They say that content is king, and it’s certainly changing the face of marketing. Content marketing has become a big initiative for publishers and brands. And as the organic distribution of content on social media becomes more difficult — a result of constant algorithm changes made by Facebook, Twitter, and other social media platforms — larger portions of a campaign’s budget are now directed towards paid content distribution. That’s not entirely a bad thing, because, despite an increased cost, a lot of marketers are able to maintain ROI while increasing the value they provide to the reader while at the same time collecting actionable data. 

That data could not have been gathered in the age of viral organic reach. Consider a publisher like Little Things who filed for bankruptcy back in 2018. Back in the day, it was one of the largest online publishers for lifestyle content. It certainly was a big fish in Facebook’s sea. But when Facebook changed the algorithm and prioritized content from friends and family over publishers, this whale was left beached on the shore as organic traffic receded. The publisher couldn’t, during its peak profitability, know a lot about who was coming to the site, what they found interesting, and a host of other data points that can only be known through deliberate targeting. When you A/B test your audience targeting, you can get granular data that can be acted on.

Since a growing percentage of marketing spend is being allocated to the distribution of content, how are marketers assuring their content marketing efforts are efficient? That content is being delivered to the target audience? Or in other words, what are content marketers doing to make sure their content performs effectively and their dollars are well spent? The answer, unfortunately, is not enough. 

Marketing Audiences: Then and Now

The process used to shape most content still uses the same notion of “audiences” that marketers used to develop TV commercials and print advertising in the days before digital. Audiences, historically, were defined at a pretty high level of granularity — for example, moms with children under the age of 5. This used to make sense because:

  • That’s how audiences were defined by the media companies that sold TV commercial time and print advertising space.
  • Brands used to have the mindset that they wanted to get one or two messages to as many people (impressions) as possible.

Most content marketers still think about audiences the same way today. But they shouldn’t be. With digital marketing and social media platforms, it no longer makes sense to push out mass content to a broadly defined audience. Marketing platforms like Facebook and Twitter collect rich sets of data about their users and share that information with marketers to help them target specific audiences. Here are some of the data points these marketing platforms are capturing about their users:

  • Age
  • Gender
  • Location
  • Interests
  • What they read online
  • Past interactions with content

Thanks to all of this available data, content marketers should define their audiences differently and design a customer experience, or a content funnel, that caters to their newly defined audience. This data also affects the content the marketers use in their digital marketing. In a positive-feedback loop, the new segmentation would allow marketers to see which content brought in the users with the highest value and create more content to cater to that target audience. 

Marketers should develop content for sub-segments of their broader audience. For example, if your target audience is moms with children under 5, rather than constraining your content to topics that will appeal to all moms in the target audience, it’s more effective to develop content that speaks to a specific sub-segment — say, moms with children under 5 and who like Kate Middleton — and then distribute the content to just that population. The cost to reach that segmented audience will probably be cheaper than paying for the broader audience, and the user engagement will probably be higher.

Content Creation in Action: Coca-Cola

Some brands are early adopters of the data-driven approach to audience targeting. For example, in late 2012, Coca-Cola unveiled a new version of its corporate website that features content more similar to a consumer magazine than a business website. The site, Coca-Cola Journey, features articles on a variety of subjects, like food, culture, business, and sports. Coca-Cola can distribute each piece of content to specific audiences by targeting people who are interested in each of those topics on various marketing platforms.

Another example, of a company with a completely different target audience, is Net-A-Porter. The online luxury retailer employs content marketing with Porter magazine to reach its target audience. No doubt that this sophisticated marketing strategy also generates a lot of information on which articles drive the highest ROI, and from which audiences. In turn, this data could inform the editorial team to write more articles that resonate with their existing or newly found target audience. 

Content Targeting With Data-Driven Audience Insights

There is another way to approach the subject. So far, we’ve discussed creating content with data about your target audience. But this neglects the power of paid distribution and audience targeting we mentioned at the beginning. Smart data-based audience targeting is a tool to add to your marketing strategy now, not after you create content to fit new sub-segments of your audience. 

Treating organic traffic’s decline as a fact, publishers have little choice but to turn to paid efforts. This could prove as a blessing in disguise. Adding paid distribution to your marketing strategy means you can use social media’s audience segmentation, and Facebook has hundreds of millions of possible audiences, to find the right Facebook audience for each piece of content.

For example, Anyword analyzed the content of one of our partners who drives revenue with affiliate links. We found that while they wrote their content with a young user in mind, the best responses and ROI came from women at the age of 45+. Only after a paid campaign has proven that the data was correct and the ROI could be better by catering to that market, did the publisher started creating content pieces to cater to it. 

So, how can content marketers use data to create targeted content and get it in front of the right audiences? There are a couple of options:

  • Work directly with the audience targeting capabilities of marketing platforms. Working directly with the various marketing and social media platforms gives you full access to the raw data generated, but requires a large team to manage at scale and to stay updated with policy changes. 
  • Use a cross-platform content marketing solution to define your audience. Working with a content marketing solution lets you leave the targeting specifics on each platform to the pros.

Are you spending your content marketing dollars effectively? Is your content getting in front of the right readers? Take advantage of the rich data about your audience to create a more relevant user experience and get the most out of every content dollar.
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