We tested how the four AI models reshaping product discovery — ChatGPT, Claude, Gemini, Perplexity — answer questions about Nespola. We ran the test twice: once for Nespola and once for PublishingOS, because you operate under both names and the data is only useful if it covers both surfaces.
In the average response, the brand is recognised correctly 8.6% of the time. The other 91% — AI either invents facts about you, asks for clarification, or doesn't mention you at all. Both names hit the same ceiling, and AI models don't yet understand that PublishingOS is the product made by Nespola.
| Brand 1 | Nespola (nespola.io) |
| Brand 2 | PublishingOS (same domain, repositioned as the product) |
| Industry | AI-powered eBook publishing on Amazon KDP |
| Platforms | ChatGPT, Claude, Gemini, Perplexity |
| Prompts per brand | 50 across awareness, reputation, consideration, comparison, recommendation, sentiment |
| Responses analysed | 395 |
| Tracked competitors | Publishing.com (AI Publishing Academy), Driven Publishers |
Every response was classified into one of four mutually exclusive states — recognised correctly, hallucinated, clarification request, or not mentioned. Full definitions are in Appendix B. The split matters because being mentioned wrongly is worse than not being mentioned at all: a fabricated description carries the appearance of authority and is repeated at scale.
You operate under two names — Nespola and PublishingOS. The strategic question we tested: does AI search currently understand they're the same entity?
| Metric | Nespola | PublishingOS | Delta |
|---|---|---|---|
| Recognised correctly | 8.6% | 8.6% | 0.0pp |
| Hallucinated | 12.1% | 9.6% | −2.5pp |
| Clarification request | 15.2% | 13.2% | −2.0pp |
| Not mentioned | 64.1% | 68.5% | +4.4pp |
Both names hit the same accuracy ceiling. Neither alone wins. PublishingOS shows slightly less hallucination but slightly more silence. The underlying problem: AI models do not have enough verified, citable signal about either entity, and they do not understand the relationship between them.
The work compounds across both names. The same citations, schema, listings, founder anchoring, and content all serve both. Same investment, double surface area.
This is the most urgent finding in the report. When asked to describe PublishingOS, several AI models confidently attribute the brand to your largest competitor:
"They are not competitors. They are two different products created by the exact same company — PublishingLife (founded by Christian and Rasmus Mikkelsen, often known as the Mikkelsen Twins)."
"PublishingOS (also known as Publishing.ai or tied to Publishing Academy / AIA by the Michaelson brothers) lacks direct beginner endorsements… plus negative associations such as federal investigation scrutiny."
"No, PublishingOS is not widely seen as trustworthy. It appears to refer to Publishing.com… methods that have led to Amazon bans for its founders."
"PublishingOS is a project management and workflow tool created by Sean Dollwet, a well-known YouTuber and course creator in the Amazon KDP space." (Sean Dollwet is another competitor in the KDP coaching space.)
When a high-intent buyer asks an AI about you, the model is — in multiple instances — handing them off to Publishing.com / Mikkelsen Twins as the authoritative answer. Every one of those instances is a customer who walked away believing your brand and your competitor's brand are the same thing.
The Nespola side is no better. AI invents at least six different "Nespola" people:
"Nespola is Valerio Nespola's self-publishing programs…"
"Romina Nespola, a KDP educator focused on low/medium-content books…"
"Nespola is run by Tommi Pedruzzi, Manu Sisti, Nic Della Pina, and Mark Tavoni…" (Manu Sisti and Mark Tavoni are not part of your team.)
And on the most basic prompt of all — "What is Nespola?" — every platform other than ChatGPT defaults to the Italian fruit (loquat / medlar).
These are top-line answers being delivered to people who specifically asked about your brand. Today.
Not edge cases. Not subtle errors. Confident, declarative misattributions that — across platforms — most often hand your brand identity to a competitor or an unrelated category (Notion templates, enterprise CMS, Italian fruit).
| Platform | Recognised | Hallucinated | Clarification | Not mentioned |
|---|---|---|---|---|
| Perplexity | 16.0% | 12.0% | 8.0% | 64.0% |
| ChatGPT | 12.0% | 6.0% | 18.0% | 64.0% |
| Gemini | 4.0% | 26.0% | 4.0% | 66.0% |
| Claude | 2.1% | 4.2% | 31.3% | 62.5% |
| Platform | Recognised | Hallucinated | Clarification | Not mentioned |
|---|---|---|---|---|
| ChatGPT | 22.4% | 4.1% | 10.2% | 63.3% |
| Perplexity | 6.0% | 6.0% | 16.0% | 72.0% |
| Claude | 6.0% | 0.0% | 24.0% | 70.0% |
| Gemini | 0.0% | 29.2% | 2.1% | 68.8% |
Mention quality split by question type. Both scans show the same pattern.
