September 23, 2006: Understanding Value in Online Media

Audience behavior is much more transparent online than in any previous medium. The implications are still being worked out from the business perspective, as we reconfigure our understanding of core metrics, circulation, ad performance, content performance, pricing, and other parameters to incorporate all the data that are now available.

Here we're actively aiming to evolve our online media business into an "ROI engine" where we fully understand the cost of every type of content and the value of every type of advertiser exposure and can therefore program the site to optimize ROI. I believe the entire media industry will operate in this fashion in just a few years, but there are some steps required to get there from where we are today. For one, the content management, web analytics, content selection, and ad serving systems need to operate from a common taxonomy and all talk to one another.

An ROI focus suggests many other interesting possibilities, such as compensating content creators based on the value they deliver to the business, potentially including pageviews, core readership demographics, or contributions to other business areas, such as events and lead gen. If we mine the data sufficiently we could calculate an ROI on every piece of content on the site.

In order to structure the business as a value equation two disciplines are key: economics, which uncovers the supply and demand dynamics driving our ability to match advertisers with audience, and finance, which explores the interaction between risk and value. Here are a couple of examples of how economics and finance provide insights into day-to-day operating challenges. As any media business is all about audience, so online media is built around pageviews. Ad impressions sold represent demand for pageviews, while audience browsing provides supply. But site managers quickly learn that providing raw pageviews isn't enough. To truly deliver value the views must come at the right time on the right pages. Breaking traffic records in a month with low ad demand doesn't deliver more value. Optimizing traffic means building many demand curves, not just one.

At the same time, finance teaches us that predictable traffic is more valuable than unpredictable, because of the discount that must be applied in uncertain (risky) situations. Take an example of two editors whose articles each deliver a million pageviews over the course of year. Editor A consistently draws about 80,000 views a month while Editor B typically produces just 50,000 pageviews a month, but sporadically writes "blockbusters" that can bring in 200,000 views in a month. Clearly Editor A is more valuable to the business. The same reasoning explains why the so-called "content annuity" of archived material actually has little value. It's possible old content will find a new audience but the uncertainty around timing and traffic volume requires a high discount factor to be applied to the value of those pageviews.

Succeeding in a new media business requires additional skills beyond what sufficed in traditional media, particularly on the analytical side. An industry where intuition and persuasion were powerful is evolving toward a more transparent, numbers-driven basis. To be a leader rather than a follower in the transition, brush up on economics and finance and make sure your Excel skills are top-notch.