PostUp will unveil a new solution to help publishers boost subscription revenues next week.
The email service provider will launch Dynamic Content Wall, a marketing product that allows publishers to personalize pay and registration walls for each individual reader. It's an extension of the company’s Audience Development Solution, an email marketing suite for publishing companies.
PostUp, which helps the media industry increase its email subscribers and readership, works with such publishers as Disney, NBC, and The Onion.
Keith Sibson, the company's VP product and marketing, described how publishing companies can personalize their business model with Dynamic Content Wall in a conversation with Email Marketing Daily.
There are two types of cost structures in the publishing industry, and news companies generally either make money from advertising or via a subscription cost. Sibson believes the latter paywall solution is the direction in which publishers need to go, as a programmatic business model does not support companies with high product costs for content.
“Consumers will pay for quality content,” says Sibson.
PostUp’s Dynamic Content Wall takes a hybrid approach to a traditional paywall solution and can be personalized for each individual reader, versus a one-size-fits-all solution.
“The fear of paywalls is that you turn away your audience,” says Sibson. “People that might sit on your site all day and look at ads get shut out. Maybe they aren’t willing to pay, but they would consume ads.”
There are also some notable failures that may deter publishers from changing their revenue model. For example, in the U.K., The Sun put up a paywall and tore it down within six months. The New York Times, however, had its best-ever quarter for subscriber growth in the first quarter of this year.
PostUp uses machine learning to help publishers maximize their income by setting parameters for each individual. As with any machine-learning technology, the solution trains over time and becomes more intelligent as it incorporates more data.
PostUp’s machine-learning technology focuses on two variables: how much content a reader consumes and how that might affect the “ask.”
“Everyone as an individual has their own appetite for content,” says Sibson. “Everyone has their own threshold.”
For example, someone who visits a news outlet for the first time from a Facebook post probably won’t immediately pay for a subscription, although a reader who visits frequently and types in the publisher's URL might.
“A value exchange could be something more fluid than just money,” says Sibson. “It might be an email address, or an answer to a survey question. There are different options that you can prompt the reader with.”