The Athletic Turns Comment Counts Into a Homepage Click Driver

The Athletic grew revenue by one-third to $54 million in Q2 2025, and one of the tactics it uses to drive clicks is strikingly simple: it displays comment counts on selected homepage articles.

Now part of The New York Times Company, The Athletic also posted an adjusted operating profit of $5.8 million that quarter, and advertising revenue nearly doubled to $14.1 million. As the source analysis notes, the Times and The Athletic together form publishing's most profitable case study. That makes their homepage mechanics worth examining.

The comment-count display tells readers which articles generate real discussion. It is a direct use of social proof on a surface the publisher fully controls.

Why does this matter for practitioners?

People gravitate toward content other people already care about. If one article shows 500 comments and another shows one, a reader is far more likely to click the former, the analysis argues. The count signals a conversation worth joining, or at minimum something interesting enough to make people talk.

Clickability, in other words, extends beyond images and headlines. Every publisher is trying to build community, and visible engagement counts tell like-minded readers where that community is active.

The tactic is particularly valuable for publishers with a large direct audience. As traffic continues to drop, the argument runs, publishers must extract more value from the audiences they already own.

Engagement signals do not stop at comments

Comments are one measure among several. The analysis recommends a more rigorous approach:

• Experiment with shares, likes and other signals to identify resonant content.
• Accept that not every strong article generates hundreds of comments; some are widely shared instead, or show unusually high engagement relative to traffic.
• Make visible what the audience values, and prioritize the best-performing content accordingly.

Most publishers already use composite engagement scores, the analysis observes. The industry is de-prioritizing raw traffic in favor of session duration, clicks, scroll depth and comments, on the belief that these behaviors build a truly engaged audience.

Can engagement data drive content prominence?

Yes, and the analysis outlines how. Publishers can use statistical modeling, potentially supported by AI, to identify articles over-performing against expected engagement levels, using a Bayesian-style approach. Those articles can then surface more prominently across homepages, section fronts and topic pages.

The effect is to combine editorial judgment with actual audience behavior rather than rely on judgment alone. The expected result: a better user experience and more click opportunities on owned surfaces.

How to test it

The analysis prescribes a simple sequence with clear KPIs:

• Start with comments: display counts on selected homepage articles and measure click-through rate.
• Expand signals: test likes, shares and other indicators, establishing which ones drive valuable repeat behavior.
• Identify over-performers: benchmark article engagement rather than promoting whatever has the most traffic.
• Improve prominence: test whether featuring over-performing articles increases engagement across owned surfaces.

One caution stands out. CTR is not a perfect success measure; the most clickable content can veer into rage-bait or clickbait, exactly the material publishers should avoid.

As referral traffic becomes harder to generate, the practical question is what publishers can do with the audiences they already have. Visible engagement counts, the analysis concludes, are a simple and almost certainly effective answer.