Television advertising media expenditures are the biggest single component of a typical marketing budget – and yet are the least accountable when it comes to proving direct product sales or other return on investment (ROI) success.
Over the decades, that’s made for very good business for traditional networks, stations, and other television advertising outlets– as well as for the dominant and relatively straightforward measurement and trading currency that defines it.
For marketers and the agencies that buy TV ad time– not so much.
Translating product marketing targets into the broad demographic vernaculars of the TV industry is messy, inefficient, and rife with waste. But it is relatively easy – and that will be increasingly problematic in the years to come.
Today, when a TV seller offers a marketer the chance to advertise during a program that is promised to do well in a demographically-defined range like “Males 18-49″ – how many products or services neatly fit into that seemingly arbitrary targeting environment? Aside from some base commonalities (you can pretty much figure out what some of those “boys-will-be-boys” areas might be), a (barely) adult male who’s 18 years old and a (hopefully, fully grown) adult male who’s 49 years old are radically different people – one is likely to be in college, while the other is most definitely trying to figure out how to pay for it.
Yet that is how marketers must contort themselves to advertise on television today – take the opaque box of linear TV, all-at-once scaled demographic audience as coarsely defined – or leave it.
Luckily, evolutionary solves for this conundrum – such as XACTV’s new automated AI-powered unwired network for local broadcast TV spot inventory – are already coming to market, as advances in digitally-derived targeting programmatically-managed inventory, and AI-driven aggregation techniques allow advertisers to better aggregate audiences on their own terms. While transacting on age and gender may be the way of today setting the foundation now, is building for the future.
By the end of the decade, however, the “TV” advertising landscape will look decidedly more complex. The migration of TV/video distribution to more pure digital IP (Internet protocol) delivery infrastructure (hello, over-the-top streaming video and connected TVs), coupled with “big data” advances in MVPD set-top and streaming device ACR analytics (insert one of a few dozen data/tech startups here) will usher in a new era of increasingly precise audience-based targeting that will make the last 15+ years of online/digital advertising evolution look like child’s play.
The skills gleaned from online marketing’s adolescence are quickly becoming something akin to a dress rehearsal for the Big Daddy of ad spend allocations, as the “medium formerly known as television” fast morphs into free(er)-flowing video formats across multiple consumption environments – each with discrete, granular and measurable data points from which to judge relative success. And just in time, too, as video audiences splinter across a myriad of programming options, viewing devices, and consumer-dictated linear/live vs. non-linear/on-demand delivery dimensions.
As a result, traditional TV advertising units (looking at you, 30-second spots) are starting to become increasingly data-segmentable and, at the early edges (courtesy of local spot MVPD addressability), tantalizingly atomizable – allowing advertisers and their agencies the unprecedented ability to more effectively create multiply simultaneous gerrymandered audiences, directly and natively tailored to marketers’ organic targeting criteria.
Thus, modern TV/video advertising success will come only to those skilled in both the sophisticated science of analyzing “big data” for actionable insights, and the subjective art of aggregating myriad atomized bits of audiences digitally spread across time, place, and device into whatever relative scale makes economic sense to marketers’ expected returns.
As such, CMOs and their agents will need improved quantitative skills to market to multiple audiences simultaneously – relentlessly informed by consumer data before, during and after campaigns – and with an “always on” mindset devoted to monitoring impact, while optimizing outcomes and efficiencies.
Creative messaging, too, will become an order of magnitude more complex – but also increasingly compelling – as TV “spots” become more data-intelligent about the audiences they are reaching, as well as inherently more resonant with the pre-identified tribes of predisposed consumers primed (and ideally, eager) to engage with them.
How advertisers and agencies adjust accordingly and scale smartly for these inevitable realities will ultimately determine the ongoing marketing value of TV/video advertising.