Authority Engine

Why This Framework

B2B buying has changed over the past decade. The decision process is longer, more people are involved, and an increasing share of the research happens before the buyer gets in touch. AI models like ChatGPT, Claude, Perplexity, and Gemini are now part of this research phase, alongside Google, LinkedIn, and industry channels.

This means marketing has to do more than create attention. It has to build a coherent position that's recognizable across channels, credible to skeptical buyers, and visible where they actually look.

AIDA, inbound, demand generation, and similar frameworks cover important aspects of this and have their value. Authority Engine isn't a replacement, but the way I structure work with clients who want to build visibility and position over time, including in AI models, which is a relatively new dimension most frameworks don't address explicitly.

Four Dimensions That Drive Growth

The framework consists of four dimensions. Three of them generate demand: Position, Proof, and Visibility. The fourth, Conversion, turns demand into pipeline.

The dimensions work best when they work together. A strong position makes it easier to produce credible proof. Strong proof increases the impact of visibility work. Visibility without conversion becomes expensive attention without commercial effect. That's why the four must be seen as an engine, not as separate projects.

Dimension 01

Position

What you stand for that no one else can copy

Position is the answer to the question "why us and not someone else?", and that answer must be clear, precise, and defensible over time. This is the core of your brand strategy, what binds business strategy to market messaging.

For many B2B companies, position in practice consists of a sentence on the website and an internal agreement that "we deliver quality." That's not a position. It's an intention. Real brand positioning must be testable against the market, recognizable to customers, and expressed consistently across surfaces.

What characterizes strong position

• •A clear, recognizable differentiator that's not about price or relationships
• •A clearly defined ICP (ideal customer profile) and value proposition that fits that group
• •Consistent use of the same positioning on website, sales materials, LinkedIn, and in customer meetings
• •Employees who can explain the same story regardless of who you ask
• •The position is tested against real customers, not just defined internally

What's often missing

• •Ownership. Without one person responsible, the position becomes abstract and slowly drifts
• •Visual and verbal consistency. Position manifests in everything from word choice to design system
• •Connection to business strategy. The position must reflect what the company actually delivers
• •Clear category fit. AI models need to understand which category you compete in

Position is the first thing I look for when starting an engagement, because everything else hangs on it. A company that doesn't agree on who they are and why they exist won't produce consistent content, and therefore won't build credibility in the market.

Dimension 02

Proof

Why the market should listen

Proof is what makes someone believe the position. It's the difference between saying you're an expert and being perceived as an expert. The first is advertising. The second is authority.

Proof is built over time and requires the company to both do good things and make them visible. Many B2B companies deliver good work without any public trace of it. Then buyers have to trust the company's own words, which is a tough starting position in a market with many vendors.

What characterizes a strong proof base

• •Thought leadership published regularly that takes a stance and contributes perspective
• •Citations and mentions in media, podcasts, trade publications
• •Visible experts among employees: leaders, subject matter experts, technical specialists
• •Concrete customer cases published publicly with numbers and results
• •Social proof in the form of recommendations, reviews, and shared experiences
• •Original thinking: frameworks, methods, named approaches that are documented

What's often missing

• •Continuity. One post per quarter builds little. A strong proof base requires rhythm
• •Personal voices. Companies talk through their leaders. People listen to other people
• •Substantive content that dares to take a position, not safe summaries of what everyone already knows
• •E-E-A-T signals (experience, expertise, authoritativeness, trustworthiness) that AI models and search engines use to evaluate sources

In the AI era, proof has gained an additional dimension: what AI models cite. ChatGPT, Claude, and Perplexity often draw from established media sources, academic publications, and companies that have built topical authority. A company without visible traces in these sources struggles to be recommended.

Dimension 03

Visibility

Where you show up when someone is looking

Visibility is about being present in the channels that actually drive buying decisions. It's no longer just Google. In 2026, it's a broader ecology of search and research surfaces, and B2B buyers move freely between them.

What's included in modern B2B visibility

• •SEO (search engine optimization) for the searches that still go through Google
• •GEO (Generative Engine Optimization) or LLM visibility in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews
• •Social visibility: LinkedIn is still where B2B decisions often start
• •Industry-specific visibility: events, conferences, forums, professional communities
• •Brand search: direct searches for the company name, which is a strong indicator of position strength

How AI Models Work Differently

While Google shows ten blue links, AI models typically give one to three recommendations. That means the shortlist is shorter, and the effort to be on it is higher. AI models pull their answers from a broad set of sources: websites, media outlets, Wikipedia, databases, and industry-specific authority sources. Companies that are cited and referenced in these sources have a higher probability of being recommended.

GEO work is about mapping what AI models actually cite in a given category, identifying the gap between that and how the company shows up, and building presence where it matters.

Periscopify is the SaaS tool I'm co-founder of, which measures and improves this kind of visibility for B2B companies.

Dimension 04

Conversion

How demand becomes pipeline

The first three dimensions generate demand. Conversion is the mechanism that turns demand into actual sales opportunities.

Conversion is about all pipeline-building activities that deliver sales opportunities to the company, not just marketing-generated leads. It includes outbound, partners and alliances, and direct sales. Demand generation, lead nurturing, and follow-up have to work together. The CMO's job is to ensure the company enters each quarter with enough pipeline from all sources.

Many B2B companies have a hole here. They invest in content, campaigns, and visibility, but when interest first appears, they lose much of it to poor follow-up or missing infrastructure.

What characterizes strong conversion

• •Clear, prominent next steps on the website, not hidden in a footer
• •Content that helps the buyer evaluate solutions: comparisons, calculators, guides, audits
• •At least one high-quality lead magnet that people actually download
• •Follow-up of new leads within 24 hours, with relevant outreach
• •Clear coordination between marketing and sales, with shared definitions and goals
• •Attribution that shows which sources actually generate pipeline

What's often missing

• •Lead routes with substance. A newsletter form isn't enough. There has to be content worth exchanging an email address for
• •Marketing-sales link. When marketing generates interest without coordinating with sales, much is lost in the handoff
• •Measurement. Many companies don't know how much of their pipeline actually comes from marketing activity

Conversion is where most value disappears in modern B2B marketing, because it requires coordination across functions. It's rarely technically difficult. It's organizationally difficult.

The framework isn't a recipe, but a structure. What's actually done varies a lot between companies. A company with weak position needs something different than a company with strong position but weak visibility.