AI Advisory Builds the Brand Reputation
That Earns AI Recommendations

AI cannot evaluate your product directly — it infers quality from reputation signals. AI Advisory measures your Brand Echo Score and builds the recognition that makes AI confident recommending your brand across ChatGPT, Gemini, Copilot, and Perplexity.

50%
B2B Buyers Now Start Research in AI
G2, 2025
47%
Choose ChatGPT First — 3x Any Competitor
G2, 2025
70%
Of Buying Journey Complete Before Contacting Sales
6sense, 2023

The Citation Gap

The disconnect between being visible and being recommended is wider than most brands realize.

Visibility Signals
Rankings
Traffic
Mentions

Where most brands focus

The Gap
Recommendation Strength
ChatGPT
Gemini
Copilot
Perplexity

Where buying decisions happen

The Reputation Problem

AI Recommends Based on Recognition — Not Rankings. Do You Have Enough?

AI cannot evaluate your product directly. It infers quality from reputation signals — third-party mentions, reviews, consistent recognition across sources. When buyers ask AI for recommendations in buying situations, the brands with stronger recognition signals get recommended. The rest get ignored. G2 Buyer Behavior Report, 2025

The Invisible Shortlist

AI makes recommendations before you know you're competing. ChatGPT is the #1 choice for 47% of B2B buyers — nearly 3x any other platform. By the time RFPs arrive, the shortlist was already shaped by what AI recommended — and if you weren't on it, you were never considered.

G2 Buyer Behavior Report, 2025

Rankings ≠ Recommendations

80% of pages AI cites don't rank in Google's top 100. Ranking measures placement. Recommendation requires reputation. Sites that rank #1 often have zero recommendation strength in buying situations because they lack the recognition signals AI uses to decide what to suggest.

Ahrefs, 2025

Recognition Deficit

AI can't test your product. It infers quality from reputation signals — third-party mentions, reviews, consistent recognition across credible sources. Without these signals, AI isn't confident enough to recommend you when buyers ask "what's the best X for Y?"

The Reputation Gap

Your competitors have been building the recognition signals that AI uses to make recommendations. B2B buyers complete 70% of their buying journey before ever contacting sales. The brands AI trusts get recommended in that research. You don't. The gap compounds daily.

Gartner / 6sense, 2025
Proprietary Measurement

Brand Echo Score Measures Whether AI Trusts You Enough to Recommend You

Brand Echo Score is a composite 0-100 metric that measures reputation strength across ChatGPT, Gemini, Copilot, Perplexity, and Google AI Overviews. Our proprietary analytical platform continuously monitors recognition signals, recommendation strength, sentiment, and cross-engine consistency — the factors that determine whether AI recommends you in buying situations.

68/100
Average
Tracking started
Example
1

Recognition Signals

We track the third-party mentions, reviews, and references AI uses to know you exist

2

Sentiment Quality

We analyze whether AI associates your brand with positive outcomes and trusted authority

3

Recommendation Strength

We measure how confidently AI suggests you in buying situations relative to competitors

4

Reputation Consistency

We monitor whether your Brand Echo is uniform across all AI platforms

Five Channels That Capture 95% of AI Research Behavior

We focus on the five channels where your buyers actually research and make decisions — backed by market data, not hype. AI Advisory analysis of market data, 2025

Brand Echo Score

Our composite metric across four AI engines

G

ChatGPT

800M weekly users. 60% market share. The #1 choice for 47% of B2B buyers — nearly 3x any competitor.

Dominant Leader OpenAI, G2 2025
G

Gemini

350M+ standalone users growing 30% monthly. Powers Google's AI Overviews reaching 1.5B users.

Google Ecosystem Similarweb 2025
C

Copilot

14% US market share. Embedded in Microsoft 365, Teams, and Outlook — the tools B2B buyers use daily.

Enterprise Embedded eMarketer 2025
P

Perplexity

780M queries/month. 80% graduates, 30% senior leaders. Research-first, citation-heavy.

High-Value Researchers Comscore 2025
+

Why not Claude, DeepSeek, or Grok? Claude dominates enterprise API usage but 85.9% of Claude users also use ChatGPT — optimizing there captures both. DeepSeek's 97M users are 51% in China, India, and Indonesia. Grok remains consumer-focused with limited B2B adoption. We focus where your buyers actually research.

Similarweb 2025
Strategic Framework

The 5 Strategies: Building the Reputation That Earns Recommendations

AI Advisory uses five distinct strategic approaches to build the Brand Reputation that earns recommendations: building recognition at scale (Volume Play), establishing early authority (Quick Wins), displacing competitor reputation (Competitive Gap), focusing on buying situations (Commercial Intent), or building sustainable reputation (Balanced Portfolio). Strategy selection depends on current Brand Echo Score and business objectives.

Volume Play Quick Wins Competitive Gap Commercial Intent Balanced Portfolio

Volume Play

Recognition at scale

Build recognition where the most buyers research. Establish presence in high-volume queries so AI becomes familiar with your brand and confident in recommending you.

Quick Wins

Early authority

Capture low-competition queries where you can become the recognized expert quickly. Build momentum that compounds into stronger recommendations over time.

Competitive Gap

Reputation displacement

Identify specific buying situations where competitors get recommended and you don't. Build the recognition signals that shift AI's default recommendation to you.

