In Fall 2025, Les Coops de l’information, a collective of six Canadian media outlets (Le Soleil, Le Droit, Le Nouvelliste, Le Quotidien, La Tribune, and La Voix de l’Est) launched an innovative subscription drive named internally as the “Pay what you can project”.

Designed to coincide with the 2025 Municipal Elections, the campaign aimed to lower the barrier to local news while reinforcing the value of independent, cooperative journalism.

Results were beyond their expectations:

• 4.2% increase in subscribers
• Despite the minimum amount being $1 per month for the first three months of subscription, the average amount paid was $3.12 per month. This increased to $3.50 after increasing the suggested price

Principal Director, Audiences and Platforms, Marc Gendron shared how this strategy boosted subscriber growth and increased ARPU for those on this offer.

“Pay what you can” strategy

The core of the initiative was a flexible pricing model for the first three months of a new user’s subscription.

“We wanted to make an audacious promotion that would be too good to ignore! It shouldn’t rely solely on a heavy discount, but also on our unique value proposition at a time when it’s more relevant than ever.

Our gamble was: we know that there will be more interest towards our local politics content during the municipal campaign, so let’s surf on that wave and make sure our new promotional subscribers get the most out of their plans, that they feel that they are getting much more than what they are paying for. Instead of opening up access to our elections coverage, or setting up a fixed promotional price, we wanted to give more power and autonomy to users by letting them choose their price.”

Key components include:

• Democratic access: The campaign was rooted in the belief that a strong democracy requires exhaustive and impartial electoral coverage.
• Price autonomy: Prospective subscribers were invited to “fix the price” for their initial three-month period.
• Transparency and trust: Using the slogan “Un média qui vous ressemble, un média qui nous rassemble” (A media that looks like you, a media that brings you together) the group highlighted its status as an employee-owned cooperative.

“Our goal was to increase the total number of subscribers, between 3.5% and 4.3% of total subs. 

We mobilized everyone we could in order to achieve these targets. The new features we needed to implement, flexible pricing mechanics, everything was put on the development roadmap early in 2025. Our collaborators from Wizeline, who take care of all our platform development projects and Arc XP integration, worked tirelessly to have every feature ready for the fall campaign.

We also got the help of Drakkar Digital (renamed deRabane since), our long-lasting marketing partner, in order to create the visuals, copy and plan the delivery of all the marketing messages.

The editorial team was mobilised too, because the success of the campaign relied heavily on their capacity to deliver unique, useful and original content during that specific period.

Finally, our small digital growth team (including the IT and customer service team) operationalized the whole process.“

Feature gating: creating a product worth paying for

Of course, a promotional project is only as good as the product you’re selling! Les Coops has worked on developing strategic “feature gating” to build a subscription worth paying for, with clear value and strategic steps through registration towards subscription: 

Interactive engagement: Features like the “Question of the Day”  required users to be connected to vote and view live, constantly updated results.

Bookmarking across devices: Registered users gained access to a bookmarking feature, allowing them to save their favorite articles across web and app platforms.

Premium audio: Audio versions of articles were restricted to “All-inclusive” and “Ultimate” subscribers, serving as an upsell for basic plan holders.

Access limitations: To maintain account integrity, the platform limited simultaneous access to four devices, automatically disconnecting the oldest session when the limit was reached.

Premium content: Chroniques (articles written by columnists) and archives (articles published more than 30 days ago) have been hard paywalled as a key part of their subscription value proposition 

Marketing across site

As with any campaign, design and messaging needs to be consistent across the website and platforms, including the paywall. 

Dedicated paywalls: Les Coops d’Information built dedicated “Pay what you can” paywalls in Poool, including a live countdown to create urgency.

Subscription landing page: To ensure continuity of messaging through the user journey, dedicated subscription landing pages were also created in Poool, highlighting the value proposition, sharing subscriber testimonials and providing reasons why users should subscribe. 

Multi-channel promotion

The campaign was supported by an intensive five-week marketing blitz:

Email campaign: 72 unique emails (12 per media outlet) were delivered, each utilizing different angles and value propositions.

Targeted ads: The group targeted known non-subscribers through Google Ads, StackAdapt, and Bing Ads

In-app and newsletters: Non-subscribers were greeted with dedicated “Pay what you can” headers in free editorial newsletters and pop-up messages upon opening the mobile app.

Results 

“The final results were pretty impressive. By the end of the five weeks of promotion, our total subscriber base had increased by 4.2%, more than our targets and very close to our most optimistic forecast.

