Editor’s Note: This article about adaptive marketing platforms appeared originally in Martech Series.
Does your marketing platform enable you to take advantage of artificial intelligence and machine learning so that you can have the personalized, one-to-one interactions with your prospects in real-time across the customer journey and accelerate your business?
It’s a feeling too many customers and prospects know: the sense they’re simply spokes in a brand’s wheel, rarely recognized for the individuals they are. Marketed to as if they’re part of one big blob, static and unmoving, when what they crave most is personalization – messages timed to where they find themselves in a given day, tailored to their needs and interests.
Put yourself in their shoes, if you can. What would you do if you paid a website a visit and got back a generic email for your troubles? Something bland and impersonal that seemed to know nothing about you? Wouldn’t you delete it without a second thought and question whether that brand deserved your business?
It’s a conundrum we might’ve solved in eras past with segmentation and personas – identifying the characteristics common across a specific group (their habits, their preferences), adjusting our outreach accordingly – but trying to go beyond a one-size-fits-all approach, at the level expected by today’s buyers, is hard to scale. Customers engage with businesses across a variety of digital touch points (websites, social media, etc.), on multiple mobile devices. They expect a more customized experience throughout.
MarTech 2.0: The Adaptive Marketing Platform
That’s what makes artificial intelligence and machine learning so compelling to the modern marketer, and why we’re likely to only see more of it in the technologies marketers leverage.
We can already see glimmers of this zeitgeist in some of the consumer applications now on the market – in any number of offerings from Google, for instance: Google Lens, which gives consumers the ability to learn more about a business simply by snapping a picture; Google Assistant and GoogleHome, which account for and respond to trends in buyers’ daily habits.
The thinking behind these products is simple – consumers require solutions that can adjust to their real-time movements, and want individualized shopping experiences. It only makes sense for B2B marketing technologies to follow suit, enabling personalized, one-to-one interactions in real-time across the customer journey.
If anything, AI and machine learning mark natural evolutions in these technologies. Marketing automation, for instance, has always served as a particularly efficient engine for gathering and activating engagement data (details on buyers’ histories, behaviors, general shopping habits), and is uniquely positioned to transform how marketers approach the customer journey. AI will empower marketers to build Adaptive Journeys™ that adapt to each individual and their preferred channel and send time and delivers the most relevant message in real-time as the customer goes about their research and discovery process. The journeys that buyers travel don’t keep to the straight lines we think; there are twists, there are turns, and marketers must make every effort they can to accommodate these in real time – to be proactive, where they once were reactive. That’s why it’s important for marketers to embrace this Adaptive Journeys concept, and for brands as a whole to leverage technologies capable of supporting these fluid, real-time customer journeys.
We can look at the evolution of mapping technologies to explain the Adaptive Journeys concept, looking specifically at Waze technology that knows where the driver is on their route and can predict the best commute for them based on real-time traffic conditions and external factors; ultimately recommending the best path the driver should take to get to their destination most efficiently.
More importantly: this is the kind of continuous learning marketers require in order to deliver the customized experiences their buyers expect, and also the functionality they should prioritize in solutions they implement.
We need to be agile in how we respond to and care for our customers, and our customers, in turn, need to feel like more than just a number. AI and machine learning can allow for this, and make our lives easier in ways we don’t expect – serving, perhaps, as more of a recommendation engine for us than an outright replacement for the work we do; something that suggests the best path forward, which we then choose for ourselves, so that we’re freed up to be more creative, more strategic. The future of marketing is adaptive. Let’s greet it with open arms.