Content Marketing Manager at Leadspace
But beyond the insatiable, irrational love B2B marketers have for catchphrases, there are some very good reasons why ABM and AI are gaining so much traction. Both have a great deal in common as solutions whose times have come, in an era in which lead generation professionals find themselves drowning in more “big data” than they can possibly process.
So, naturally, here are 6 reasons account-based marketing and artificial intelligence are the perfect match. (Or alternatively, 6 things account-based marketing and artificial intelligence have in common.)
Account-based marketing and artificial intelligence both make lead generation more efficient and effective
The most obvious thing ABM and AI have in common is the problem they solve. As mentioned above, account-based marketing and artificial intelligence are above all ways to make B2B marketing and sales more efficient.
Let’s start with AI. Artificial intelligence is used in so many fields for precisely this purpose. While they may not have the creative thinking or intuition human beings possess (yet…), robots are able to process a great deal more information than people can.
In fact, AI can process unlimited quantities of data — which is just as well, when you consider the huge volume of information contained within an enterprise company’s CRM for example.
The use cases for AI in B2B marketing are almost as limitless, though industries are only just beginning to come to terms with its potential. AI is moving towards providing businesses with an all-elusive “single source of truth” — concentrating and processing their data in one place, to be used in increasingly sophisticated and lucrative ways.
Advanced, AI-powered predictive analytics is one such application — enabling companies to accurately predict which leads are most likely to convert, and prioritize resources accordingly.
And the power of AI is amplified by the amount of quality data it has to work with — which is why more “basic” data services such as enrichment are so much more effective with AI. For example, Leadspace’s AI algorithms are rooted in our Virtual Data Management Platform, which enables us to add 80+ data fields per lead or contact, down to such granular insights such as keywords used online and the technologies they are familiar with. Again, a flesh and blood sales or marketing rep would have trouble gaining that kind of information accurately for a small handful of leads — let alone tens of thousands, hundreds of thousands, or even millions.
Fittingly, that level of highly-polished accuracy makes AI perfect for powering ABM, through functions such as lead-to-account matching and more advanced site-level matching.
Account-based marketing itself has a similar function for lead generation — though as an approach to marketing as opposed to a technical solution.
ABM makes lead gen much simpler and more effective. It increases the productivity of your sales and marketing reps themselves by directing their efforts more efficiently.
First, ABM dictates identifying and focusing on a handful of named accounts – that is, those companies for whom your product or service is most well suited. Then, sales and marketing work on zeroing in on the few key influencers and decision-makers within those accounts, and tailor their content and pitches directly to them.
Both AI and ABM build upon decades of work and innovation — but are relatively simple to implement in practice
It might surprise you, but AI as a theory is in fact centuries old, entertained as a fantastical concept by scientists and philosophers alike. Early ideas about AI even found their way into popular fiction – most famously Mary Shelley’s Frankenstein, which arguably set the tone for the deep-seated suspicion with which the popular imagination still treats the notion of artificial intelligence to this day.
As a tangible, practical science, however, AI emerged in the mid twentieth century. Still, it’s at least more than half a century in the making. And from its humble beginnings solving mathematical equations, AI has evolved into something infinitely (literally) more sophisticated.
While considerably less sophisticated in origin and form, ABM is itself the product of the accumulated knowledge and experience of a generation of marketers. Nothing about “ABM” as a phenomenon is revolutionary in its own right — account-based marketing simply applies tried-and-tested marketing tactics in a novel way, and uses them to inform a holistic, overarching approach to B2B marketing (and sales) itself.
Yet precisely because of their years of refinement, both AI and ABM are relatively simple to integrate into your business. As mentioned, ABM isn’t a totally new strategy, but rather an approach to marketing which can be adopted either in-tandem with non-ABM lead generation strategies, or as a way of refining them.
Adding AI solutions to your marketing and sales stacks is perhaps easier still. Major CRM and marketing automation systems like Salesforce, Marketo, Eloqua and Hubspot are all AI-friendly.
They’re both well into the Gartner Hype Cycle
They may be more than mere catchphrases, but account-based marketing and artificial intelligence have both certainly influenced the discourse within the B2B world in a massive way. Everyone’s talking about them, while on the ground businesses are still learning how to utilize them efficiently.
That makes account-based marketing and artificial intelligence two of the most vivid illustrations of the Gartner Hype Cycle.
In both cases, we are almost certainly somewhere around Gartner’s “peak of inflated expectations.” As the conjecture and big promises reach critical mass, both ABM and AI are misleadingly wielded as immediate solutions to practically every sales and marketing problem out there.
What this means, of course, is that without a measured, nuanced appreciation of either, many adopters of both are hurdling towards the “trough of disillusionment” before they reach the “plateau of productivity.” (Who comes up with this stuff? Oh yeah, Gartner…)
Both are already delivering results
While AI in particular is relatively new in the B2B space, for ABM in particular what is emerging is a fairly clear picture of something which really works for marketers.
From our own research here at Leadspace, we’ve seen that some 60% of B2B businesses who adopt ABM see an increase in revenue within the first 12 months.
And by last year, “more than 70 percent of B2B companies have staff that are fully or partially dedicated to driving ABM-specific programs,” according to SiriusDecisions’ 2016 State of ABM Study.
AI has already proven itself as a force-multiplier of immense potential across countless industries.
And by now the B2B industry is waking up to its potential in a big way too.
Both rely on the quality of your data (and can help you better that as well)
Herein lies the key to avoiding Gartner’s dreaded “trough of disillusionment”.
As Leadspace CEO Doug Bewsher pointed out in a previous post:
“Data is AI’s Achilles’ heel. No matter how good the algorithms, AI will not produce usable insights and information to drive demand generation if you cripple it with the static data in your CRM or purchased from traditional data vendors.”
The same goes for ABM. If your databases aren’t up to scratch, poor data quality could end up scuttling your ABM campaign before it even gets going.
Both have fancy names and deceptively-simple acronyms
But more than any of the above factors, the success of account-based marketing and artificial intelligence in the B2B marketing space is due to the one thing B2B marketers love more than anything else: impressive-sounding, fancy names, which can be compressed into deceptively-simple acronyms.
What would we do without them?
Learn how to use Artificial Intelligence to create more pipeline, generate better quality leads and drastically increase conversion rates:
Picture by geralt from Pixabay | CC0 Public Domain