What was the most interesting though was the fact that, despite the minimum amount requested being 1$ per month for the first three months of subscription, the average amount paid was 3.12$ per month. This average increased to 3.39$ when we suggested 5$ in the price field and to 3.50$ when suggesting 6$. Each time we changed the suggested amount, we saw an increase in the number of users choosing to go with the suggested amount.

There are even some new subscribers that paid more than the regular price of a subscription!

Another really encouraging fact: 84% of these new subscribers had never subscribed before! This is probably one of the most encouraging findings of this adventure. It means that there is still room for us to grow.”

What’s next?

“This kind of campaign is a little more complicated than one with a fixed set of promotional prices. But the results we got were pretty impressive.

The fact that the user sets the initial price does add a layer of interactivity however, and it lowers the entry bar to a level where they feel comfortable. The core of the challenge remains though: to convince newly converted subscribers that our offer is worth the regular price.”

What should another publisher make sure of before testing this same project? 

“They should immediately get the buy-in from all important stakeholders as the impact on ARPU can be unpredictable. In our case, we feel that we were quite lucky to get an average ARPU of more than 3$ despite the fact that the minimum amount required was 1$. But that is still below the average ARPU we got with fixed price promotions and way below our regular numbers. Make sure that you manage everyone’s expectations. Even your own! 

That being said, as we have been galvanized by the nomination we got for this project at the INMA Global Media Awards, we will reactivate the Pay what you can promotion for two weeks in order to see if we can get similar, or even better, results this time around.”

The post Les Coops de l’information “Pay What You Can” Campaign appeared first on Audiencers.

Spektrum der Wissenschaft, a leading German science journalism publisher, embarked on a multi-phase journey to optimize its digital subscription model, Spektrum+. Facing the challenge of engaging a broad audience with “deep, heavy, nerdy science content,” and understanding the limitations of resources, the publisher turned to a rigorous, data-driven testing strategy to build a product based on actual user behavior rather than internal assumptions (what a crazy thought, I know!).

At Audiencers’ Festival in Hamburg, Ann-Kristin Ebert, ecommerce Manager at Spektrum, shared their two phases of getting started with segmentation. 

TLDR: lessons from Spektrum’s journey

- Start by testing everything to understand audiences and prove the importance of segmentation

- Then test what matters based on learnings. Prioritize based on valuable, large and underutilised segments 

- Let go of perfectionism! Accept that some things that can’t be done now, and maybe not next month, maybe not even this year. “We can’t bake big pretzels with tiny ovens!”

Phase 1: “Testing Everything” (test like Darwin was watching!)

In the initial phase, Spektrum adopted an exhaustive testing philosophy, described as “testing as if Darwin was watching”. The goal wasn’t necessarily to find a single winning variation immediately, but to build a comprehensive understanding of how different tests performed across diverse user segments.

Strategy and implementation

Spektrum focused on rapid, lightweight tests at the beginning of the purchase funnel to gain quick-win insights while minimizing cross-team dependencies. They initially targeted user groups they already knew well or could reach directly.

Key learnings from phase 1:

• Free trials: A banner promoting a free trial across all user groups had a significantly smaller impact on conversions compared to blocking walls in any usergroup. This led Spektrum to shift its focus toward testing its “hard paywall”.

• Contextual messaging (Facebook): Testing informal vs. formal language for Facebook referrals revealed that informal messaging (“Du” instead of “Sie”) nearly doubled click-through rates (CTR) for these audiences.

• Paywall design: Spektrum tested walls with one, two, and three offers across the 4 engagement groups defined in Poool’s dynamic paywall dashboard. While a single offer proved least effective across all segments, a three-offer wall with a central “Best Offer” highlight emerged as the strongest performer for the general audience.

• Text density: On the subscription offer page, most segments preferred shorter, concise text. However, a notable exception was print magazine subscribers, who converted better when presented with more detailed information.

Ann-Kristin shared that this first batch of testing proved very helpful for understanding the behavior of different segments, convincing the team that dynamicity is essential, and that they should start adapting to actual user needs, not just team assumptions.

“Evolution is a perfect way for the perfect adaptation for everyone – if you have some million years of time (spoiler: we didn’t).”

Phase 2: “Testing What Matters” (Test as if Marie Kondo could knock on your door at any time)

Recognizing that they lacked the “million years” required for total evolutionary adaptation, Spektrum moved into a more focused phase: “testing what matters”. This phase prioritized high-impact user groups rather than every possible variation for every segment.

