In this guide, we share the various ways that publishers can segment their audience to develop a dynamic paywall model, with examples for each type of segmentation:
> By content type: free vs premium, user needs, date of publication...
> By user profile: level of engagement, user status, location...
> By acquisition channel: Google, social media, newsletters...
Some quick definitions:
> Audience segmentation: grouping users based on their profile or context, i.e. data that could impact their behaviour, inform us on what could convince them to subscribe or make them more or less likely to convert in that moment
> Dynamic paywall: a paywall that adapts for different audience segments. This could be in terms of the paywall design, messaging or even the journey itself (e.g. seeing a paywall or not). Note that "dynamic" doesn't necessarily equate to AI-driven. It's often rule based - i.e. a user reading a "politics" article sees a different paywall to a user reading a "sports" article.
There are 3 main buckets of audience segmentation with the goal of increasing conversion rates:
- By content type
- By user profile
- By acquisition channel
