AI Revenue Engine for Media

5 Ways Publishers are Using Deep Data

By now, deep (or big) data is fully on your radar. You know it has value for your business. You know it requires your attention (or that of someone on your team). You know it’s not about betting on the fastest pig. And, you know that publishers experiment with it daily—you may be one of those publishers. But, what’s working? 

First, publishers who don’t let the hype around data overwhelm their strategy are the publishers who are seeing results. Deep data tells you what is working in your business and helps inform the direction of your content. It can serve as a catalyst for changes to your strategy, but it isn’t your strategy.

Secondly, publishers who remove data silos and combine advertising and audience data with content creation and editorial are gleaning the most meaningful data and actionable insights.

Now that we’ve addressed those two foundational items,

How are publishers using proprietary and 3rd party data to build engagement and revenue?

  1. Evaluating Engagement. We’ve talked about the potential for this with deep data, but with better metrics—like attention minutes, time on page, user satisfaction—publishers are actually doing it. They are better able to determine audience engagement and interest in content and advertising. This leads to an ability to know what is meeting the interests of your readers and what isn’t.
  2. Increasing Contextual Delivery. By tracking data specific to a reader, publishers can better gauge their interests and are now effectively sorting readers by interests or intent, so that they can present them with highly contextual content recommendations. Publishers are also using location awareness to hone in on greater context for readers.
  3. Leveraging Customer Reviews for Better E-CommerceWith customer reviews, product comparisons and onsite storefronts, purchase decisions are made easier and related products are becoming the next purchase, and the next . . .
  4. Transforming “Browsers” to Paid Subscribers. Audience behavior data and content engagement data can help publishers to develop offers that readers are more likely to bite on. It’s easier for them to subscribe when they know they will get more of what they like in the way they like it.
  5. Using Cohesive Revenue Data to Make Strategic Decisions. Without those silos we talked about earlier, publishers are capturing more accurate revenue data in one location—combining advertising and content data into a bigger picture that results in a better-informed strategy to shape revenue streams.

There are ample ways to use data in your content strategy. If you incorporate these five, you’ll start seeing changes in engagement and revenue. Just watch—and adjust accordingly.

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