Priority segments

Spektrum identified four key segments for prioritized testing:

• Biggest Group: currently “Volatiles” on mobile devices.
• Most Overall Conversions: currently “Volatiles” on desktop devices.
• Best Converting Group: currently newsletter subscribers.
• “Hidden Gems”: High-potential audiences, a segment that’s hard to identify. Ann-Kristin described this as like playing poker! At the moment, they think these audiences are those receiving mailings already

Device-based segmentation

A critical finding in Phase 2 was the difference in behavior between desktop and mobile users. While an “Unlock article now” prompt outperformed “Continue reading with Spektrum+” on desktop (raising both CTR and purchase rates), the same prompt on mobile increased CTR but dropped the purchase rate. It wasn’t so much the variations that were important here, but simply the proof that mobile and desktop users need to be treated differently. 

Operational framework and final lessons

To maintain this rigorous testing loop with a relatively small team, Spektrum implemented several organizational priorities:

1. Alignment through OKRs and RACI: They used three-to-four-month Objective and Key Results (OKR) cycles to define focus and RACI matrices to establish clear accountability for who is responsible, consulted, or informed for every task.
2. Data visualization: Spektrum emphasizes that seeing user segments visualized (e.g., in donut charts) makes it impossible to ignore the importance of the largest and highest-value groups.

3. Pragmatism over perfectionism: The team adopted “Zen mode,” accepting that “we can’t bake big pretzels with tiny ovens”. They focused on what could be accomplished immediately rather than future ideals.

Spektrum concludes that there is no “final version” of their product, only the next iteration, as user behavior and opportunities constantly evolve.

The post Spektrum’s evolution of audience segmentation and testing appeared first on Audiencers.

This article summarizes the session presented by Maxime Moné (CEO of Poool) and Virginie Clève (founder of Largow, a consulting agency) at the Audiencers Festival Paris on September 16, 2025. Together, they explored the question of “SEO & Paywalls: how can you combine audience and subscriptions in the age of AI?”

This presentation summarized in 5 points: 

- Choosing the paywall type (super hard/hard/soft) should be a strategic decision, not a technical one: each option has a different impact on visibility, content protection, and subscription conversion.

- Anticipate AI: allowing Google to read your content also means opening the door to ChatGPT or Perplexity; blocking Google risks a drop in SEO.

- Secure markup, and calibrate text before the paywall to prevent content leakage and find the balance between SEO (≥ 800 characters) and conversion.

- Adopt a hybrid blocking model: adjust the level of openness according to the value, lifespan, and type of content, rather than a single rule.

- Don't confuse protection with growth: blocking AI protects your content, but only a strong brand and a clear offering will create subscribers.

A lively presentation, Maxime and Virginie gave a candid overview of the current situation. SEO, paywalls, and now artificial intelligence are intertwined in a complex balancing act, where every decision influences visibility, conversion, and content protection.

1) Three types of paywalls… from an SEO perspective

Virginie pointed out that in SEO, paywalls fall into three main categories:

• Super hard: Google is treated as a non-subscriber, with no access to paid content. Examples: Les Échos, L’Équipe.
• Hard: Google is considered a subscriber, so it can crawl all content (e.g., Ouest-France and Le Canard Enchaîné).
• Soft: the majority of the market (~80% of sites)—paid content is visually hidden but remains present in the code, accessible to robots… and to any resourceful user.

Problem: in most newsrooms, this choice is not made by marketing management but by developers or SEO specialists, despite this being a highly strategic decision. “We can no longer treat the type of paywall as a technical parameter,” insists Virginie.

2) Why AI is changing everything

Before the advent of generative AI, a bypassable paywall was no big deal: crafty users were in the minority and subscriber growth continued. Today, it’s a different story. AI such as ChatGPT, Perplexity, and Meta AI can query Google via SERP API and reconstruct all or part of the paid content, without compensation for publishers.

The result: if you consider Google as a subscriber (hard or soft paywall), you are indirectly leaving your content open to AI. But if you close the door completely (super hard), you penalize your SEO. This is an unprecedented dilemma that requires careful consideration and discussion among teams.

Another new development: since August 28, 2025, Google has officially recommended that soft paywalls no longer be used. The search engine wants to avoid indexing paid content by mistake, particularly due to new AI features such as AI Overviews and Gemini. In short: a clear line must now be drawn between free and paid content.

