Our latest white paper is out: A how-to-guide on building a churn prediction model in Google Analytics. Ready for you to follow step by step and develop your own model.
Data. Not really a word that provokes a tickling feeling, is it? Nevertheless, data is extremely valuable if you understand how to use it properly.
For instance, it can be used to identify specific subscribers, who aren’t engaging much with your product. Subscribers who may even be thinking about cancelling their subscription - commonly known as churn. Wouldn’t it be nice to know who they were before they acted on this thought? Well that’s actually possible.
In our latest white paper, you can learn how to build a Churn Prediction Model in Google Analytics. By doing so, you can identify users who show low engagement with your product, and this gives you a far better chance of reaching them before it’s too late. Now it tickles, right?
Get User ID tracking in your solution
Visiolink developed User ID Tracking back in April 2017. This feature enables you to link events such as publication openings, downloads, page views etc. to specific users. This opens a wealth of possibilities, one of them being churn prediction.
It’s even possible to set it up to work together with your current tracking system, whether it's Chartbeat, comScore or another system. Then you'll have all your tracking data from both website and ePaper in one place.
Feel free to contact our Business Development Lead Daniel Rostamzadeh, firstname.lastname@example.org if you want to implement User ID in your solution, or if you have any questions about User Tracking, anti-churn, key metrics etc.