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Customer churn, also known as customer attrition is a vital metric that businesses should track. After all, retaining existing customers is just as important as adding new ones. It is critical for businesses to keep track of customer churn and prevent it from occurring as subscription services and SaaS become more commonplace in the delivery of content and products.

When you conduct a customer churn evaluation, you can narrow down key points in the customer journey within which they are losing interest and develop strategies to keep them engaged and committed to your brand.

In this blog, we will discuss how you can leverage sentiment analysis to reduce customer churn. Let’s get started.

What is customer churn?

When customers quit your company, you have churn. Some of the plausible causes for this include switching to a rival, canceling their membership owing to poor service, ceasing all communication with a business due to insufficient interactions, and so on. For obvious reasons, customer turnover analysis is crucial as revenue is directly impacted by a decrease in the number of clients.

Key reasons for customer churn

Now that you know what customer churn is, let’s look at some of the main reasons why customers leave a brand or product.

reasons for customer churn

Cannot meet customers’ needs

When it comes to customer churn, this is generally what comes to mind first. Customer turnover is inevitable if you fail to deliver on the promises you make to them in your product.

There are many reasons why a product fails to satisfy client expectations, and this isn’t always due to the quality of the product itself, though it can be a significant issue. There are also instances when the guidelines and onboarding process can lead customers to believe that your product isn’t high-quality.

The product or service wasn’t a good fit

In your churn analysis, you may also discover that the customer was not a good fit for the product. In this circumstance, it can be especially annoying to spend money on marketing resources like social advertising and email campaigns, only to have them go to waste if the buyer leaves right away. You need to do extensive market research ahead of time in order to identify your ideal customers.

Customer service is lacking

Poor customer service is one of the most apparent reasons why customers give up on a brand. Aside from attrition, chatbots are making it easier to keep customers. Customer attrition is inevitable for a business with poor customer service.

Many clients would rather stop doing business with your firm than deal with customer service issues. When you can’t make changes to your account or contact someone about a problem, it’s frustrating.

Lack of interactions after conversion

Customers may not be displeased with your product or service; instead, they may have simply forgotten about you since you have forgotten about them. If you convert someone, you can’t assume they’ll be a lifelong customer.

Make it clear that you appreciate their business, remember them, and care about keeping them satisfied. A range of methods, such as free birthday gifts or emailed discounts, are available for following up with client touchpoints.

Competitors have better offerings

You can’t blame your clients for going with the cheaper alternative if your product is of the same quality and features as your competitor’s, but the price is lower.

You need to keep a close eye on what your competitors are doing to capture the same audience as you and either match or surpass their efforts. Companies that can adapt and respond quickly to changing client demands are virtually always more successful than those that are unable to do so.

Using sentiment analysis for analyzing customer churn

Here’s how you can use sentiment analysis to reduce customer churn.

analysing customer attrition

Apply sentiment analysis across all channels

Use sentiment analysis across all your channels to take the prior churn analysis approach to a whole new level. There are many other ways customers can share their thoughts about your brand, including through support requests, online reviews, social media mentions, and more.

With the help of machine learning and artificial intelligence-enabled sentiment analysis, you can gain a better understanding of what is prompting customers to leave your product or service.

Identify customer drop-off points

It doesn’t matter if your customers aren’t posting reviews or contacting customer service about specific issues; you can still utilize churn analysis to figure out what led them to go.

For instance, your SaaS product’s AI chatbot conversations skyrocketed after you launched a new feature. If customers are complaining about the new technology or feature, this is an indication that it is causing them trouble.

In order to find out what your clients don’t like about your brand, you need to keep an eye out for changes in your business and the resulting customer churn.

Perform customer segmentation for building customer profiles

Because no two customers are exactly the same, segmenting your turnover data by factors such as age, gender, income, membership type (if applicable), and history with your product will help you learn more about your consumers. As a result, your consumer outreach will be more effective and tailored to the specific requirements of each segment.

There is no need to treat a new customer the same as a long-standing loyal customer. Upselling possibilities can be discovered by segmenting customers depending on the type of customers who frequently seek more features at certain points in the customer journey.

Inspect support tickets to identify key issues

As part of your plan for churn analysis, you should be on the lookout for any common customer issues. It doesn’t matter if your customer care team uses support tickets, chatbots, or any other method to keep track of concerns.

There may be a serious flaw in your product that you are unaware of based on the number of complaints you’ve received from angry customers. On a routine basis, you should be gathering and classifying this input, and taking care of any concerns that keep reappearing.

Analyze social media mentions and customer reviews

Social media mentions of your product and the customer reviews associated with it are a goldmine of information that can support the further enhancement of your product. What’s more, it can help you identify customer complaints which if overlooked can lead to losing new customers.

Also, when it comes to social media channels, you never know what may go viral and that includes product reviews as well. So, it’s better to keep track and identify such conversations and resolve them before they go viral and tarnish your brand reputation.

Analyze competitors

If you’re offering the same level of quality at a lower cost, you’re going to lose customers. If your competitors are exceeding you in certain areas, you should focus on improving those aspects of your own business in order to reduce client churn.

It’s important to recognize where your competitors are susceptible and weak so that you may leverage your strengths and potentially pull their customers over to you. The same goes for the strengths and aspects of their product or service that customers get drawn towards.

Sentiment Analysis Tool

Now that you know the importance of customer churn analysis and how sentiment analysis can help you in it, you need an effective tool with which you can automate the process. Fortunately, I know just the right tool for it.


BytesView sentiment analysis tool

Yes, it’s our very own tool, but hear me out.

You can use BytesView, a premium text analysis tool based on machine learning and NLP, to analyze and extract actionable information from unstructured text. With BytesView’s different text analysis models, you can detect and extract useful information from large volumes of text. One of those models is sentiment analysis.


BytesView sentiment analysis demo

Key features of BytesView:

  • Dedicated plugins to integrate data
  • API access to build custom solutions
  • Various text analysis models for data analysis
  • Build and train custom data analysis models
  • Compile and analyze large volumes of unstructured text data
  • Transform unstructured text into business intelligence

Wrapping Up

Sentiment analysis is one of the best ways to learn more about your customers and their needs. You may learn about your consumers’ worries and utilize that information to create products and services that meet their demands. Get started right away!

Using Sentiment Analysis to Reduce Customer Churn
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Using Sentiment Analysis to Reduce Customer Churn
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