3) Hidden SEO risks in your pages

Structured markup: in the NewsArticle or ArticleBody format, you should never insert the entire paid text in plain text. Otherwise, any AI tool or scraper can extract it and republish it elsewhere.

The same problem applies to machine translations: Google Translate can host media pages that are translated and laid out identically, but without tracking or advertising. This is simply a case of value capture.

The text before the paywall: Google considers that below 800 characters, a page is “thin content,” and below 1,200 characters, it is of average quality. On the other hand, the more you give, the less you convert. Each media outlet must therefore find its balance between SEO and conversion—ideally through A/B testing.

4) Hybridization, the future standard for paywalls

However, the solution is not to close everything off. Max and Virginie advocate a hybrid blocking strategy: adjusting the level of protection according to the value and lifespan of the content. For example, temporarily opening a news article, then closing it once its peak visibility has passed. Some publishers, such as Ouest-France, are already experimenting with engines capable of automatically arbitrating between free and paid content.

At the same time, other avenues are emerging: technical solutions such as Cloudflare or Akamai (access control, pay-per-crawl), or collective approaches (via GESTE, the Alliance, or joint legal action). But they all rely on one principle: this issue must be addressed across the board—product, SEO, subscriptions, and tech all around the same table.

5) Blocking is not enough to convert

Maxime Moné reminded us: “Users don’t subscribe just to access content. They subscribe for a brand, an experience, a promise.” Work on paywalls and AI is vital for the sovereignty and value of the media, but it will never replace editorial content, trust, and product quality.

The post Paywalls & SEO in the AI era appeared first on Audiencers.

Max Moné is co-founder and CEO at Poool, the dynamic journey builder to boost subscription conversion, engagement, and loyalty.

This article is the second in a 6-part series where Max shares what he learned from studying 100 subscription business models across 15+ industries. If you haven't read the first one yet, start here. 

Why we’re focusing on media for this one

In most subscription businesses, the rules for accessing the paid offer are simple. You subscribe to a box, you get the box. You hit a usage limit on Claude, you’re asked to upgrade. You want to get access to Calm for guided meditation? You get 1 week, then have to pay. Each model has its logic, but it’s tied directly to the product.

In media, it’s different.

Media online was historically free (almost always). Then publishers moved to paid models, and products got more complex: apps, newsletters, podcasts, games, bundling, community. Because of this, an enormous variety of access models emerged.

So we decided to go deep into media alone in today’s episode. Because the question “what’s free and what’s paid” is one of the most consequential product decisions in our industry.

And there’s no right or wrong answer. The right model depends on your organization, your editorial DNA, your content, your business model… It’s specific to each media, each newsroom, each audience.

The goal here isn’t to tell you what to do. It’s to show you the range of what exists, so you can figure out where the opportunities are for your unique context.

The engagement-frustration trade-off

The data on this has been clear for a while now.

In 2021, we published the Digital Media Review (DMR – a research initiative with Google and Le Geste – a french association for publishers) at Poool. One data point stood out: the relationship between the share of traffic exposed to paid content and conversion. The correlation is clear: the more you expose, the more you convert. But only up to a threshold. Past that, conversion plateaus or falls. Frustration alone is not a sufficient reason to subscribe.

And the other side of the coin is just as important: the DMR also showed a strong correlation between traffic on paid articles and the share of users who simply leave the site when hitting a paywall. The more you frustrate, the more people bounce. That’s not just a missed conversion. That’s a direct hit on engagement, on page views, ad revenue, and your ability to build any relationship with that user.

In the same year, Mather Economics published a study (part of a GNI LatAm Subscriptions Lab report) looking at paywall hits per user. Subscription probability follows a bell curve: up with each hit, peaks, then back down. Same conclusion, different data.

Then in 2022, the New York Times shared what brought all of this together (Audiencers analyzed it here). When they launched their paywall in 2011, the meter limit was the same for everyone: a fixed number of free articles, a regwall, some more articles, and finally a paywall.

Over the years, they developed the Dynamic Meter, a machine learning model that sets personalized meter limits per user.

The core insight: the model optimizes for two metrics simultaneously, engagement and conversion. And these two metrics have an inherent trade-off. More paywalls → more subscriptions, but less readership. They proved this with randomized control trials: as the meter limit goes up, engagement increases but conversion drops.

