How Newspapers Can Monetize Data
Identifying content preferences of focus groups and providing custom products:
By identifying the sections frequented by specific groups of readers, newspapers can produce magazines and editorials customized to their needs. Pew Research Center shared an example of one such initiative by the Daily Herald, which has rolled out a successful monthly health magazine and a new men's lifestyle magazine. They plan to introduce a real estate product early in 2013. It seems like an ambitious enterprise for a small operation with modest resources, but Publisher Mark Palmer says the health magazine has been "very profitable" and initial results from the new publications are quite positive. Affinity Express partners with many newspaper clients by taking over the production of special sections, helping them to draw new advertisers and reach target audiences at dramatically lower costs.
Finding new pockets of growth in micromarkets:
Data offers a new ability to combine, sift and sort vast troves of data to develop highly efficient sales strategies. While micromarkets are most often understood as physical regions, they don't have to be. For example, business executives returning from work by train are a lucrative micromarket for newspapers, as they are captive audience who would willingly buy magazines to read during their commutes. Exploring and exploiting new-growth hot spots involves three steps: 1) defining your micromarkets and determining their growth potential; 2) using these findings to distribute resources and plan your sales sales strategies; and 3) evolving operations and organizational cultures to support decisions backed by data. An interesting example of micromarketing is a special edition to be distributed in schools which will have double impact. One, focused exposure to school audience will draw advertisers targeting youth and, two, the newspaper will build a bond with readers from an early age.
Serving news on demand:
As online ads are displayed in context with the content being viewed, newspaper websites could also store and use data about their readers’ preferred content pages, history of articles read and liked and comments shared in the past to show content that they might prefer. This works similar to the way Amazon recommends products in real time based on visitors’ previous searches and profile history, as well as the latest contextual information gathered from the website (e.g., roll overs, page visits, carts, etc.). Real time decision engines will certainly add tremendous value and play a pivotal role while displaying news users want and expect. Starting with the basics in this way can be a radical change for some organizations but it becomes essential if the ambition is to become the preferred news brand on smaller screen devices.
