What do B2B marketing and counterterrorism have in common?
Overall, not a great deal, of course. But there is one commonality that any business — and marketers in particular — should bear in mind when looking to adopt advanced marketing analytics and AI technologies.
In a recent interview with DemandGen Founder and CEO David Lewis, Leadspace CEO Doug Bewsher explained how our Founder and CTO, Amnon Mishor, applied his know-how in the field of counterterrorism to the world of B2B marketing.
B2C and B2B marketers both increasingly rely on analytics tools; but despite superficial similarities, their respective use cases are actually very different.
“If you’re in a room of a thousand people, in a B2C context you want to know a little more about everyone,” Doug explained.
But that dynamic is totally different for B2B marketers, who want to know “who are the ten guys you really care about,” and then get the intelligence you need about them to engage them effectively.
“Terrorism is no different,” he continued. “You need to make sure you figure out who are the ten people who will cause problems, and that you don’t miss anyone.”
To succeed with AI, focus on a specific business challenge
That B2B marketing is a more focused endeavor than the consumer kind isn’t news (although the counterterrorism imagery is pretty original). But Bewsher went on to note that when it comes to Artificial Intelligence, and marketing analytics tools more generally, that sense of focus is just as crucial — whether in the B2B context or any other.
The above analogy is in fact “very similar to many other use cases… of AI today,” he observed.
“People talk sometimes about the ‘general’ AI problem” of the kind portrayed by Hollywood: i.e. free-thinking humanoid robots that can do just about anything.
“But most of the successful deployment of AI today is done on specific problems — that is, a specific issue.”
And that typically requires “a strong understanding of the data, as well as a strong understanding of the analytics.”
“If you think about Tesla… (it) isn’t trying to cook your dinner for you as well as drive you down the road. It’s a piece of AI combined with a strong data set that helps you achieve one goal, which is to get your car from A to B without crashing it.”
Here at Leadspace, for example, we combine AI and big data to solve the central challenge of demand generation: identifying and engaging with your ideal customers. But our models, as advanced as they are, can’t play “Go” or command legions of autonomous droids (although we could totally make them do that if we really wanted to).
With that in mind, it’s clear why businesses are quickly waking up to the reality that their data is at least as important as the technology they’re feeding it into. With AI in particular, no matter how powerful the technology, it will live or die by the data it is provided with.
Beware of “Analysis Paralysis”
As much as this highly focused approach is important when looking strategically at what AI/marketing analytics tools to adopt, it’s at least as crucial on the operational level, if not more so.
Marketing analytics technologies haven’t evolved in a vacuum — the purposes they’re suited for have changed too. Prior to the advent of “Big Data,” analytics were simply used to translate what little data marketers had into actionable intelligence to inform future decisions. Today, however, marketers — especially in the B2B world — actually have too much data, and the challenge instead is that marketers are buffeted with “so much noise that you can’t work out what it all means,” says Bewsher. Again, it’s the question of focusing on what data you really need to analyze, and getting the most out of it.
The problem is, many marketers are still operating as if that shift in paradigms never occurred — or at least, they’re trying to. The result is data overload and frustrations over low ROI from their marketing stacks.
“Because marketers are all taught that the main goal is to measure everything, and are thrown into a very noisy world where precision is tricky, we can get into a situation where people obsess about ‘measure, measure, measure,’ and sometimes lose sight of the bigger picture,” he cautioned. That “bigger picture,” Bewsher emphasized, revolves around one simple question: “What decision do we want to make, and does the analysis help us make a better decision?”
To get the most out of their marketing analytics tools, B2B marketers need to strike a delicate balance “between how do we make good decisions with the increasingly large amount of data that we have and bring it together onto a single platform so you can draw insight from it”; while making sure not to “overdo it to a point where we can’t make decisions, act quickly and move fast — which is the hallmark of good marketeers.”
You can hear the full interview with Doug Bewsher on DemandGen Radio here:
To learn more about how Artificial Intelligence (AI) is helping marketers get the right intelligence on their prospects and customers, check out our free B2B Marketer’s Guide to AI.
Picture credit: iStock