Artificial Intelligence (AI) has captured the human imagination since its inception.
With that, there’s a tendency for that imagination to veer towards machines “taking over” in some way. Often, the predictions are apocalyptic (think Terminator, I, Robot, or practically any other movie involving AI). Other times, we’re warned of AI rendering one profession or another redundant. Basically, we’re all going to either die, or be unemployed.
So when I came across a recent Forbes article asking whether AI threatens the future of human content writers, it was time for me to take on the machines (thank me later).
While it was dramatically titled “Will Content Marketing Die To Robotic AI?”, the article’s conclusion was that, no, it wouldn’t. But the question itself is absurd. Sure, computers can be programmed to write simple (boring) stock updates or sports results – or even assemble complex machinery – but writing compelling, creative content is a very human endeavor. It requires imagination, intuition and instinct – and if Hollywood has taught us anything it’s that if computers ever gain those traits, unemployed content marketers will be the least of our worries.
Predictive analytics: Handle with care
There is no doubt, however, that as it continues to advance, AI will change our lives for the better in ways previous generations could scarcely imagine. And, while it may not be as sexy as droids or CIA supercomputers, predictive analytics is one of those fields in which AI is revolutionizing the way we do business.
For B2B marketers, predictive analytics provides a vital layer of intelligence, of the type we take for granted in most other aspects of life.
Consider: Whenever we make major purchases, such as a new phone or car, we research the best models, create a shortlist, and use that to inform our decision. So when you’re chasing tens of thousands of potential leads, being able to narrow your search down to those most likely to buy seems like a no-brainer.
The problem is, letting a machine make a decision for you is like… well… letting a machine make a decision for you. Marketing is another of those creative, non-binary endeavors a machine simply can’t do for you.
This was a challenge recently encountered by leading SaaS business communications provider RingCentral. They recognized the need for a predictive analytics solution – particularly as they moved towards a highly-targeted Account-Based Marketing (ABM) model – but they understood the limitations of traditional predictive solutions.
Part of RingCentral’s long-term strategy was to move into fields they weren’t previously established in, but for which their product would still clearly be suited for. There was only one problem: since they had never sold to such customers before, most predictive analytics wrote them off automatically, ranking them as low-value leads unlikely to convert.
Avoid “Black Boxes”
What they needed was a solution which combined advanced predictive analytics and machine-learning with good old-fashioned human brainpower. A “black box” solution which churned out probabilities without clear insights into why a lead was ranked high or low just didn’t work. Apart from anything else, it prevented their own experienced sales and marketing teams from giving their own valuable input into their ideal customer profile.
Leadspace’s unique, hybrid prospecting tool was their ideal solution. By combining their Ideal Customer Profile (ICP) with Leadspace’s advanced predictive analytics, RingCentral were able to successfully break into new markets.
“It was pretty amazing,” RingCentral Chief Marketing Technologist David Cowings said. “What we found with Leadspace was that 80% of the time Leadspace called something into a segment, it was falling right in line with what the sales reps had previous aligned that target with.”
AI: Smart, but not smarter than you
It’s actually a common problem for B2B marketers. During a recent sales call, a leading enterprise technology company told us they had opted for Leadspace over competitors for the same reason.
Until relatively recently their marketing model had been largely B2C, but over the past few years they have increasingly moved towards B2B markets. Other predictive analytics options provided skewed results which reflected that past sales record, rendering the results unusable – only Leadspace could provide the intelligent solution they needed.
The lesson here is that machine learning can only go so far. Predictive analytics is definitely the future, but only if human intelligence, experience and knowledge can be effectively brought into the mix.
So, fellow marketers, you can breath easy: there’s no chance of the robots taking over.
In fact, you can get your hands on the “next generation” of lead generation technology and strategy to look like a marketing hero.
Hear RingCentral’s David Cowings explain how:
The post How RingCentral Overcame the One Limitation of Predictive Analytics appeared first on Leadspace.