Have you ever wondered why your customers stop buying your products or stop using your services? This is called customer churn, and actually, almost every single brand has this problem. This is why you need to take advantage of customer churn prediction.
Partly that’s related to the huge amount of possibilities on the market. Choose any product or service and we bet you can find at least several competitors. In some businesses, like FMCG or fashion, those competitors are counted in hundreds. No wonder, that customers are purchasing products and services in many different places. This is how the modern world works, but that doesn’t change a simple fact, that no company wants to lose customers. But partly that’s their fault.
Nowadays most businesses are focused only on growth, business development, and customer acquisition, but what about your existing customers? Sometimes, they are just left out. “Well, we have already managed to get them, so what is the purpose to focus on them?” – you might think. But that’s a huge mistake, that causes you to lose tenths of thousands of dollars every year! Why? Every customer who leaves your company causes you to lose money! Sometimes that’s just a few dollars, but sometimes that’s tenths of thousands of dollars! What happens when 500 consumers decide to leave you? You are in trouble, and your cash flow is seriously threatened!
So the problem of customer churn is very serious! As one report* reveals, customer churn is costing US businesses $136 billion a year. What would be the worldwide number? But what’s even worse, according to another report, “79% of high-income earners shunned a company for more than two years after they had a bad experience”. So if you want your company to grow, you just have to face this challenge and avoid customer churn.
How to Predict Customer Churn?
Happily, you are not left to yourself with the customer churn problem. Because there are companies like Addepto, that try to solve those issues with AI, especially predictive machine learning systems. Every year they are more and more advanced and their work – more and more accurate. But let’s start with the beginning.
For instance, have you ever tried to analyze why customers have left your online store (e-commerce) or stopped using your services (maintain your car in your particular service center[MŻ1] )? It is very important to analyze those reasons, because it allows to modify your current activities and maybe even offer, to suit your customer’s needs. And as a result, fewer of them will churn. How to do that?
Two words – machine learning. The answers to all those questions could be discovered using advanced technologies with support from the machine learning consulting company. Customer Churn Prediction using machine learning will help you to identify risky customers and understand why your customers are willing to leave. The connection is obvious – the less consumers leave your business, the smaller customer churn is – the more money you make, the faster you grow!
Today every business utilizes a lot of data on its customers. The real value is to use it in a way beneficial to the company. Amongst the vast amount of data, find the most important factors and correlations: transform data, create algorithms and automate flow, which will give you favorable results. Those techniques could be used in up-sell system, CRM or marketing automation software. And all of these techniques are possible to implement in almost every company, thanks to the predictive machine learning systems. Today, you don’t have to think about why do consumers leave. You can figure that out and even apply customer churn prediction thanks to machine learning technology. Sounds unbelievable? Well, keep reading 🙂
“Increasing customer retention rates by 5% increases profits by 25% to 95%” 
How to start with a customer churn prediction
No matter what size is your business or what is your operational model, if you are selling products or services, virtually for every industry the problem is the same – customer retention. Keeping your existing customers with the company as long as possible could be very challenging. But it’s definitely worth the effort because it is still simpler than soliciting new customers. It can be called a vicious circle – you gain new clients, then in time they leave because you weren’t paying enough attention to stop them. You are spending lots of money in order to get new clients, and the circle is complete. The only way out is to try stopping the customer’s churn. So as you can see by now – it’s not an option. It’s a necessity! Without that, you are exposed to continuous loss of money. Can you afford that? We don’t think so!
To keep your customers satisfied throughout the time, you need to know their needs, have good customer service and know why would they leave your business. We will talk more about that in a second. When you possess this knowledge, you can work on your retention rate and improve overall performance significantly. So one of the keys to stopping customers churn is to gain as much data about them as possible. That’s the starting point, which is also necessary for machine learning predicting systems, that will help you with the process of customer churn prediction.
Keep consumers at your side
You already know which customers are not buying from you anymore or not using your services. You can tell that easily, just by the lack of orders from them. And in many cases, this is the point when it’s too late. They are already lost, and bringing them back to your company or e-commerce is as challenging as acquiring new ones. Of course, we are not saying here that it’s impossible, but if you could avoid it – you definitely should!
