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. So, 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 the 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. And 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 that 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 — in this way, they will understand that they are important to you, 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. We have already created a guide on product recommendation systems, feel free to check it here.
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.
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 stop they 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. So use it 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. And if you are still wondering what cross-selling and up-selling are, take a look at this article.
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 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.
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. But if you still 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. We are always here to provide you with a better understanding of how to use AI for customer retention increase.