“Take for example Cheetos. A few years back, Cheetos announced a gift collection ecommerce site timed with traditional retail holiday promotions. The site sold pretty much everything but the popular snack, from cologne and branded leggings to bronzer and a $20,000 jewelry set. No AI parsing through Cheetos marketing data sets would ever tell their CMO to sell pricey baubles. But with over 100M impressions, countess press pieces, social medial trending topics and a complete store sell out (yes, even the $20k jewelry set), Cheetos became the hot holiday season story. It’s these brave, and sometimes silly, choices that can resonate deeply with consumers in an age where marketing is becoming increasingly formulaic.”
“Technology now accounts for a whopping 29 percent of the total marketing expense budget, making martech the single largest area of investment when it comes to marketing resources and programs
Investments in AR and VR, a small segment of AI, are expected to grow from $11.4 billion in 2017 to $215 billion in 2021, according to IDC.
Meanwhile, 56 percent of senior AI professionals peg a lack of qualified workers as the single greatest barrier to AI implementation (Ernst & Young).
The volume of data created worldwide is growing at a staggering 40 percent per year, feeding a near-unimaginable level of intelligence into organizations attempting to make sense of and activate it.
It’s the next step in automation that gets exciting, and that is the combination of automation and AI. Intelligent automation takes the efficiency and productivity of automation and layers on data analysis, decision-making and even prioritizing next steps.
Marketing and customer analytics have been named by 40 percent of CMOs as the top capabilities needed to support the delivery of their marketing strategies over the next 18 months.
At least 99 percent of big data is not even analyzed, according to the IDC.
Today, deep learning allows us to take massive and sometimes unstructured datasets and reap actionable, relevant insights.
What’s more, predictive analytics activates those insights by facilitating real-time optimization, ongoing measurement, and further optimization.”