In a market with many uniform products and big competition, a decrease in the number of customers leaving the company and increased customer loyalty means a significant improvement for any company. Loyal customers stay with the company for longer and buy more often and therefore companies that focus on retaining their customers will be able to achieve an increase in revenue and earnings.
In many companies, customer retention is high on the agenda, but the actual execution can cause problems because how do you know that a customer is leaving? How do you know what to do to increase the chances of them staying? And how early should one intervene to maintain them?
When you want to find out which customers want to leave the company, or which ones are the most loyal, you use algorithms - also called Advanced Analytics or Machine Learning - to predict the probability of a customer leaving the company - also called churn prediction.
With the right database and algorithms for the purpose, Machine Learning can quickly and with great statistical certainty tell you which customers are at the risk of leaving you.
68% of your customers leave because they think you do not care about them.
2% Improvement of Customer Retention has the same effect as a 10% cost reduction
80% of your future earnings will come from 20% of your current customers
Use the right data properly - and retain your customers
With that information in hand, you can make an effort to retain these risky customers. Many of them may not know they want to leave you yet and this gives you a unique opportunity to engage in targeted retention activities. You can give the customer the right offer based on their specific behavior, thus ensuring customer retention. In addition, you can also use the information to identify who looks like them and systematically try to eliminate that they also end up in the risk group. By analyzing the customers in the various risk groups further, you can also gain a better understanding of the factors that form the basis of their decision to leave the company, and thus adjust in e.g. internal processes or employee behavior that affect customer satisfaction.
While the algorithm identifies who is at the risk of leaving you, you will also generally get to know your customer group better. You also learn what characteristics your most loyal customers have, and you can use it to adapt your marketing efforts to them so that they remain customers.
If you understand and use this knowledge correctly, it can be the key to happy and satisfied customers. Happy and satisfied customers mean more loyal customers and customers who are more likely to buy again.
Ultimately, a targeted effort around customer retention will result in the company becoming more efficient, reducing sales costs and increasing earnings.