Week 3/4 The Zero-to-Visible in AI Experiment

Happy New Year! New opportunities and new challenges ahead. If you are new here, this is a live experiment testing what it actually takes for a new brand to show up inside AI answers (ChatGPT, Perplexity, Gemini, and more).

Weeks 3 and 4 marked the shift from setup to signal testing.

Our First AI Visibility Analysis Is In

Now that No Fluff is officially in market, we ran our first AI Visibility analysis to understand what AI systems actually do with our brand once we’re live. We measured visibility across three simple buckets:

Presence – does AI mention us?
Authority – does AI treat us as credible?
Recommendation – does AI suggest us as an option?

Next week, we plan to publish a blog post that goes deeper into our metrics and scoring. But to start, here’s the headline:

Across our full prompt universe (~150 prompts), our brand mention rate is hovering around 30% (with minimal movement across the two weeks). That means No Fluff appears by name in roughly one-third of the AI answers we tested.

Where do we have visibility across prompt types?

Hallucinations: When Visibility Becomes Confusion

The good news: No Fluff appeared earlier than expected, largely from LinkedIn and launch consistency.

The problem: not all mentions were real, as in several cases, AI blended us with other brands of a similar name.

Two things we believed happened:

Site speed: If AI can’t fetch a page within ~5–15 seconds, it moves on. Structure, templates, and server configuration directly affect visibility. If AI can’t reliably read the key source (our site), it will pull from other sources to assemble an answer. Its priority is speed to answer users’ questions, not accuracy. We had fixing to do!

Context: “No Fluff,” similar company names, founders talking about the same topics… it adds up. We have training to do to ensure AI systems know who we are, what we do, and entity connections.

Breaking Down Our Next Moves

After our first report, we had two primary questions we needed to dig deeper into.

Where is AI pulling answers from? Instead of only looking at “top” citations, we analyzed all sources AI referenced across our prompt set. That allowed us to:
- Identify which domains AI already trusts
- Decide which sources to compete with, partner with, or earn placement in
- Fix first-party content before PR or link building, so attribution sticks
Which prompts offer the highest chance to win with the least competition?
- Our early movement first appeared in semantic and methodology-driven prompts—the “how does this actually work?” questions—not in “best agency” or list-style prompts. But we still have work to do. Instead of spreading effort across our full prompt universe, we isolated the top 8–10 prompts that:
  - Have the lowest competition
  - Show consistent retrieval behavior
  - Can be influenced with structured content (not backlinks alone)

The chart shows how we prioritized AI prompts using three key metrics. This allowed us to find ones with the least competition and the highest chance of influence

What’s Next

Over the next sprint, we’re focused on:

Cleaning up identity and disambiguation signals to reduce hallucinations; Site speed!
Building presence where AI already looks (Medium, YouTube, Reddit, more)
Doubling down on winnable prompts; building focused pages, FAQs, and structured explanations for those top 10 prompts
Expanding credibility beyond our own site (directories, backlinks, PR) after analyzing those top sources

Let’s see if our hard work moves the needle by week 5!

Catch up on all our insights

Stat of the Week

Only ~11 % of sites are cited by both ChatGPT and Perplexity in AI answers. (Averi.ai)
AI systems draw from a wide range of sources and models. Showing up on one platform doesn’t guarantee you’ll show up on others. Build the foundation to be seen by all.

Fresh Reads

Each newsletter, we’ll share our favorite articles and breaking news.

As always, reach out anytime at katie@nofluffmktg.com if you’ve got questions or if you’re building your own visibility story too.

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Frequently Asked Questions About Zero-to-Visible and No Fluff

What is the Zero-to-Visible experiment?

Zero-to-Visible is an ongoing experiment that documents how a new brand becomes discoverable, explainable, and citable by AI systems. It tracks which signals influence whether AI systems recognize and recommend a company during early buyer discovery.

What does “AI visibility” mean in Zero-to-Visible?

In Zero-to-Visible, AI visibility means whether AI systems can recognize a brand, accurately explain what it does, and include it in AI-generated answers when buyers ask category-level questions.

Who is running the Zero-to-Visible experiment?

The Zero-to-Visible experiment is run by No Fluff, a B2B growth firm focused on how AI systems recognize, explain, and recommend brands in AI-generated answers.

Why is No Fluff running this experiment publicly?

No Fluff runs Zero-to-Visible publicly to document real-world signals that influence AI visibility. The goal is to replace speculation about AI search with observable patterns and repeatable methods.

Are the results specific to one AI platform?

No. Zero-to-Visible observes patterns across multiple AI systems, including retrieval-based and generative models. While individual outputs vary, consistent signals tend to produce similar visibility outcomes across platforms.

Can other B2B brands replicate these results?

Yes. When the same structural signals—clear brand definitions, consistent category positioning, structured content, and third-party validation—are applied consistently, similar AI visibility patterns can be reproduced.

Does Zero-to-Visible replace SEO?

No. Zero-to-Visible shows how AI visibility builds on SEO foundations. SEO enables access to content, while Zero-to-Visible focuses on whether AI systems trust, explain, and recommend a brand once that access exists.