InPublishing Special: Datawalls & Paywalls

This article was written by Vicky Macey as part of the 'Subscriber Acquisition Special' with InPublishing.

Q: What is best practice?

A: Best practice is striking the right balance between monetisation strategy and user happiness. It’s not just about slapping up a pay / data wall and hoping for the best; it’s about figuring out the combined impact of the specific treatment on both the business and the audience/s.

One-size never fits all. This approach has been proven to fail since the beginning of digital publishing plans. Dynamic paywalls that adapt and respond to user behaviours — frequency of visit, what they read, whether they’ve engaged before and how — are far more effective than a hard and fast, rigid barrier.

Of course there is an AI use case here! AI-driven paywalls can analyse behaviours to determine the best monetisation approach in real time. For example, it can assess whether a user is a casual passer-by or a loyal visitor and adjust the paywall experience accordingly — be it a free trial, discount, or restricted access to premium content at the right moment.

Datawalls and paywalls are friends. Email addresses and a few basic demographic details in exchange for limited access to premium content can be a great way to build up first-party data without scaring potential readers off. It also supports segmentation for personalised approaches and offers later on.

Readers will drop off if signing up or subscribing is remotely painful. Keep it simple with friction-free registration, multiple standard payment options and single sign-on so users can move across devices.

A/B See! Testing placement, messaging and pricing is crucial. As is regular — if not continuous — assessment and refinement.

Mix up monetisation models to find a sweet spot for your specific audience. Some audience segments will pay for premium, while others with exactly the same content interests are quite happy to read for free with ad-supported access. The hybrid model — free, metered and full paywall — gives audience agency and maximises revenue potential.

Data-driven decision making is the foundation of all successful pay and datawall strategies. Keep on iterating based on what your audience does and not what you think they’ll do.

Q: What does outstanding performance look like?

A: Higher conversions, better engagement and sustainable revenue growth — all without driving away casual readers. Some examples we’ve seen working on:

• Adaptive AI-powered paywall that adjusted access based on reader engagement levels — the AI analysed the frequency of the visit, types of content consumed and whether they had shown interest in subscriptions before. The system then decides whether to let the reader in for free, show a datawall or trigger a paywall with a personalised offer. This led to a solid uplift in subs while keeping ad revenue — the publisher’s bread and butter until now — steady.
• First-party data done well, by setting up a datawall whereby users had to register before accessing premium content. Data-driven insights then allowed for razor-sharp segmentation, allowing for more targeted marketing and optimised subscription offers. This boosted both data collection and conversion over time.
• Tailoring subscription offers by analysing browsing habits and engagement so that it could be determined which users are most likely to subscribe, then serving the right offer to the right user groups; for example, discounts to frequent visitors, trials for new ones and premium bundles for high-value users.
• A number of publishers are taking a super flexible, hybrid approach — keeping some ad-supported content while introducing premium subs-only articles. Again, data behind the scenes has been key to getting the balance right between monetisation and audience satisfaction.

The best pay and datawall strategies don’t just generate revenue but create amazing experiences for all users, making them stick around for longer.

Three top tips

1. Let data guide you. Always. And all the better if you can get AI to do the heavy-lifting while you do the thinking around optimised offers and experiences for audience groups and revenue models. Track content consumption, frequency of visits and engagement to determine when and how to introduce a paywall for the best chance of conversion.
2. Whether the aim is sign-up or subscribe, make it dead easy. A painful paywall is a lost opportunity. The process should be smooth, clear and largely uneventful for the user. Automation can be used to streamline further, predicting when users are likely to drop out and budging them back on track with the right incentives.
3. Experiment with different models. Don’t just rely on one approach because that’s what’s always worked in the past. A carefully crafted combination of datawall, metered paywalls and premium content tiers maximises appeal to different audience segments. Effective use of AI and data strategies can help identify which types of users are more ad-tolerant and which are more likely to subscribe and really channel your efforts and treatment of each group.