With a fixed approach, you’re forced to choose. Maximize engagement, or maximize conversion. Not both. There’s always a window of lost revenue that a single rule can’t capture. The Dynamic Meter expands that window by personalizing: more frustration for high-propensity users, more openness for low-propensity users.

None of this is new. DMR: 2021. Mather Economics: 2021. NYT: 2022. We’ve known this for years. And yet, the vast majority of publishers still use a uniform paywall for all users.

If you don’t personalize, you’re forced to make a choice between engagement and frustration. And that choice won’t be the right one for all users. That’s why more and more sophistication has developed. And the jump from “manual” to “1-2-1” isn’t binary. There’s a whole spectrum in between.

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The 6 levels of paywall sophistication

Being at level 1 doesn’t mean you’re behind. But it means there are probably missed opportunities. The question is whether these missed opportunities are big enough to justify the resources needed to reach the next step.

• Level 1: Fully manual

Free and paid decided by hand, article by article. An Atlas & Audiencers’ study confirmed this is still the norm: the decision is based on the article’s perceived value. Breaking news free, analysis behind the wall (to simplify it to its core).

• Level 2: Manual + automated rules. Paid content still decided manually, but rules modify access based on additional criteria.

Foreign Policy shared their approach on The Audiencers. They segment by publish date (under 7 days: hard-walled; older: standard meter), but also by cohort. Users with high search intent and churned subscribers are hard-walled (high subscription propensity). Social referrals see a registration wall with a free page view (low subscription propensity, but conversion on registration is 100x higher than on subscription). That registration data became their strongest conversion driver. No AI needed. Just smart segmentation.

• Level 3: Manual with override.

The base decision is manual, but the system can override contextually: closing a free article for a high-propensity user, opening a premium one for a segment you want to engage. A first step toward personalization without losing editorial control.

• Level 4: Manual + a third automated category.

Free and premium decided manually, but a “grey zone” is managed automatically based on user profile, device, or source. Ideal for publishers in transition between fully manual and more automation, while still giving the editorial team a great deal of control (yes, the business side gets some autonomy, but only on categories validated with editorial).

• Level 5: Fully automated for conversion and engagement.

The system decides everything: whether to show a wall, which type, what meter limit, per user. The engagement/frustration trade-off managed dynamically.

Business Insider does this with AI: reading habits, traffic source, content genre propensity. The algorithm decides: paywall, registration wall, or nothing.

The NYT does it with the Dynamic Meter (as we talked about earlier). It learns from first-party engagement data (no demographic or psychographic features), adjusts per user, and continuously runs randomized trials to improve. This is the model that expanded the opportunity window we described above (source).

• Level 6: Fully automated for conversion, engagement, AND advertising.

The decision also integrates ad revenue. Fortune’s CCO at the time, Selma Stern, explained that if a user’s subscription probability is too low (first-time visit, smartphone, social media), the paywall opens and the page view is monetized through ads. The goal is to maximize total user value, wherever it comes from (which I personally think is an amazing model for short term profitability – because yes, sometimes long-term profitability might require less revenue in the short-term).

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What you can take away from this (and test tomorrow)

Figure out which level you’re at. If all your users see the same paywall regardless of behavior, source, or profile: what are you missing?

Try one rule-based variation before thinking about AI. Foreign Policy’s 100x stat didn’t require machine learning. It required a hypothesis and a way to test it.

Start by looking at your bounce rate on paywalled content. If a significant share of users leave the site when they hit your paywall, that’s revenue you’re losing twice: no subscription AND no engagement. The DMR, Mather Economics, and NYT data all showed the same thing: a uniform paywall always forces a trade-off. Even a simple first step (like showing a registration wall instead of a paywall to low-propensity users) can start closing that gap. That’s what Poool makes it easy to test.

See you next week for Article 3, where we leave media and look at how the best subscription businesses across all industries think about conversion.

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PS: This article was about the decision logic (who sees a paywall, and when). We didn’t cover the blocking method: how the paywall is technically implemented, front-end or server-side, and what that means for content protection, AI scraping, and SEO. That’s a separate topic, and we covered it here: “Paywalls & SEO“. All 6 levels above work with all blocking methods.

The post What’s free, what’s paid, and why it’s really an engagement trade-off: episode 2 appeared first on Audiencers.

Lindsay Ederheimer is Director, Consumer Revenue at The New Yorker and Vanity Fair.

