CMOs May Move to AI as TV, Global Ad Spend Dips
Artificial intelligence may be able to make the world and the customer journey more predictable for CMOs who are trying to allocate budget as TV ad spend dips and ad agencies lower marketing payout predictions.
Ironically, these marketing models may come from the same technology consumers are using to replace TV and other channels that marketers had been using to reach them. One former powerhouse of mass marketing, TV, dips this year to become 34.9 percent of total media ad spending in the U.S. “and is expected to fall below 30 percent by 2021,” eMarketer reports on Wednesday.
Digital ad spend overtook it, moving up to 38.4 percent in 2017, eMarketer predicted in March 2016. With TV at No. 2, print is the No. 3 channel at 12.9 percent.
“This year, U.S. TV ad investment will expand just 0.5 percent to $71.65 billion, a figure down from the $72.72 billion predicted in our Q1 forecast for 2017,” eMarketer revised on Wednesday.
Agencies revised their budgets this year, too, the Wall Street Journal reports on Monday in “Media Agencies Lower Global Ad Spending Forecasts.” One agency forecasted the “North American ad spend to grow 3.6 percent this year,” which reflected overall agencies’ lowered expectations — but markets outside the U.S. will see spending drop-offs of as much as 4 percent, the article states.
This is the year one of those media agencies, Zenith, predicted Internet would take over TV — which indeed, it has. That usurpation needn’t be at the expense of the mass marketing channel used for brand awareness, though, Zenith research showed in a June 2016 article in Target Marketing.
“One of the reasons for television’s loss of share is the rapid growth of paid search,” reads the report’s executive summary that shows paid search growing from nearly $71 billion in 2015 to more than $102 billion worldwide in 2018, “which is essentially a direct response channel (together with classified), while television is the preeminent brand awareness channel. Television does not compete directly against search, and indeed the two can complement each other. For example, by running paid search activity to take advantage of the increase in searches driven by a television campaign.”
AI to the CMO's Rescue
So where should CMOs be spending their marketing dollars? With lots of data and perhaps few answers about how to reach, for instance, the “cord-cutters” and “cord-nevers” who shun TV in favor of streams, mobile video and other digital options, a couple recommendations emerge.
Feeding data into AI can help marketers see patterns, which they can then use to create predictive models to apply to customer journeys. The predictive analytics requires a question related to a business goal, but the technology can make life a lot easier for CMOs who are accustomed to more labor-intensive data modeling.
On July 2017, Datorama CMO Leah Pope writes for the American Marketing Association:
The sheer scale of our data in a pre-AI world has limited our ability to see opportunities and act on them, but if our results need to be predictable, we also need our pipeline of insights to become more predictable. With AI, it will be. Across the millions or billions of rows of data we’re expected to create insights from, the AI bots work to find what’s moving in our performance, but also answer why it's happening and what we can do about it. These are the paths we and our teams can use to flip that switch to “always-on” optimization. This is the next chapter in AI-powered insights.
Similarly, Bulldog Reporter writes “CMOs Know Cognitive Computing Will Be Disruptive — But They’re Unprepared” on Aug. 30, 2017, for AgilityPR.com. (The same author writes on Aug. 9: "Cognitive computing is a next generation information system that can understand, reason, learn and interact with humans in natural language. While traditional analytics can provide data-based insights, cognitive more easily turns these insights into actionable recommendations.") The Aug. 30 article reads:
Many marketing and sales executives fear the shift to cognitive will require them to “rip and replace” the tools and processes they use to analyze customer data and create customer experiences. Instead, there are numerous types of cognitive solutions — from improved capabilities for personalization to content tagging — that marketers and sellers can implement in stages to target specific challenges and often can be integrated into companies’ existing cloud platforms and data management systems. By starting small, companies can begin to enjoy the benefits of cognitive computing and determine how best to expand over time. More than half of “outperformers” have already started their shift to cognitive. The real risk would be to wait too long on the sidelines while the competition forges ahead.
What do you think, marketers?
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Related story: TV Ads Still King, Mobile Vying for Crown