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How to see through space and time

You have twenty customer interviews. Three hundred survey responses. Sales calls. Support tickets. Battlecards.

Enough raw data to build a category-defining message.

Yet, it still takes three weeks to synthesize, and no one onws the process.

By the time you've pulled the "insights," two competitors have repositioned and your narrative already needs work to stand out.

So you try the shortcut. Dump it all into ChatGPT. Ninety seconds later you have clusters, themes, and pain points.

But nothing you can trust to actually write copy that converts.

AI organized your data. It didn't help you understand it.

Here's what I realized working with 50+ B2B SaaS companies: the teams with messaging that resonates don't have "more research." They have 3D empathy—they can hold three realities at once without losing clarity:

Internal reality: what you can actually deliver and how you communicate it internally.

External reality: how buyers think and decide before they know youand after they buy from you.

Market reality: the language competitors use and the moves they make.

And AI can help you build that empathy fast—when you use the right way.

AI as an inpout machine

Most B2B SaaS teams practice one-dimensional empathy.

They either go deep on customer research but ignore what their product team can actually deliver.

Or they track competitors religiously but don't understand why their own customers chose them in the first place.

Or they're drowning in internal strategy decks but haven't talked to a customer in six months.

One dimension empathy just risks being confirmation bias.

I learned this the hard way—not in marketing, but in industrial automation.

For ten years I programmed assembly machines for biomedical factories. I'd stand in the workshop between three simultaneous conversations:

On one side, our electrician explaining why the sensor placement wouldn't work. On the other, the mechanical engineer asking my software to patch the design tradeoffs they had to make. And on another, my laptop showing the client's email demanding faster cycle times.

I couldn't optimize for one without understanding all three.

When I moved to copywriting, I realized the same skill applies to messaging.

3D empathy is night vision for decisions. It's what Bob Moesta calls the ability to "see around corners and through space and time." (get his book “Learning to build” btw, it’s great)

This is where AI becomes powerful—not as an output machine that writes your copy, but as an input machine that helps you develop 3D empathy at scale.

The system I use with clients (the PATH Framework) works like this:

P — Prepare: Feed AI curated research—customer interviews, sales transcripts, support tickets, competitive intel, internal team feedback. The vivid, emotional moments where people reveal what they actually care about.

Focus on emotion and decision-making dynamics, especially within their teams, over pure demographics. Capture hesitation, urgency, relief, and the progress they want to make.

A — Articulate: Use AI to build a synthetic persona grounded in that data. You can lierally train AI to become that persona, so you can interview it across all three dimensions.

Is it 100% realistic? No. But it's directionally 70% accurate—close enough to make better decisions faster, then validate with real customers.

T — Test: Time to play! Interview your synthetic persona with questions that gauge each dimension:

External reality:

• "What would make you delay this decision, even if everything looked good on paper?"
• "Walk me through your buying committee. What does each person care about most?"
• "Tell me about a time you bought something similar and regretted it. What happened?"

Market reality:

• "Why would you choose [Competitor X] over us?"
• "If you removed our logo from our website, could this be any of our competitors?"
• "We say we're different because of [X]. Does that matter to you? Why or why not?"

Internal reality:

• "How long do you expect implementation to take? What does that process look like in your mind?"
• "If we told you this integration takes 6 weeks instead of 2, how does that change things?"
• "When something breaks, what's your expectation for response time?"

Cross-dimensional tests:

• "You said ease of use matters most. Three of your alternatives make the same claim. How do you decide?"
• "Sales told you implementation takes 2 weeks. Our product team says 6. How does that change your timeline?"
• "Your champion loves our product (external). Your CFO is asking about security compliance we don't have yet (internal). Competitor X just got SOC 2 certified (market). How does this decision play out?"

These questions reveal gaps—between what you're promising and what buyers expect, between your positioning and competitive reality, between buyer timelines and delivery constraints.

Most teams never surface these gaps until a deal falls through or a customer churns.

H — Harmonize: Validate with real customers. Pick one specific insight from your synthetic persona testing. Test it with a small sample:

• Send an email addressing that fear directly
• Show homepage copy to recent customers
• Run it by your sales team

Ask: “Does this resonate? Which message is better? Why?” Not "do they like it"

If outputs don't match reality, go back. Maybe you fed it the wrong data. Maybe market conditions shifted.

With AI and this 3d empathy perspective, you can spot the mismatches between what you promise and what you deliver. The gaps between how you position and how competitors position. The objections hiding in buying committees that never surface on sales calls.

And you create messaging that resonates because you've tested it from all three angles before you ship it.

Start here: the 3D empathy smoke test

Want to pressure-test whether you're actually practicing 3D empathy?

Pick one claim you're currently making. Something on your homepage, in your pitch deck, or in your sales messaging.

Now ask yourself:

Internal reality:

• Can our product deliver on this promise today?
• Does our team believe this claim, or do they hedge when talking to prospects?

External reality:

• When was the last time a customer used this exact language to describe our value?
• What objection comes up most often when we make this claim?

Market reality:

• How many competitors make a nearly identical claim?
• Could this claim belong to any of our competitors if we removed our logo?

Most teams can't answer all six questions with specificity.

That gap—between what you think you know and what you can prove across all three dimensions—is likely where your messaging needs work.

If you're ready to build this level of systematic empathy into your messaging process, let's talk.

DISCOVERY

Messaging lessons from obsessively generous customer service

I've been a fan and customer of True Classic t-shirts for a while and when I heard their founder talk about how they do customer service, I saw the light. Here I wrote a few lessons I'm taking from it into my messaging and copy work.

Context is everything, learn how to use it

I've been saying how much context engineering matters in order to produce anything good with AI, and this video by Tiago Forte gives you a very clear deep dive into how to structure it properly.

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RESONANCE

The Tao Te Ching

Have a great weekend!

Cheers,

Chris

Chris Silvestri Founder & conversion alchemist

🙌🏻 Let’s be friends (unless you’re a stalker)

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