Cohort 1 · Confidential Results · Used With Permission

Three brands.
From filtered out to cited.

Same playbook. Two YMYL categories. One pre-launch challenger. One founder-led outdoor brand. Each one invisible at intake. Each one cited by AI engines at exit.

60 daysAll results shown reflect the first ~60 days of engagement. The most substantial outcomes typically emerge after the full 6-month engagement.

Outdoor Gear · Founder-led DTC

Outdoor Vitals

A founder-led ultralight brand fighting for shelf space in a category the answer engines had already decided belonged to someone else.

Timeline · 11 days

Engines · ChatGPT · AI Mode · Perplexity

The Challenge

Invisible across all AI engines — 0 citations in a category controlled by Zpacks, Enlightened Equipment, and Gossamer Gear. When buyers asked AI for lightweight backpacking gear, the answer set was already written, and Outdoor Vitals wasn't in it.

The Strategy

The category incumbents had a decade of forum threads, gear reviews, and third-party validation feeding the models. We couldn't out-publish them — so we out-structured them. The thesis: the machines weren't rejecting the brand, they simply had nothing clean to cite.

We rebuilt the brand's content layer around the exact comparative questions buyers ask AI — weight, packability, four-season use, price-to-warmth — and made Outdoor Vitals the most extractable source on each one. Authority isn't volume; it's being the cleanest, most quotable answer to a specific question.

Implementation

Entity mapping & gap scan

Ran a 60-query × 3-engine baseline to map exactly which questions the brand was filtered out of and which competitors owned each answer slot.

Comparative answer pages

Built structured, citation-ready content for the high-intent comparison queries — explicit specs, plain-language verdicts, and machine-parseable schema.

Third-party validation seeding

Aligned reviews, spec sheets, and founder commentary so external validators reinforced the same entity facts the models needed to trust the brand.

Lessons Learned

Incumbency in AI answers is structural, not permanent — clean, extractable data can displace a decade of legacy content faster than anyone expects.
Winning a few high-intent comparison queries decisively beats thin coverage across hundreds of low-intent ones.
The fastest visibility gains came from formatting facts for extraction, not from publishing more articles.

The Results

AI Visibility at intake

34%

AI Visibility Score

In eleven days the brand went from zero presence to being cited in 22 of 60 monitored AI results — peaking at 80% visibility on its core lightweight-backpacking query. Same products, same founder. What changed was the content layer the machines read.

22 / 60

Results citing the brand

80%

Visibility · lightweight backpacking query

11 days

From invisible to cited

Eleven days from invisible to cited. Same brand. Same products. Same founder. What changed is the content layer the machines read.

AI Visibility — multi-query scan

At intake · May 80%

After 11 days · May 1934%

Best query · lightweight backpacking80%

Source · AEO.co Visibility Tracker · 20 queries × 3 engines

Menopause Telehealth · YMYL · DTC

Winona

A telehealth brand in a Your-Money-Your-Life category where AI engines apply their strictest trust filters — and were leaving Winona out of the answer.

Timeline · One cohort

Engines · ChatGPT · AI Mode · Perplexity

The Challenge

Filtered out of the answer set for menopause-care queries in a category dominated by Gennev, Midi Health, and Elektra Health. In YMYL health topics the engines demand the highest bar of trust signals, and Winona's clinical authority wasn't being read or surfaced.

The Strategy

YMYL categories reward demonstrable expertise and clinical trust over marketing language. We treated each AI engine as a separate channel with its own evidence threshold rather than chasing one generic visibility number.

The plan: surface Winona's medical credentials, treatment protocols, and clinician-reviewed content as structured, verifiable signals — then optimize channel by channel, starting where the brand could win the answer outright on Google AI Mode.

Implementation

Channel-by-channel baseline

Measured share of voice separately on ChatGPT, Google AI Mode, and Perplexity to find where authority signals converted to citations fastest.

Clinical trust layer

Restructured treatment and condition content with clinician attribution, sourcing, and schema the engines could verify as expert, trustworthy health information.

