How well-moderated comments provide rich audience insights to publishers

Olivia Collette, director of content and communications, Viafoura

In 2022, two things are true when it comes to publishers. First, with the impending deprecation of the third-party cookie, they need to take action to maintain a meaningful and comprehensive understanding of their audience. The tracking, managing and analysis of user data are essential to painting a basic portrait of their audience from which they can drive outcomes to move their business forward. 

And second, publishers love to hate comments sections. Comments can indicate how readers feel about a publisher’s content, but if not moderated properly, discussions can spin out of control, which alienates users, the newsroom or both.

While these factors may seem unrelated, tackling the challenges of the comments section can materially help publishers fulfill their need for first-party data. User-generated content, like that in comments sections, can provide publishers with valuable audience insight to continue to engage with their readers meaningfully.   

What’s necessary to make comments sections rich sources of data?

Gathering useful insights from comments sections depends on at least a couple of conditions. Firstly, comments need to be moderated by AI. And secondly, only people who are registered with the site can be enabled to comment. The minute a reader registers, the process of capturing data can begin.

When a publisher follows a registered user’s movements on their site, there’s quite a lot to glean from their interactions with the comments section alone. 

There are declarative data, which includes information that a user actively gives, such as when they post a comment. And there’s also inferred data, which tracks a user’s interest, tone or sentiment. For instance, inferred data could come from a reader reacting to a comment with a “like” instead of commenting. 

Then there’s augmented or enriched data, which is acquired when the AI learns qualitative information about commenters to gauge individual users’ behaviors, preferences and desires and how people feel about specific content. This type of data can get very granular because it eventually allows publishers to identify purchase intent and brand affinity.

For instance, imagine a controversial author publishing a high-performing opinion piece on a publisher’s site, and they want to get a sense of whether or not readers think it’s too inflammatory. Most publishers probably don’t have the resources to sift through, say, several thousand comments — even if the AI doesn’t publish the uncivil ones in the first place. In this example, the machine-learning tool can instead process the language in the comments to determine the positive percentage (in agreement), negative (in disagreement) or neutral.

The potential applications go deeper as well. If, in another example, one user always comments on restaurant reviews, but only for fancy establishments and never for a snack shack or greasy-spoon diner, the AI tool would learn that this user is a foodie. This individual is likely to respond positively to beautiful images of food and elevated restaurant experiences. Beyond just learning some information about the user, this data also presents an opportunity to tailor more content or advertising to that user and others with similar tastes.

How is commenting tied to other indicators of engagement? 

Commenters don’t just tell publishers how their content is performing. They also help the site perform. A survey by Viafoura of more than 650 million users found that commenters generated 48 times more page views and 99 times more dwell time than anonymous users. Digiday found similar results a few years ago when polling the Financial Times on its readers who also comment. This group is estimated to have a dwell time that’s seven times higher than those who skip the comments, and they come back to the Financial Times site more often. 

And it’s partially the comments themselves that keep readers engaged and on the site. According to a survey by the University of Texas at Austin’s Center for Media Engagement, nearly one-third of commenters spend as much time reading the articles as they do reading the comments on a site that has both.

How can publishers encourage user engagement?  

This all points to the fact that gaining access to meaningful first-party data is much easier when it’s built into a publisher’s engagement strategy. And it’s worth thinking about because a study conducted by Entrust shows that nearly 64% of consumers would willingly give up their data as long as they get “relevant, personalized and convenient services” in return. 

Relevance, personalization and convenience are all experiences, and experiences are often at the core of engagement.

Successful publishers are evaluating what users do when they’re on their websites. Do their actions add value to the content? The richer that experience is — i.e., author or topic follows, a personalized content carousel, several opportunities to like things, etc. — the longer they’ll stay on the website, and the longer they stick around, the more that can be learned about them. 

The publisher’s approach is evolving beyond considering the first-party data issue as a tracking problem, thinking of it instead as an experiential challenge. It’s easy to enable registrations, but what reason do users have to register in the first place? Publishers need to communicate that value exchange clearly, and in return, they’ll reap the benefits of a more engaged audience. 

Sponsored By: Viafoura

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