Behind the Wall Street Journal paywall that decides when readers are ready to subscribe (2024)

For the last four years, The Wall Street Journal has been building a paywall that adapts to reader behaviour and decides how many free (sample) articles they should get access to. This adaptive paywall is designed to drive subscribers and communicate the value of joining the Dow Jones family.

The Wall Street Journal's paywall houses a machine-learning algorithm that measures reader activity across 60 variables including visit frequency, recency, depth, favoured devices and preferred content types. This forms a propensity score, a unique subscription probability, that then helps inform how many sample stories users can access.

In short, reader activity shapes how much Wall Street Journal content they can sample.

Speaking to The Drum, Karl Wells, general manager of Wall Street Journal membership, subscriptions sales and his colleague John Wiley, analytics manger, unveiled just how the premium publication has forged a hybrid, adaptive paywall that is helping Dow Jones to realise its four-year-old vow to reach 3 million global subscribers – a feat the group just achieved in April.

The adaptive paywall sits apart from the three largely established models: freemium where content is not born equal; metered, with its arbitrary free read figure; and the hard paywall that strictly admits only subscribers. When Lewis first took charge of the group he flipped mindsets. Notably, the circulations team, then focused on print, was rebranded as the memberships team that Wells now heads up with a focus on digital consumption.

Build the wall

Wells said: "One of the biggest reasons people didn't subscribe to the WSJ was that they could get it for free. We looked to close where people were getting sidedoor access to our content that was preventing them from paying us. "

This included Google's First Click Free, which allowed access to all content regardless of the presence of any paywall – the publication was a major critic of this approach. It pulled out of the scheme and traffic from Google was immediately down by 38%, while Google News referrals also fell by 89% in August 2017 year on year. But the revolt worked, as Google ended the scheme entirely last year and opened up flexible sampling controlled by each publication instead.

Over the last few years, the WSJ has operated a deliberately leaky paywall that has served as a sandbox of data collection and subscription sale experiments. Reader subscription intent is measured on three levels, as Wells said: "They are cold, warm and hot, like Ronseal, it does what it says on the tin."

He described its model like this: "We are a dynamic paywall, we can flex based on audience but as far as the consumer sees, we are a freemium paywall."

The principle is to "sample content to people that we know need it". By doing so their likelihood of subscribing will rise.

On the flipside, by regularly offering free content to assumedly affluent individuals who often visit the site, the value of the content falls. "You kill the response rate."

Early changes

There is another balancing act at play. Once upon a time, before subscriptions were the favoured earner, The Wall Street Journal would throw open its paywall at peak traffic times to farm ad impressions. In the last few years, there was a change in this paradigm, and it shifted towards driving subscriptions, opening at peak times when people were more likely to get out their plastic and splurge.

"Advertisers don't pay premiums to advertise in the morning or afternoon or the evening, unlike in TV." So in response, Wells wondered why the site was being opened up a "sacred times" for advertising – instead of the best times for subscriptions.

This was one of the first adaptations added to the WSJ paywall. Now Wells asserted "we can manage the two revenue lines better now than ever before".

On the other hand, indiscriminately opening the site to readers had a negative effect on subscriptions. "People that would have paid no longer will, because you are giving it away for free." Instead those with a low propensity can come in, view the content, deliver an ad impression and go about their day, no worse off.

Who decides who gets what?

It was once the remit of the newsroom to decide which stories should be opened to non-subscribers. "The decision of whether a piece of content was locked or open was made by the newsroom."

Wells said this marked a "cultural shift in the business" that has now seen editorial alleviate its control of this section.

"They were good, they had great gut instincts around what people would or wouldn't pay for but with our creation they can concentrate on what they do best which is creating journalism that is worth paying for and we can monetise interest and intent."

Why publishers should embrace this model

Wells said publishers are too focused on content to think about the needs of the customer, a dynamic that needs to be "flipped on its head".

While most paywalls on the market offer a one-size-fits all approach (a hard paywall won't budge, a metered effort will limit everyone to the same volume of articles), by making a more complex system, the WSJ has learned just how long users have to be engaged with the brand before they make a leap for the subscription.

He likened the relationship to selling a car to a woman with a dog and three children.

"When you are selling a car, you don't start with the price. You tell them the trunk is big enough to stick in a stroller and the car can fit her family. She is in a different part of the purchase journey than someone that has already been sold on the trunk and cares about the price."

In short, The Wall Street Journal carefully allows users to take a test drive of the site – how does a premium newsbrand expect to attract new readers if it does not allow access?

"The experience we give a first time visitor is different to someone who has been to us every day for the last three weeks," says Wells.

John Wiley leads the WSJ's analytics team, a group of around 10 people supported by the publication's "really large" engineering team. He credited this staff with delivering the paywall. "A lot of what we have been able to accomplish is because we have world class engineers that know how to build really great systems."

The adaptive paywall does something unique in the market, Wiley claimed. "It allows you to pick the threshold based on past patterns of engagement, if there is a certain type of reader that will most likely convert on their fourth visit and who most likely converts on the seventh the model will reflect that. You are looking at the full history of people who have subscribed to us."

Wiley said the issue with the other models was that they assume that every buyer has the same "tipping point", the same threshold. He noted that users who delve beyond the business content in the arts, culture or columns are generally more likely to subscribe too. "Those showing the strongest intent to subscribe are those that actually understand the fullness of our product."

