For those of us navigating the brave new world of media, the data rushing into the market has been met with both exhilaration and, let’s face it, a bit of dread. What datasets are most predictive and valuable? How can a company best manage all of its data and connect it seamlessly across platforms? What metrics are most useful and capable?
The recent Cynopsis Data and Measurement Conference offered some insights into these questions, showcasing trends in media data from its impact, its measurement, its use by advertisers and its targeting applications. Here are some takeaways:
Lazy Data Confounds the Path to Purchase
Lazy data is misleading data, according to Mike Rosen, Executive Vice President Portfolio Sales and Strategy, NBCU. Lazy data is essentially those datasets that are not efficiently and accurately attributed back to the sale or are not adequately counting the value of certain consumer groups. “Data in the service of marketing and media is a very human endeavor,” he explained, “We can use data to understand human behaviors.”
But as a Baby Boomer, Rosen believes that his spending patterns are not given the credit they deserve. He does not have a social footprint but he spends on a variety of goods and services from shopping at a range of online and offline stores, using credit cards, “I own two cars, I have insurance policies, I travel, own loyalty cards and spend on entertainment. I throw off lots of data but because of lazy data, they can't find me.” Advertisers are “targeting demos like Millennials and Gen X. I am a Boomer. I am out.” Advertisers consider older consumers acceptable waste, reached anyway. “If you market to me do I not shop?” he intoned, “I am a human consumer with a high credit rating. You can't seem to find me.”
The root causes of lazy data, according to Rosen, are:
1. Sticking with age and gender categorizations which don’t count valuable consumers.
2. Buying by network and not by program, diluting the ability to efficiently reach target viewers.
3. Equivalizing platforms. Platforms have different viewing experiences and different levels of engagement.
4. Correlation Causation. “We so badly want to relate things to each other but it could just be coincidence. I live in Westport. I love Greek yoghurt … but not because I live in Westport,” he stated.
Without an attribution model, the problem of lazy data will not go away, “It is never quite that simple to determine the path of purchase,” Rosen concluded, “The messaging route by platform each carries a different role in purchasing.”
Unified Measurement Pessimism
Let’s face it, finding a unified measurement that works well across platforms is not an easy task. In fact, according to a questionnaire floated by Cynopsis before the conference, 60% of all respondents believe that we will never attain unified measurement. This is a staggeringly high percentage of pessimists.
George Ivie, Executive Director and Chief Executive Officer, Media Ratings Council, is writing the viewability standard. He asked his panel, “What metrics matter? Which are the most relevant? Why are we rushing to try and equalize metrics? Shouldn’t we focus on value and let them be different?” There was general agreement here. According to Manu Singh, Group Vice President Commercial Insights and Digital, Discovery, “not all impressions are created equal.” Brian West, Director, Multiplatform Research, ABC added that he is, “focusing on the full life cycle of measurement by setting requirements in place, implementing measurements, validating them and using them to drive insights,” implying the creation of many metrics. “Inventory is the goal to measurement,” noted Ed Davis, Chief Product Officer, Fox. “What delivers attention to the brand - how much and how long?”
There is no ideal. It all depends on the campaign goals. There may be multiple ad formats that, in my opinion, make standardization difficult. So it may come to pass that there is never going to be a unified measurement across platforms. But according to some industry executives, we may not need one.
Taking unified measurement one step further is the idea that technology advancements are creating unintended considerations that are bubbling up in measurement discussion. For example: In a world where media companies can disable fast forward … or not … how do you measure forced versus organic viewing durations comparably? Ivie discussed duration weighting and developing metrics that demonstrate how platforms and content perform differently. Singh noted that, “We want to standardize those metrics. We support duration weighting.” The MRC is also tackling deduplication, focusing a great deal of attention on its methodology. “When it comes to unduplicated reach, there is still work for us to do as an industry,” noted West.
The measurement wish list is long. Singh would like, “all interactions of consumers to funnel into one repository,” and to also, “take into account qualitative data.” While West added, “It's not a one size fits all. We work consultatively with our clients. What is the ROI? What is the impact on brand? We make some form of compromise. Data is device based when we want persons based, for example. We need to advance on that.”
Jamie Power, Chief Operating Officer, one2one Media may have summed it up by saying, “When it comes to multichannel measurement, it is easier to find audiences but harder to measure them.” With all of these great minds pondering the measurement universe, maybe we can convince the pessimistic 60% that some form of standard measurement (or measurements) might indeed be possible one day.
This article first appeared in www.MediaVillage.com
This article first appeared in www.MediaVillage.com