Customer Retention

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What Is Customer Churn Prediction & How to Improve It

<p class="p1">One of the main challenges of a growing business is figuring out how to retain more customers. Measuring customer churn is an effective way to gain insights into your business and your retention strategies. It will also help you identify areas for improvement and <a href="https://www.podium.com/article/customer-feedback-examples/" target="_blank" rel="noopener"><span class="s1">feedback</span></a> you should address.</p>
<p class="p2">Once you learn the importance of understanding and predicting customer churn, you can work on preventing it.</p>
<h1 class="p1"><b>Understanding Customer Churn Prediction</b></h1>
<p class="p2">Before we can get into customer churn prediction, you need to know what customer churn is.</p>
<h2 class="p2"><b>What Is Customer Churn?</b></h2>
<p class="p2">Churn is the percentage or number of your customers that stopped using your product or service during a given period. It can also be called customer attrition.</p>
<p class="p2">Importantly, customer churn negatively affects your business. You lose sales from the customer that left and have to spend more money to <a href="https://www.podium.com/article/customer-acquisition/"><span class="s1">attract new clients</span></a>. Adding the marketing costs and lost revenue will give you the cost of the churn.</p>
<p class="p2">There are many reasons that customer churn can occur, including:</p>
<ul class="ul1">
<li class="li2"><b>State of the Competition: </b>Your business always has to think about competitors. If your competition offers something more appealing than your company or suddenly improves, you may lose customers. Avoid this by paying attention to pricing, customer service, and the overall customer experience.</li>
<li class="li2"><b>Changes to Your Products: </b>Making changes to your product line is a common cause of customer churn, especially when customers believe that the new product is worse. That&#8217;s why it&#8217;s so important to get customer feedback before changing products.</li>
<li class="li2"><b>Changes to Customers’ Circumstances: </b>Sometimes, customers stop using your product or service because they feel they have already used it to its fullest. They may love your company and support it but just not need your offerings anymore. This can indicate you may need to expand the products and services you offer.</li>
<li class="li2"><b>Poor Customer Service: </b>Poor customer service is a very common reason that people look for other products or services. So, you should always make it a priority to deliver good customer service and create a positive customer experience.</li>
</ul>
<h2 class="p2"><b>What Is Customer Churn Prediction &amp; Analysis? </b></h2>
<p class="p2">Customer churn prediction is when you forecast (or predict) which customers have a higher risk of leaving your business. You&#8217;ll typically hear about customer churn prediction and prevention together with churn analysis because they&#8217;re all typically based on data.</p>
<p class="p2">Now you may be wondering, “What&#8217;s customer churn analysis?” It refers to looking at customer behaviors toward your product or service to help you predict future customer churn. You can think of it as using data to create and use a churn prediction model.</p>
<p class="p2">You want to figure out approximately how many customers will leave your business and why. This will let you work toward churn prevention by addressing the possible losses ahead of time. It is a crucial part of your <a href="https://www.podium.com/article/customer-retention-strategies-to-snag/"><span class="s1">customer retention strategies</span></a>.</p>
<p class="p2"><strong>The overall goal of customer churn prediction is to figure out how many customers will leave within a given time frame.</strong></p>
<h2 class="p2"><b>Why Is Customer Churn Prediction Important?</b></h2>
<p class="p2">Overall, customer churn prediction and analysis give you the data-based insights you need to be more proactive at maintaining your customer base. The importance of these predictions applies to a wide range of use cases, from companies that are hoping to retain online subscribers to businesses that want to retain shoppers in their brick-and-mortar stores.</p>
<p class="p2">A churn prediction model will help you identify the main reasons that customers leave. You can then use that knowledge to come up with an actionable strategy to overcome those obstacles and keep customers from leaving.</p>
<p class="p2">You can use customer churn prediction to:</p>
<ul class="ul1">
<li class="li2">Identify customers at risk of leaving</li>
<li class="li2">Identify customer pain points</li>
<li class="li2">Create strategies to reduce customer churn and <a href="https://www.podium.com/article/customer-retention-down-heres-what-to-do/"><span class="s1">increase customer retention</span></a></li>
</ul>
<h2 class="p2"><b>Challenges of Customer Churn Prediction</b></h2>
<p class="p2">The ability to gather every single bit of relevant customer data and put it together in a useful way is one of the biggest challenges that businesses face when predicting churn. This is why the first step to customer churn prediction and prevention is to ensure that your customer data is well-organized, accurate, and up-to-date.</p>
<p class="p2">Some other challenges that may come up when predicting customer churn include:</p>
