Customer Anti Churn. Use AI to Predict Customer Churn

Did you know that avoidable customer churn costs US companies over $130 billion per year? Or that 67% of churn can be avoided if the client’s issue is resolved during their first interaction with the company? Or that reducing customer churn by only 5% can increase your profits by 25-125%? Sounds impressive, doesn’t it? Even if you haven’t tried to prevent customer churn yet, these facts should be enough to convince you to do this. Moreover, it is possible to use AI for customer churn reduction and creating anti churn system — it can be a great help!

But before we will tell you how exactly artificial intelligence can help you to deal with customer churn, let us provide you with a quick definition.

What is customer churn?

Customer churn is a percentage of clients that stopped, for example, buying your products during a specific period of time. It is one of the most crucial metrics for any business, as it is usually much cheaper to retain existing customers than to attract new ones.

It can be calculated in this way: divide the number of clients you lost during a certain time frame by the number of clients you had at the beginning of that period.

Obviously, the best possible result you can ever get here is 0%. But to reach it, you will have to develop a reliable anti churn strategy. As we already said, artificial intelligence (AI) can significantly simplify your struggle against customer churn.

Here are several issues it can solve in order to eliminate churn (or at least to reduce it) and reach customer retention increase.

Anti-churn and anticipation

It is always better to avoid the problem than to deal with it, and customer churn is not an exception. Good relations with your customers are crucial for your anti-churn approach.

Maintain contact with them after they make a purchase. This way, they will understand that you value them and that you take care of each of them in particular.

Here are some things you can do using artificial intelligence:

Recommend other products to your customers

You may think that this is a useless task to complete in case a client made only one purchase. But it’s not like this — to build a recommendation system, you don’t have to wait until each of your customers will buy dozens of products.

Read more: Product Recommendation System: Algorithms, Challenges, Benefits

Use artificial intelligence to improve your customer service

Ideally, you should still have some support agents ready to solve specific tasks, but repetitive questions can be answered by AI. In this way, simple issues will be solved very quickly, while clients with unusual questions will enjoy the personal touch. This strategy will improve customer experience and increase the retention rate.

Personalize newsletters

What a newsletter can be about? Product recommendations, discounts, your company’s news, and so on. However, sending the same letter to all of your customers is not the best thing to do. Regarding the product recommendations, everything is clear — they should be personal. But what about discounts and news?

To personalize such letters, send them at a specific time. Analyzing your clients by their location, demographics, and behavior, you will understand what is the best time for each of them to receive a newsletter. As a result, the subscribers will be more likely to check your emails than to miss them.

Data capture backed by a predictive approach

To detect future churn probabilities, it is essential to take a closer look at the data from the customers that have already churned in the past. Then, using a predictive approach, you will be able to build a predictive churn model. In turn, this model will provide you with an understanding of those customers’ pattern habits.

To put it simply, you will know what actions your clients usually perform before stopping using your services. Then, when an existing client performs a similar action, you will understand that they are probably about to leave and do something to prevent it.

As always, artificial intelligence is a perfect tool for analyzing big data sets and automating predictive modeling. Regarding the data set, you may need the following information to understand your customers and their behavior:

• Customer’s info (occupation, gender, zip code, etc.)
• How often do they check your newsletters?
• What types of products do they buy?
• Do they ever use coupons?
• How often do they make purchases? What value do these purchases have?
• What payment methods do they prefer?
• Do they ever complain about something? If yes, how exactly (by phone, email, etc.)?
• Are their complaints resolved and questions — answered?

The more data you have, the more accurate your model will be. And, therefore, it will be much easier to identify churn probabilities and deal with them. Analyzing the collected data on your own doesn’t make a lot of sense — a human will never be as efficient here as artificial intelligence.

Use AI to reach the desired results on customer churn prediction.

Alerts for sales managers with anti churn AI system

To increase revenue and improve your position on the market, you should regularly offer new opportunities to your customers. An anti-churn system based on AI and machine learning can make this task easier.

Analyzing the behavior and buying tendencies of customers, artificial intelligence can alert sales managers to potential solutions and improvements. For example, AI can recommend new cross-selling and up-selling opportunities.

