The host argues that AI's highest-value role is not merely replacing a person for one content asset. It lets a human team multiply its output across many narrowly defined audiences while preserving audience-specific pains, KPIs, and messages.

Use AI to multiply human output rather than only replace labor
Create distinct content for each micro audience
Base personalization on specific pains and emerging KPIs
Move from one broad ICP campaign to many tailored campaigns
Keep the ICP as the foundation for all smaller segments

“I can have human plus AI create a hundred videos for a hundred micro audiences versus how it works today, create one video for a…”
22:30

“So your ideal customer profile is your foundational audience, and you break that into micro audiences, and then you use AI to personalize your marketing…”
22:30

#human plus ai#content scale#personalization#future of marketing

Explainer· 5

Explainer01:00

Why AI Makes Micro-Audience Marketing Economically Viable

Traditional B2B marketing targets broad ideal customer profiles because serving smaller groups requires too much human labor. AI changes the economics by helping marketers identify, research, and create tailored assets for many smaller audience segments at scale.

Traditional campaigns need audiences large enough to justify dedicated marketers
AI reduces the labor required to serve narrowly defined groups
Micro audiences enable more personalized messages and campaigns
Human-plus-AI teams can produce many tailored assets instead of one generic asset

“Now, the thing that AI allows you to do is to market to what I call microversions of that audience in a more personalized way.”
01:30

“AI allows you to have a huge marketing team without ever having to hire a lot of marketers.”
08:00

#ai marketing#micro audiences#personalization#b2b

Explainer05:00

Build a Current ICP from Internal and External Evidence

The episode demonstrates creating an ideal customer profile by combining recent internal documents with external market evidence. The resulting profile covers buyer roles, success metrics, pains, competitors, differentiators, and exclusion criteria that can seed later audience research.

Prioritize recently edited internal customer documents
Use analyst reports, job listings, technology stacks, funding signals, and community discussions
Capture buyer success metrics and typical pain points
Define exclusion flags to avoid irrelevant prospects
Review and refine questionable AI-generated conclusions

“prioritize the 10 most recently edited files because you want them to be most up to date.”
05:00

“Then I look at external resources, things like analyst reports, things like LinkedIn jobs, things like tech stacks, things like funding signals, things like community…”
05:30

#ideal customer profile#customer research#b2b marketing#data

Explainer09:00

Use Job Ads to Discover Emerging Buyer KPIs

LinkedIn job advertisements reveal metrics that companies are newly assigning to relevant buyer roles. Comparing those phrases with an ICP's established KPIs surfaces emerging needs that conventional positioning may not yet address.

Start with buyer roles and baseline KPIs from the ICP
Search for companies hiring people in those roles
Extract metrics absent from the baseline KPI list
Treat repeated new metrics as evidence of an emerging need
Use the new KPI language to shape tailored positioning

“I am purposely going after new Ryzen phrases, things that we would not have thought of before that are going to be in these LinkedIn…”
09:30

“In this example, what it's doing is looking for mentions of new metrics they're accountable for that we may not have seen before, right?”
11:30

#intent signals#linkedin jobs#kpis#buyer research

Explainer12:00

Score KPI Clusters by Intent and Company Fit

Companies mentioning the same emerging KPI can be grouped into a micro audience. The number of companies sharing that signal indicates intent strength, while employee count or market tier provides a separate measure of customer fit.

Cluster companies by a shared new metric
Use signal frequency as a simple intent indicator
Treat five or more matching companies as a high-intent example
Score customer fit separately from intent
Prioritize clusters that combine strong intent with suitable company characteristics

“And then I have a simple score that is an intent and fit score.”
12:00

“And the fit is basically, you know, are they SB at mid-market? It's just employee count.”
12:30

#lead scoring#intent#segmentation#kpis

Explainer21:00

Find Prospects Through Complementary Tool Stacks

Technology combinations can provide another micro-audience signal beyond KPIs. The example targets companies using Calendly and Slack but not HubSpot, creating a segment whose existing stack supports a more specific integration or consolidation message.

Look for complementary technologies commonly used with your product
Exclude companies already using the product being marketed
Group firms with the same stack pattern
Tailor the campaign to the tools already in place
Use stack evidence as a practical fit and intent signal

“And what it would do is find firms that have two complementary tools.”
21:30

“I could use that to do a micro audience on just companies that have Calendly and Slack and no HubSpot.”
21:30

#tech stack#prospecting#intent signals#segmentation

Story· 1

Story14:00

How Three Job Ads Became a Pipeline-Velocity Campaign

The demonstration identifies three mid-market companies whose recent job advertisements mention lead prioritization and pipeline velocity. Perplexity Labs converts that shared signal into a named audience with a pain statement, product hook, campaign suggestion, and intent score.

