This week’s Field Notes is about aligning sales and SEO efforts.
This is one of those topics that has come up over and over through the years in various ways:
- How can we improve sales outcomes through our organic growth efforts?
- How can we leverage our sales team to inform content and SEO priorities?
- How can we ensure we’re reaching the right people through our organic channels?
I’ve long believed that one of the primary data inputs for effective SEO strategy comes from your sales team.
So this essay will address the synergistic relationship between sales and search.
Quote of the Week
“Go straight to the seat of intelligence.” – Marcus Aurelius
Field Notes
I was (relatively) early on a few things:
- Ice baths (way before Huberman came on the scene)
- Brand mentions and surround sound SEO
- Wearing a mustache and, briefly, a mullet (maybe this isn’t a trend everywhere, but take a walk around Bushwick…)
- Kava (ask me about my kava website)
- A cocktail of esoteric nootropics I won’t name here for liability reasons
Only one of those made me any money, but that’s neither here nor there.
The point isn’t clairvoyance, it’s pattern recognition.
I don’t believe trend spotting is a gift.
I think it’s a consequence of behavior.
I read voraciously (and very broadly). I listen to a frankly unhealthy number of podcasts. And I talk to a wide spectrum of people – agency leads, SEO strategists, musicians, landscape architects, cab drivers, strangers at the dog park – and I really listen.
Over time, patterns start to emerge. Fractal repetitions of ideas. The same phrase muttered in different rooms, possibly using different language but angling around the same themes.
One major benefit to this, from a marketing perspective, is you can get a tiny head start on trends that are about to break.
This is actually very meaningful, as the majority of marketers tend to index on easily available data, which causes a flight to the mediocre median (where the competition is highest, and the expected value of investment is quite low).
One can get major alpha from simply widening the aperture of data points, and though it may sound banal to you, by simply talking to prospects and customers.
We all know that abstractly; it’s the first tip on every MarTech blog listicle (KNOW YOUR CUSTOMER!)
Here, however, I want to walk through how this works in practice – merging insights from sales into effective organic growth strategy, leveraging SEO landing pads as signals for sales, and the emerging inventory for “sales enablement content” to be distributed by LLMs.
Effectively, you can build compounding feedback loops by moving your seat slightly closer to the sales org.
Let’s walk through the geometry of this new relationship.
The Accidental Intelligence Layer
I spend a lot of time on sales calls. Client calls too.
Every call is a data point in the market’s subconscious.
A prospect blurts out their frustration with a migration or a past agency. Another mutters a hesitant “we don’t know how LLMs will affect our roadmap.” Someone else worries about onboarding a dozen SEO contractors across a fractured brand portfolio.
None of these questions show up in Ahrefs. They don’t have search volume …yet. But they’re the real stuff.
So I record every call. I use Day.ai, but there are several personal productivity tools out there like Granola, Fireflies, etc. as well as platforms like Gong and Chorus that most mature B2B organizations are using.
I take the transcript and feed them into an AI workflow I built, and watch as patterns emerge across conversations. I couple this with more anecdotal data points, such as VC dinners, coffees and lunches, canaries on Slack and LinkedIn, and sometimes just pure frequencies transmitted to my subconscious.
This helps me identify trends early – for example, the macro-trend of generative engine optimization (which, to be fair, was easy to spot), as well as micro-trends or questions within broader themes (questions popping up now: attribution in the AI era, how to plan content outside of keyword research, and on a meta level, how to incorporate sales insights into SEO).
Then I build roadmaps that include pages with zero detectable search demand. Not because a tool says so, but because the people with budgets are saying so. It’s often how I come up with talk tracks for webinars or podcasts. It’s the fuel for all of our Kitchen Side episodes, and most of these Field Notes (why do you think we called it Field Notes?!)
And the results can feel paradoxical, at least to a data-driven mind, apprehensive to make decisions without a soothing data point to back it up.
One client of ours – I hate to say it – has been losing traffic to their site. Even though we’ve talked a lot about the traffic trap, and this is a common trend across sites, it’s still never fun to report. By traditional SEO metrics, this is bad. But conversions continued growing every month.
Half the pages driving those conversions had no discernible search volume. They existed only because sales reps were tired of improvising answers to the same questions. CS teams wanted somewhere canonical to point customers. The content was not made for merely to adhere to an Ahrefs export. It was made for humans.
And because of that, it worked — both as landing pads for buyers and as ammunition for sales. It’s also playing incredibly well into LLM visibility (more on that later).
The ICP Honeypot
There’s another, more subtle benefit to aligning content efforts closely with sales intelligence.
When you mine sales calls for questions, you’re not just getting ideas for blog posts. You’re building what one could cheekily call an ICP honeypot.
Every question a buyer asks is an arrow pointing to their intent. When you write content in their own phrasing, you create an asset that resonates with a very particular type of person – definitely, your ICP (as they are qualified through your sales conversations). You publish this on, say LinkedIn, and prospects then see themselves in it.
