Transparency is the only way to overcome the challenges of media measurement

Because of the monopolistic actions of giants like Google, Facebook and Apple that have pushed control of measurement into their own hands under the guise of simplification, it has become increasingly difficult for marketers to accurately measure the success of their multi-channel campaigns.

Marketers are currently given the choice between trusting self-attributing networks that maintain a heavy fog over their processes, enlisting pricey in-house data science teams, or signing up with independent third parties to aid in measurement.

The limitations of various approaches

For some time, there’s been a growing belief among marketers that many ad platforms, including those for TV, have inherent biases. They supposedly have a vested interest in showing positive results for their advertisers, which can ostensibly lead to skewed metrics. For example, last-click channels are often given too much credit for conversions, while the channels that drive interest and create intent are left out. After all, not every platform can be the best solution and prove it with data.

Marketing mix models have been touted as a more accurate way to measure the success of campaigns, as they attempt to take in the effect of higher-funnel channels like radio, television and print. However, the thinking goes, they too have their own biases and drawbacks.

Once a marketer has a preference for a certain method of measurement – like last-click attribution – they are unlikely to undermine their own credibility in order to do something new and innovative. This can lead to results that are not necessarily reflective of the true success of a campaign.

The question of bias

Whether it's an ad platform, a third-party measurement partner or an multi-touch attribution model, there will always be some subjectivity involved in modern campaign management. Every platform has biases and vested interests. It's currently up to marketers themselves to recognize these biases and take them into account when analyzing their results.

However, this doesn't mean that marketers should simply accept biased measurement techniques. If being unbiased and transparent is a priority, then it's time for the right platform to step up and support measurement and media in a new and innovative way. The industry has grown accustomed to perceived biases in models and measurement providers, but bias can hardly be claimed if the data is sound.

Elements of a trustworthy measurement platform

So, what should marketers look for in a measurement platform or self-attributing ad platform? Firstly, it should be transparent about its methodology and the metrics it uses. TV, for example, can never look as good as last-click attribution, because there’s no last-click functionality for TV. Transparency, coupled with sound data science, however, can allow marketers to better understand how their campaigns are being measured and make any necessary adjustments in the service of bottom-line business outcomes.

Secondly, a reliable platform should be able to measure multiple outcomes, not just one. This will provide a more holistic view of campaign success and allow marketers to make more informed decisions about their ad spend.

It's currently up to marketers to recognize existing biases and take them into account when analyzing their results. However, there is a growing and essential role for platforms that value transparency and accuracy. A platform that is transparent about its methodology, can measure multiple outcomes and is independent will help marketers make data-driven decisions and measure the true success of their campaigns.

David Koye is cofounder and chief product officer at tvScientific.