At present, b2b marketing is witnessing a somewhat disconcerting phenomenon — the tools are getting far too smart.
Not in an eye-catching “check out this nifty dashboard” Way. More so… Quietly, reliably… AI is beginning to understand your customers much better than you do. And yes, that’s going to sting a little if you’ve spent many years creating buyer personas, mapping buyer journeys, conducting sticky note workshops with colleagues.
Since now, a machine simply… Bypasses all that.
The persona issue (we rarely discuss this much)
For years, b2b marketing relied heavily upon personas. You’re familiar with these types of personas…
“operations Olivia”
“cto Chris”
“founder fiona”
You assigned each of them job descriptions, goals, frustrations. On occasion, even personal interests (e.g., “Chris enjoys golf and craft beer”… Sure he does).
However, the issue lies with these personas; they have been/are… Approximations. Informed estimates at best. And occasionally, simply internally-determined opinions masquerading as strategic determinations.
And AI? Does not estimate in the same manner.
It observes. Tracks. Learns. Adapts.
Rather than stating “Olivia is concerned with efficiency,” AI observes that 37% of your high-value prospects are reading three unique articles, visiting price pages twice, and researching competitor offerings late at night. That’s not a persona. That’s action. Real action.
Action that occurs on a regular basis.
When data begins to provide insight
There are aspects of using modern AI in b2b marketing that create some discomfort (albeit in a good Way).
Modern AI applications collect information from multiple sources including:
Intent data platforms
CRM activity
Web-based interactions
E-mail response patterns
third party signals that did not previously exist
And then, they link together connections you would likely never identify.
For example, while you may believe your ideal prospect will convert after attending a demonstration, the AI application could indicate that conversions increase immediately prior to the demonstration — specifically after downloading a particular white paper and viewing your case studies twice during the previous week.
Therefore, how should we proceed?
Do we rely upon our past experience… Or the trend identified by the data?
That conflict is growing. And i’d argue… Rather awkwardly.
Predictive analytics is no longer simply a catch-phrase
A few years ago, predictive analytics seemed like nothing more than a vendor-created buzz word designed to support pricing.
Today, however, predictive analytics is… Real. And relatively effective.
AI models can:
Determine which leads are most likely to convert
Assign a Score to accounts based upon purchasing intent
Suggest the optimal time to contact potential customers
Reveal which pieces of content can move a deal forward
And it is certainly imperfect. Let us acknowledge that. There are times it identifies trends that seem absolutely absurd (and/or humorous) .
However, it does improve over time… Quietly and continuously.
Eventually, it begins to perform significantly better than human intuition in certain areas.
That fact isn’t commonly spoken aloud.
The “uh oh, why would we?” Situation
If you’ve implemented an artificial intelligence system within your marketing platform, you’ve probably experienced this situation.
The AI application recommends something… Unusual.
Perhaps it indicates that you need to focus on a segment you’ve long since overlooked. Or perhaps it suggests promoting a product/service you hadn’t seriously considered pushing. Or perhaps it indicates that you should allocate funds to a promotional vehicle that you believed underperformed.
Your initial instinct is typically:
“that doesn’t seem right.”
And in reality… Sometimes you’re right. However, at other times? The AI has picked-up on micro-signals, subtle actions or timing issues that elude you.
It’s similar to working with an associate who doesn’t provide justification for his/her recommendations… But somehow appears to make correct calls more frequently than anticipated.
Frustrating. Yet… Beneficial.
Are Marketers now obsolete?
Short answer: no.
Longer answer: also no… Your role is changing regardless of whether you wish it to or not.
Artificial intelligence does not supplant Marketers. Artificial intelligence alters what constitutes successful marketing.
In lieu of:
Speculating about audience requirements –> you interpret actual data
Developing static campaigns –> you adjust dynamically
Constructing personas –> you examine current behavior
Marketing evolves toward:
Posing better questions
Analyzing patterns
Determining what not to do
And possibly most importantly… Identifying when data is misrepresentative.
Since data can be misleading.
The human aspect remains crucial (far more so than you believe)
One misconception regarding AI in b2b marketing is:
Many assume that due to its capacity to optimize results, AI can develop emotional connections with consumers.
Not exactly.
AI can inform you concerning consumer activities. However, AI generally fails at understanding why such behavior is significant emotionally.
Emotion remains in b2b marketing; it merely exists beneath layers of logic, approval procedures, and budgets.
Individuals still require:
To feel assured in decision-making
Reduce risk
Identify credibility indicators
Recall experiences, not solely data points
Similarly, individuals continue to appreciate physical experiences, thoughtful gestures, and well-designed branding experiences as much as (if not more than) basic interactions with technology.
AI can direct you toward opportunities; however, it cannot entirely duplicate human resonance.
At least not currently.
How many organizations mistakenly implement AI
Many organizations enter the AI fray and… Essentially miss the mark.
These organizations:
Implement new tools without altering strategy
Automate inefficient processes (now failing at a quicker rate)
Over-rely upon scoring without contextualization
Disregard insights that contradict internal views
Possibly the greatest mistake is assuming AI will replace thinking.
It does not.
If anything, AI requires better thinking. Better decision making. Greater willingness to question assumptions.
That creates discomfort. But also presents opportunity.
Better methodologies for utilizing AI
Therefore, what defines “better usage” of AI?
Perfect? Not quite.
Simply… Better.
Something akin to:
Utilize AI to recognize patterns. Not necessarily blindly follow them.
Permit data to test your personas. Not eliminate them completely.
Pilot-test AI-generated suggestions in controlled environments before scaling.
Combine machine-generated insights with real-time conversations (underutilized).
Yes. Be willing to acknowledge that at times, the machine is correct. Even when it does not appear to be correct.
That’s likely the toughest aspect.
Final thought (somewhat discomfiting)
Should AI be able to comprehend your customers better than you do… What is your competitive advantage?
Commoditization has occurred as regards access to data. Everyone has access to tools today.
Competitive advantage exists through:
Judgment.
Style.
Timing.
Contextual awareness.
Ability to transform knowledge into meaningful experiences connecting with consumers.
That’s where the true differentiator is moving toward.
And honestly, the companies that figure this out early—whether it’s an in-house team or a partner like xGrowth B2B Marketing Agency—are the ones that won’t just keep up with AI…
They’ll quietly outgrow everyone else.
Even if it feels a bit weird along the way.