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The Proof Center

Measurable authority.
Documented outcomes.

Every claim on this page is backed by client data from real PearlOS engagements. These are not satisfaction scores. They are measurable changes in AI authority — tracked from Day 1 through Day 90 and beyond.

3.2×
avg. AI recommendation increase
47 days
avg. to first AI citation
94%
avg. Knowledge Graph completion
Results dashboard
Results metrics
Performance Dashboard

Across all active engagements.
Averaged at 90 days.

3.2×
Average increase in AI recommendation frequency
across all active engagements
47
Average days to first measurable AI citation
from PearlOS activation
94%
Average Knowledge Graph completion score
at 90-day mark
6
AI engines monitored per engagement
ChatGPT, Perplexity, Gemini, Claude, Copilot, AI Overviews
+68
Average Authority Score point gain
from baseline to 90-day review
340%
Average AI Share of Voice growth
within primary service category
Authority Score — Typical Progression

From baseline to competitive
authority in 90 days.

Authority Score is a 0–100 composite metric measured at engagement start, Day 30, Day 60, and Day 90. Most clients enter with a score between 18–35. The 90-day average across all engagements is 86.

Day 0 (avg.)
27
Day 30
51
Day 60
72
Day 90
86
96%
Entity Verification
94%
Knowledge Graph Completion
91%
Citation Accuracy
89%
Schema Coverage

All metrics represent averages across HeyPearl client engagements at the 90-day mark. Individual results vary by market, category, and engagement scope.

Featured Case Studies

Real clients.
Documented outcomes.

Client details are anonymized by request. Market context and results are real.

Case Study 01·Luxury Real Estate AgentSeattle, WA·Independent Agent
Timeline: 90 days
The Challenge

A 12-year veteran with 200+ five-star reviews had zero AI presence. Buyers asking AI who to call for luxury properties in Seattle got three competitor names — never hers. She learned about the gap when a client told her they almost called someone else first.

The Solution

PearlOS built her entity architecture from scratch: a verified Knowledge Graph record, six Authority Pages targeting luxury buyer queries by neighborhood, and GEO content engineered around the exact prompts her buyers were using.

Modules Used
Authority PagesKnowledge GraphGEO EngineAI Visibility
Measured Results
14
buyer queries now surface her as primary recommendation
0→1
movement from invisible to top AI citation in her specialty
61
days from activation to first consistent AI recommendation

"I had no idea the gap existed. Now I know exactly where I stand — and so does AI."

Luxury Real Estate Agent, Seattle, WA
Case Study 02·Independent BrokerageAustin, TX·Brokerage Brand
Timeline: 90 days
The Challenge

The brokerage had 22 agents, strong local reputation, and active social presence. But when buyers asked AI which brokerage to trust in Austin, the AI named four competitors and never mentioned their brand. Individual agents were occasionally cited — the brokerage entity itself was invisible.

The Solution

Full PearlOS engagement: brokerage-level entity architecture, hierarchical agent connections, brand-level Authority Pages for every major Austin neighborhood, and GEO content targeting "best brokerage in Austin" category queries.

Modules Used
Authority PagesAuthority ScoreKnowledge GraphAI VisibilityGEO Engine
Measured Results
#1
AI-cited brokerage in Austin across all 6 engines tested
88
Authority Score at 90-day mark (from 31 at baseline)
4.1×
increase in AI recommendation frequency vs. pre-engagement

"We went from invisible to the most-cited brokerage in our city. That's not a small thing."

Independent Brokerage, Austin, TX
Case Study 03·Real Estate TeamScottsdale, AZ·Team Structure
Timeline: 75 days
The Challenge

An 8-agent team had strong individual agent profiles but no unified team brand in AI search. When buyers asked AI about the team by name, they got inconsistent descriptions — sometimes individual agents, sometimes nothing. The team's specialization in luxury new construction was completely absent from AI answers.

The Solution

Hierarchical entity build: team brand as the primary entity, individual agents as verified sub-entities. Specialty Authority Pages for luxury new construction. GEO content targeting buyer queries around new development communities.