So, the real challenge is to identify which customers will leave in the future, not those that already gone, but they are can still be very useful! They will deliver to us priceless knowledge – by analyzing them, we can find the common denominators. If we compare the data from current clients and the data from previous ones we will be able to find out what causes customer churn! And this is the place where machine learning predicting comes into play!
Unfortunately, it is very hard for humans to spot correlations between thousands of data points. Using the computational power and Machine Learning algorithms (ML), your historical customer data will be put to work to accurately predict future churn. If such a task were given to the human worker, it would be very difficult for him or her and time-consuming (if not impossible!) to accomplish it. Predictive machine learning system is your best bet – it’s faster, more accurate and doesn’t go on a sick leave 🙂
Proven approach for Customer Churn Prediction
We are using our authorized Customer Churn modeling approach to help companies retain their customers. Using historical data we could target “at-risk clients” by assigning them a given churn ratio and find any opportunities to stop clients, who might in the near future leave your business. What does our work look like? Take a look at the three steps:
- The first thing is to start from your business definition of a “churn”. Our machine learning predicting system has to be very specifically “told” what it is supposed to look for. Usually, a customer “churn” is defined by as inactivity for some period of time, let’s say half a year. Additionally, you should setup also success criteria which are very important to this step and ROI (return on investment) calculation.
- After we collected needed historical data for prediction and extracted it from source systems, we can start the modeling phase. During this stage, the predictive machine learning model will be created. Also, this stage includes model validation, performance monitoring and parameters tuning steps – to get the most accurate customer churn prediction from your historical data points. This is where all the data gathered by your company about your customers is needed.
- At the last step, we should define an agree on predictive machine learning model implementation and integration inside your organization. Firstly, from data architecture point, integration with internal systems such as CRM and reporting or training standpoints.
Benefits of Machine Learning for Customer retention (Customer Churn Prediction)
When all black-boxed work is done and, as a result, you get insights on customers that are likely to churn, it will have a significant ROI for your company. Machine learning in marketing can help you to segment your customers into different groups of churn risk. A particular churn ratio will be automatically predicted for every client and every group. That’s a very important feedback for you – now you know on which clients and groups of clients you should concentrate to avoid the churn.
And maybe you could provide them with some additional benefits, that will keep them by your side? Maybe you will show them some extra care? It’s your decision and it’s based on many factors and circumstances, but it indicates where you should turn your attention in order to fight the customer churn problem. Those features will help you to understand which customers are likely to leave and why, so you will be able to take action on them and try to retain more customers.
What may cause customer churn?
Someone might say, that customer churn depends on so many factors and circumstances, that it is pointless to create a list of dos and don’ts. Nothing further from the truth! For instance take a look at the 2019 Customer Expectations Report, made by Gladly.com**. You can find there many interesting factors, important for the modern consumer. All of them are directly related to the customer churn topic! Take a look at some of them:
- “63% switched to a competitor with better service. 52% without any warning.” What does it tell you? That you have to concentrate on a great customer service! Your customer probably won’t write an e-mail to you, saying “Dear Mr. X, I’m leaving! Have a great day!”.
- “77% would return for a great service vs. a great marketing campaign”. We have talked about that already. It is easier and cheaper to stop consumers from leaving than acquiring new.
- “Most people still say they’re treated like a case number, not a person” and the number of people saying that increases! In 2018 it was 61%, in 2019 it is 68%. So still there’s much to do.
- “84% of customers switch after three poor customer experiences. 17% switch after the very first one”. So you can’t afford any mistakes. Your customer service has to be perfect. As that report shows, some of your clients WILL DO give you a second chance, but it’s wiser to not give them reasons for it 🙂
From the general guidance to the solution
So you know where to start when fighting customer churn. Knowing the reasons will help you predict the churn and then – avoid it. And one of the main reasons causing customer churn is poor customer service. Another one is the prices. You should continuously compare your prices with your competitors. If your prices stand out in a negative meaning, don’t expect people to stay with you. After all, no one wants to overpay! But as we have said – this is general guidance. It might help you look at your company from a different perspective, but it won’t do the entire work. At some point, you stop in a situation where without additional help not much more can be done.