<h3><b>1. Not Enough Data</b></h3>
<p class="p2">While having relevant data can be a challenge, you may also not have enough of it. If there isn’t enough data, the churn prediction model you use may be insufficient. This will lead to inaccurate predictions.</p>
<p class="p2">It is very common for newer businesses to have a lack of data. Your predictions should become more accurate over time as you get data on customers and their buying behavior.</p>
<h3><b>2. Too Many Data Features</b></h3>
<p class="p2">When there is too much data, your model can include a lot of “noise.” That extra noise can lead to false predictions, particularly when there are unseen data involved. This highlights the need to clean up your data and keep it well-organized.</p>
<h3><b>3. Too Many Nulls</b></h3>
<p class="p2">If your data model has too many nulls, then the model can become useless.</p>
<h2 class="p2"><b>How to Develop a Customer Churn Prediction Model in 6 Steps</b></h2>
<p class="p2">Next, you&#8217;re ready to look at the process of developing a customer churn prediction model.</p>
<h3><b>1. Identify Your Goals</b></h3>
<p class="p2">As with most other data models, you want to have a clear idea of your goals before you create a churn prevention model. Remember that you should be as specific as possible. Some common goals for churn prediction models include the following:</p>
<ul class="ul1">
<li class="li2">Identifying customers at a high risk of churning to reduce the churn</li>
<li class="li2">Understanding why at-risk customers are at risk of churning</li>
<li class="li2">Improving the customer journey to retain at-risk customers</li>
</ul>
<h3><b>2. Consolidate a Database</b></h3>
<p class="p2">As mentioned, one of the biggest challenges with churn prediction is having access to clean, organized, sufficient data. You need enough data, and it needs to be usable. Take your time consolidating your database—there are various tools that can help you with this to speed up the process.</p>
<h3><b>3. Segment Your Customers</b></h3>
<p class="p2">As you organize your consolidated database, segment your customers. This is the time to look at historical data on customers to see who is likely to stop using your products and services. There are multiple ways that you can segment your customers, and the method you<span class="Apple-converted-space">  </span>choose will depend on your goals. You can segment based on demographics, behavior, contract terms, contact with customer support, revenue information, product usage, and more.</p>
<p class="p2">Some potential ways to segment your customers include the following:</p>
<ul class="ul1">
<li class="li2">Whether they are using their product for personal use or as part of a company</li>
<li class="li2">How often customers use the product</li>
<li class="li2">Which features customers use most</li>
<li class="li2">How often users reach out to customer support</li>
<li class="li2">How long they have been a customer</li>
<li class="li2">The revenue you earn from the customer (including predicted customer lifetime value)</li>
<li class="li2">How long is left until the product expires and requires renewal (especially for businesses with subscription models)</li>
<li class="li2">Pricing tiers or plans (for service-based businesses and those with subscription models)</li>
</ul>
<h3><b>4. Identify Customers with a High Risk of Leaving Your Company</b></h3>
<p class="p2">Once you segment your audience, start using that data to identify the customers that have the highest risk of churn.</p>
<p class="p2">For example, customers that use your product daily or have bought multiple products or services have a low risk of churning. Or in the case of software and some other service-based businesses, regular communication with customers can indicate a low risk of churn.</p>
<p class="p2">Some of the biggest warning signs to look out for among existing customers include:</p>
<ul class="ul1">
<li class="li2">Customers who use the product less than they have (or buy less than they used to)</li>
<li class="li2">Customers who signed up for a service but never followed through</li>
<li class="li2">Customers who never sent in support tickets (especially for software and SaaS)</li>
<li class="li2">Customers who send in a lot of support tickets for similar issues</li>
</ul>
<h3><b>5. Look for Patterns to Identify Future Churn Cases</b></h3>
<p class="p2">Whether you use a prediction service or manually look at your dataset,  look for patterns in the data. This will let you identify the future churn.</p>
<p class="p2">There are predictive analytics and services available for all budgets that manage this for you, or you can do this manually in-house.</p>
<p class="p2">Some of the most common predictive models and algorithms for customer churn include binary classification and decision trees. Binary classification gives a true or false answer, such as asking if a specific action causes churn. Decision trees offer various scenarios, possibly more than two.</p>
<p class="p2">The following are some examples of the types of patterns you may find regardless of the type of model or data type you use:</p>
<ul class="ul1">
<li class="li2">A lot of customers leave right after signing up for your service (maybe due to your plans being confusing or the onboarding process not being user-friendly)</li>
<li class="li2">Churn right after product updates (possibly because of poor resources and information about the updates)</li>
<li class="li2">Churn with longstanding customers (possibly from lack of communication)</li>
