Even though email subscriptions grow at a much slower pace and aren\u2019t subject to the same level of virality that you can experience with Facebook pages, publishers have found that newsletter subscribers are more loyal and drive more revenue. The New York Times, for instance, discovered<\/a> that subscribers to its free newsletters were twice as likely than non-email subscribers to convert into paying members. Conde Nast\u2019s data team found<\/a> that whether someone subscribed to a New Yorker email newsletter was the No 1 indicator that they\u2019d eventually pay for the magazine\u2019s content. And Seattle Times email subscribers are 25 times more likely to convert<\/a> to paid members than Facebook subscribers. <\/p>\n\n\n\n But while the email newsletter dates back to the 90s as a mode of distribution, this doesn\u2019t mean publishers aren\u2019t continuing to develop new innovations with the medium. In fact, news outlets are constantly experimenting with editorial formats, design interfaces, and machine learning algorithms to derive more and more value from their email operations.<\/p>\n\n\n\n Take Quartz as an example. The business-focused publisher has launched standalone newsletter products like Quartz Obsession<\/a>, a daily email that dives deep on a single topic and can be consumed in its entirety within the inbox. Quartz\u2019s tech staff has built out a number of interactive features for the product that allow its editors to quiz subscribers and run polls. This resulted<\/a> in an open rate of about 78 percent, a level of engagement that\u2019s pretty much unheard of (average open rates hover in the low 20s).<\/p>\n\n\n\n For years, newsletter editors have possessed the ability to perform a\/b testing with their email subject lines; you send versions of the newsletter with two different subjects to a small percentage of your followers, and then blast the full subscriber list with the subject that drove the most opens. But a\/b testing merely appeals to the whims of the majority, and it\u2019s limited in its ability to cater to individual user preferences. <\/p>\n\n\n\n Increasingly, publishers are leveraging personalization software that\u2019s long been available in the consumer product and B2B space. This technology tailors each individual email to the recipient\u2019s content tastes, and there\u2019s strong evidence that it leads to increased engagement for publishers. Take The New York Times as an example. It\u2019s rolled out<\/a> dynamic email signup forms that steer you to newsletters that you\u2019re not currently subscribed to; that way you\u2019re not prompted to sign up for a parenting newsletter you already read every day. The Times has also integrated<\/a> a machine learning algorithm into its Your Weekly Edition email. \u201cWe algorithmically select the articles we hope will be most interesting to you, based on articles you have read as well as stories that other Times readers found interesting,\u201d the Times wrote in its June 2018 announcement.<\/p>\n\n\n\n The Washington Post has applied machine learning<\/a> to \u201cpop-up newsletters,\u201d which are sent to a subset of its larger subscriber base to highlight individual stories. Rather than promoting an array of article headlines, these pop-up newsletters will only link to a single story that\u2019s likely to appeal to that particular subscriber. \u201cClick-through rates for the personalized newsletters are three times the average and the overall open rate is double that of the average for the Post\u2019s newsletters,\u201d reported Nieman Lab.<\/p>\n\n\n\n Some publishers are prompting readers to manually input their content preferences when subscribing to a newsletter. The Austin American-Statesman built a tool<\/a> that allowed users to choose from hundreds of content keywords, and it deployed an algorithm to recommend newsletter stories based on those tags. It then ran a test comparing the engagement rates of its personalized newsletter against another newsletter curated by a human editor. \u201cAggregate engagement data below show that [the personalized newsletter] outperformed the [human-edited newsletter] on all variables except unsubscribe rate during the test period,\u201d wrote Tracy Clark, who helped develop the product. \u201cDaily emails from [the personalized newsletter] were nearly twice as likely to be opened and almost three times more likely to have a story actually read by a subscriber.\u201d<\/p>\n\n\n\n These personalized emails don\u2019t just generate more engagement, they\u2019re also more likely to drive reader revenue. The UK newspaper The Times, with the help of a $1.2 million grant from Google, developed an AI-powered newsletter<\/a> that not only personalized content selections for each individual user, but also delivered the newsletter at the time you were most likely to open it. For a nine-month period, The Times delivered this personalized email to 117,000 randomly chosen paying subscribers, and it found that subscriber cancellations fell by 49 percent in this test group. \u201c[The newsletter] created habits among the lowest engaged groups which are the hardest groups for us to retain,\u201d said<\/a> Mike Migliore, head of customer value at the newspaper. <\/p>\n\n\n\n Of course, newsletters are only one of many distribution methods that can be personalized. Publishers are experimenting with personalizing everything from home pages to mobile push alerts. Often, this technology is best at increasing loyalty among more casual readers, the ones who don\u2019t dedicate as much time browsing through a publisher\u2019s content searching for the stories they find most appealing. With so much riding now on paid subscription business models, publishers need ways to serve their least-engaged users. Generating paid subscriptions is only half the battle; the real struggle is retaining the subscribers you already have.<\/p>\n\n\n\n
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Simon Owens is a tech and media journalist living in Washington, DC. Follow him on <\/em>Twitter<\/em><\/a>, <\/em>Facebook<\/em><\/a>, or <\/em>LinkedIn<\/em><\/a>. Email him at simonowens@gmail.com. For a full bio, <\/em>go here<\/em><\/a>.<\/em><\/p>\n\n\n\n\n\n
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