I was humbled on a recent Sunday afternoon by a phone notification informing me of my weekly screentime report. I’m not brave enough to share what my total time was (that will stay between me and Apple), but it was yet another reminder of how often I’m glued to my phone. On the bright side, I can at least defend the minutes I spent in the New Yorker app playing our newest daily word game, Shuffalo. 

That moment got me thinking about what actually feels worth the time I spend on my phone, and why games have become such an important part of what we do at The New Yorker.

Digital games are becoming ubiquitous for publishers and users alike. Everyone from The New York Times to LinkedIn have invested in games as a way to grow, engage, and retain audiences. 

The post The power of puzzles: How The New Yorker approached a games paywall appeared first on Audiencers.

Heiko Scherer is CEO at tschop and champion of a community- and audience-first' approach to digital media.

When it comes to paywalls, Heiko find that most teams focus on optimisation whilst missing the real question: what system are you asking users to join? 

The wall doesn’t create value, it reflects whether it was there to begin with.

For over a decade, the paywall has been the most visible signal of value in digital publishing. It’s where revenue meets retention, where UX meets editorial judgment and where the funnel becomes measurable. Teams debate how high it should be, how wide, when to trigger it and what language best converts.

The post What your paywall says about your product (and why it matters) appeared first on Audiencers.

A paywall blocks users and asks or requires them to pay for subscription in order to access content. And with digital reader revenue strategies on the rise across the globe, paywalls are popping up across publisher’s websites in all shapes and sizes.

Here are 160+ paywall benchmark examples to inspire your own paywalling efforts!

*Note: these have been collected since October 2022 and are continuously added to, meaning the paywall you see here may not be live on the publisher’s website right now. The oldest examples are at the top.

Paywall best practices to takeaway:

Consider a soft conversion strategy, such as registration, to increase engagement prior to fully blocking the reader

Ensure users have the chance to discover the value of your premium content

Communicate a strong value proposition

Include brand colors, selecting a single color to represent subscription

In a freemium model, label premium content to reduce frustration

Integrate other funnel steps into the paywall (such as the offers, payment or data collection) to reduce clicks and potential friction points

Work on optimizing paywall visibility rate, aiming to balance frustration and engagement (we found 80% to be optimal, but A/B testing is recommended to find the best visibility for your publication)

Make subscription easy, such as by offering account creation through Facebook/Google or payment through PayPal or Apple

If you’ve already collected key data points (such as name or content interests) make use of it to personalize the paywall and experience. For instance, you could build a subscription offer suited to content consumption habits, or adapt the value proposition to their profile

The post 160+ paywall examples to inspire your subscription strategy appeared first on Audiencers.

Adapting the paywall to a reader’s context, and particularly to the editorial topic they’re interested in, has enabled the women’s magazine ELLE to boost conversion rates. We spoke to Sophie Thierry-Clébant, Premium Manager, who tells us all about the project.

Where did you get the idea of contextual paywalls from?

When we launched the premium offer on ELLE, we obviously looked for the paywall model that would work best:

• In terms of visuals, images and colors
• In terms of how to present the offer

We often offer strong promotions, which we adapt to current events or seasons (sales, vacations, Mother’s Day, etc.):

These paywalls work very well, but you can’t run promotions all the time!

We needed to liven up the non-promotional periods by developing a more harmonious and coherent creative concept, linking print and digital. We also wanted to adapt our paywall to the profile of our female readers based on their browsing behavior, to ensure we met their expectations. Thus the idea of contextual paywalls was born!

What were your constraints in this project?

We have a predominantly mobile audience, so the paywall needs to be short, easy to read and understand quickly.

Our other constraint is a legal one: we have to show all subscription benefits in the paywall directly (since they’re not listed on the next registration page).

What was the outcome of this thought process?

We therefore thought about a fixed composition of paywalls that could be adapted to the reading context and the section the reader is in, via:

• A targeted tagline
• A frieze of visuals that are relevant to the topic
• As well as an adapted benefit, highlighting the editorial pieces most appreciated by subscribers in that specific section

We have now developed:

• 1 generic paywall, deployed on the site’s smaller sections

• 7 paywalls for various editorial topics:
  • Society (“Société”)
  • Fashion (“Mode”)
  • Psychology-relationships (“Psycho-sexo”)
  • Beauty (“Beauté”)
  • Design (“Déco”)
  • Cooking (“ELLE à table”)
  • Well-being / Fitness (“Forme / bien-être”)

> How the fashion magazine ELLE is using a dynamic paywall and continuous optimization to improve conversion rates

How did this work technically?

