Essays

The medium data world of media audience measurement

Welcome to the medium data world of audience research, says MEC’s Bhaskar Khaund

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In their Big Data: A Revolution That Will Transform How We Live, Work and Think Viktor Mayer-Schonberger and Kenneth Cukier identify the availability of all of the data points as the defining characteristic of big data. In other words, big data is to be understood in contrast to sample-based data. They then go on to argue that in a big data world, since all of the datapoints are available, sample-based extrapolation becomes redundant.

How does this construct – big data as N=All and the redundancy of sampling – apply to media audience measurement?

Audience measurement today comprises two parts: the big data world of digital media where the entire audience is captured in real time (N=All) and the ‘small data’ world of offline media where it is extrapolated from samples (N= sample size).

Audience measurement uniquely straddles both worlds. ‘Uniquely’ not because other domains are exclusively one or the other but because of two unique characteristics.

First is the asymmetry between data availability and the share of pie of each part. The big data digital component accounts for less than a third of total ad spend worldwide Put differently, around half or more of the spend is based on ‘small data’ measurements. Too much is riding on sample extrapolation for it to go away anytime soon.

The less obvious reason is the second unique characteristic: the interdependency between the two data types. Sample-based small data is a critical requirement for unlocking the full value of the available big data and big data is increasingly being used to improve sample-based systems.

These dynamics, together with concerns about whether current measurement adequately covers the complex media consumption of today, are driving hybrid research in several markets worldwide.

Hybrid refers to the fusion of ‘census’ (N=All) big data and ‘panel’ small data to estimate audiences better than what each could do alone. Three key areas this encompasses include: (a) Target audience-based reach/ frequency metrics for online campaigns (b) Panel television viewership augmented with return path data from set top boxes (c) ‘Total video’ audience measurement covering TV and online video.

Given the size of TV and the growth of multiscreen online video, ‘Total Video’ as a combination of both is arguably the Holy Grail of audience measurement today. There are several projects across leading global markets being directed by joint industry committees. Many are conducted by the TV measurement agencies such as Nielsen and Rentrak in the United States, BARB in the United Kingdom, Mediametrie in France and AGF/AGOF in Germany. Other key players include comScore and Google. In the MENA region, Ipsos Connect have a Fusion project in its initial stages.

These projects are work in progress and there’s no magic button around the corner. Adding to the methodological complexities and logistical difficulties are the operational challenges of working with multiple bodies, stakeholders and partners. Costs are a major challenge especially in the absence of clear demand for the final product.

Turnaround into usable planning software is, therefore, bound to lag the rapid evolution of media consumption. That should not, however, prevent planners from applying the understanding of these measurement issues to creatively think out of the box vis-à-vis the available data, and develop their own back-of-the-envelope planning guidelines.

For example, a region-specific methodology for TV and online video integration needs to   go beyond E-GRPs, which is relatively simple, and into calibration against TV GRPs, wherein measurement differences add significant complexity. The comparison involves ‘actual’ online video ad views in real time versus sample-extrapolated, next-day telephone interview-based views on TV. A like calibration could work via estimating the ‘accuracy losses’ involved between the two systems via comparable differences versus electronically measured TV systems such as peoplemeters which capture ad viewership. While such a system is only indicative at best, it can nonetheless provide useful guidelines for video budget allocation.

Returning to the starting point of this piece in conclusion, big data in media audience research in the strictest N=All sense is limited mainly to online campaign analytics data wherein all of the exposures are captured. For the rest at a general level, it needs to be qualified to N=Nearly All. For a variety of reasons, all of the data points are simply not available. What census big data does is to add on to panel sample data.

Sampling affects not only the offline media it measures but also the comparative value – and therefore share- of the online media it shares the budget with. Therefore, there is a need to ensure that the old fashioned checks are in place: that samples are robust, random and representative and the analyses rigorous. This is particularly true for markets where those checks were much less in focus to begin with. The big data era, far from making it redundant, accords an arguably greater importance than ever before to small data.

Welcome to the medium data world of audience research.

(Bhaskar Khaund is regional head of TV & Multiscreen, MEC MENA )

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