Have you lost subscribers recently? Did your subscribers switch to another app?
If these questions ring a bell, you need to read this blog. Customer churn is the percentage of customers that stopped using your company’s product or service during a certain time frame. Customer churn is one of the most important metrics for a growing business to evaluate. While it’s not the happiest measure, it’s a number that can give your company the hard truth about its customer retention.
For example, if you start your quarter with 500 customers and end with 480, your churn rate is 5% because you lost 5% of your customers.
Types of Customer Churn
Customer churn can be voluntary or involuntary.
Voluntary churn: When a customer decides to switch to another business or service provider due to dissatisfaction levels/poor service by the current provider. Businesses need to understand the cause of dissatisfaction to reduce churn levels.
Involuntary churn, however, occurs when the customer moves to a distant location or is faced with an adversity in life i.e., death. Businesses can seldom control such unavoidable factors of churn.
Top Reasons for Customer Churn
- Poor customer service
- Value for money is less – customers feel the service is highly priced when they are not satisfied with the experience.
- Poor quality of communication
- Low level of brand loyalty
In this section, you will learn about the success story of implementing our churn prediction model for a leading telecom company in India.
Key Challenges
Our client was experiencing high levels of customer churn and wanted to find answers for key business questions such as:
- Which customers to focus?
- Identify reasons for churn.
- Devise and plan an effective retention strategy
- The existing model of analytics was not much reliable and didn’t have enough lead time.
Solution Approach
I will describe the approach our team of experts at AppsTek followed to develop a customized solution for the client. Research by Frederick Reichheld of Bain & Company suggests increasing customer retention rate by 5% increases profits by 25% to 95%.
Our team contacted the company to understand their pain points and recommended a tailored analytics solution to retain customers and achieve higher levels of customer satisfaction.
The model was trained on 26 different parameters using open-source technologies. The solution was developed to collect and analyze data points such as customer demographics, existing plans, payment modes, subscription plans, add-ons customer complaints, and details of customers who left in the last six months.
Churn Prediction Model
Data analysis of historical data was carried out to train the model. Major outcomes were accurate churn probability and tailored recommendations for each segment of customers.
The model was able to reduce the customer churn from 12% to 1.67%.
Previously, the client was impacted by a huge burden of loss, which was reduced by 77% with the help of our analytics solution. The telecom company was also able to retain more customers after implementing the solution.
Now, if you ask me why clients would select our Churn Prediction model, I will clear your doubts in the following section.
Why would enterprises select the Churn Prediction model?
It is proven that the cost of acquiring a new customer is five times the cost of retaining a customer. Hence, a company cannot afford to lose its customers. This problem is resolved by our analytics solution. Moreover, it also enables businesses to cater to the dynamic needs of the customer.
With the help of the churn prediction model, businesses can develop target-specific retention plans and offer varied discounts or add-ons, etc. to the different customer segments.
Moreover, the model also alerts businesses about the daily probability of churn, which helps enterprises to take the right action at the right time. For example, a 70% churn will need implementation of retention plans with immediate effect.
With efficient execution, the model predicts accurately, giving enterprises proper lead time to customize different offers for their end users.
To conclude, the churn prediction model is a value-add for businesses as it helps understand why customers are leaving and gives an opportunity to the service provider to improve their performance levels.
Still in doubt about why retention is your new growth strategy. Don’t worry. We are happy to help you. Drop us an email at info@appstekcorp.com to know more about the churn prediction model or to schedule a demonstration.
