What exactly is “cross-media” beyond a big data vision of bringing ‘online’ media and above-the-line media (AV in today’s money, audio-visual media) into the same measurement pool?
The clue may be in the use of “holistic” in the cross-media measurement context, oftentimes used as a short-hand for the industry’s stakeholders’ various plans and roadmaps in this respect.
Under this “holistic” context for cross-media measurement ambitions, of course, no single data solution provider, or JIC, has a true-north, off-the-shelf ‘whole’ source of data and so proposed “holistic” solutions across online, social and above-the-line (AV) inevitably must be built on a multi-data source aggregation model.
That’s OK to a point of course, so long as ‘holistic’ isn’t then misconstrued or believed to be a true whole, a true north in the singular sense.
I’ve heard it said that any number is better than no number. Advertisers understandably want the reassurance of “holistic measurement”, but in reality, cross-media measurement can never be more than the aggregated sum of all these multi-various data inputs. Literally a sum of the parts.
So, the pursuit of holistic “cross-media” measurement somewhat involves the dark arts necessary to algorithmically bring these multiple parts to an acceptable “holistic” conclusion. So, isn’t “holistic” in cross-media measurement just a euphemism for systemic intelligent guessing?
Let’s accept that a reasonable, near-north intelligent estimate is better than no number, but it does focus the mind, or it should, on making sure there’s a clear understanding of the unique and intrinsic contributing value of any part designated for use in a holistic cross-media solution.
Let’s keep that train of thought and simplify the cross-media measurement jigsaw. For brands in 2023, ‘cross-AV’ is still the central piece of the ad measurement jigsaw to get right for most CMOs. They are under real and present pressure to especially understand how to efficiently recover the lost reach of their traditional broadcast TV audiences. And to then extend total TV reach further without unnecessary duplication of spend.
What was once just “TV” is now a series of un-joined measurement dots, audience silos of premium video now being happily watched in the familiar lean-back world of big screen TV viewing. Herein lies the measurement challenge for brands looking for best practices in joining the dots. How is it possible to measure all AV without adding undue complexity and obfuscation? Both add unwanted doubt to the output. So, is that sort of data-derived destination a reasonable, convenient place to settle aim at TV investment? If the goal is true north, near north may be good enough for now maybe, but not for long. The cross-TV audience is surely not standing still. Fragmentation is far from over.
For most brand advertisers, it’s still TV measurement and brand measurement that matters most and getting those right is a major milestone. It’s important to acknowledge that in some marketing quarters, there is understandably a sense of confusion around cross-TV measurement and the volume of TV data that now exists. The key question ought to be, therefore, how can the quality of data be improved? It could be that some solutions being deployed are either over or understating what’s really happening if performance is being framed by a blended view derived from multiple data sets.
Whilst one or two advertisers may have chosen to settle on a trusted solution in the interim to help to fill the large “cross-media” data hole that was there a few years ago. It must be said that in the last year, the confusion level grew every time a new or updated data solution was announced. So much so, there’s now a side industry in measurement landscape graphics of vendor logos, segmented every which way to prove just how cluttered it all looks and feels if you’re looking to navigate a route through.
Peter Drucker, the father of management by objectives and a pioneer business thinker gave the business world the notion that “management is doing things right; leadership is doing the right things” (The Effective Executive (New York: Harper & Row, 1967)
In trying to navigate the AV measurement landscape, doing the right thing might for starters, look at replacing right with accurate and see how that immediately changes the measurement perspective.
Paraphrasing Drucker for TV ad measurement, “leadership is doing the accurate thing”.
In TV measurement, accuracy is no friend of undue complexity and obfuscation. Fragmented TV viewing is the big wave that hit the legacy measurement beach.
It created, and continues to create, responses predicated on multiple data sets to track an individual’s viewing using household-level or device-level data. And measuring the fragmenting channels like CTV, BVOD, AVOD, and OLV in separate data buckets.
Meaning that someone then must derive a credible set of assumptions and a working formula to bring these data sets together. Creating layers of data science, unified statistics, and complexity to get that intelligent guess at a reasonable view of total R&F or incremental reach when fused with JIC TV data. And possibly available CTV/set-top box impressions data.
More data sets, more aggregation, more assumptions, and more algorithms to derive a probabilistic estimate for cross-TV measurement. Undue complexity by design driven by unintended consequences.
The plain truth is that the cost of good measurement data is still seen as a tug of war between buyers and sellers and this generates the reliance on probabilistic data algorithms and fusion data methodologies. This inevitably means that all such solutions will always be out of date without verified and independent first-party data underpinning them. Everyone with an algorithm-based dependency is frankly going to be out-algorithmed by someone smarter down the line. So why start there?
Why not seek out independent first-party measurement data that is deterministically collected and build your own metrics from there?
Doing the right thing is putting quality first. The pursuit of data accuracy immensely simplifies the TV measurement landscape. Unduplicated, cross-TV measurement of efficient reach, effective reach, incremental reach, and overlap reach doesn’t have to be complex if you know your onions.
Top-quality measurement data is based on verifiable accuracy in data collection, which gives the data its unique provenance, its origin, and its authenticity. Independent, single-source measurement data for TV (all AV too) is the purest quality data that money can buy. Quality and accuracy in TV measurement are not about big data at scale, it’s about having the right data to confidently move forward.
There is a sometimes view that measurement costs are non-working stuff, taking the budget away from the media investment itself. Measurement has a more central role than that, but it has to be credible. There needs to be a shift in mindset around the cost of ad measurement, if you consider measurement as a non-working cost, how do you know that your media investments in working stuff are accurately working without it?
Accuracy matters, it’s the competitive differentiator in delivering verifiable efficiency and effectiveness improvements in cross-AV, the bedrock of most ad campaigns.
All routes with the following accuracy as a true-north beacon lead to single-source measurement data. Single-source data is not commodity data. It’s premium data, an investment that pays for itself over and over.
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