Content Curation and the Interest Graph: Delivering Context to the Consumer

advantages to reading marketing content

In December, an article I wrote “Content Is King, But Distribution Is Queen and She Wears the Pants” was nominated and won an end-of-the-year contest for the best content marketing post of 2013. The contest was run by a new startup called ShareBloc, a new content distribution platform for professionals to share help with content curation.

The original post identified the growing problem of content saturation on the Internet. Good distribution — whether paid or earned — can help content marketers cut through that noise.

Looking back on the merits of ShareBloc’s contest, I’d add an addendum to that winning post: Consumers who are good at content curation will benefit the most from marketers deploying distribution strategies. Today’s social media and content distribution platforms are content curation engines at their core. It’s the curation of content on these platforms by consumers that empowers marketers with the ability to only deliver proper, prudent content with context.

The Interest Graph

When Twitter first became popularized in 2006 no one knew what an interest graph was. Unlike the social graph, which is a consumer’s network of friends and family as popularized by Facebook, the interest graph contains people and topics of interest. If a person follows Justin Bieber and HubSpot on Twitter they’ll be suspected of being a bielieber and a marketer.

One compelling force driving consumers to social media platforms — whether they know it or not — is that there’s too much content on the Internet. This is why interest graph platforms like Twitter have become more relied upon for feeding content with context to consumers. There are many other social networks and distribution platforms for consumers like this including Pinterest, Reddit, and Tumblr. Even niche media sites like GoodReads and Spotify can be considered interest graph platforms.

As the volume of web content continues to increase, so will the noise in consumers’ inboxes, Google searches and Facebook feeds. People will likely turn to even more niche interest graph platforms to find the content they want. From designer shoes on Pinterest to an artist’s portfolio on Behance, consumers are discovering and increasing their reliance on niche interest graph platforms.

As consumers become more sophisticated in curating their own interest graphs marketers will get even better at delivering the best content that matters to individual consumers

Machine Learning

Many celebrities are highly influential to the consumers who follow them. Think about the impact Oprah’s favorite things has on consumers’ purchasing habits. Can machines do a better job than Oprah? A recent article in The Atlantic explored how Netflix has complicated algorithms to suggest movies and shows based on consumers’ viewing habits.

Netflix accomplishes this through machine learning — which is a type of artificial intelligence that continually gets smarter when consumers engage. Netflix analyzes everything a consumer watches and combs through its expansive library to suggest something the next time they visit.

They’re not the only company using machine learning to create a customized experience. Amazon shares what a consumer may want based on purchasing behaviors and Pandora algorithmically suggests music based on listening habits.

Marketers Adapt

Whether or not a consumer gets their content through people, interest graph platforms, or a combination of both, this is a win for them and marketers alike. With more content being curated by individual consumers and the development and growth of their own interest graphs, marketers can get even closer to one-to-one marketing.

Marketing software tools and machine learning is empowering marketers to learn from the interest graph and deliver only prudent content with context to the individual consumer. It’s this content that consumers actually want to receive.

Today’s online marketers can parse large demographics based on age, sex, geography, interests, behaviors, and others to deliver content that is specific and prudent to the individual. Technology improvements will make this type of targeting even more granular in the future. As the volume of content published on the Internet continues to grow, consumers can help shield themselves from the noise that doesn’t matter to them by curating only the content that matters on interest graph platforms like Twitter and ShareBloc.