What's the key to boosting newspaper profitability?

Unlocking the meaning behind the data


The Digital Data Challenge

The business of digital news publishing is data intensive. Publishers have realized the need for data, and in many cases are spending vast sums to capture data without a clear return on the investments they are making. To generate revenue, lower costs, improve customer retention or enhance operational performance, data must add insight within the decision-making process. Without clear utility to the organization, data has no value by itself.

Disparate Data Sources

As digital revenue streams have emerged, analyzing data on those operations has become necessary for determining business strategies. Taking a holistic view of a publisher's digital revenue is essential because limiting access to online content, in order to sell it to customers, had immediate effects on advertising inventory and the associated revenue.  Managing these two revenue streams independently will inevitably lead to less than optimal results.

The digital data challenge is a symptom of the silos that exist within publishers:  the advertising function is separate from the audience group and neither work closely with editorial. Each of these groups have tools they use to manage their digital business operations and they deploy and operate these tools independently of each other.

For example, advertising departments often use Google's DoubleClick for Publishers to deliver digital advertising impressions to web pages. The data forthcoming from DFP reflects the schema developed at that publisher for impression delivery on its web properties, which is optimized for ad sales and operations. Audience and editorial departments often use Google Analytics to measure page views, unique visitors and other online activity. Data from GA will reflect the organization of the site that editorial uses for content categorization and delivery. Combining these data at a level of detail necessary for meaningful analytics is often impossible due to inconsistent page addresses or a lack of common fields for merging data files. Furthermore, these tools often have free and premium versions with varying levels of data access. 

Common data capture tools, such as Omniture, are often very expensive and require extensive knowledge to utilize all ­of their capabilities. As news media organizations have transformed their businesses, they often lost the staff with knowledge of how those tools were implemented and how to use them. The raw data these tools capture can be vast, requiring special hardware, software and expertise to yield meaningful insights.  In many instances, a publisher may have bought a "data-Ferrari" when he could be driving a Lexus (or even a Toyota). Interestingly, as the costs of data capture and storage fall, particularly with cloud-based tools, the costs of these legacy data capture products does not fall with them.

Many other applications such as dashboards or meters capture data for their own purposes, which are not always shared with the publisher. These applications are frequently developed to pursue a single objective, which limits the available data to that one activity. When these tools are no longer needed, the data they have captured often goes with them. If publishers have several of these products running simultaneously, they are likely paying multiple times for silos of data capture and storage.

An Answer to the Challenge

Publishers need to capture the right data, at the right time, and at the right price, to support analytics that generate real, actionable insights. To meet this need, we developed ListenerTM, a new tool designed to meet the digital data challenge inexpensively and efficiently.

ListenerTM is a web-based tool that gives publishers that holistic view of customers that they need – all in one place. First, Listener combines data from several sources into one data file when a page is loaded into the browser, eliminating the need to later combine these data with limited accuracy. This enables publishers to capture data on the activity of individual customers, even if they are anonymous, while simultaneously capturing data on the advertising impressions delivered to them.  Second, revenue for delivered impressions can be added to this data file, so publishers can determine what actions will maximize digital revenue from both advertising and audience streams. Data from other sources can also be added to the Listener file as well, such as demographics, account history and product bundles.

Finally, Listener can capture data on other events taking place on a page, such as a meter count or a payment module, supporting other analytics. All of this happens behind the scenes without impacting the user's online experience, allowing a publisher to, for example, model the behavior of customers and to use those insights to reduce churn, drive advertising revenue and strategically price and bundle subscriptions.

Whether publishers find Listener or other data collection tools to be right for them, the key is to unlock the meaning behind the data so that strategies that generate revenue, lower costs, improve customer retention and enhance operational performance can be developed and implemented.

Matt Lindsay has more than 20 years of experience in helping businesses improve performance and grow revenue through economic modeling. In consulting roles over the past 15 years, he has shared this expertise and developed pricing strategies and predictive models for clients, including the Intercontinental Exchange, Gannett, The Home Depot, NRG Energy, Tribune, IHG, McClatchy, the Everglades Foundation, Walton Foundation, Dow Jones and The New York Times.


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