Retention AnalysisThe 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 with Clozd—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. Clozd helps replace that speculation with real customer input, giving 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.

Clozd’s 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.

Clozd’s Live and AI-powered Flex Interviews help companies capture direct, candid feedback from both retained and churned customers—so you can 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

or 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

or 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

1

Customer acquisition cost

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.

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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.

Clozd’s AI Interviews and Live Interviews are designed to uncover the “why” behind churn. 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 within the Clozd Platform, where generative AI highlights themes, tags keywords, and surfaces decision drivers—so your team can quickly act on the insights that matter most.

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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.

Clozd consultants 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.

The Clozd viewpoint of churn analysis is a little different from the status quo. Though most research focuses on lost customers, Clozd also captures insights from customers who renew or expand—revealing what’s driving loyalty and growth, not just loss.

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:

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

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 * average customer lifetime value.

ARPA

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

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

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.

Analyzing your insights and making 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.

Clozd’s platform and expert services 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.

“I love the Slack integration. We have a Slack group dedicated to win-loss. As the interviews are added to the platform, they come through Slack and email in real time. And then those in that program can link directly to the full interviews from Slack and also access the dashboard in Clozd which shows our win rate, the top wins and losses, the top reasons we're winning and losing, and all the interviews that were recently posted.”

—Heather Pepe, Senior Manager of Solutions Marketing at Calendly

Share churn analysis data

One of the biggest mistakes we see 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 we see various stakeholders 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. When Clozd completes a churn analysis interview the information is shared within the Clozd Platform and notifications go out to stakeholders about the new data.

Roll up key insights on a consistent basis into simple, easy-to-consume formats.

Publish specific team feedback to their team’s Slack channels. For example, if you are getting feedback about customer success or support, share it with them.

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.

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 we see companies could implement or improve from our 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 from churning if they had been handled differently. Flagging commonalities in support tickets with customers that churned on existing customers can provide warnings that those accounts might be in danger. 

Competitor actions: There are always going to be competitors in the market and it’s important to be aware of what your competition is doing. If they offer cheaper prices or better deals on your same services, this could be a potential reason a customer churns.

NPS scores: Using NPS scores to measure how satisfied your customers are with your service before they churn. You could also correlate NPS score data with churn data and it may give you a danger threshold of a customer churning hopefully giving you enough time to correct the problem before the customer churns.

Sales and implementation handoff: This comes up a lot in the churn analysis interviews we do. One common problem is a customer’s perception of a product from sales and marketing to the reality they are hit with when implementation begins can be jarring if your comp any is over-promising and under-delivering. We see in our churn analysis interviews that many times a customer decides that they are going to churn during a bad implementation experience, they just have to wait out their contract.

When you know what and where the problems are, you can work to address the problem and improve the situation—whether it’s trying to improve your customer service, creating new features, or fixing bugs in your system that cause problems for customers.

One example is Xactly, which conducts ‘stay’ interviews to identify pain points and increase customer loyalty.

"We tried to get information on our own, but customers are more closed in terms of what they’ll share with us. Using a third party helped us uncover important details they just weren’t sharing with us.”

—Kathy Hassett, VP of Customer Success & Renewals

Read the full Xactly case study.

With the accurate, unbiased analysis results you get from Clozd, it’s easier for you and your team to come up with data-driven solutions that benefit your customers and your company.

Market Segmentation

One of the benefits of doing churn analysis is it helps you identify where you win and retain customers in the market. You’ll be better equipped to understand your ideal customer profile (ICP). With this data you can help focus more of your company’s efforts into bringing in new customers that will stay long term.

Clozd’s structured, qualitative feedback also helps you segment by the reasons customers stay—not just by demographics or firmographics—so you can target and retain your best-fit customers with precision.

Learn more about market segmentation here.