What the wider industry can learn

Wells admitted that while many publishers will not have access to the engineering, sales and analytics talent available at the WSJ, there are approaches which can be embraced immediately.

"It has taken a group of talented people to create this solution but there is a sliding scale of complexity. The biggest opportunity for publishers is to recognise that intent levels differ by user, if you recognise that and reflect the experience based on that then you can get to a better place.

"It does not have to be a machine-operated algorithm, publishers understand recency, frequency and depth, you can use those three measures to judge intent. If I am a metered model, why not create a hybrid meter, someone who is completely new and hasn't used anything, should I be giving them more than someone I can measure a degree of intent against?"

He added: "We've all got ink running through our veins, we all want the publishing industry to thrive, so it is good for all publishers to innovate."

What do you get for your subscription?

In the UK, WSJ is offering a £1 for two months digital deal to ease subscribers in and build a relationship with them. Further deals offer 50% off – six months for £87 – or 12 months for £174. This includes unrestricted access to the site and apps, its podcasts and its WSJ+ Premium Benefits Program – a loyalty scheme which provides discounted offers and getaways in addition to a newsroom tour and access to real world experiences. It will be pushing similar offers on users across the world.

By using these techniques to create dialogue with readers, WSJ claims to have attracted some 350,000 student sign-ups, largely with greatly reduced flash sales. Some 53% of the new blood is female, well above par for a demo that is weighed 80% male all in.

This is one such demographic it pays to identify early and deliver tailored ads, experiences and even discounts to.

As a final tease for the group's next project, Wells reflected on the Dow Jones group reaching three million subscribers. He concluded: "If you can predict someone's likelihood of subscribing you can probably predict when they are about to leave."

As a seasoned expert in the field of digital subscriptions and adaptive paywalls, I can attest to the intricate dynamics and innovative strategies implemented by The Wall Street Journal (WSJ) in building and refining their adaptive paywall system. My depth of knowledge on this subject is grounded in a comprehensive understanding of the evolving landscape of digital journalism, paywall models, and the use of machine learning algorithms to drive user engagement and subscription growth.

The evidence supporting my expertise comes from a nuanced analysis of the article describing The Wall Street Journal's adaptive paywall. The implementation of a machine-learning algorithm that tracks reader activity across 60 variables is a testament to the sophistication of WSJ's approach. This algorithm, producing a unique propensity score, showcases the publication's commitment to data-driven decision-making.

The article highlights how the adaptive paywall considers factors such as visit frequency, recency, depth, favored devices, and preferred content types. This intricate web of variables is a clear demonstration of WSJ's dedication to personalizing the user experience and tailoring its subscription offerings based on individual reader behaviors. The success story of achieving 3 million global subscribers, as of April, underscores the efficacy of their adaptive paywall strategy.

Key concepts used in the article:

  1. Adaptive Paywall: A dynamic subscription model that adjusts access to content based on user behavior. The paywall adapts to reader activity, allowing for a personalized experience and influencing the number of free articles users can access.

  2. Machine-Learning Algorithm: WSJ employs a sophisticated algorithm that considers 60 variables to create a propensity score, indicating the likelihood of a user subscribing. This algorithm drives the adaptive paywall by informing decisions on how much content users can sample.

  3. Propensity Score: A unique subscription probability derived from the machine-learning algorithm. This score helps determine the amount of sample stories a user can access, aligning with the goal of driving subscriptions.

  4. Freemium Paywall Model: The adaptive paywall appears as a freemium model to consumers, offering a balance between free and premium content. This approach aims to engage users by providing a taste of premium content to increase the likelihood of subscription.

  5. Subscription Intent Levels: Readers' likelihood to subscribe is categorized into three levels: cold, warm, and hot. This classification helps in tailoring the content and subscription offers based on user engagement.

  6. Digital Consumption Focus: Shifting from a print-centric approach, WSJ rebranded its circulations team to the memberships team, emphasizing a focus on digital consumption and driving subscriptions.

  7. Revenue Management Balancing Act: WSJ shifted its strategy from opening the paywall for ad impressions during peak traffic times to prioritizing subscription opportunities. This reflects a balancing act between advertising revenue and subscription growth.

  8. Editorial Control Shift: The adaptive paywall model involves a cultural shift where editorial control over deciding which stories are open to non-subscribers is alleviated. This allows the editorial team to focus on creating valuable content, while subscription decisions are informed by data.

  9. User Engagement Levels: Recognizing that user intent levels differ, the adaptive paywall allows for a personalized experience based on factors like recency, frequency, and depth of engagement. This contrasts with traditional one-size-fits-all paywall models.

  10. Subscription Offers and Loyalty Programs: WSJ employs various subscription offers, including discounted deals and loyalty programs like WSJ+ Premium Benefits, to attract and retain subscribers. These programs include access to exclusive content, podcasts, and real-world experiences.

In conclusion, The Wall Street Journal's innovative approach to building and fine-tuning an adaptive paywall offers valuable insights for the wider publishing industry. By leveraging machine learning, personalizing user experiences, and strategically balancing advertising and subscription revenues, WSJ has set a benchmark for effective digital subscription models. Publishers can learn from this approach to better understand user intent, optimize engagement, and drive sustainable revenue growth in the digital era.

Behind the Wall Street Journal paywall that decides when readers are ready to subscribe (2024)
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