Dynamic paywall
A dynamic paywall adapts its rules to each reader's behaviour and propensity to subscribe, rather than applying one fixed meter to everyone.
Larger publishers use it to show the right offer to the right reader, but it needs data and tooling to run well.
Why it matters for publishers
A fixed meter treats a first-time visitor and a daily reader identically. A dynamic paywall varies the number of free articles, the offer and the messaging by reader, so you stop giving away content to people who would happily pay and stop pushing offers at people who are not ready.
How publishers use it in practice
- Start simple: two segments (casual vs engaged) already capture most of the upside.
- Feed it real signals — visit frequency, recency, referral source, device, article topic.
- Test the offer, not just the meter: a discounted annual plan may work better than an extra free article.
- You need volume for this to pay off; below roughly 100,000 monthly readers a well-tuned fixed meter usually beats a poorly trained model.
Frequently asked questions about dynamic paywall
- What data does a dynamic paywall need?
- First-party behavioural data: page views per session, sessions per month, recency, entry channel and whether the reader is registered. No third-party cookies are required.
- Is a dynamic paywall worth it for a small publisher?
- Usually not at first. Fix pricing, offers and churn before investing in propensity modelling — the gains there are larger and cheaper.