Query-level targeting

Prioritized high-stakes queries — HRT and premium menopause care — where owning the answer compounds across the whole category.

Lessons Learned

YMYL visibility is earned with verifiable expertise and trust signals, not persuasion copy.
Each engine weights evidence differently — treating them as one channel leaves the easiest wins on the table.
Dominating a few decisive clinical queries reset how the engines framed the entire category around the brand.

The Results

13%

AI Visibility at intake

50%

Share of Voice · Google AI Mode

In a single cohort Winona went from filtered out to 50% share of voice on Google AI Mode — a 5× lift over its ChatGPT baseline — and owned 100% of the answer on premium menopause queries. Channel-by-channel optimization, not a one-size-fits-all push, drove the gain.

5×

Lift vs. ChatGPT baseline

60%

Share of voice · HRT query

100%

Share of voice · premium menopause query

From filtered out to 50% share of voice on AI Mode in one cohort. Channel-by-channel optimization works.

Share of Voice — by channel & query

ChatGPT baseline10%

Google AI Mode · overall50%

AI Mode · HRT query60%

AI Mode · premium menopause100%

Source · AEO.co Visibility Tracker · Google AI Mode · Apr 30 2026

Prenatal & Fertility · CPG · Pre-launch

BabyRx

A pre-launch challenger with no audience, no backlinks, and no history — proving AEO rewards clean data over incumbency.

Timeline · 3 weeks

Engines · ChatGPT · AI Mode · Perplexity

The Challenge

Pre-launch challenger with zero citations in a category dominated by legacy giants — Ritual (21 GPT citations/week at peak), Naturemade, and Fullwell Fertility. With no traffic and no brand recognition, conventional wisdom said the engines would never surface BabyRx.

The Strategy

Without legacy authority, the only path was to give the models the single cleanest, most complete dataset in the category. We bet that AI citation favors structured, verifiable facts over brand age or audience size.

We engineered BabyRx's ingredient science, sourcing, and prenatal-safety information as the most extractable evidence available — designed to be the answer the moment an engine reached for a fact the incumbents hadn't structured well.

Implementation

Category citation map

Tracked GPT citations across incumbents to identify the factual gaps where even Ritual's coverage was thin or unstructured.

Evidence-first content build

Published ingredient, dosage, and safety data as clean, sourced, schema-rich content engineered for direct extraction by the engines.

Pre-launch authority seeding

Established consistent entity facts across every surface so the brand read as a credible, verifiable source before it had any sales history.

Lessons Learned

AEO doesn't reward incumbents — it rewards whoever gives the machines the cleanest, most verifiable data.
A pre-launch brand can win citations before it wins customers when its evidence layer is the strongest in the category.
Structured factual gaps in incumbent content are the fastest opening for a challenger to be cited.

The Results

GPT citations at intake

First

To earn GPT citations

In a three-week window the smallest, youngest brand in the category earned 6 GPT citations — outpacing established players Naturemade and Fullwell Fertility, who earned none — and hit 33% visibility on its best query. The engines rewarded the cleanest data, not the biggest name.

GPT citations in a 3-week window

33%

Best query visibility

Citations for Naturemade & Fullwell over the window

Smallest brand. Smallest audience. First to be cited. AEO doesn't reward incumbents — it rewards the brand that gives the machines the cleanest data.

GPT Citations — 3-week window vs. category

BabyRx (pre-launch)6

Fullwell Fertility0

Naturemade0

Ritual · category peak21

Source · AEO.co Citation Tracker · GPT · Apr 6 → Apr 18 2026

Results are confidential and used with permission. All data is from AEO.co citation and visibility trackers. Individual results will vary.

Three brands. From filtered out to cited.

Outdoor Vitals

Entity mapping & gap scan

Comparative answer pages

Third-party validation seeding

Winona

Channel-by-channel baseline

Clinical trust layer

Query-level targeting

BabyRx

Category citation map

Evidence-first content build

Pre-launch authority seeding

Three brands.
From filtered out to cited.