It’s a different story with predictive machine learning! Our systems can compare and spot correlations basing on the data from your company. We compare such factors as for example: time of a response, time of loading a website, how many orders have been made, when (time of a year, time of a day), from which country or city, how complicated it is to make an order, exactly when customers resign, how many attempts have they made and many, many more! Everything that’s necessary to stop customer churn!
How to stop customer churn?
Now you know, that in most cases customer churn is strictly related to the customer service, but how to prevent it? We have prepared some general tips & tricks that might help to keep customers at your side:
- Educate them and share content with them. People like to receive something for free. Especially if it’s useful knowledge. Maybe you could do some webinars or write an useful ebook on a subject related to your business?
- Keep them updated, but do not flood them with messages. Let them know “what’s new?”, ask them for their opinion, share new offers and products with them. Don’t assume that they will remember your company, just by making one order!
- Concentrate on the customers that make the biggest orders. If you see that a given consumer makes big orders – write to him personally and thank him for that. Offer some incentives: discount of free shipping.
- Do for them more than they expect! For example, if you are selling shoes online, why don’t you put a spare pair of shoelaces in the box? A gift should be cheap, otherwise, you will end up with a loss and that’s not the point of running a business 🙂 But it also has to be memorable: useful, funny, positive and above all – related to the order!
Think about that, and now let’s go back to the machine learning!
Benefits and Facts of using machine learning
Below are some key Benefits and Facts. Although the quoted report gives some general idea, about why consumers might leave, it’s very important to compare it with the situation in your exact company. Because the report does can say that 63% of customers have switched to a company with better customer service, but it will never tell what was bad with the previous one, namely – yours. So acknowledging the value of a great customer service is extremely important, but it is not sufficient. And now we go back to where we started – to machine learning. How could it be beneficial to your company:
- Increase Revenue: – Upsell to existing customers is easier and more cost-effective rather than selling to new ones. – Keep your revenue stream on a stable level because the acquisition of a new customer is 10 times more expensive than retaining existing customers
- Win Business Back: – An ability to analyze customers with 360 view and understand which factors impacted a particular customer to churn can help you to get them back – Increase retention KPI
- Retain More Customers: – Launch new loyalty campaigns and strategies to increase loyalty to your product or service – Protect future retention by eliminating factors which lead to churn
- Avoid Losses: – Retaining your existing customers means stopping customer churn, and can help you to prevent revenue decreases or opportunity for competition.
The solution for many companies
Those are only examples of benefits your business could obtain. Don’t view them as a closed list of benefits. Just write to us or give us a call and we can together discuss what we can do for your company’s growth! Every industry has individual specifics in customer service, relationship management, and retention. For this reason, benefits can be much more visible in your particular business. Some of the businesses with a great background for implementing the machine learning system are Fin-tech, Healthcare, Insure-tech, Fitness or mobile gaming. We always urge our potential clients – never think of machine learning as of ready-made products, that either helps or not. It’s a custom-made product, that is built from scratch specifically for your company’s needs and expectations.
Conclusion – stop customer churn with machine learning!
It’s time, to sum up. If we had to put everything together in one paragraph it would be like that: you can learn how important it is to provide amazing customer service to your clients. You can do research and send surveys to your customers. You can read reports and spend hundreds of thousands of dollars on a variety of marketing services to increase your sales.
But all that effort has to be combined with a deep analysis of your consumers and your market. Only then you will receive accurate data that can help to predict and to prevent customer churn. You will be able to increase your customer retention rate with predictive modeling, machine learning, and data science consulting. All based on correlations in your client’s datasets. With the help of machine learning you can:
- Focus on users who are actually at risk and hence save up on retention costs
- Save up on acquisition costs to replace the churning users
- Protect the Future Revenue from churning users
In this way, if your churn model works correctly, you will be able to stop many consumers from leaving, and by that – make more money. Money, which you can then invest in new customer acquisition and expand your business much faster than the competition!
If you have any questions or need an explanation on how to use Machine Learning for predicting customer churn ping us a message. We are always keen to dispel your doubts and help you to understand how customer churn prediction with machine learning can be beneficial to your company! And remember – it doesn’t really matter what kind of business you run, whether it’s an e-commerce, wholesale, service company or other kind of online business. Predictive machine learning IS for you!