile customer is lost. They could have been a major percentage of revenue or a key strategic deal in a new market. Be careful not to fall into the trap of recency bias and use one deal to guide strategy for your entire customer base.

In general, if you aren't noticing concerning numbers and you haven't introduced new goods or services, it's still a good idea to perform a churn analysis at the end of every year. Doing this gives you continued insight into your company's performance and can help you game plan for the future. It is also a key business metric for measuring the health and future success of your business.

How to do churn analysis

Before you do a churn analysis, you need to figure out the scope and direction the analysis should take. To figure this out, use your overall churn rate or industry standards as a baseline, and customer information to guide you on where to look deeper.

Two ways churn rate can be calculated are by customer churn or revenue churn. Select the time period that makes sense to your business. If you are working with annual contracts use a year as the time period to calculate churn rate.

Customer churn simply means the number of customers (i.e., logos, accounts, etc.) that you lost in a certain period. For example, let’s say you had 100 customers at the beginning of the year. Out of those 100 customers, you lost 10 of them during the year. You would calculate your customer churn rate like this:

(# of Lost Customers / Total Customers) x 100 = Customer Churn Rate Percent

From the example above: (10 / 100) x 100 = 10% Customer Churn Rate

Revenue churn shows how much revenue a company loses from churned customers. Using the example above, let’s say that the 10 customers that were lost each had an annual contract value of $10,000. Let’s also assume that the remaining customers had annual contracts for $20,000 each. The total revenue lost (10 x $10,000) ends up being $100,000 and the retained revenue is $1,800,000 (90 x $20,000). Taking this information you can then calculate your revenue churn rate like this:

(# of Lost Customers / Total Customers) x 100 = Customer Churn Rate Percent

From the example above: (10 / 100) x 100 = 10% Customer Churn Rate

Now that you know your overall baseline churn rate, it is time to identify problem areas where the churn is higher. You can see from the sample above that by also calculating the revenue churn rate alongside the customer churn rate, a pattern of excess loss develops in deals with smaller than average contract values. Taking this information you can look for similarities with these customers and look for signs of loss reasons.

Next, it is time to dig deeper. The process of digging deeper can be broken down into a few steps.

Churn analysis in 4 steps

Step 1: Break down churn rate by factors

Many companies don’t have the bandwidth to fully investigate every lost deal. You should start breaking down the churn rate by different factors in your CRM. With your baseline or overall churn rate start looking more specifically at trends in different regions, by products, size of the customer companies, pricing and packaging differences, or other factors.

This will be specific to your business. Perhaps you notice that when a specific feature of your product offering is not included in the pricing and packaging the churn rate is significantly higher versus when the feature is included. Or your company offers tiered service plans. You could analyze all of these churn rates together but you’ll get a general overview of customer churn information.

However, if you were to analyze churn rates by subscription level or other smaller segments, you can get more accurate information about customer attrition. Say your customers in subscription level one are holding strong with minimal loss, but those in level two are dropping like flies. You want to understand the churn rates for level two specifically—not levels one and two together.

Once you have your specific churn rate numbers you can prioritize what your churn analysis is trying to discover, the scope it should take, point it in the right direction, and determine what data channels to use.

Step 2: Choose your churn analysis data channels

There are several data channels you can utilize to understand why customers left. This could include CRM information, customer surveys, internal surveys, and customer interviews.

Live interviews let you talk directly to key decision-makers to capture nuance and context that a checkbox survey can’t reveal. AI interviews make it easy to collect honest feedback at scale from champions, users, or churned accounts—helping you understand the value customers are seeing (or missing).

Each interview is recorded and transcribed in real time, where generative AI highlights themes, tags keywords, and surfaces decision drivers—so your team can quickly act on the insights that matter most.

Step 3: Determine why customers are churning

The main purpose of a churn analysis is to determine why your customers are canceling or leaving your services. While you can get some general information just based on the numbers you’re seeing, the best way to get the most accurate churn information is to talk to your lost customers.

Consultants can conduct probing, adaptive interviews that help you uncover the real reasons behind customer attrition. Customers are far more likely to open up to an impartial third party, which helps you capture honest, actionable feedback and identify opportunities for improvement.

A comprehensive viewpoint of churn analysis also captures insights from customers who renew or expand—revealing what’s driving loyalty and growth, not just loss.

Step 4: Analyze insights and make a plan to improve churn rate

Once you have performed an effective churn analysis it is time to take the information you have and create a plan to improve. This is where the best companies separate themselves from the pack.

Platforms and expert services can make it easy to share key findings with the right teams. Insights can be automatically distributed through Slack, CRM integrations, or email summaries—so every stakeholder can act on real feedback right away.

Share churn analysis data

One of the biggest mistakes with a churn analysis program or project is when the data gets siloed to an individual or small team. You should give access to a large number of stakeholders. When this happens, various stakeholders can begin to take immediate action on improving churn rate by executing strategies within their purview.

Tactics for sharing churn analysis data effectively include:

• ​Automatically alert leaders each time a churn analysis summary from a customer is obtained.
• ​Roll up key insights on a consistent basis into simple, easy-to-consume formats.
• ​Publish specific team feedback to their team’s Slack channels.
• ​Embed the data gathered into your CRM so the information can be easily accessed at a later date.
• ​Compile data that comes up about competitors into robust battlecards for your sales team to use.
• ​Hold internal debriefs with relevant stakeholders, centering the conversation around the customer’s feedback.

Which metrics matter?

As you perform a churn analysis, look at the following key performance indicators (KPIs), which are used to measure the financial impact of churn.

LTV (Lifetime Value)

The lifetime value (LTV), also known as the customer lifetime value, is essentially how much predicted revenue a company can get from a single customer during the time period they are a customer, otherwise called the customer lifetime.

It is simple to calculate LTV for a single customer. Say you charged a customer $10,000 a month for your service and the customer stays with you for 12 months. Their LTV is calculated like this:

$10,000 x 12 = $120,000

To calculate what your average LTV is across the business you’ll need to know the average revenue per account multiplied by average customer lifetime value.

ARPA (Average Revenue Per Account)

Average revenue per account (ARPA) is essentially how much revenue a company can get from a single customer account over a specific period of time. If you are looking on a monthly basis you’d calculate ARPA by dividing your monthly recurring revenue by the total number of accounts. (Monthly recurring revenue / total accounts = ARPA)

MRR (Monthly Recurring Revenue)

MRR stands for monthly recurring revenue and it is directly affected by churn rates related to cancellations and delinquent accounts. As you properly track your MRR and related churn rates, you can create a better product, market it more effectively, and continue to see compounding growth.

ARR (Annual Recurring Revenue)

If your company offers a yearly subscription service, your churn rates will directly impact your annual recurring revenue (ARR). When customers cancel subscriptions, miss their payments, or don’t even engage with the service, you bring in less revenue and face more customer loss.

Measuring progress and improving churn rate

With all of the churn analysis data you’ve gathered you should have a solid understanding of why your customers left or why they stayed. With company stakeholders, create plans to improve in the areas that influence churn and double down in the areas that helped keep a customer. These plans should include KPIs and goals to track progress.

Some initiatives companies could implement or improve from churn analysis experience include:

• ​Customer engagement/usage: Companies found that certain customers that hadn’t adopted the product or service or started to decline in engagement/usage became ripe for churning.
• ​Support tickets: Through a churn analysis, companies found that the account had key support conversations or tickets that could have saved the customer.