In December, we talked about how The Wall Street Journal’s engagement strategy centers around three components: who, what, and where. Today, I’d like to dive deeper into how we identified the “what.”
For many years, our engagement efforts focused on just a few key product features and actions. However, as we considered building out a more robust, churn-reducing contact strategy, we started to think that there must be more. My team partnered with data analytics (led by John Wiley) and optimisation (led by Peter Gray) to set out to find those retention drivers through an exercise called Project Habit.
Our first step was to make an exhaustive list of all the things a member could do on our site. The list was quite long, including actions from “e-mail article” and “play puzzle” to “build watchlist” and “comment.”
Next, the data team built a model to ingest all of these actions or “habits.” The team decided to borrow techniques commonly used in medicine by applying the Kaplan-Meier estimator to member retention. Essentially, the model compares the “survival rate” of members who have taken a particular action against the rate of those who did not. It looked at the impact of performing these actions within the first 100 days of membership and how it affected retention in 30-day increments over the course of their first year of tenure.
Here are some of the top line trends we found:
- Loyalty: Whether it be loyalty to a particular section or a particular journalist, members who consistently visited the same coverage area or author proved to stay with the Journal longer. The particular area or author didn’t matter, as long as they were loyal to it.
- Cadence: Those who read content that publishes with a regular and obvious cadence stayed at an above-average rate. When readers know exactly when to expect something, they come to rely on it and read it each time it comes out.
- Play: While we’ve known our members rely on the Journal’s financial and political reporting to inform their business decisions and professional lives, the model revealed that lean-back content and features drive retention too.
Armed with the lessons of Project Habit, we were able to make data-driven and meaningful adjustments to our engagement strategy. We used the newfound data to diversify and optimise our existing communications, as well as champion a longstanding need for more prominent member messaging within our products.
While there’s no silver bullet to soundly eliminate churn, our quantifiable understanding of what actions drive retention gives us powerful ammunition in the fight against it. Coupling this insight with bigger, better space to communicate with members has allowed us to build an engagement strategy that drives better product usage and retention.