Three companies shared a recent KPI signal
The cluster was named pipeline velocity optimizers
The inferred pain involved unqualified leads and slow pipeline movement
The cluster received a three-out-of-five intent score
The output included a suggested tailored campaign

“These pipeline velocity optimizers. Three mid-market companies posted job ads in the last 45 days.”
14:00

“It started to create micro audiences around these new Ryzen KPIs that people are being held accountable for.”
15:00

#pipeline velocity#job ads#campaign example#hubspot

Tool· 3

Tool03:30

Perplexity Labs as a Multi-Step Marketing Workbench

Perplexity Labs can combine web research, document analysis, and code execution within a single task. Its multi-chain workflow makes it useful as a lightweight marketing team capable of completing connected research and production tasks.

Perplexity Labs requires a Perplexity Pro account
It can chain research, document analysis, and code execution
Spaces organize related work like projects
A single prompt can coordinate several kinds of task

“Perplexity labs is like a workbench version of Perplexity.”
03:30

“It can do lots of different tasks all from a singular prompt.”
04:00

#perplexity labs#ai tools#marketing automation

Tool13:30

Turn Audience Research into a Micro-Audience Card

The research output is condensed into a practical card that marketers can pass to another AI assistant. Each card names the cluster and records its signal, pain, sales hook, and suggested campaign so research can flow directly into execution.

Give each cluster a memorable marketing name
Record the observable intent signal
State the audience's core pain
Connect the product to a relevant hook
Recommend a campaign suited to the cluster

“It has a micro audience card format.”
13:30

“You have a signal, you have a pain, you have a hook, and you have a suggested marketing campaign that you'll run to them.”
13:30

#audience segmentation#campaign planning#marketing operations

Tool20:00

Two Controls That Expand or Narrow a Micro Audience

The number of matching companies can be tuned through the job-ad lookback window and the size of the KPI phrase seed list. Longer time windows and broader phrase lists increase reach, while shorter windows and tighter seeds preserve recency and specificity.

Adjust the job-ad lookback beyond 45 days to find more companies
Expand from a small KPI seed list to dozens of related phrases
Ask the AI to return newly discovered KPI phrases
Cluster companies by each expanded phrase
Balance audience volume against signal freshness

“So you could obviously go back 90 days, 180 days, a whole year would actually give you a lot more companies.”
20:00

“So the number of days since the job ad has been posted and the number of key phrases in that seed list, these kind of…”
21:00

#audience sizing#kpi research#linkedin#segmentation

Takeaway· 2

Takeaway06:30

Treat Shared AI Prompts as Lego Blocks, Not Finished Products

The host cautions against copying prompts unchanged. Shared prompts should provide a starting structure that marketers adapt to their own company, data, audience, and goals.

Do not assume a shared prompt fits every business
Copy useful components rather than treating the whole prompt as final
Edit and refine prompts around your own needs
Use generated outputs as drafts that still require judgment

“Everything I share is not meant to be for copy and paste. They're meant to be for build-in blocks.”
06:30

“I think of AI in some ways like Lego blocks.”
06:30

#prompting#ai workflow#customization

Takeaway18:00

Use a Separate Prompt for Every Campaign Asset

A single multi-asset prompt can demonstrate an entire campaign but usually sacrifices output quality. For production work, the host recommends a dedicated prompt for each carousel, email sequence, landing page, or video, supported by asset-specific style instructions.

Use multi-asset prompts primarily for demonstrations or rough drafts
Give each production asset its own dedicated prompt
Add style guidance for the specific format
Teach the AI how to create each asset well
Retain shared audience context across the individual prompts

“I would have a separate prompt per campaign asset.”
18:00

“When you try to stitch in multiple asks, like create this asset, this asset, and this asset, and we'll not do a good job.”
18:00

#prompt design#campaign assets#content production

Frameworks in this episode

AI Building-Block Prompting Model

AI Micro-Audience Marketing Playbook

Evidence-Synthesized Ideal Customer Profile

Micro-Audience Campaign Kit

Micro-Audience Hunt Expansion Controls

Micro-Audience Intent and Fit Scorecard

Novel-KPI Micro-Audience Hunt

Stack Synergy Signal Hunt

Insights & moments

◆Hot Take· 1

The Future Is 100 Tailored Videos, Not One Generic Video

✶Explainer· 5