The AI Visibility Blind Spot Just Got Closed: What Stacker + Scrunch Means for Earned Media Strategy

By Jaxon Parrott, CEO of AuthorityTech

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When two platforms announce a strategic integration, the press release usually reads like corporate Mad Libs: "synergies," "best-in-class," "industry-leading." You skip to the second paragraph hoping for something concrete, find more buzzwords, then close the tab.

Last week's Stacker + Scrunch announcement is different. Not because the press release was particularly artful—it wasn't. But because it closes a visibility gap that's been hiding in plain sight since ChatGPT went mainstream: we've had no systematic way to measure how earned media actually influences AI search results.

Until now.

This isn't just another tool partnership. It's the first integrated solution that connects what brands distribute through third-party channels to what AI engines actually cite. If you're in PR, comms, or content strategy, this changes your measurement framework overnight.

Let me explain why this matters more than you might think.

The Visibility Blind Spot

Here's the problem Stacker + Scrunch solves:

What we could measure before:

• How many placements we secured
• Which outlets published our content
• Estimated reach/impressions
• Clicks and traffic (when attribution worked)

What we couldn't measure:

• How those placements influenced AI citations
• Which earned sources ChatGPT/Perplexity actually trust
• Whether third-party content strengthened our entity profile
• ROI of earned media on AI visibility

This gap created a strategic problem. Brands knew AI search was growing—daily users jumped from 14% to 29.2% in 2025 alone (HigherVisibility data). They knew earned media drove citations—95% of AI citations come from non-paid coverage (Muck Rack analysis).

But they couldn't connect the two. You'd secure a TechCrunch placement, cross your fingers, and hope it somehow translated to AI visibility. No tracking. No attribution. No feedback loop for optimizing future placements.

It's like running paid ads without conversion pixels. You know something is working, but you're blind to what, why, and how much.

Why Existing AI Visibility Tools Weren't Enough

To be fair, AI visibility platforms already existed: Otterly, Siftly, Goodie, AthenaHQ, and others. These tools track brand mentions across ChatGPT, Perplexity, Google AI Overviews, and Gemini.

They answer critical questions:

• When does our brand appear in AI answers?
• What queries trigger our citations?
• How do we compare to competitors?
• What sentiment do AI engines express about us?

But they all share the same limitation: they focus on owned content discovery.

These platforms excel at monitoring whether your website gets cited. Whether your blog posts appear in AI answers. Whether your product pages rank in AI search.

What they don't track—what they can't track without integration like Stacker + Scrunch—is how earned distribution through third-party publications influences those results.

When Forbes publishes an article featuring your brand, existing tools see the citation. But they can't tell you:

• Did that Forbes placement create the citation?
• How many additional queries now surface your brand?
• Which earned sources drive the highest AI visibility lift?
• What's the citation velocity from different publication tiers?

This is the blind spot. And it's massive.

What the Integration Actually Does

The Stacker + Scrunch partnership closes this loop by pairing two previously siloed capabilities:

Stacker side:

• Content distribution platform built for earned reach
• Tracks which stories get placed across third-party publishers
• Monitors where your brand-funded editorial content appears
• Provides placement data: outlet, date, URL, performance metrics

Scrunch side:

• AI search visibility tracking across ChatGPT, Perplexity, Google AI, Gemini
• Brand mention monitoring in AI-generated responses
• Citation frequency and sentiment analysis
• Competitive benchmarking for AI share of voice

Together:

• Direct attribution: "This TechCrunch placement increased AI citations by X%"
• Source analysis: "Forbes placements drive 3x more citations than tier-2 outlets"
• ROI measurement: "Earned media generated $Y in attributed AI-driven pipeline"
• Strategy optimization: "Focus future PR on outlets Z for maximum AI impact"

According to Stacker CEO Noah Greenberg, "AI search rewards credibility, and credibility is increasingly built outside your owned channels. By integrating Scrunch into Stacker, we are making offsite URL tracking and AI visibility insights real, usable, and scalable for customers."

Translation: you can finally answer the question every CMO asks about PR—what's the ROI?—with data instead of anecdotes.

Why This Is a Category-Defining Moment

Three things make this integration strategically significant:

1. It Validates Earned Media as a Measurable Growth Channel

For decades, PR suffered from the measurement problem. Unlike paid ads (direct attribution) or SEO (traffic + rankings), earned media relied on vanity metrics: impressions, AVE (advertising value equivalent), media tier designations.

These metrics never satisfied CFOs. "You secured a Forbes placement—so what? Did it generate pipeline?"

Most PR teams couldn't answer that question with data. So PR budgets stayed small, treated as "brand building" rather than demand generation.

Now, with earned media directly tied to AI visibility—and AI search driving purchase decisions at scale—PR becomes quantifiable:

• Input: Secure placement in TechCrunch
• Output: 340% increase in AI citations for "best [category] platforms"
• Outcome: 15 demo bookings attributed to AI-assisted discovery

Suddenly PR isn't soft. It's the highest-leverage channel for AI-era discoverability.

