Churn Prediction
Churn Prediction
Who is Churn Prediction For?
Churn Prediction uses an AI algorithm that assists businesses in predicting customer behavior before they churn. So, Churn Prediction is for all businesses that want to easily predict and reduce customer loss. In fact, analysis has shown that improving customer retention by just 5% could increase profit by 50%.
Ease of Use
Churn Prediction has an easy-to-use UI that requires less intervention from Users. With BIG-AI, it’s easy to import data and get real-time predictions. In fact, data may be imported from databases, SQL and No SQL alike, or, Users may upload data in real-time from any machine in any format like XML, JSON, or SQL or unorganized. Our in-built data cleaning mechanism cleans the data using the best algorithm and data science techniques. Keeping with ease of use, Churn Prediction can be integrated with your customer portal.
- Churn Prediction uses the last few years of data
- Data can be uploaded in real-time
- All formats are supported
- Works with SQL and No SQL databases
- Easily import data from the customer portal
- Intuitive UI design
Results
Churn prediction reduces the churn rate significantly by providing recommendations on retention campaigns and loyalty programs etc. Churn Prediction alerts Users of type 1 and 2 errors.
Turilytix Insights
- Identifies high-risk and high-value customers
- Correction alerts for type 1 and 2 errors
- Identifies customers that have a high propensity to churn
- Identifies why they want to leave
Features
- A no-code AI platform for data analytics
- Powered by BIG-AI, our homespun Business Insight Generation Engine
- The easiest to use analytics platform for any size business.
Decrease churn by 5% and increase profit by 50%. Best of all, our AI algorithm cleans and processes all formats of data.
Don't Hesitate To Contact Us If You Have Any Questions
We help businesses through insights using machine learning, artificial intelligence, automated analysis, visual intelligence, and simple easily read graphs.