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.

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Brainstormed personas are obsolete. They’re slow to build, easy to forget, and completely disconnected from how people actually buy because they’re built on opinions, instead of data.

AI-built customer avatars replace guesswork with proof, pulling live buyer data and cross-checking insights across multiple AI models, evolving with every sale.

These systems define who to target, what to say, and how to win before a single ad goes live.

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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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Most product teams claim to be “data-driven.” Most are lying to themselves. They’re not driven by data; they’re driven by dashboards they don’t understand and metrics that don’t move the business.

The skill gap isn’t in collecting data or analytics tools; it’s in the ability to translate data into product growth.

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Become an AI native marketer

A six-week live cohort for marketers. Every week you build one AI native workflow you can use at work: a 90-minute live workshop on Tuesday, then you build it on your own data with us in the community, and demo it on Friday.

You don't need more AI tips. You need five working AI workflows. Starts 28 September.

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