| Category | Recognised | Hallucinated | Clarification | Not mentioned |
|---|---|---|---|---|
| Comparison | 21.9% | 18.8% | 21.9% | 37.5% |
| Recommendation | 9.4% | 9.4% | 6.3% | 75.0% |
| Consideration | 9.4% | 3.1% | 12.5% | 75.0% |
| Reputation | 8.8% | 8.8% | 17.6% | 64.7% |
| Sentiment | 3.1% | 12.5% | 18.8% | 65.6% |
| Awareness | 0.0% | 19.4% | 13.9% | 66.7% |
| Category | Recognised | Hallucinated | Clarification | Not mentioned |
|---|---|---|---|---|
| Comparison | 16.1% | 12.9% | 19.4% | 51.6% |
| Reputation | 8.6% | 11.4% | 14.3% | 65.7% |
| Awareness | 8.3% | 5.6% | 22.2% | 63.9% |
| Sentiment | 6.5% | 6.5% | 12.9% | 74.2% |
| Recommendation | 6.3% | 12.5% | 6.3% | 75.0% |
| Consideration | 6.3% | 9.4% | 3.1% | 81.3% |
Comparison is the surface where the category leader's grip is weakest.
Comparison performs best on both scans (16–22% accurate). Comparison prompts force the AI to engage with both names side-by-side, which surfaces whatever signal does exist about the smaller brand. AI search is already being asked these questions and is currently failing to answer them well.
Verbatim from the analyzer log. Every one of these is currently being delivered to users.
"Nespola (also known as loquat in English) is a fruit that is particularly popular in Mediterranean countries, especially Italy. Scientific name: Eriobotrya japonica…"
"Nespola is a self-publishing agency / B2B service provider focused on modular ghostwriting and translation."
"Nespola has a free Skool community with over 10,000 members and lifetime one-on-one consultations." (Free-tier number is correct. Paid tier sits at ~300 members at $99/mo. The "lifetime one-on-one consultations" is fabricated — no such offer exists.)
"PublishingOS is a generic enterprise publishing software platform for media companies."
"PublishingOS is a Notion-based premium template for indie authors."
"PublishingOS is a custom-built Notion workspace created by Dane McBeth."
"PublishingOS is not Amazon KDP — it's a generic third-party service / tool."
When AI models justify their answers, they cite sources. The same names came up repeatedly across both scans:
| Source | Times cited | What it is |
|---|---|---|
| 8 | Top-level platform reference | |
| YouTube | 7 | Video authority — the Mikkelsens dominate here |
| Trustpilot | 4 | Review platform |
| r/KDP | 3 | Subreddit specific to KDP |
| r/selfpublish | 2+ | Largest indie publishing subreddit |
| KBoards | 1 | Long-running KDP forum |
| The Nerdy Novelist (YouTube) | 1 | Influential KDP YouTuber |
| Kindlepreneur.com | 1 | Authority site for KDP tools |
| kdp.amazon.com | 1 | Amazon's official KDP help |
| PW Learning Lab | 1 | Publishers Weekly education |
This is the most actionable section of the report. Every venue here is a place AI search is already looking for evidence about your brand. Where you're present and well-represented, AI gets you right. Where you're absent, AI invents.
Publishing.com / Mikkelsen Twins have heavy presence on Reddit (multiple long threads), YouTube (the Mikkelsen brothers' channel and dozens of reaction videos), Trustpilot, and Writer Beware. They have deliberately built citation density across these venues over four years. That is why AI models confidently — and incorrectly — describe PublishingOS as "made by the Mikkelsen Twins."
Today, every piece of AI-search demand in your category that doesn't have a brand name in the prompt flows to your competitor. Closing that gap takes both: traditional SEO and the entity-citation work AI search runs on.
This audit is the baseline. AI models update their training signals constantly; recognition, hallucination, and competitor capture are moving numbers. The version of this scan we'd run 12 weeks from now will measurably differ — if the right interventions happen between now and then, in the right order.
The companion Engagement Proposal covers what those interventions look like, how we'd run them, and the three engagement shapes that fit Nespola best. The audit stands alone whether or not you take any of them.
50 prompts per brand, generated by an AI prompt-generator we built specifically for this analysis. Prompts span six buyer-journey categories (awareness, reputation, consideration, comparison, recommendation, sentiment) in proportions that mirror real query distributions. Roughly one third of prompts name the brand explicitly; two thirds test category-level discoverability.
Each prompt was sent to ChatGPT (GPT-5.4), Claude (Sonnet 4.6), Gemini (3.1 Pro Preview), and Perplexity (Sonar Pro). We use OpenRouter for normalised access. Each prompt × platform combination produced one response.
Every response is passed through an LLM-based analyzer (GPT-5.4 mini) that reads the response alongside the brand profile we built with you, then classifies the response into one of four mention types, extracts hallucination details, captures cited sources, and identifies competitors mentioned. Outputs are reviewable per-row in the dashboard.
We worked from a brand description that includes founders, business model, pricing, member count, and category positioning. Hallucinations are flagged only when the response contradicts a fact present in the brand profile. Vague responses are not flagged as hallucinations.
198 responses for Nespola (50 prompts × 4 platforms, minus 2 platform errors), 197 for PublishingOS (50 × 4, minus 3 platform errors). Both samples are well above the threshold for trustworthy proportions at 95% confidence.