Growing Your Margins: Content’s Role In Audience Identification

29 Nov 2017 | By Tobias Arns

In my last blog post entitled "Responsive Metering: The Monetization Elephant In The Room", I commented on the changing nature of conversions and the premium this puts on data quality and fidelity.

Here, I want to open with a crazy sounding idea: in the push toward an ad-less media experience, treat a piece of content like an ad for itself.  

Say what?

Look at it this way:  the three fundamental forces driving conversion are inventory quality (here, articles/ media),  targeting optimization (segmentation, audience), and delivery (placement, time, UX). Sounds like ads, right? A context-sensitive call to action is fundamental to drive monetization by promoting more of what a reader has already found to be consistently useful and enjoyable.

If the mission is to monetize content using finely-tuned targeting and conversion tactics, it begs the observation: why don’t we already deploy content offers as well as or better than targeted as ads are served now?

Well, it's a lot harder.

All publishers have audiences and content collections of varying but finite size, prompting the common concern: how can publishers boost existing revenue or discover pockets of new revenue by introducing smarter and more numerous conversion points against a finite group? The answer lies in letting the content do the heavy lifting for you.

Matthew Capala, writing for TheNextWeb, explains that content monetization is moving towards optimizing “a reach [in] incremental buyers and leads on platforms that offer a large number of engaged users who are there for one reason: to buy premium digital content.” The two key words here are “reach” and “incremental.” Both of these have a lot of math underneath them, but the heart of defining monetizable ‘reach’ and ‘increments’ rely on a publisher's ability to permute content and readers based on critical content consumption questions:

How well do you know what your readers are reading?

  • Why are they reading it?

  • When do they need content the most?

  • When do readers need open access?

  • How can you price these readers?

  • When is the best time in the journey to deliver an offer?

  • What are their UX preferences?

Putting this in perspective with an example, how can you sift a group of market news readers into investors and regulators merely by their reading habits? How do you target a call to action? A miscalculation here can increment you in the wrong direction.  

Another example of misguided targeting:  I might get a robo-investor ad if I read a lot of regulatory news. Conceptually close, but the audience fit is way off because of a lack of  high-fidelity semantic, preference, and interest data on the users at the topic and entity level.

In both cases, meta-tags are not enough; tracking and applying event-, behavioral-, and semantic-analytics is what surfaces new audiences.

The last missing piece: behavioral walls, a more clever version of the paywalls to which we’ve largely become accustomed.  A behavioral wall decouples the offer (e.g. “ 1 dollar per month”) from a contextual delivery strategy ("deploy after reading the 5th article where X and Y are mentioned") to ensure happy readers and maximize conversion. Again, the semantic value of the content facilitates putting the right CTA in the right place at the right time to the best-fit audience.

So to come back to the question: why don’t we already deploy content offers as well as or better than targeted as ads are served now?  We can, but it relies on having the right core technology to allow content do the heavy lifting —  surfacing those incremental audiences and identifying the best places to convert the reader journey.

Feel free to connect with Cxense if you'd like to discuss how to use your audience data to drive monetization.