Robynn Farrell

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As an editor and strategist with a 10+ year obsession with psychology and the human narrative, I engineer content that drives organic growth and moves people to action. I help B2B brands discover their voice, forge authentic connections, and transform complex ideas into measurable impact.

You’ve been there. You start building lead scoring in HubSpot or Marketo, and immediately fall into dropdown purgatory: endless clicking through menus, assigning point values to job titles, email opens, and webinar attendance.

Weeks later, you launch it. Before you know it, you’re stuck QAing, checking how your rules affect MQL flow, and realizing you may have over-scored or under-scored in ways that ripple through your ABM funnel. 

The problem isn’t the tool. It’s the approach.

Manual lead scoring treats every signal equally and forces you to guess point values before you see the data. You’re building a lead scoring model based on intuition, instead of patterns. And once it’s live, changing those rules means clicking through the same menus again.

ABM fit scoring is the faster, saner alternative.

Instead of scoring individual leads based on behavior, you’re scoring accounts based on how closely they match the patterns of customers who actually closed.

This article outlines how Steve Armenti, founder of twelfth agency and former ABM lead at Google, uses AI to build fit scoring outputs using enriched account data, a scoring prompt, and a scored CSV (ideally with confidence indicators and top drivers). 

This isn’t about replacing HubSpot or other platforms entirely. It’s about using AI to do the pattern recognition work that humans are terrible at, then importing those scores into whatever CRM you’re using.

Here’s the playbook.

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Brainstormed personas aren’t customer research. They’re easy to build, easy to forget, and often disconnected from how people actually buy because they’re based on opinions instead of evidence.

AI can help replace that guesswork with actual customer evidence. Feed it purchase data, surveys, reviews, and competitive research, and it can surface patterns that would take a team much longer to identify manually.

The result should be a working customer avatar that helps you decide who to target, what to say, and which messages are worth testing.

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B2B audience research shouldn’t be a luxury item. If insights require a massive budget, most teams will never get them. 

You don’t need a six-figure research sprint to learn what people want. The conversations you need are already public, sitting on Reddit, LinkedIn, review sites, and forums, waiting to be mined. The only thing stopping most marketers is habit and a misguided belief that market research needs an agency badge to be legitimate.

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Conversion rate optimization is about more than changing buttons or landing page copy. Good CRO combines customer research, analytics, psychology, experimentation, and statistics to understand why people convert and what to improve.

That matters more as traffic gets harder to earn. Contentsquare’s 2026 Digital Experience Benchmark, based on 99 billion sessions across more than 6,500 websites, found that traffic fell 3.8% year over year and conversion rates fell 5.1%. Returning visitors also converted at 2.9%, compared with 1.7% for new visitors.

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Marketing didn’t suddenly reinvent itself. It just stopped rewarding amateurs. The easy wins are gone, channels are crowded, attention is expensive, and “pretty good” means invisible.

The fastest-growing marketers aren’t doing more; they’re doing what works, on purpose, with systems behind it, quicker than the market shifts. They’re complete marketers who can spot a real opportunity, position it cleanly, tell a story that lands, pick the right levers, and measure what matters. And that’s why they keep getting the bigger briefs, bigger budgets, and bigger titles.

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Every company wants a “strategic” product marketer, but not many know what that actually means. You can ship launch decks, update competitor comparison sheets, and still have zero influence on profit and loss.

Most product marketers are stuck in launch mode and never make it past messaging. Real product marketing starts after launch; when the market responds, when your GTM strategy gets tested, and when you have to adapt fast or get buried.

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Most email marketing courses still teach the easy part: sending campaigns, testing subject lines, and reading basic engagement metrics.

The harder part is building email into a channel that actually drives revenue. The latest email marketing data puts ROI at 10:1 to 36:1, with top-performing programs exceeding 50:1. Yet only 13% of teams use advanced personalization, despite 93% saying personalization improves leads or purchases.

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Product analytics is the process of using behavioral data to understand how people use a product, where they experience value, and what changes can improve activation, engagement, retention, and revenue.

That skill is becoming more important as analytics moves beyond static dashboards. Mixpanel’s 2026 State of Digital Analytics analyzed more than 22 billion user actions across eight industries and found that leading teams are increasingly using analytics to reduce time to value, identify friction, improve retention, and decide what to do next rather than simply report what happened.

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