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Video measurement must evolve with changing privacy regulations

Video measurement must adapt to changing data privacy regulations and Accuity’s Seraj Bharwani makes the case for using data based on user-initiated behaviors like branded search and branded video viewership.

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Video measurement must evolve with changing privacy regulations

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Changing privacy regulations are influencing many aspects of the media and advertising sector, with one of the major areas being video measurement. As behavior tracking options gradually disappear, measurement models are not keeping up. We have already seen platforms such as Facebook impacted by changes made by Apple last year.

How are these changes impacting video marketing? What can and should marketers do to achieve better business outcomes from brand advertising as they attempt to build brand awareness this year?

Most brand advertising is done using video ads delivered as ad breaks within content. Video ad types include short- and long-form stories on linear and addressable TV and on-demand channels like connected TV, online video and native video. Such branded video advertising efforts seek to build brand awareness and keep brands top-of-mind for viewers who may be in-market. Effectiveness is usually measured through survey-based techniques involving control and exposed consumer groups to determine ad recall, brand favorability and intent to purchase.

MMM and MTA measurement come with limitations

As awareness channels are becoming more addressable, advertisers are subjecting upper-funnel media to the same scrutiny they do to lower-funnel performance media channels. They also expect explicit attribution of branding media to sales and market share growth.

Various media mix modeling, or MMM, approaches using econometrics models, and multitouch attribution, or MTA, techniques enabled by behavior tracking are being employed for upper-funnel attribution. Both approaches come with their respective limitations.

MMM approaches require months of time series data to make a reasonably accurate estimate of its effect on sales, which limits their applicability in contemporary media environments requiring rapid media reallocations and optimizations.

Meanwhile, MTA approaches are becoming less effective as constraints from privacy regulators and device makers are severely limiting the ability to track user behavior through cookies or alternate identifiers. These regulations also are forcing behavior tracking at the cohort level to protect consumer privacy.

All this begs the question: What could be alternative — and potentially better – predictors of sales and market share growth for investments in upper-funnel brand advertising?

Emergence of user-initiated behavior measurement

What if the measurement was based instead on user-initiated behaviors like branded (i.e., organic) search and branded video viewership at the aggregate level?

The effects of awareness advertising on branded search have been researched extensively by the likes of Les Binet over the past few years. Binet’s research across multiple vertical industries (e.g., phone sets, automotive and utilities) demonstrates that the excess share of branded search leads to incremental sales and market share gains. The impact of share gains is predictable from three to 12 months in advance depending on the category.

In a similar vein, user-initiated behaviors to watch and/or interact with brand-produced video ads (on brand channels) has proven to be an early indicator of brand advertising’s effect on sales and market share. Measuring these activities can be done via publicly accessible data from YouTube at scale across many vertical categories and can be aggregated and analyzed without major costs to advertisers.

Over the past decade, dozens of brands have seen high correlation between user-selected, branded video viewership (user-chosen ads) and incremental sales for brand advertising around major events (i.e., Super Bowl, Olympics, March Madness, Oscars, etc.). In addition, when you look at brand channels in industries such as mobile devices, direct-to-consumer mattresses and sneakers, branded video viewership trends point to high correlations between the share of views and market share growth (with low statistical variance, R2 > 85%) in select studies.

For the DTC mattress category, there is a direct correlation between share of brand-channel video views and e-commerce share of sales growth across top DTC mattress brands. Most importantly, share of views tends to lead share growth by three months. This makes share of user-selected branded video views a leading indicator of share growth in select categories.

A scalable, privacy-protected solution

Advertisers on the hunt for privacy-protected measures of media attribution at scale should consider both share of branded search and share of user-initiated video viewership as potential candidates. Advertisers will need privacy-protected measurement techniques that provide a real-time measure of media effectiveness for upper-funnel, awareness advertising as state and federal privacy regulations go into effect.

 

Seraj Bharwani is the chief strategy officer at AcuityAds, inventor of illumin, a journey automation platform for omnichannel digital advertising. Seraj previously co-founded Digitas, a global digital advertising agency, and Visible Measures, a third-party digital video measurement company. Over the past 25 years, Seraj has done extensive research on viewership trends across digital platforms and is an authority on consumer trends and insights guiding the future of consumer marketing.