We’ve been using Poool’s journey builder for several years now, so it was very easy for us to put these ideas into practice. All we had to do was upload the subject tags into Poool, before building an adapted scenario for each rubric.

In the Appearances section, we created the generic template, duplicated it 7 times, adapted it to each context by modifying the tagline, the visual frieze and the first subscriber benefit and integrated then integrated each into the relevant scenario.

Did you launch on 100% of your audience straight away?

On the 7 major sections concerned, we A/B tested the generic paywall vs. the contextual paywall 50-50, to analyze the impact on conversions. We also tracked click-through rates, but our main KPI remains the conversion rate.

What are the results of these dynamic paywalls?

Custom paywalls clearly outperformed generic paywalls. Specifically, 3 sections showed a leap in conversion rate of +50% on average on contextual paywalls versus the generic paywall.

Other sections trended towards a +10% conversion rate, and only 2 sections performed either similarly to or slightly below the generic paywall. In the last 2 cases, we believe that the teasers were not optimal and are currently reworking them, before continuing the A/B tests to validate our hypothesis.

Overall, in the last quarter of 2024, the conversion rate to subscription using the paywall source rose by +20%!

Have you put any other dynamic strategies in place that adapt to a reader’s context?

Yes, absolutely. It’s something we’ve had for a few years now, but readers of certain newsletters have seen paywalls adapted to the theme of their newsletter:

The lesson to anyone reading:

In conclusion, contextualizing paywalls according to reader preferences and needs is proving to be a particularly effective and profitable way of optimizing our KPIs.

By placing the reader at the heart of our strategies, we can send the right message, at the right time to maximize the impact of our actions. It’s a great example of how to increase conversions when you’re under pressure with little time on your hands!

The post Contextual paywalls on ELLE.fr increase conversion rates by 20% appeared first on Audiencers.

The days of one-size-fits-all paywalls are over! Dynamic models, that adapt the paywall to a reader’s profile or context, are essential for success in today’s digital subscription market.

Even if you’re firmly set of a hard paywall model (where all readers are blocked by a paywall on all articles) there’s room for dynamicity. In fact, it’s arguably more valuable in a hard paywall model so that you can convince even your less engaged readers to convert.

But how do you get started with making your paywall dynamic?

This is exactly what we’ll cover in this article! The steps to understand your audience, put them into groups, adapt your paywall accordingly and be inspired by other publishers already employing a dynamic paywall.

Not quite sure of what a dynamic paywall is? This article is a great place to start.

1. Audit: Who are your audience & what content are you publishing?

Understanding who your readers are and what you’re publishing is the essential first step. And by this, we don’t just mean personas and value propositions.

If you’re going to build a dynamic model, this means you need to know who accesses your website, where, when and how. This will help you build groups (or segments) of readers.

• How do readers access your site? (mobile, desktop, app)
• Engagement: How frequently do they visit? How much time do they spend with you?
• Do you have logged readers? What percentage are logged compared to anonymous?
• Where are your readers based?
• How do audiences find you? Where do they come from? (social media, Google, news referral sites…)

Content:

• What content are you publishing?… topics, user needs?
• Which KPIs do you follow for article performance in each group and what percentage of content produced falls into each category? (for instance, Mather uses this useful matrix to define 4 key article types according to its goals.)

> Read more on the topic of evaluating the success of your subscription model here

2. How do they differ?

Now you know who your audience is and what you’re producing, the next step is to see how these different ‘types’ of reader profiles and articles impact conversion rates. For instance, do you have higher conversion rates on mobile vs desktop or vice versa? Maybe those who already have a free account convert better with subscription offer X than offer Y.

You don’t need to have answers to all of these questions immediately, it’s through testing different paywall models that you’ll find most of this out. But what is important is to always start with the data to create hypotheses. For instance, if data suggests offer X is more popular with logged readers then you could test pushing this offer alone on the paywall for this segment.

Questions you can ask yourself include:

• Which device leads to the highest conversion rates?
• Which ‘type’ of user converts best? Maybe those with a certain level of engagement or those who are logged compared to anonymous.
• Do readers on your app behave differently?
• Do any reader groups prefer a different payment method or use a different currency?
• Which content is the most read by subscribers?
• Which content converts the best? For instance, maybe some articles are more valuable for advertising revenue and so are worth leaving open.

