visitors to WSJ.com now each receive a propensity score based on more than 60 signals, such as whether the reader is visiting for the first time, the operating system they’re using, the device they’re reading on, what they chose to click on, and their location (plus a whole host of other demographic info it infers from that location). Using machine learning to inform a more flexible paywall takes away guesswork around how many stories, or what kinds of stories, to let readers read for free, and whether readers will respond to hitting paywall by paying for access or simply leaving. (The Journal didn’t share additional details about the score, such as the exact range of numbers it could be. I asked what my personal score was; no luck there, since the scores are anonymized.) “I think back to maybe eight months ago, when we were looking at all these charts with a lot of different data points. Now we’ve got a model that’s learned to a point where, if I get a person’s score, I pretty much know how likely they will be to subscribe,” Karl Wells, the Journal’s general manager for membership, told me when we spoke last week, with a Journal spokesperson on the call. “What we’ve found is that if we open up the paywall — we call it sampling — to those who have a low propensity to subscribe, then their likelihood to subscribe goes up.” (The Journal’s model looks at a window of two to three weeks.)
The Journal has found that these non-subscribed visitors fall into groups that can be roughly defined as hot, warm, or cold, according to Wells. Those with high scores above a certain threshold — indicating a high likelihood of subscribing — will hit a hard paywall. Those who score lower might get to browse stories for free in one session — and then hit the paywall. Or they may be offered guest passes to the site, in various time increments, in exchange for providing an email address (thus giving the Journal more signals to analyze). The passes are also offered based on a visitor’s score, aimed at people whose scores indicate they could be nudged into subscribing if tantalized with just a little bit more Journal content.