You can’t grow your business effectively if customers are leaving too often. Using machine learning techniques, you can identify which customers are most likely to leave, keep them for longer and increase their value to your business.
Keeping hold of existing customers costs less than getting new ones, but even that can be difficult to do when your customers have lots of choice and your competitors have lots to say. Keeping your customers for longer is just a case of knowing why they might leave, but that’s not always easy to find out and your customers won’t always tell you.
Peak pulls together lots of different types of data about your customers’ behaviour, such as purchases, feedback, social media activity and web usage. By applying churn detection algorithms, our data machine identifies which of your customers are most likely to move on, so you can take action that encourages them to stay.
THE TECHIE BIT
We build models that are specifically tailored to your circumstances and business. The modelling approaches we use include counting process-based survival models, logistic regression, random forest survival analysis and recurrent neural networks. By combining approaches, we can predict when a given customer is likely to leave with high precision, allowing us to suggest why this might be happening.
By identifying the customers that are most likely to leave your business and shaping strategies to keep them for longer, Peak increases the value of each customer and the profit your business makes overall. What’s more, as the strategies used are made to keep customers happy, we improve the satisfaction of your customers, too.