3. Segmenting audiences: what can you adapt to?

With all of the above research and data from your audience in mind, it’s time to start grouping readers based on their profile (who they are) and context (location and article they’re trying to access). With these groups, you’ll be able to start testing adapted paywalls to each type of reader. For instance, based on level of engagement.

Some examples of segments:

• Device type (mobile, desktop) and web vs app
• Level of engagement: at Poool, audiences can be segmented into Volatiles (the least engaged), Occassionals, Regulars and Fans based on a customizable RFV score (recency, frequency & volume)
• Source of traffic: such as newsletters, social media, Google search, etc.
• Location
• User status: anonymous, logged, ex-subscriber, print subscriber
• Content type: politics, lifestyle, etc.

Or a combination of a few of these, according to your strategy. For instance, Jeune Afrique combines location (creating country groups based on propensity to subscribe and preferred payment method) and user engagement scoring.

> Find more on Jeune Afrique’s dynamic model and how it helped them double conversion rates in this interview with their team

4. Testing dynamic elements – what can you change according to the user/content?

Of course, once you’ve built your segments, you should adapt the paywall to the different behaviors of each group. So, what could you change?

• User journey: number of articles for free before the wall, type of wall presented (newsletter wall, paywall, registration)
• Text: for instance messaging centered around your value proposition or more focused on the benefits of subscription, the length of the text
• Design: colors, images, inclusion of subscription offers or not, order of elements on the wall, etc.
• Pricing: discounts, forefronting annual vs monthly
• Offers: which subscription product is promoted in the wall

But remember, despite all of these options, you should start simple and develop from there, making sure to always go back to the data and your targets. What works for your audience and publication might not work for another, and sometimes simple dynamic elements are more effective than going too complex.

5. Continuously test, learn and optimize

Ultimately, it’s only through regular testing and analysis that you’ll understand what resonates with each audience segment. It’s one of the reasons why manual work is so important when getting started with dynamicity.

And this can start very simple. For instance, before launching their paid offer, Blick in Switzerland tested different messaging angles for their registration wall to see if a focus on social proof, appreciation or congratulating users was more effective for conversions.

The social proof and appreciation tests were displayed across lower-engagement segments, whilst the ‘Congrats’ text was tested amongst highly engaged users.

Inspiration to get started with a dynamic paywall

Financial Times: currency adapted to location, a simple change that’s valuable for lowering the barrier to converting for international readers.

Jeune Afrique: messaging and offer adapted to propensity to subscribe.

For less engaged readers, the focus is more on sharing the publisher’s value proposition and explaining who Jeune Afrique are, with a low-entry (€1), low-commitment monthly-payment offer. Whilst for engaged readers, a discount on the annual offer to maximize retention (50% off), and messaging that focuses on the subscriber benefits as these engaged readers likely already know who Jeune Afrique are, they just need help understanding what more they can get by subscribing.

Different payment methods are also used based on location. Below, a wall for “Mobile money” (similar to PayPal) countries in Africa to reduce the barriers to subscribing for readers in these countries.

ELLE.fr: dynamic text and images according to the article tag. Below, examples from the ‘beauty’ and ‘cooking’ section.

The Kyiv Independent: messaging based on location, below the example for readers visiting the site from the US.

Medium: personalized text based on the user (first name), the content they’re reading (here, an article by Damian Radcliffe) and articles by similar authors.

NordJyske: login button or not based on a user’s status.

Those who are already logged into their free account won’t see the “Already subscribed? Login” text, whilst anonymous readers will see the wall on the left, offering easy access to login. This is a very simple dynamic element but one that can make all the difference.

La Croix: A different newsletter is promoted according to the content topic.

AOC: a soft paywall (newsletter wall) for readers who have been gifted an article by a subscriber. The reader gets access to all content for free for 48 hours in exchange for subscribing to the newsletter.

The post Inspiration on how to make your hard paywall dynamic appeared first on Audiencers.

Foreign Policy re-launched its paywall back in 2018 which was initially fairly open. But with increasingly more buy-in internally on the value of this model, the paywall model has tightened over time. Today, 50% of revenue is from digital subscriptions.

I spoke to Corinne Osnos, VP Subscriptions and Marketing at Foreign Policy, about how they divide content into free vs premium, some of the tests they’re running to better answer this question and the set up internally for ensuring every team is working towards optimizing for their digital subscription model. 

The post Testing, hard paywalls and editorial buy-in: Foreign Policy’s take on the free vs premium question appeared first on Audiencers.