If Publishers Are Going to Harness Data, We Need One Language

    by Sachin Kamdar
    November 18, 2014
    Public domain image from DARPA

    The following is a guest post. Read more about MediaShift guest posts here.

    Almost three years ago I wrote an article about “Why Publishers Are About to Go Data Crazy.” This prediction came true, but the degree that publishers have gone “data crazy” wildly beat my expectations. Publishers now have the ability to capitalize on audience interests and behaviors (i.e., types of content preferred, which links are clicked or shared, etc.) with various types of analytic tools. Success now depends not just on having data, but on obtaining straight-forward data rather than complex metrics and false dichotomies — data that keeps various stakeholders at publications sane and honest in a market that increasingly demands transparency.

    "If departments can't speak the same language, your largest problem will quickly be everyone wasting time and money."

    As they say, “knowledge is power,” however, each of these stakeholders using a different data set about their audience actually leads to operational weakness. With a pervasive lack of industry control over site traffic data and all sorts of definitions around what counts as engagement and attention, it’s understandably confusing to decide what data to trust when considering editorial direction and what data to present to brand advertisers. There will always be niche information required for smaller, more urgent, tactical decisions, but enacting data cohesion across an entire publishing organization brings real operational advantages and confidence.


    Unlocking revenue for publishers relies on their ability to create data cohesion — to make sense of the data that they’ve spent so much time, effort and money to collect. From editorial to sales to product teams, every stakeholder banks their decisions and livelihood on an engaged and inspired audience to continually visit the publisher’s content time and again. It’s why you’re seeing the New York Times focused on hiring for audience engagement and BuzzFeed promoted a growth and data scientist to a publisher.

    Data Silos at Traditional Media Publishers

    Speak with any publisher today about their analytics stack and it will more than likely result in a discussion centered around “tool overload.” Each group (social, editorial, business, management, etc.) within a publisher purports their own unique problems when it comes to data, and they often use multiple vendors to tackle them. This, unfortunately, creates a subtly sinister problem around what the data is truly saying about an audience, and how to effectively align strategies across an organization. It’s common for something to get “lost in translation” when it comes to data. Rather than speaking five or six languages across an organization, publishers need to avoid accelerating confusion by focusing on speaking a single language throughout all internal departments.

    If you work at one of these companies, is your organization guilty of this? How many metrics get presented when seeking an answer on a single question? Many stakeholders have different ways of counting, analyzing and delivering that information. How do you decide which is the authority? Is there an authority?


    Welcome to the multiple data points domino effect. If departments can’t speak the same language, your largest problem will quickly be everyone wasting time and money chasing inconsistent or inaccurate performance data.


    This situation may have been acceptable — even defended — when editorial and business teams strictly followed the traditional “church and state” divide, but that’s no longer the case.

    Today, siloed business insights based only on digital subscriptions numbers, for example, could leave you treating readers via clunky, old-school segmentation rather than with the personalization that readers desire. Analysts and product teams only looking at page-load times or click-maps miss out on context provided by semantic or topical analysis. Additionally, the time has come to stop patronizing writers by not granting them the same access to audience data as other business units. This is their world too.

    Using a Single Language of Data to Become Data Driven

    In the fast-changing world of digital technology, being data-driven at the core (meaning everyone’s bought into the value of it) represents publishers’ competitive edge and enables them to provide a great experience to readers. Addressing business goals in parallel can only be effectively done with a single view into an audience’s behaviors and interests as well as the performance of content. For some, this may feel like an unnatural transition at first, but data cohesion ensures that all decisions — from product to sales to editorial and beyond — are made confidently against a single point of truth.

    Going data crazy won’t move the needle forward unless that data can be used to power decisions throughout the company. Let’s get data-driven crazy.


    Sachin Kamdar is an NYC entrepreneur and the CEO and co-founder of Parse.ly, an audience insights platform for digital media publishers.


    Tagged: analytics buzzfeed data digital business model new york times

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