Kiss your personas goodbye (and say hello, AI)!

Your buyer personas are about to become as out-of-date as an Altair 8800. Contributor and AI marketing guru Venkat Nagaswamy explains why you’ll be grateful.

Chat with MarTechBot

artificial-intelligence-ai-machine-learning-brain-ss-1920

There’s a great cartoon by Tom Fishburne that cuts right to the quick. A marketer is detailing “Al,” a targeted buyer persona: “39-year-old Scorpio, drives an Acura, watches “Game of Thrones,” has a Jack Russell terrier, favorite Beatle is George.”

When he’s asked, “How will this help us sell ERP software?” he replies, “Sales is your job. I’m in Marketing.”’

Up until now, that’s been the core issue for buyer personas. By necessity, they’re drawn up at the macro level, since marketing traditionally operates at scale. They haven’t incorporated the personalization and 1:1 insights that are key to the sales process.

Personas work, of course. They’ll drive results like one marketer’s 900 percent increase in length of visits, 171 percent uptick in marketing-generated revenue and other lifts.

Persona problems? Take your pick.

“So what’s the problem with using personas?” is a reasonable question. There’s a big list we trot out to answer it, and its extent invariably surprises people:

  • Present-day personas aren’t “personalized.” They’re archetypes developed using whatever data a marketer can scrape together about the target, but they’re inherently limited by that data, or by the ability of the marketer to analyze it.
  • They focus on roles and titles. Most personas are title-based profiles, and you can’t cram complexity and nuance into the archetype because it’s not cost-effective to perform that level of segmentation using human assets.
  • Titles can steer us wrong. If your persona is trying to zero in on “Debbie, the Data Center Director,” you may already be in trouble. Job titles can be misleading: just because Debbie has the right-sounding title doesn’t mean she’s the actual decision-maker you want to engage. If you’re wrong about that, any outreach you make toward Debbie gets interpreted as spamming.
  • They don’t leverage online behaviors. Old-school personas are based on interviews, or available name/title/demography data, but they don’t account for online behaviors, such as targets’ preferred social media channels or browsing habits. Yet those behaviors are far more indicative of their status, interests and concerns at any given moment. That disconnect prevents the marketer from efficiently targeting prospects in digital channels with relevant messages.
  • They’re dependent on the process behind them. One survey found that a mere 15 percent of marketers used qualitative buyer interviews to craft personas. No surprise, then, that the number of respondents who judged their personas to be “very to significantly effective” was identical, also a tiny 15 percent.
  • Even with research, personas are guesswork. They’re only rough outlines until published content uncovers the actual responses and behaviors of your audience, at which point personas have to be modified to fit the new data.
  • Unlike personas, people are constantly evolving. Profiles devised by human beings will eternally lag behind the wants, needs and behaviors of any target audience, even if they’re continually updated.
  • They’re hard to adopt. Just 44 percent of B2B marketers were using personas a couple of years ago, according to ITSMA, thanks to the sizable investment of commitment, time and cost to develop and operationalize them.
  • Updating personas is pricey but compulsory if a marketer wants to maintain their effectiveness. That’s an expensive treadmill to chain yourself to, but imagine marketing at global scale and trying to localize to multiple segments in far-flung markets. That’s a whole new level of difficulty for persona upkeep.
  • Buyers demand more and more relevance. B2B buyers increasingly expect highly personalized digital experiences, and they’ll reward you for your effort — or drop you hard if you’re not relevant. A CEB study in the Harvard Business Review reported that stakeholders receiving supplier content tailored to their specific needs were 40 percent more willing to buy from that supplier than buyers who didn’t receive customized content. It’s one reason cold calling is a dying art: One Salesforce survey found buyers think only 20 percent of sales reps add value to the purchase process — undoubtedly the ones who did their homework.
  • They drag down marketing ROI. Even marketers seeing improved results thanks to current persona-building practices are probably still leaving money on the table, since the shortfalls I’ve described are hamstringing their marketing automation platforms, web content management systems and other tools and channels.

AI can evolve personas toward personalization

What’s the solution to these headaches? In the end, it’s all about getting as close to true personalization and 1:1 engagement as possible. Artificial intelligence will make buyer personas more valuable than ever for marketers by making them far more accurate and personalized. How? By absolutely reinventing how persona building works:

  • AI platforms are capable of collecting and analyzing prospect and customer data at oceanic scale, far beyond the capability of human beings, by drawing from internal databases, third-party sources, even from social media.
  • By yielding accurate, brain-like associations and insights from this trove of data, an AI can automatically craft rich profiles of a marketer’s optimal prospects, resulting in far more accurate lead generation for sales teams and outbound marketing.
  • The marketer can then serve up digital experiences fine-tuned to maximize relevance to prospects and customers.
  • An AI can continually update these personas in real time, so engagement strategies and messages stay relevant over time. AI allows account-based marketing (ABM) to actually execute at scale across all of a marketer’s accounts.
  • By automating the process, AI removes work, costs and workflow bottlenecks (like those interminable persona-building brainstorms, for instance), freeing marketing and sales teams to focus on acquisition and selling.
  • An SaaS-based lead gen AI platform can plug into existing marketing stacks with no muss or fuss, bootstrapping marketing ROI while adding interoperability and scalability.

Here’s an example in practice: A MarianaIQ customer gave to us and a traditional lead-gen service the same list of 5,000 companies, asking each of us to identify the people at those firms in charge of SEM.

The other service returned 55K names, but only 15 percent (or 8K) matched our customer’s criteria. Our AI engine recommended just 20K names, but with 81 percent accuracy, resulting in 16K matching leads.

The persona is dead. Long live the persona!

To sum up? Reinventing the “buyer persona” so that it’s a tool for highly accurate, real-time, multi-channel engagement with B2B prospects absolutely requires an AI solution.

Otherwise, there’s no way out for any B2B marketer leashed to old-school ways of building personas. The complexities of leveraging Big Data are too daunting, and competitive pressure from AI adopters will force them to make the same move… or leave the field.

But the benefits far outweigh any reasons to hesitate. By automating persona-building via AI, that marketer will find they’re able to kick costs and inefficiencies to the curb, make ABM an at-scale reality, and get a leg up on laggards who haven’t made the same move.

All told, it’s a pretty good argument for giving your old personas their well-deserved retirement.


Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. The opinions they express are their own.


About the author

Venkat Nagaswamy
Contributor
As co-founder and CEO of MarianaIQ, Venkat Nagaswamy brings a long and diverse background in high technology to bear on applying artificial intelligence and Deep Learning to help marketers make account-based marketing (ABM) an at-scale reality. "Big Kat," as he was nicknamed by friends and colleagues, has led teams in creating analytics, technology and business development solutions at McKinsey, Juniper Networks and GE Plastics, among others. He's worked in enterprise and digital consumer hardware, SaaS, corporate and business unit strategy, market entry strategy, product development, marketing planning and more, allowing him to understand martech challenges from both the CTO and CMO's point of view. A proud graduate of the University of Michigan and the Georgia Institute of Technology, he holds an MBA and a Master's in Aerospace Engineering.

Fuel up with free marketing insights.