The next media disruption: Predictive Analytics

Inspired by Steve Gray's article published on INMA website: "Predictive analytics: the next media disruption tool" I want to share my thoughts on this.

I believe that many media companies struggle in their digital business because they give out their most valuable asset - their audience data - to third parties. Tens (or sometimes up to a hundred!) advertising scripts publishers use to monetize their content pull out this data and ship it off. Additionally, publishers tend to use many analytic tools, but they don't allow collection and use first party data to build new business models, often based on those predictive analytics.

All this is wrong.

Reversing this situation by implementing the right data platforms as the biggest players like the FT, Guardian, NYT, and Washington Post did is the first step. Afterwards, publishers are able to leverage the assets they have and build value around them. The automotive and real-estate ideas mentioned in the article look very promising.

I would add more to the article:

  • use raw data to build custom metrics and performance indicators for your teams (content, product, sales, etc.) and use predictive analytics models to predict if these goals will be accomplished
  • predict how content will perform based on early signals, especially what content might go viral
  • build scoring models for subscribers to predict churn
  • score leads in selling subscriptions
  • build precisely crafted segments for advertisers and use lookalike predictions in performance-based campaigns (e.g. cost per lead or cost per sale models)
  • and the really important thing: content recommendation systems that predict what's interesting for users and are able to deliver this on main pages, newsletters or chatbots.

All of this brings me to the conclusion, that there’s a huge potential to re-innovate the business model for publishers based on technology and data.

Maybe we should be inspired by other industries, like telecommunications, where fixed-line players leveraged their user bases to become 3P then 4P and now continue to innovate by building their financial or energy offerings.