
Last Updated on February 3, 2025
First, let’s talk about the deleterious effects of architecting an organic growth strategy without a “boots on the ground” view of your ICP and how modern SEO works.
We’ve talked a lot here about the “traffic trap” – the hamster wheel of chasing illusory wins and vanity traffic growth at the expense of auditing performance and driving meaningful business results with SEO and content.
If you’re unfamiliar, I’ll reiterate that traffic (or impressions or awareness) is, tautologically, necessary for demand, conversions, and revenue. But in far too many cases, it’s divorced from paired metrics, or even a feasible stretch of logic, it is completely irrelevant to what a potential buyer would care about.
You know the playbook: mine high MSV keywords, publish articles, build links, and watch the clicks roll in. But here’s the problem: traffic isn’t a business outcome unless you’re selling ad slots.
We had Mark Lindquist on the podcast recently, who told a story about when he worked with a business obsessed with growing traffic. Their directive was clear: more visits, no matter the cost. The result was a bloated content library optimized for high-volume, low-relevance keywords. It looked good on dashboards but had almost no impact on leads or revenue. They had fallen into the traffic trap—solving for a vanity metric instead of solving for their customers.
In some sense, I believe the root cause of the traffic trap is a miscalibration of strategy and the market (as well as an unwillingness to confront that reality, especially with solid telemetry and accountability from marketing leadership).
Contrast this with a calibrated content strategy, which starts with customer pain points and works backward.
At Omniscient, we’ve developed a trifecta for aligning content with reality:
- Start with customer insight: Conduct interviews, analyze sales calls, and understand your ICP’s challenges.
- Map content to your product or service: If your content doesn’t solve a problem your product can address, it may attract the right audience and be great brand marketing, but won’t fall within a reasonable time window for performance. Not bad necessarily, but non-ideal.
- Use channel data to prioritize distribution: Keyword research and channel optimization come last—not first.
Another related angle here is content quality, which hamstrings growth teams’ execution through endless debate and murky definitions.
Content quality isn’t entirely subjective (nor is it universal). Let’s just make it simple and say it is about utility. Does your content solve the problem your audience came to address? If not, it doesn’t matter how well it’s written or how many backlinks it has.
One common misconception is that quality equals length—like the idea that every blog needs to be a 5,000-word Brian Dean-style epic. But quality, properly defined, is about alignment with user intent. Whether it’s a 500-word how-to guide or an interactive calculator, the litmus test is the same: did it serve its purpose?
AI & Future Bets: Doing Beats Debating
AI has become the Rorschach test of our time: people see what they want to see.
On one side, you have the fearmongers predicting the demise of jobs, creativity, and humanity itself. On the other, you have opportunists hawking courses on how to “leverage AI” without ever building anything themselves.
At Omniscient, we try our best to avoid both extremes (as well as long arch predictions). Instead, we use AI tools like Clay, Perplexity, Day, and GPTs to solve tangible business problems:
- Automating repetitive tasks: Clay helps us enrich outreach data, saving hours of manual work.
- Extracting insights at scale: Custom GPTs + Python + Day turn sales call transcripts into actionable content ideas.
- Augmenting research: Perplexity speeds up top-level research, helping us contextualize industries quickly.
We’re not focused on where AI will be in 2027 or whether it will “kill” search. Instead, we’re focused on where it adds value today. That’s the key: ship first, theorize second.
For instance, while others debated the limitations of ChatGPT, we were building tools to extract voice-of-customer insights from sales calls and surface patterns that informed both messaging and product development. These projects didn’t require endless pontification—just curiosity, experimentation, and iteration.
Case in point, both David and I – co-founders at Omniscient with many other things to do – are actively taking courses on how to build and deploy AI-centric apps in order to better understand the real business utility.
Here’s my take: if you’re going to have an opinion about AI, base it on something you’ve built. Solve real problems. Experiment. Calibrate your perspective to what the tools can actually do—not what you imagine they might or might never be able to do.
Customer Research: The Only “Shortcut” That Works
If there’s one consistent lesson I’ve learned in every role I’ve had, it’s this: talking to customers solves almost everything.
At CXL, my content and product strategies were informed an obsession with experimentation and the industry. I attended conferences, mingled in lobby bars, and ran user surveys to understand the challenges faced by the experimentation industry. I read the comments section of blogs and responses to our email newsletter. I took courses. I ran experiments myself.
This hands-on immersion was the foundation for building both our content marketing strategy as well as, upon launch, CXL Institute’s data-driven user personas, which guided everything from messaging to product development.
Recently at Omniscient, we embarked on a project to interview 35-40 marketing leaders, expecting to hear certain themes like attribution challenges and ROI concerns.
Those were there, but we stumbled on surprises, too, like the fact that content production remains a pain point for startups and enterprises alike. Even with tools like ChatGPT, the ability to ship high-quality, high-performance content consistently is still elusive.
We wouldn’t have really understood the depth and importance of that problem by reading LinkedIn posts, only through actual customer / prospect interviews.
Why do so many companies skip this step? Because customer research is messy, time-consuming, and inherently unscalable. But it’s also irreplaceable. Here’s how you can start:
- Analyze conversations: Use Gong or Chorus to mine sales calls for patterns.
- Run surveys and interviews: Even informal conversations can yield gold.
- Immerse yourself in communities: Forums, Slack groups, and social platforms often reveal insights no survey can.
The closer you get to your customers, the clearer their problems—and the solutions you need to provide—become.
Leadership: Get in the Trenches & Lead from the Front
There’s a popular piece of advice in management circles: “Hire great people and get out of their way.” It’s not wrong, but it’s incomplete. Great leaders don’t just delegate—they immerse themselves in the details when it counts.
At Omniscient, I’ve found that working alongside my team on experimental projects provides clarity and focus. Whether it’s testing a new content framework or launching an unproven growth tactic, being in the trenches allows me to feel the market’s pulse and identify what works.
This isn’t about micromanagement—it’s about calibration. Leaders who detach from the day-to-day risk becoming like Robert Moses, the urban planner described in The Power Broker:
“He was making plans based on beliefs that were not true anymore.”
That’s the danger of leading from the back seat. Whether it’s content strategy, product development, or team management, you need to feel the friction to guide effectively.
The balance is subtle but crucial: trust your team enough to give them autonomy, but stay close enough to understand the nuances of the work.
Closing Thoughts
Calibration is the difference between good strategy and great outcomes. It’s the art of aligning with reality—through customer conversations, hands-on experimentation, and the humility to challenge your assumptions.
Robert Caro’s account of Robert Moses serves as a warning: don’t design highways without driving them. Similarly, don’t build strategies without immersing yourself in the realities of your audience, tools, and team.
Talk to your customers. Test your assumptions. Experiment with new tools. Get your hands dirty.
Let me know how you’re calibrating your strategies—I’d love to hear your story.
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