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Predict Customer Churn
Identify the customers you are about to lose and retain them before it becomes too late.
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Learn how to combat customer churn with the power of predictive analytics. Our video tutorial provides an overview on creating a predictive churn model using Graphite Note. Don’t miss the opportunity to bolster your retention strategies and elevate your business to new heights. Ready to master churn prediction?
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The Challenge
The one challenge businesses always face – is customer churn. A churn is when customers stop buying a product or opt-out of service. Often, this entails the need to find new leads and pipelines so you can still meet revenue targets.
The more ideal solution, however, is to map out reasons for customer churn to prevent customers from turning to a competitor.
Understanding customer churn goes together with customer retention analysis. Knowing why customers are leaving can improve your customer retention rates and help you understand the weaknesses of your product and strategy.
Monitoring churn helps businesses stay in touch with their customer base. Though it might seem like a straightforward process, many companies find it challenging to address churn.
Churn can be challenging to predict as the raw data needed for an accurate analysis can be messy and might require data to be engineered into a more usable format. Collecting data can be labor-intensive and requires removing outliers and identifying potentially essential features.
Is there an easier way to gather and sift through data to predict churn?
The Solution
Customer churn is a normal thing, but it is rare for businesses that are doing well. When churn rises, it can create an imbalance between loyal customers and customers who choose another company’s products or services.
In such cases, a predictive model might not give you accurate data.
Using an AI no-code machine learning system will provide you with more practical insights. ML methods can help you build business models with data that can more accurately predict customer churn.
Graphite, the company behind the world’s easiest no-code machine learning platform, can help you deal with churn.
Using our system, your sales and marketing teams can identify customers you’re likely to lose by analyzing their transaction history and purchasing behavior.
We can also show you your business’ historical churn rates during certain times of the year and seasons.
When you have a system that can predict churn rates, you can mobilize your sales and marketing teams to find new leads and enact customer retention measures ahead of time.
The Impact
Customer churn is unavoidable, but predicting it can help businesses understand their weaknesses and implement strategies to lower it.
An AI-generated system that collects, arranges, and analyzes data can lower your churn rate. It can also provide you with better insight as to how your customers relate to your products and services.
An increase in your customer retention by 5% – 10% may have a tremendously positive effect in the long run.
See Graphite Note in Action
Live Demo: Predict Customer Churn
In this demo example, we are using the CRM dataset with historical sales leads.Predictive lead scoring is a powerful tool for businesses of all sizes to quickly and accurately gauge the strength of leads.
With a no-code tool like Graphite Note, businesses can leverage the power of predictive lead scoring without the need for complex coding or IT resources.
Further Reading
Precision versus Recall Introduction Precision versus recall are important metrics in machine learning. Understanding the difference between precision versus recall...
