Understanding the convergence of industry 4.0 and the rise of autonomous vehicles
Contributor Joe Veverka looks at search as an indicator of attitudinal behavior shifts to better understand the rise of the autonomous vehicle (AV) and the mega-disruption of our time: convergence.
As a society and as marketers, we’ve moved into embracing a brave new world bursting with myriad emerging technologies so quickly that we don’t take the time to understand the interconnections. We see new entrants like cryptocurrency and the internet of things (IoT) as singular, when in fact, they are symbiotic in nature. Together, these trends form an extensive, disruptive infrastructure.
Search advertising is often discussed within the context of a digital marketing vacuum, with the words “performance” and “efficiency” driving conversations. In our busy daily routines, we seldom look past the last click to see what the future may hold.
But search behavior is one of the most accurate predictors of human intent on earth. So, why don’t we look to it more often to answer important questions about what’s happening in our time?
Today, we’ll do just that. Let’s use search in the context of a leading indicator of attitudinal behavior shifts to better understand the rise of the autonomous vehicle (AV) and the mega-disruption of our time: convergence.
Groundbreaking technologies and the as-a-service economy are deeply interrelated. If you take time to think with precision about the impact of these disruptive trends, you will begin to clearly identify the power of convergence and how these seemingly unique ideas are ubiquitous and closely intertwined. Convergence is the truest form of digital transformation, and it’s happening all around us.
Bing Ads (my employer) recently analyzed 600,000 instances of queries over 16 months from categories aligned with a variety of disruptive trends to better understand and quantify their momentum. What we’ve learned, and our methods, can benefit marketers seeking to reach B2B and B2C audiences in these emerging areas.
In the stream graph below, we looked at six months of recent data and used average site time as a proxy to understand user engagement:
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