Your Growth Problem Is Audience Similarity

Howdy readers 🥰

In this newsletter, you’ll find:

🛑 Stop Retargeting In Disguise

🔍 A 1,885-Page Study Just Challenged One of SEO's Favorite AI Visibility Tactics

🏆 Ad of the Day

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Together with Hubspot

Stay connected to the context that matters.

You have more tools than ever. So why does it feel like critical context is still missing? 

HubSpot's 2026 Essential Apps for Marketers collection brings together 14 apps across creative, ads, events, and more, so the context you need travels with every campaign, decision, and handoff.

🛑 Stop Retargeting In Disguise

The creator's audience is your targeting signal. Pick creators who look like your customers, and you cancel it.

Partnership ads work because the creator's audience does cold targeting for you. Most brands undo this by picking creators whose audiences look like people already buying. You think you're reaching new customers. You're hitting the same warm pool through a different face.

Strategy 1: Check If Your Creators Are Identity-Matched Or Adjacent

Three creators look different on camera. Their audiences look identical in the data. Which problem are you solving?

If three or more active creators share the same demo and niche, Meta is hitting the same cold pool through three different faces. A skincare buyer can be reached through a beauty creator, but the cold pool only opens when she's also reached through a home decor creator with a similar audience, or a parenting creator whose followers share her life stage but not her category.

The audit:

• Tag each creator by audience demo and niche
• Flag any group of three sharing both
• Map the gaps the group is missing

Strategy 2: Match On Psychographics, Not Category

The default move is finding creators in your category. It feels safe. It's why most programs hit the same ceiling within months.

Category-matched creators have audiences already in your file. Real growth comes from creators whose audiences share your buyer's life stage, income, or values but in a different niche.

The brief:

• Skip creators matching your file too closely
• Pick a shared life stage or values in different niches
• Test one adjacent-niche creator per identity-match

This is hard at volume. Insense gives you 80,000+ vetted creators with automated contracts and full usage rights, making adjacency sourcing doable at scale. You can book a free strategy call by May 22 and get a $200 platform credit towards your first campaign.

Strategy 3: Track New-Customer CPA Separately Per Creator Type

Blended CPA hides the answer. The adjacency wins in a number most teams that never split.

Pull new-customer CPA on its own, then tag each ad as identity-match or adjacency. Adjacency creators usually have lower new-customer CPAs even when identity-match creators look stronger on surface metrics, because identity-match creators reach people who'd have bought anyway.

The setup:

• Pull new-customer CPA per creator
• Tag each as identity-match or adjacency
• Move budget toward the gap

The advantage compounds only when audiences are different.

🔍 A 1,885-Page Study Just Challenged One of SEO's Favorite AI Visibility Tactics

JSON-LD schema is code embedded in pages to signal content structure to search engines. Ahrefs ran a controlled study across 1,885 pages to test whether adding it actually improves how often AI systems cite your content.

The Breakdown:

The 3x Gap Was Never Proof - AI-cited pages carry schema far more often than uncited ones. But those same pages also publish better content and build stronger backlinks. The association was always about site quality, not schema itself.

Numbers Across All Three Platforms Came Back Flat - AIO fell 4.6% against matched controls. AI Mode gained 2.4% and ChatGPT 2.2%, neither clearing the threshold for statistical significance across four separate tests.

The AIO Drop Is Smaller Than It Looks - Control pages were declining too before schema was introduced. The gap between groups amounted to around 12 fewer daily citations on pages already pulling hundreds.

These Pages Were Never a Fair Test - Every URL in the dataset had cleared 100+ AIO citations before the study began. Pages already visible to AI have little room to gain from structural markup.

AI systems, including ChatGPT, Claude, and Gemini, pulled only visible HTML during live fetches, skipping JSON-LD entirely. Schema still drives rich results and entity recognition. For citation volume on established pages, the data says it changes nothing.

🎥 Ad of the Day

What Works:

1. "Our ancestors'" is a tribal identity trigger, not a history claim. It signals belonging to a group of people who think critically about what they put in their bodies. The buyer self-selects before reading another word.

2. The dark moss environment does the "natural and ancient" storytelling, the copy doesn't need to. Forest floor, wet stone, ambient darkness, the set design communicates pre-industrial purity without a single ingredient callout or "all-natural" badge.

3. 13,000+ reviews placed bottom-right is a trust anchor timed perfectly. It appears after curiosity is already triggered by the headline. At that point, social proof doesn't create desire; it removes the last remaining friction before the click.

If your product format is unfamiliar, don't explain it, historicize it. Framing something as ancestral wisdom bypasses the "does this actually work" objection entirely and replaces it with "why did we ever stop using this." 

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