</ul>
<p class="p2">Carefully choose the metrics you want to look at in your data analysis based on your goals.</p>
<h3><b>6. Come Up with a Response Plan</b></h3>
<p class="p2">Now that you have spotted patterns leading to your current churn rate, you can work on your response plan for churn prevention. To do so, you&#8217;ll have to identify the reasons behind the patterns you discovered in the customer data.</p>
<p class="p2">We can illustrate this by going back to the examples in the previous step. If your customers leave right after signing up, figure out if there is an issue with the onboarding process, they found your plans confusing and signed up for the wrong one, or something else. Then, address the issue.</p>
<p class="p2">Likewise, if customers find your subscription plans confusing, adjust the information on your website to provide more details or add more detailed descriptions during the sign-up process, whether you are a telecom, tech company, or sell physical products on a subscription model. If the issue is onboarding, make the process more user-friendly through tutorials or knowledge bases and add more customer support.</p>
<p class="p2">If customers are churning after product updates, start by making sure that customers actually want the updates. Then, confirm that they understand the reasons for the updates and how to use them. If necessary, add more support and resources immediately before and after product updates.</p>
<p class="p2">Your long-term customers may also show patterns of leaving. You can add more touch points to keep your product or service fresh in their memory. Offer loyalty incentives, discounts, or other incentives to keep them happy.</p>
<h2 class="p2"><b>How to Prevent Customer Churn: 5 Tips &amp; Strategies</b></h2>
<p class="p2">You don’t need to hire a team of data scientists to predict churn, as some very basic data science and analysis will give you a good starting point. Remember that the whole point of customer churn prediction is to be able to prevent churn.</p>
<p class="p2">You can also take the following steps to reduce churn.</p>
<h3><b>1. Improve Your Customer Service</b></h3>
<p class="p2">Satisfied customers are much less likely to churn, so you want to do your best to offer excellent customer service. A simple way to improve customer service is to ensure that you can easily respond to all messages from customers. Podium, for example, lets you <a href="https://www.podium.com/inbox/"><span class="s1">make customer communication easier for everyone</span></a>, as you will see all your messages in a single platform.</p>
<p class="p2">You will also want to look into other aspects of customer service and communication, such as response time and how satisfied customers are after talking to your support team.</p>
<p class="p2">Remember that customer communication and customer service give you the ability to engage customers before they even consider leaving. If you regularly reach out to customers or answer their messages promptly, you can take action as soon as you are aware of a problem. By being proactive, you can ensure it never gets bad enough for your customer to churn.</p>
<h3><b>2. Consider a CRM</b></h3>
<p class="p2">Using a customer relationship management system (CRM) is an excellent way to improve the customer experience as well as your efficiency behind the scenes. When you have <a href="https://www.podium.com/contacts/"><span class="s1">every customer contact in one platform</span></a>, your team has all of the relevant information at their fingertips. This gives them context for every conversation with a customer, helping them improve the customer experience.</p>
<h3><b>3. Get Positive Reviews</b></h3>
<p class="p2">To some extent, getting positive customer reviews can prevent churn. But it can also help you attract new customers to overcome the loss of customers. After all, <a href="https://www.podium.com/reviews/"><span class="s1">more reviews mean more business for you</span></a>. But even current customers are likely to look at your reviews if they want to try a new product or service from you. Or even the act of asking customers for reviews can help, as it gives you feedback.</p>
<p class="p2">With a <a href="https://www.podium.com/google-review-link/"><span class="s1">free Google Review link generator</span></a>, you can easily encourage these reviews.</p>
<h3><b>4. Take Customer Feedback Into Account</b></h3>
<p class="p2">Reviews are just one form of customer feedback and a very public one at that. You should also encourage customer feedback in other ways, such as via surveys. This will let you address pain points before the customer experience worsens and causes customer churn.</p>
<p class="p2">Don’t forget to ask for feedback from customers who have stopped using your products and services. Even if only a small percentage of them explain the reasons they left, it will give you optimal insights into the reasons for the churn. It can also give you an opportunity to send a follow-up after you address the issue and potentially win back the lost customer.</p>
<h3><b>5. Incentivize Loyalty</b></h3>
<p class="p2">As with attracting customers, providing incentives is an effective way of retaining customers. This is why loyalty programs are so popular. For example, consider texting exclusive offers to current customers with Podium.</p>


What Is Customer Churn Prediction & How to Improve It

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