Consider goals, tech readiness to unlock opportunities for AI-powered paywalls

By Katherine Ruane

Director of Strategic Marketing

Mather Economics

Atlanta, Georgia, USA

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With recent news from Digiday revealing Business Insider increased conversions by 75% using an AI-powered paywall, we're taking a closer look at how publishers can leverage similar strategies for their own success.

This guide introduces key areas for assessment and poses critical questions you can take back to your team to identify gaps in your current paywall strategy and unlock new opportunities with AI.

Whether you've already implemented AI or are just exploring its potential, AI-powered paywalls offer transformative possibilities, enabling data-driven decisions that optimise total revenue, enhance the reader experience, and drive greater efficiency.

AI can offer incredible assistance to media companies, but its success requires companies to properly define their needs and readiness.

Define your goals.

Start by clearly defining what you want to achieve with your paywall strategy. It may seem obvious, but whether you're already using AI or not, regularly revisiting your business objectives is essential to ensure you're maximising your return on investment.

Key questions:

• What's not working well in your current paywall strategy?
• What are you trying to optimise for with the help of AI? Are you looking to increase subscriber conversion rates, streamline content blocking decisions, or maximise total revenue across subscription revenue and advertising?
• Is your organisational structure aligned with key goals and willing to experiment?

Assess your tech and data readiness

Next, ask yourself if your paywall system is making the most of the connections across your tech and data ecosystem.

While it may be integrated with content management, ad servers, and analytics tools, the question is whether you're leveraging these integrations to their full potential. AI-powered paywalls often go beyond traditional setups, enabling smarter, real-time assessments of content and user value to drive better decisions.

Key questions:

• Is your current solution tailored specifically for news publishers or built for the broader subscription market?
• Is your paywall integrating well with your content management system (CMS), ad platforms, and analytics tools?
• Does your paywall provider support easy integrations with essential platforms?
• Does your setup facilitate experimentation and A/B testing?
• Where is your paywall data activation in the context of the overall data maturity pyramid?
• Have you determined whether to build, partner, or buy AI solutions to enhance your paywall strategy?

Ensure precision and agility in your paywall intelligence

Optimising and maximising total revenue is central to any paywall strategy. The stronger the data science and analytics behind your decisions, the better the results.

Publishers still developing their paywall approach may depend on rough approximations or simple rules-based systems to determine which users or content types trigger a paywall. However, AI can elevate this process by leveraging advanced algorithms to analyse user and content data in real time, driving improved performance.

Key questions:

• What data is driving your paywall decisioning today? Are you relying on user segments or content topics, or are you looking holistically across user and content data?
• Is your paywall optimising in real time based on your audience's data?
• Can your paywall determine when it's more optimal to deploy a registration wall versus a hard paywall?
• Does your paywall consider the content lifecycle, adapting its decisioning based on whether the content is newly published or considered archived content?
• Is your paywall responsive to seasonal trends and unexpected events in the news cycle?
• Do you have control over the intercept rate for predictable, sustainable success?
• Can your paywall resolve conflicting business rules while maximising revenue within editorial guidelines?
• Are you incorporating accurate advertising data, such as real-time ad performance, to improve the trade-off analysis between subscriptions and advertising?

Personalise and optimise all paywall levers

Even beyond the initial wall or no-wall decision, a personalised, audience-first approach is essential to boosting conversion rates.

Publishers who rely on one-size-fits-all models may miss out on key opportunities to engage different audience segments. By using AI-driven personalisation, publishers can tailor content, offers, and messaging to individual readers in real time, helping to boost the likelihood of conversion.

Key questions:

• Are any of your current paywall tactics still following a one-size-fits-all approach?
• Is your paywall adapting messaging and content access dynamically as users move through different stages of their journey?
• Can your paywall leverage AI to deliver the right offer (e.g., discount, trial, or full subscription) at the most opportune moment?

Test, test, test!

A/B testing is fundamental to uncovering what drives the most revenue from your paywall. AI streamlines testing, which automates experiments and analyses the results to determine which strategies are most effective. This ensures you're continuously optimising for your North Star goal, whether it's conversions, revenue, or user engagement.

Key questions:

• Are you equipped with the right tools and resources to implement A/B testing?
• Which paywall elements (offers, timing, or content triggers) are you currently testing?
• How frequently are you analysing test results and making adjustments?
• Are you spending too much time on testing, and could you benefit from adding AI to streamline the process?

Monitor key metrics

During testing and beyond, tracking the right metrics is crucial to understanding how well your paywall strategy is performing.

AI provides real-time data, enabling you to adjust your strategy on the fly. Key performance indicators like conversion rates, churn, and revenue per user offer insight into what's working and where there's room for improvement.

Key questions:

• Is your paywall evaluating conversion rates in real time and adjusting strategies accordingly?
• How is AI helping to optimise the balance between subscription revenue and ad revenue?
• Are you tracking user engagement metrics to understand how your paywall strategy impacts retention?
• How effectively are you using AI-driven insights to reduce churn and boost subscriber lifetime value?

Adapting your paywall strategy for ongoing success

As the media landscape rapidly evolves, it's essential for publishers to keep refining their paywall strategies.

AI offers a way to stay agile, responding to audience behaviour in real time and ensuring you're always adapting to the needs of your readers. Whether it's balancing ad revenue with subscriptions or personalising offers to build deeper connections, AI enables a more dynamic, data-driven approach.

Ultimately, the key is to consistently evolve your strategy in support of both your business goals and your journalistic mission.

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About Katherine Ruane

Katherine Ruane is director of strategic marketing at Mather Economics in Atlanta, Georgia, USA. Katherine can be reached at [email protected].

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