Commercial Intent

Buying situation focus

Prioritize queries where money is about to change hands. Focus reputation building where recommendations convert directly to revenue.

Balanced Portfolio

Sustainable reputation

Diversified recognition building across all strategies. Compound Brand Echo for organizations building long-term market authority.

Proof of Methodology

From Recognition to Recommendation — B2B Manufacturing and DTC Beauty Using the Same Framework

AI Advisory's methodology is industry-agnostic. A $100M+ global manufacturer and a Shopify-based DTC beauty brand had the same structural gaps: weak recognition signals, inconsistent reputation across engines, content built for clicks not recommendations. The same framework built both their Brand Echo.

B2B Manufacturing

A $100M+ Global Manufacturer

Market leader in precision measurement technology with strong Google presence but weak AI recommendation strength

Before
Not recommended in buying situations
After
Recommended in high-intent queries across all 4 engines
AI Advisory client engagement, 2024
"Our diagnostic tools showed their product pages ranked well but AI wasn't confident recommending them. We built the recognition signals that earned AI's trust in buying situations."
DTC Beauty

A DTC Beauty Brand on Shopify

Growing direct-to-consumer brand with strong social presence but zero AI recommendation strength in consideration-phase queries

Before
Invisible in "best" and comparison queries
After
Now recommended alongside category leaders
AI Advisory client engagement, 2024
"Our analysis revealed social following doesn't translate to AI reputation. We built the recognition signals that AI uses to make recommendations in buying situations."
Why AI Advisory

We Build Reputation, Not Just Visibility — Across 5 Channels With Cross-Vertical Proof

Most approaches monitor AI presence and deliver dashboards. AI Advisory builds the reputation that earns recommendations — implementing the recognition signals, sentiment architecture, and extraction framework that makes AI confident recommending you in buying situations.

5
AI Recommendation Channels
2B+
Monthly AI Touchpoints Covered
Combined platform reach
35%
More Clicks for Brands Recommended in AI Overviews
Seer Interactive, 2025
95%
AI Research Behavior Covered

The Difference Is Reputation Building

Capability Many Approaches AI Advisory
Multi-channel reputation building (all 5 including AI Overviews)
Extraction Architecture expertise
Recognition signal optimization
Diagnosis AND implementation
Strategic framework (The 5 Strategies)
AI Overviews tracking (1.5B users)
Proprietary analytical tools for diagnosis
Engagement Model

Five-Phase Process: Audit, Strategy, Architecture, Reputation Building, Brand Echo Tracking

AI Advisory engagements follow a structured path from measurement to implementation. Phase 1 is the Citation Gap Audit measuring Brand Echo Score across all channels. Phase 2 selects from The 5 Strategies. Phases 3-5 implement Extraction Architecture, build recognition signals, and track Brand Echo over time.

1

Citation Gap Audit

Using our proprietary diagnostic tools, we measure your Brand Echo Score across ChatGPT, Gemini, Copilot, and Perplexity. Discover whether AI recommends you in buying situations — and what recognition signals you're missing.

1-2 weeks
2

Strategy Selection

Based on audit findings, we identify which of The 5 Strategies fits your reputation goals, resources, and timeline. Not every brand needs the same approach. Strategy selection matters.

Collaborative session
3

Extraction Architecture

Restructure your product catalog so AI can recognize and recommend you. This isn't about creating new content — it's about building the architecture that earns AI's confidence.

4-8 weeks
4

Reputation Building

Systematic building of recognition signals across all channels. Each engine has different requirements. We build the reputation infrastructure so AI confidently recommends you everywhere buyers research.

Ongoing
5

Brand Echo Tracking

Our monitoring platform provides continuous measurement of your Brand Echo Score over time. Track recommendation strength. Identify new gaps. Adjust strategy. The AI landscape changes constantly — your reputation needs to evolve with it.

Continuous
The Cost of Waiting

5 Brands Capture 80% of AI Recommendations Per Category — Everyone Else Splits the Rest

The brands that build their AI reputation now will compound their advantage. AI recommendation dynamics are winner-take-most — early movers capture disproportionate recommendation share. Waiting means competing for scraps.

Invisible Pipeline Loss

Deals are decided in research phases you can't see. When buyers ask AI for recommendations and your competitors get suggested instead, you're eliminated before you know you're competing.

Winner-Take-Most Concentration

Just 5 brands capture 80% of top AI-generated recommendations for any given B2B category. If you're not in that top 5, you're splitting the remaining 20% with everyone else.

Magenta Associates, 2025

Accelerating Disadvantage

AI learns from patterns. Competitors who build reputation now establish recommendation positions that compound. The longer you wait, the harder — and more expensive — it becomes to displace them.

Reputation Decay

Content built for traditional search doesn't build AI reputation. Every day your brand lacks the recognition signals AI needs, your competitors' recommendation advantage grows.

Founding Client Program

We're onboarding one client per vertical. Engagements include full implementation by our team, powered by our proprietary optimization platform — access to which is complimentary until your Brand Echo improves, then converts to a subscription.

Discuss Fit

Start With a Citation Gap Audit

Our diagnostic tools reveal whether AI recommends you in buying situations — or suggests your competitors instead. We'll show you exactly where you stand across all five AI channels and what it would take to earn those recommendations.