How Can Publishers Tell a Better Audience Story?

Publishers have access to potentially lots of first-party data. There are user’s web and mobile browsing behaviors, site and app registration, location data from in-app, email signup and behavior, and even survey data.

The value of that data by itself is somewhat limited. Unfortunately, a lot of publishers haven’t connected all of the dots on all of that data to really get to know their audiences as intimately as they could and should. To dig deeper and gain a better understanding of their interests and motivations, and more important—their intent to buy.

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For years publishers have sold advertising targeted around specific content, using available first-party data as the basis for establishing value around the opportunity. More recently though, publishers started offering branded content sponsorships that highlight reaching specific audiences with articles created in cooperation with an advertising partner. In both cases a publisher’s value proposition is around the scale of the audience that engages with this content; ultimately that value proposition boils down to selling pageviews, impressions and clicks.


That someone is interested in a piece of content doesn’t really communicate the entire story. First-party data is only the start of being able to tell advertisers a meaningful story about your audience’s consumer journey. Often it’s necessary to beef up consumer engagement across more channels and devices with third-party data that has the ability to uncover the why behind consumer actions.


Your audience is a lot more than just pageviews and demographics. The better you know your audience, the more engaged they will be with your content, and then the more valuable that audience will be to your advertisers.

Consider cleaning up and better structuring your data and then create custom dimensions to provide you with deeper insights into your audience—and a stronger monetization opportunity. The following three steps will start you on your way to shaping a better story about your audience for advertisers.

1. Start with Pre-Sales Insights

Research and sales planning begins with audience insights. This is where you collect and analyze all of the user data you have from all of the sources available to you, including web, mobile, email, surveys and also CRM and/or connected TV.

Once you’ve collected all of the inputs, become data informed by looking at your audience based on a set of characteristics. It’s not enough to know who they are, you’re going to want to look more closely at where they’re going (both online and offline) and what they’re doing. Can you answer why they’re doing what they’re doing?

Are you looking at cross-channel data in social and mobile and digging deep into their programming and content preferences to help you better stitch together a story about why they’re engaging with a certain type of content or advertising? Can you answer exactly what it is that they want?

2. Build High-value Audiences for Advertisers

Once you better understand the desired target audience, how do you package those audiences up for advertisers? You’ll have to take your first-party data beyond demographics and geography to include psychographics and gain real insights into their behaviors and intent.

Knowing how many women aged 25-34 visit your site is one thing, but knowing how many of them prefer reading about health and beauty content instead of parenting content is a powerful story. Would that story become even more compelling if you knew how many of those readers had an affinity for a specific beauty brand or subscribed to a certain streaming service? That’s strong potential to help drive sales opportunities.


Custom audience segmentation is the process of building out audiences based on attributes. What are their affinities? Once you gain a deeper understanding of your audience, you can start to see trends emerging that will enable you to deliver highly targeted engaged audiences. Say for instance dads 25-34 who like to drink wine, specifically boxed wine.


But you might find that your custom target audience is too small and you’ll need to create audience extensions by finding the right partner who can help you to model richer and deeper target segments beyond your own data. You might want to find a partner who can answer the why that leads to stronger customer engagement and a better outcome for advertisers.

3. Analyze and Readjust

Developing insights into your audience data and creating custom segmentations is only part of the journey. Being able to validate the opportunity is a critical differentiator. As a publisher, it’s table stakes to demonstrate that you have the right target audiences and that they’re performing well for your advertisers. Validating audiences and branded content campaigns requires publishers to incorporate modern advertising agency disciplines into their workflow and offerings.

You’ll want to constantly track and analyze your results so that you can provide actionable insight reporting. The audience you thought was highly engaged in a particular category might not perform as well as you predicted. That requires time, systems or tools, assuming you have the people to help do that consistently.

The pre-sales audience strategy that made the sale possible is only part of the equation; a publisher’s best practice is to incorporate A/B testing by tracking the creative and content efficacy across multiple campaigns and audience targets. This step provides a greater opportunity to learn even more about your audiences and adjust targets if necessary.

Successful publishers understand that an audience strategy is bilateral; having the tools to help define, shape and validate that the publisher’s audience is right for an advertising partner also involves delivering value back to that advertiser from the very beginning and throughout the partnership.

This article is the second in a three-part article series:

  1. Part I: How Do I Know Data Is Quality?
  2. Part II: How Can Publishers Tell a Better Audience Story?
  3. Part III: Be Your Advertisers’ Chief Data Consultant