With ad revenue falling year after year and adblock usage on the rise, many publishers are returning to direct reader revenue strategies. One of the first steps in growing digital subscribers is setting up a paywall. But the paywalls of yesterday are no longer successful, from The New York Times initially offering 20 stories per month for free to the need to plug all the leaks from social, search, and cookies manipulation. To help publishers develop a stronger paywall strategy, Lenfest’s Matt Skibinski paywall best practices from over 500 publications worldwide—though the whole report is very enlightening, 3 main insights stand out.
Aim to reach 5-10% of your readers
Metered paywalls do drive subscriptions–a study from the Media Insights Project found that 47% of new subscribers reported that running out of free articles pushed them to pay for a subscription.
But for this to work, your readers need to actually see your paywall. To reach enough readers, you’ll need to experiment with the stop rate–how many readers are actually hitting the paywall in a given month. You’ll need to reach your most loyal, engaged non-subscribers as these will be the readers most likely to pay for your content.
Industry-wide, the most successful strategies aim to reach 5-10% of readers, as these are the most engaged readers who are in turn most likely to subscribe. To reach these readers, you’ll need to look at the data: how many stories do your most engaged non-subscribers read in a month? This will depend on your own audience, but across the industry this is usually around 5 stories. In the past few years we’ve seen this number drop dramatically, from 13 free stories in January 2012 to today’s average of 5. This may still decrease, as we’re starting to see publishers like The Boston Globe going even tighter, reducing from 5 stories in 45 days to just 2.
Personalise your paywall targeting via reader data
While adopting a metered paywall is an important first step, it is not enough. To mature in your paywall strategy, you will need to have a deep understanding of who your readers are and what motivates them to subscribe.
With this knowledge of your readers you can then move onto personalising the meter targeting rules based on variety of variables, including experiment with different rules or messages based on:
- Geography: reader’s location, either in-market or out-of-market
- Referral: how the reader arrived on your site, such as via search or social
- Ad-blockers: you can have a tighter paywall for readers using an ad-blocker, encouraging them to support your journalism by subscribing
- Subscription propensity: developing a statistical analysis of readers’ individual likelihood of subscribing
Targeting your paywall for readers based on their subscription propensity will require more analysis of your audience, but will pay off when you are able to better convert subscribers. Exactly what defines the profile of a likely subscriber may differ for each newspaper, but there are some common aspects shared industry-wide. For example, many newspapers have found that newsletter subscribers are twice as likely to pay for a subscription later on and are more loyal than readers who come to the website via social or search.
The Wall Street Journal, who launched the first newspaper paywall in 1996, have now built a paywall that adapts to reader behaviour to decide how many free articles each individual reader should have access to. It has been designed to drive subscriptions and to communicate the value of subscribing. Through a machine-learning algorithm that measures activity on 60 variables, such as visit frequency, devices, and preferred content, a propensity score is developed. This is similar to Neue Zürcher Zeitung’s flexible paywall which looks at similar variables as well as time of day to personalise the meter and the paywall message.
Develop your paywall strategy around your valuable content
We’ve all seen it before, newspapers lowering their paywall in special circumstances such as during an election or when promoting an exclusive story. But this sends the wrong message to readers: this content is so valuable that you can read it for free, the other content isn’t as valuable so you should pay for it. So instead, newspapers need to understand which articles are the most valuable for converting subscribers and develop their paywall strategy around this.
When developing the rules for your paywall, you can signal some types of stories that are either always behind the paywall (such as Helsingin Sanomat’s ‘diamond articles‘) or that trigger the paywall quicker, such as opinion pieces or in-depth analysis.
A reader who views local news stories is typically 5-10 times more likely to subscribe than a reader who views national stories, so you should tighten your meter for local stories to further encourage subscriptions. In his research, Matt Skibinski identified the types of stories that highly engaged readers are most likely to view before subscribing:
- Coverage of public transit, traffic, utilities, and other local resources
- Information about new businesses, construction, and developments, and economic changes (especially relating to job availability)
- Information about local politics, especially issues that affect education, neighbourhood development, and public safety
- Local college & high school sports coverage (beyond scores)
- Local culture and arts news, especially shows and exhibits readers can visit
We’ve seen before from INMA’s Media Subscriptions Blueprint that investigative journalism and opinion pieces stand outs as the most triggering for digital subscriptions for all types of publications. Such articles cannot be found elsewhere, so it is clear that they have a high potential for subscription conversions, something that needs to be reflected in your paywall strategy.
Still, it is imperative that you understand what is most triggering for your specific audience. For example, The Wall Street Journal found that arts and culture content, something they had previously neglected, was in fact one of the top five drivers for conversion.
Media innovation analyst @ Twipe
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