Churn FAQs

What is churn in business?
Churn in business refers to customers who stop using your product or service during a given time period—usually by canceling, not renewing, or significantly downgrading their contract. Many companies track both customer churn (number of accounts lost) and revenue churn (recurring revenue lost).
What is retention analysis?
Retention analysis is the process of understanding how long customers stay with you and (most importantly) why they stay or leave. It typically combines quantitative data (churn rates, renewal rates, revenue retention) with qualitative feedback (interviews, surveys, usage data) to reveal the drivers of customer attrition and customer loyalty.
Is churn rate a KPI?
Yes. Churn rate is one of the most important key performance indicators (KPIs) for subscription and recurring-revenue businesses. It directly affects customer lifetime value (LTV), MRR/ARR, and long-term growth, which is why churn rate is usually tracked at the executive and board levels.
What is a good churn rate?
A “good” churn rate depends on your industry, customer segment, and contract length. Many B2B SaaS companies selling to mid-market and enterprise customers aim for annual churn below 5–7%. SMB or self-serve products often see higher churn because their customers are more price-sensitive and change tools more frequently. The most important thing is to benchmark against similar companies and work to improve your own churn trends over time.
What does a 5% churn rate mean?
A 5% annual churn rate means that 5 out of every 100 customers you started the year with have left by year-end. Put another way, your annual retention rate is 95%. Even a small shift—from 8% to 5% annual churn, for example—can dramatically increase LTV and compound your revenue over time.
Is churn the same as retention?
Churn and retention describe two sides of the same coin. Churn looks at the customers or revenue you’ve lost during a period, while retention looks at the customers or revenue you’ve kept. If your annual churn rate is 12%, your annual retention rate is 88%. Many teams track both to get a more complete view of customer health.
What’s the difference between churn and attrition?
In most customer-success and SaaS contexts, churn and attrition are used interchangeably to describe customers who leave. Some organizations use “attrition” as a broader term that includes non-renewals, downgrades, and silent churn (customers who stop using the product but remain technically subscribed), while “churn” focuses on cancellations and non-renewals. The key is to define the terms clearly and use them consistently across your company.
Can a low churn rate be bad?
While not necessarily “bad,” a very low churn rate can sometimes hide other issues. For example, if you’re locking customers into long contracts but adoption is poor, or if you’re under-pricing the product to keep everyone happy. Low churn is only healthy when customers are actually using the product, achieving outcomes, and seeing enough value to justify the price.
How do you measure customer retention?
You can measure retention in several different ways:

Customer retention rate: The percentage of customers who remain over a given period.

Revenue retention (GRR/NRR): The percentage of recurring revenue you retain, including or excluding expansions.

Cohort retention: How well specific groups of customers (e.g., by signup month, segment, or product) retain over time.Combining these views gives you a deeper understanding of where you keep and lose value.
What tools can I use for churn analysis?
Many teams start with Excel or Google Sheets to calculate churn and retention metrics. As programs mature, they layer in:

CRM and billing data to segment by industry, product, or deal size

Customer success platforms to track health scores and at-risk customers

Qualitative feedback platforms like Clozd to run churn and retention interviews and analyze themes at scale

The most effective churn analysis programs combine quantitative data with direct customer feedback.
How do you do churn analysis in Excel?
You can run a simple churn analysis in Excel by:

Listing all customers with their start date, end date (if churned), and recurring revenue.

Grouping customers by month or year and counting how many left during each period.

Applying the churn formulas from this article—for example:

Customer churn rate = (Lost customers ÷ Total customers at start of period) × 100

Revenue churn rate = (Churned revenue ÷ Retained revenue) × 100 From there, you can add filters for segments like industry, product, or contract size to see where churn is highest.
What are common causes and types of churn?
Common causes of churn include poor onboarding, low product adoption, missing features, pricing and packaging issues, weak customer support, and competitive pressure. Many companies categorize churn into types such as:

Voluntary vs. involuntary churn (e.g., customer cancels vs. payment failure)

Avoidable vs. unavoidable churn (e.g., poor fit vs. customer goes out of business)

Product-related vs. relationship-related churn (e.g., missing features vs. poor support experience)

Segmenting churn this way makes it easier to prioritize the issues you can realistically fix.
What is a churn model?
A churn model is a predictive model—often built with statistical or machine-learning techniques—that estimates the likelihood a customer will churn in the future. Churn models typically use historical data like product usage, support tickets, NPS, and contract details to flag at-risk customers so your team can intervene before they leave.

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