2. It Shifts Budget Allocation Logic

When you can measure that Forbes placements drive 3x more AI citations than tier-2 outlets, you stop treating all media coverage equally.

Traditional PR prioritizes:

• Volume (more placements = better)
• Prestige (WSJ > trade publication)
• Estimated reach (bigger audience = more value)

AI-informed PR prioritizes:

• Citation velocity (which outlets AI trusts most)
• Entity strengthening (which sources compound your authority profile)
• Query coverage (which placements expand your visibility footprint)

This fundamentally changes what "good PR" looks like. A single high-citation-velocity placement beats 10 low-impact ones. A trade publication that AI cites frequently outperforms a prestigious outlet AI ignores.

You optimize for AI trust signals, not journalist vanity or media kit logos.

3. It Creates a Feedback Loop for Content Strategy

Without attribution, you can't optimize. With it, you build systems.

Old workflow:

1. Create thought leadership content
2. Pitch to journalists
3. Secure placements
4. Hope it helps
5. Repeat

New workflow:

1. Create thought leadership content
2. Pitch to journalists
3. Secure placements
4. Measure AI citation lift within 7 days
5. Identify which angles/outlets drove highest impact
6. Double down on high-performance patterns
7. Optimize and repeat

This is the difference between tactics and systems. One produces random outcomes. The other compounds predictably.

Chris Andrew, Scrunch CEO, framed it perfectly: "There's a gap between knowing which sources impact visibility and the ability to grow your brand presence in said sources at scale. Together, Scrunch and Stacker close that loop by connecting AI search performance to earned brand presence, so teams can see what is driving authority and take action."

See → measure → optimize → compound. That's a system.

What This Means for Your 2026 Strategy

If you're still treating PR as "nice to have," you're about to get disrupted by competitors who don't.

The strategic shift:

Before (2024-25):

"We do PR for brand awareness and owned content for SEO."

Now (2026):

"We do PR because it's the highest-leverage driver of AI visibility, which determines whether buyers discover us."

PR isn't adjacent to growth. In the AI era, PR is the growth channel that determines whether you exist in the consideration set.

Immediate Actions

If you're responsible for brand visibility, here's what changes:

1. Audit your current earned media against AI citations

Which past placements actually drove AI visibility? Use Scrunch, Otterly, or Siftly to baseline where you stand. Then map recent earned coverage to citation lift. You'll discover which outlets AI trusts in your category.

2. Reallocate budget toward citation-velocity outlets

Stop treating all placements equally. A tier-2 trade publication that AI cites 50 times beats a tier-1 prestige outlet AI cites twice. Find your high-velocity sources and prioritize them ruthlessly.

3. Build systematic earned distribution, not episodic campaigns

AI citation rates peak within 7 days of publication, with 50%+ citations coming from content less than 12 months old. Sporadic PR campaigns don't compound. Consistent earned distribution does. Systems beat campaigns.

4. Create cite-worthy content anchors

Journalists need angles that add new information: original research, proprietary data, contrarian frameworks, market timing insights. Build your PR strategy around research-backed thought leadership, not generic product pitches.

5. Measure AI share of voice as your North Star

Forget AVE. Track: citation frequency, brand visibility score, competitive AI share of voice, sentiment in AI responses, source diversity. These metrics determine whether you win or lose in AI-assisted buyer journeys.

The Bigger Pattern This Reveals

Step back for a moment. What's actually happening here?

We're watching the convergence of three previously separate functions:

• PR (earned credibility)
• SEO (owned discoverability)
• Demand gen (attributed pipeline)

In the traditional stack, these lived in different teams with different KPIs. PR reported to brand. SEO reported to marketing. Demand gen owned revenue.

In the AI era, they collapse into one integrated system:

Earned media (PR) → Entity strengthening (SEO) → AI citations (demand gen)

The Stacker + Scrunch integration is the first platform architecture that mirrors this convergence. It's not PR software. It's not SEO software. It's not marketing attribution software.

It's AI visibility infrastructure—the connective tissue that links external credibility signals to measurable discovery outcomes.

This is what category creation looks like: not a new feature, but a new layer that didn't exist before.

What Comes Next

The integration rolls out in March 2026. Early adopters will have a 6–12 month advantage measuring and optimizing what competitors are still guessing at.

That window matters. AI engines update their models frequently. The brands that identify high-citation-velocity sources first will compound authority faster. By the time competitors catch up, the entity graph gap will be significant.

This isn't about adopting new software. It's about recognizing that visibility in 2026 is determined by systems that connect external credibility to AI trust signals.

If you're still measuring PR success by impressions and media tier, you're optimizing for a channel that no longer drives discovery.

If you're still treating earned media as unmeasurable brand building, you're leaving measurable growth on the table.

The blind spot just got closed. The question is whether you'll be early or late to act on it.

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Jaxon Parrott is CEO and Founder of AuthorityTech. We help B2B brands build measurable AI visibility through performance PR strategies. Check your AI visibility for free to see where you stand in AI search.