Defining Loyalty: Findings From Several Interviews with Premium Publishers

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Publishers today are in a tough spot. They know that traffic is shifting to Facebook, where their articles are being posted and shared within a walled garden of engagement and data. As a result, these publishers are left stranded without enough site visitors to drive ad revenue.

To make up for this loss, they’re starting to turn to subscription revenue models — enticing readers to pay a monthly fee in exchange for access to content.

That means their number-one priority right now is increasing loyalty.

If publishers can build loyalty among their readers, they can not only keep users returning to their site, reading their content, and viewing their ads; they can also hook them enough to sign up for paid subscriptions and solve those monetization problems.

Still, there’s a consistent challenge that keeps publishers from increasing user loyalty: they aren’t sure exactly how to define and measure it effectively.

That’s like being an apple picker who needs to collect 100 green apples, except you’re colorblind and you don’t know how to count. How do you know when you’ve reached 100? How do you know which trees to pick from? How do you know if any red apples slipped in?

You get the point. If you can’t define and evaluate the metric for your goal — in publishers’ case, loyalty — you’re essentially driving blind.

To help clarify, we spoke to Elad Gov Ari, our Personalization Product Manager at Taboola to help us break down this issue further.

After interviewing several premium publishers globally, here’s what he found.

What is the metric for user loyalty?

There are so many different ways to measure loyalty. Publishers are having a tough time choosing the metric that’s right for them and their audience.

These common metrics include:

  1. Total visits within a set period of time. Among publishers, this period of time fluctuates from 14 days to up to two months, though 30 days seems to be the most common. So if a user visits twice a day for 30 days, their total number of visits is 60.
  2. Number of days a user visits in the past 30 days. Meaning, a reader is only counted once in a 24 hour period, even if they visit your site multiple times in a day. So if a user visits twice a day for 30 days, their total number is 30.
  3. Total number of articles read in a given period, regardless of the number of sessions.
  4. Average number of pageviews per visit. For example, the number of articles a person views each time she visits the site.
  5. Breadth of interest. If a user comes to your website just to read about sports, they’re not as valuable as another user who reads articles across several categories. The more topics a reader consumes on your site, the more loyal they are considered to be. This is how publishers gauge your likeliness to subscribe.

Evidently, there is no one-size-fits-all metric for assessing user loyalty.

The ideal approach is to combine these metrics into an amalgamated solution that works for your publication. For instance, you might gauge user loyalty based on a mix of site visits and pageviews.

Many publishers aren’t at that point yet. They’re still figuring out how to formulate this elusive metric for loyalty. And that’s only the beginning of this issue.

What is the threshold for user loyalty?

Even if you can choose your perfect metric, the question remains:

What is the threshold for user loyalty? At what point does someone go from a casual reader to a loyal reader? What specific number of site visits or engagements ticks the “loyalty” box?

Some publishers attack this question by segmenting users into groups. These groups can be as simple as loyal vs. non-loyal users, or publishers can get more granular with groups indicating low, medium, and high levels of loyalty.

But the question persists: How many visits, how much time, or some other unit of measurement indicates medium loyalty vs. high loyalty?

From speaking with publishers, we’ve learned that there is no consistent answer. Even among those who had chosen a specific threshold or number, they couldn’t fully explain why. It was an arbitrary selection.

Which brings us to the next portion of this issue…

How do you use these metrics to increase user loyalty?

If you are able to break down your audience into segments, how can you serve them based on their loyalty?

For instance, should you provide different content experiences for non-loyal users vs. loyal users? Or for users with medium levels of loyalty vs. high levels of loyalty?

Almost all of the publishers we’ve spoken to said they don’t deliver different experiences to these audiences, but they would like to in the future.

They do agree, however, that if they were to treat these audiences differently, they’d spend more time nurturing users who are already engaged. Why? Because you’re more likely to keep engaging if you’ve already expressed interest.

What does the data say?

Publishers are on the right track in wanting to further engage people who are already engaged.

When we analyzed the data from our publisher network, we found that users who are more loyal by one metric are more loyal in correlation to the other metrics.

For example, if a user has a high number of total visits in 30 days, they’re also likely to have a high number of pageviews per session, or a wide breadth of interest.

Where do publishers go from here?

We’ve thrown a lot of hypotheticals at you. Now, it’s time to take action. It’s time to get serious about how you measure user loyalty and convert casual readers into loyal readers.

To start, our Personalization Product Manager, Elad Gov Ari, recommends identifying your goal. Is your goal to drive subscriptions, increase traffic to generate ad revenue, or just improve engagement?

“Once you have your goal, be prepared to revamp your strategies. If you want to drive subscriptions, for example, you may need to sacrifice an ad slot for a subscription form. Or if you’re seeing return readers but they’re not spending money, you’ll need to consider serving them different experiences (i.e. targeted content, personalized content) so they eventually convert.”

Most importantly, Gov Ari stresses the value of helping your readers form habits. It’s crucial to find people who are in the habit of coming back to your website every day. (You can identify them by using a “Power User Curve” or L30, as outlined by venture capital partner Andrew Chen.)

Once you find these readers, you can start feeding their habit with content tailored to their interests. From there, you can upsell them, entice them to subscribe, and convert them into loyal users.

User loyalty may still be murky territory for publishers. But they know it needs to be a priority if they want to improve monetization and build a successful revenue model. And we’re right there with you — working to more effectively gauge user loyalty, create strategies for driving engagement, and keep readers coming back for more.

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