Read more: Up-Selling and Cross-Selling: 5 Reasons to Use Machine Learning

Repair and inversion of damaged relations

Winning back those customers who have already churned or are about to churn is a pretty complicated task. However, it is not impossible to complete it, you only have to build an anti-churn system in the right way. As always, you start with analyzing the data — with the help of AI, define the risk group. Besides, find out if there were any customers who have already come back to you. If you discover what inspired them to do this, you can use this information to develop an efficient win-back campaign.

But the basic thing you can do is sending personalized emails. They should be sent at the right time and contain something special. For example, if you are sending an email to a customer who is only about to churn, you can write something like “Thank you for being so valuable to us”. In case a customer has already churned, you can use such phrases as “We’re missing you” or “Look what you’ve missed”.

Just make sure that these phrases (in both cases) fit your company’s tone of voice. The letter itself should include some interesting content. You can also equip it with a discount coupon to motivate a customer to visit your website or shop.

Read more: Deriving insights from data in order to increase revenue in retail industry

Use anti-churn together with AI to ensure your revenue streams

80% of your future revenue will come only from 20% of your existing clients. So take care of them and do your best to reduce customer churn. Now you know how to deal with customer attrition using artificial intelligence, which can lead to amazing results.

If you have extra questions (for instance, about how to integrate anti churn system with sales software and CRM),
feel free to get in touch with us.

Addepto is a an experienced AI consulting company and we are always here to provide you with a better understanding of how to use AI for customer retention increase.

Preventing Customer Churn with AI – FAQ

What is customer churn?

Customer churn is the percentage of clients who stop buying your products or services during a specific period. It’s a crucial metric for any business, as retaining existing customers is usually more cost-effective than attracting new ones.

How is customer churn calculated?

To calculate customer churn, divide the number of clients lost during a certain time frame by the number of clients you had at the beginning of that period. The best possible result is 0%, indicating no lost customers.

Why is it important to prevent customer churn?

Avoidable customer churn costs US companies over $130 billion per year. Reducing customer churn by only 5% can increase profits by 25-125%. Furthermore, 67% of churn can be avoided if a client’s issue is resolved during their first interaction with the company.

How can artificial intelligence (AI) help in reducing customer churn?

AI can significantly simplify the struggle against customer churn by:

• Building Recommendation Systems: AI can recommend products to customers, encouraging repeat purchases and improving customer relationships.
• Improving Customer Service: AI can handle repetitive questions quickly, allowing human agents to focus on more complex issues, thus enhancing customer experience.
• Personalizing Newsletters: AI can analyze customer data to send newsletters at optimal times, increasing the likelihood that customers will read them.

How does AI help in predicting customer churn?

AI uses predictive modeling to analyze past customer data and identify patterns that indicate a likelihood of churn. By understanding these patterns, businesses can take proactive steps to retain at-risk customers.

What data is needed to predict customer churn with AI?

To build an accurate predictive churn model, you need various data points, including:

• Customer’s demographics (occupation, gender, zip code, etc.)
• Newsletter engagement
• Purchase history and frequency
• Coupon usage
• Preferred payment methods
• Complaint records and resolutions

How can AI assist sales managers in preventing churn?

AI can alert sales managers to potential cross-selling and up-selling opportunities by analyzing customer behavior and buying tendencies. This proactive approach can help in retaining customers and increasing revenue.

Can AI help in winning back churned customers?

Yes, AI can help identify at-risk customers and those who have already churned. By analyzing data and understanding what motivated previous customers to return, businesses can develop effective win-back campaigns, including personalized emails and special offers.

What role do personalized emails play in customer retention?

Personalized emails can significantly impact customer retention. For at-risk customers, emails expressing appreciation can reinforce their value to your business. For churned customers, emails that convey a sense of loss and offer incentives can encourage them to return.

Why should businesses focus on existing customers?

80% of future revenue typically comes from 20% of existing clients. Focusing on retaining these customers is crucial for sustaining and growing revenue streams.

How can businesses integrate AI-powered anti-churn systems with existing sales software and CRM?

Integrating AI-powered anti-churn systems with sales software and CRM involves customizing the AI tools to align with your existing systems and processes. For detailed guidance and support, consulting with an experienced AI company, like Addepto, can be highly beneficial.

This article is an updated version of the publication from Jul 5, 2019.