All Things Growth and Marketing

Many marketers have a bad ICP problem. The kind where the “ideal customer profile” reads: “B2B SaaS company with SMB, mid-market, and enterprise segments.”

That definition is useless. It doesn’t guide targeting, drive pipeline, or filter out bad fits.

In B2B, an ideal customer profile (ICP) is the domino that tips everything else that follows. Sales efficiency, pipeline quality, deal size, and retention all trace back to how sharply you’ve defined, and how consistently you’ve targeted, the right customer. Get it wrong and every marketing dollar you spend compounds waste.

AI can help fix that, but not by inventing a better-looking ICP from scratch.

AI isn’t just for cranking out LinkedIn posts. It can be leveraged for ABM account research, enriching data, and scoring accounts so you know who is worth your time (and who’s not).

If you’ve read our foundational article on AI, ABM, and ICP strategy, this is your hands-on follow-up to apply the model.

In CXL’s course on ICP Modeling and Targeting with AI, Eric Linssen, Growth Lead at Keyplay, showed how SaaS teams use customer data and AI to build and test more precise targeting models – which this article pulls from.

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Paid social changes fast. Meta adjusts delivery, LinkedIn adds new formats, platforms like Reddit and Pinterest keep maturing, and AI is changing how teams research audiences and monitor campaigns.

The fundamentals are still vital, but button-clicking tutorials age quickly. Paid social marketers now need to understand creative, targeting, measurement, testing, platform economics, and the systems around the campaigns themselves.

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That “whale” client you brag about? They might actually be killing your business.

On paper, they look huge. They pumped your top line, made a flashy case study, and gave your CEO a win to boast about. But in reality, the deal was a nightmare to deliver. Margins got crushed, the team burned out, and finance quietly ate the loss.

Revenue is the peacock of metrics: flashy, loud, and mostly useless once you look closely.

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Personalization used to mean effort. Now, it means intelligence. 

But somewhere along the way, ABM personalization turned into a checkbox, with marketers labeling “Hi [First Name]” personalization and calling it a day.

That’s not personalization. It’s Mad Libs marketing. And even though the intent may be right, the execution is painfully generic. 

Buyers don’t care that you know their name. They care about connection; that you understand their reality.

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Most B2B teams say they’ve “automated,” when what they’ve really done is stitch together fragile hacks that break the second you scale. And as leads vanish and sales ignores marketing’s handoffs, campaigns run like isolated experiments with no system behind them.

There’s no such thing as 100% automation. The second you remove human oversight and documentation, your stack will collapse under its own weight.

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AI hasn’t just compressed build cycles; it’s compressed thinking. Now, every SaaS site looks cloned, every brand interchangeable. 

But despite the endless copy-paste, it’s not enough to be different anymore. In crowded B2B categories, you must be distinctive. Buyers don’t remember the slightly clever tagline or the 12th corporate navy booth. They remember what sticks.

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Most B2B marketers are unaware of how impactful AI is in modern lead research. Lead research data can feed lead generation strategies, powering smarter segmentation, personalized outreach, and faster conversions at scale. 

A name and an email are all you need to turn a newsletter sign-up into a fully enriched lead profile. Within minutes, you automatically pull their LinkedIn profile, job title, company size, industry, and even have tailored talking points ready for your next outreach sequence.

Sounds magical, but it’s probably a ton of setup, right?

It’s actually easier than it looks with a simple stack: Make.com + Relevance AI + your CRM.

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The best AI SEO courses teach you how to get cited and recommended in ChatGPT, Google AI Overviews, Gemini, Perplexity, and other AI search experiences, not only how to rank in Google. Looking for traditional SEO training instead (keyword research, on-page, technical SEO, link building)? See our guide to the best SEO courses.

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