Modules Used
Knowledge GraphAuthority PagesAI VisibilityGEO Engine
Measured Results
increase in AI recommendation frequency across all monitored queries
100%
entity accuracy — AI engines now describe the team correctly
29
distinct buyer queries where team is now the primary recommendation

"Our team's specialty is now what AI leads with. That's the positioning we've always wanted."

Real Estate Team, Scottsdale, AZ
Before vs. After

What changes.
What stays the same.

Before PearlOS

AI engines cannot confidently identify or categorize the business

Buyer queries in the primary market return competitor names

Entity signals are inconsistent across citation sources

No measurement of AI recommendation frequency

Authority compounds for competitors while yours stagnates

AI visibility loss is silent — you find out when leads drop

After 90 Days

Verified entity — correctly categorized across all six AI engines

Named as primary recommendation in 14–29+ tracked buyer queries

Knowledge Graph complete, NAP consistent, schema active

AI Visibility monitoring running — changes detected within the cycle

Visibility building monthly as content and signals mature

Clear sight line into share of voice and competitive position

Typical Engagement Timeline
Day 0
Authority Score audit
Day 30
Entity & Knowledge Graph complete
Day 60
Authority Pages live + first citations
Day 90
90-day review — results documented
Methodology

How we measure.
What we hold ourselves to.

Every result reported here is measured against a baseline established on Day 0. We don't report directional trends — we report numbers, and we show where they started.

01

Baseline Authority Audit

Every engagement begins with a full Authority Score audit — measuring AI recommendation frequency across six engines, entity verification status, Knowledge Graph completeness, and competitive share of voice in the primary market category.

02

30-Day Foundation Build

Entity architecture, Knowledge Graph registration, and schema deployment happen in the first 30 days. This is the infrastructure layer that every subsequent module depends on.

03

60-Day Authority Deployment

Authority Pages go live, GEO content begins publishing, and the first AI citation data becomes measurable. AI Visibility monitoring is active across all six engines.

04

90-Day Review

Full Authority Score re-measurement against baseline. Recommendation frequency, share of voice, entity accuracy, and citation coverage are all compared to Day 1 numbers. This is when results become visible.

05

Ongoing Growth

Visibility builds monthly as GEO content matures, entity signals strengthen, and AI engines index new authority pages. Post-90-day engagements track continued growth and close emerging competitive gaps.

What the Numbers Mean

Six KPIs.
Each one defined.

Authority Score

A 0–100 composite score measuring how well-positioned a business is to receive AI recommendations — entity clarity, content depth, citation signals, and competitive share of voice.

AI Recommendation Frequency

How often a business appears as a recommended answer across a defined set of buyer queries — measured monthly across six AI engines.

Knowledge Graph Completion

The percentage of critical entity signals (name, category, location, expertise, schema, cross-platform consistency) that are verified and correctly mapped.

Share of Voice

A business's percentage of AI-generated recommendations in its market category — the primary measure of AI competitive position.

Entity Accuracy

Whether AI engines describe a business correctly — right name, service, location, and positioning. Errors and omissions are tracked and corrected.

Citation Coverage

The number of distinct buyer queries for which a business is cited as a recommendation — measured by query category, geography, and specialization.

Client Perspectives

The metrics are the proof.
These are the stories behind them.

"

The Authority Score audit showed us exactly what was broken. Six weeks later, AI was recommending us by name. The speed of the change surprised everyone on our team.

Brokerage Owner
Austin, TX
"

I spent three years building my reputation. HeyPearl spent 90 days making sure AI knew about it. These two things should have happened at the same time.

Luxury Agent
Seattle, WA
"

The monitoring alone is worth it. We now know what six AI engines are saying about us — and what they're saying about competitors in our market.

Team Lead
Scottsdale, AZ

These are other businesses'
results.Yours are next.

Book a strategy call. We'll run a live Authority Score audit on your business and show you exactly where you stand — before you commit to anything.