How To Reduce Customer Churn With AI Powered Prediction
The importance of the churn concept on a company or business development is directly proportional to the growth of that business. The addressee of the offered services, products and many other systems is the customer.
How popular and demanded the product is is also related to how many customers it reaches. Thanks to the customer churn, it is observed to what extent the services delivered to the customers are used by real customers. Product or business success is determined not by the number of people reached, but by the customers who consistently use these businesses.
For example, a purchased application gains meaning with users who are constantly active within the application rather than users who download it. A customer who constantly uses the application will indicate to the owner of the application that he is a permanent customer and that he will show continuity in return for the services provided.
The situation of inactive customers in the application is dominated by the message that they are ready to delete that application at any time, so they will lose customers. The fact that the owners of the company make this examination and reveal the ratios ensures that the product or service is maintained efficiently and effectively.
How AI Can Prevent Churn Effectively
Netmera’s analysis capability powered by artificial intelligence helps many customers to proactively predict and prevent churn rates. Our approach is the way AI is leveraged in a predictive manner. The more you can forecast churn, the better you can prevent it. With machine learning models, you can understand what is specifically causing churn. Product managers, developers, designers, and executives are spared the guessing games.
Continuous focus on customers
Companies need to focus on the customers they already have. The needs of the customer, who show continuity among all customers and who use the application and products continuously, are important. Good analysis is also required for permanent customers. Just as the reasons for the lost customers are investigated and what is not going right, why the customer who has gained and become permanent, and what the right dynamics are, should be analyzed. Properly progressing processes should be developed and teams should be motivated. In this way, the possible danger of churn will be reduced.
Making accurate analysis of lost customers
In cases where the Churn effect is visible, it should be determined which needs of the lost customers are not met, and which element and process went wrong according to the customers. In this case, companies should criticize themselves and review their teams with an objective and rational attitude. The percentage of lost customers should be taken into account and necessary measures should be taken to reduce this percentage to 0.
Intervention, acquisition, and experience
One of the best ways to prevent churn is to intervene in the customer lifecycle of profiles that are likely to churn. By triggering an alert to both the user and your internal team, you can focus on taking steps to retain key accounts or even specific individuals.
Churn isn’t always predicted just based on profile elements. It’s also predicated on acquisition channels. Based on your predictive analysis, you can target only the most lucrative users with the best retention.
Color, font, user flow, and other parts of the experience are all things that ultimately impact churn. With AI and behavioral analytics, you now have the tools to know where to focus your efforts on tweaking the user experience.
Here at Netmera, while creating predictive segments, we can change application-based metrics during the machine learning phase. We make the most accurate estimations by making differences in the algorithms in line with the goals and usage characteristics of the application. We work in cooperation with the application teams and manage the process according to their needs.