This creates a feedback loop:
- Sales hears the pain.
- Marketing articulates it publicly.
- ICPs recognize themselves and respond.
- More of those ICPs show up in the comments.
- Marketing gets more comments, feedback, and ideas directly from the ICP.
The cycle repeats.
What we do is pull sales and client transcripts through an AirOps workflow that tees up LinkedIn posts. It’s great – prospects ask questions, things they really, really care about. Writer’s block? Nah. Not when you have a semi-automated workflow that gives you pain points as writing prompts.
The ideas that resonate more broadly, hitting some threshold effect on social, can then be repurposed into more evergreen assets like sales enablement materials, long form content and essays, or webinars.
A New Organic Slot Machine
Let’s say any action or investment represents a metaphorical slot machine.
You pulled the lever and there’s some probability of reward, and some associated magnitude of reward.
Paid acquisition, particularly Google search ads, represent a probability that is relatively transparent. One can model out CAC and ROAS over time with a pretty good degree of accuracy.
SEO ten years ago was also relatively modelable, though more external variables were present. Still, you could pull a lever (write a page, build some links, rank, profit) and some coins would typically fall out.
Let’s consider now a different investment: sales enablement content.
Certainly, if your sales team asks for an ebook over and over again, one could assume there’s a commensurate amount of reward and high probability of reward. But otherwise, where does one distribute this content? It doesn’t fly viral on social media; there’s no search volume for it. Cob webs grew on this slot machine, until….
That’s right, LLMs.
I’m not sure if there’s good data on this, but many people have anecdotally come to the consensus that the way we use LLMs is slightly different than classic search.
In the LLM era, users don’t compress their needs into a two-word query and sift through links. They ask the long, oddly specific question they actually have.
They type the full objection they would’ve given to a sales rep. They self-qualify through personal and firmographic disclosure, and sometimes they attach contexts documents to their queries. Memory and personalization are at play.
In other words, highly specific pages now have, at least theoretically, distribution mechanisms through new inventory, which means there’s an incentive to index more heavily on these nascent and specific sales questions.
Especially because, if you consider the past few decades of SEO, there’s a dearth of this type of content. There are a million ultimate guides to SEO, very few talking esoteric things that come up on your sales calls.
A Quick Note on AI Attribution
Attribution is hard. It was hard before AI tools, and it’s even harder now. Yes, you can track referral traffic from ChatGPT, but that’s a tiny fraction of its influence.
You can track brand visibility against prompts, but the question then becomes, “what prompts do I track?”
You could blindly trust the companies that purport to have “prompt volume,” or you could get phrases from your actual customers. Yes, again, we turn to our sales team.
We’ve previously mentioned that self-reported attribution is important in this era, often showing a massive delta in the amount of leads coming from AI tools when compared to click-based web analytics.
The next step is to ask, on your discovery call, what prompts or questions a prospect used to find you.
I do this every time someone mentions they found us in ChatGPT. Sometimes they even share their screen and show me the thread.
Guess what? I turn right back around and create content, if it doesn’t already exist, that answers the questions and dimensions they tell me they were looking for. It’s this sort of feedback loop that ties together lead attribution and the qualitative data that can fuel smarter, more resonant content creation.
How to Collect Sales Intelligence (Even if You’re Not in Sales)
I’m privileged (and overworked) because I both sit on sales calls and create the content over here. So there’s no real baton passing.
Not everyone sits on sales calls. I get that.
But here’s the hierarchy of proximity:
- Best: Listen directly to sales or CS calls. Use Gong, Chorus, Fireflies, or whatever your org prefers. Bonus if you build a system to pattern match at scale.
- Great: Interview your sales team. Ask them:
- “What questions keep coming up?”
- “What objections slow down deals?”
- “What metaphors or stories help land the pitch?”
- Good: Analyze CRM notes, HubSpot contact timelines, and page journeys. See what people looked at before they booked the demo.
- Minimum: Ask your support team what gets copy-pasted into emails every day. That’s your FAQ page, but better.
You can also interview customers yourself. Not many SEOs do it. But it’s great practice and you get a lot of embedded insights that aren’t obvious from mere transcripts. Tone of voice, body language, emotion, etc.
We’ve mentioned before that modern SEOs should resemble product managers, and one dimension of that is closer proximity to customers.
Geometry of Alignment
Sales and SEO look different on the surface. One happens live, in the room, in real time. The other happens in advance, asynchronously, mediated by an algorithm.
But both are functions of relevance. Both try to answer the same question: what does this person need right now?
The real opportunity is when those answers align. When the content someone reads before the call sounds like the conversation they have during it. When the landing pad doubles as a sales accelerant. When the roadmap is written not only from a keyword report but from the objections that actually stall deals.
This is the geometry of alignment:
- Sales provides the angle.
- SEO shapes the arc.
- LLMs close the curve.
And when it works, the buyer feels as if they’ve already arrived before they’ve even booked the demo.
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