The Answer Layer Audit · IV-Lead for Netzer Precision · 13 September 2026
Three months of measurement, 5,301 individual AI answers, re-read one at a time. Your dashboard averages those into a single 25%. Underneath it are four completely different companies.
HubSpot portal 8606367 · 21 tracked questions · 23 April to 16 July 2026 · 46,559 citations across 1,457 domains · read-only export
Certainty first, size second. The first four are counted rather than estimated, and you can check every one of them in your own portal.
You are the second most-named of the fifty vendors we counted, on 26.0% of 5,301 answers, behind HEIDENHAIN at 28.8% and just ahead of Renishaw at 24.8%. Second and third are 65 answers apart, so read this as “front rank”, not as a position.
counted · 5,301 answersYou are effectively absent from ChatGPT outside one territory. 83 of your 89 ChatGPT mentions come from the three space questions. On the other eighteen questions ChatGPT named you 6 times in 1,504 answers, which is 0.4%.
counted · 1,753 answersOne answer in three that reads your website never says your name. 1,945 answers cited netzerprecision.com and 627 of them did not name you. Roughly 350 of those named a competitor instead.
counted · 1,945 answersYou lost three quarters of your Perplexity visibility in five weeks and nobody saw it. 48.2% down to 9.5%, recovering only to about 25%. Measurement then stopped.
counted · 13 weeksA third of your questions barely name any supplier at all. How often the engines name any company predicts your score, with a correlation of 0.87. Eight questions average 2.0%, ten average 46.2%.
correlation · 21 questionsYour tracked list accounts for 62% of competitor name-appearances, so 38% of the field is invisible to the dashboard. Five of sixteen slots hold vendors under 2%, one of which appears zero times in 5,301 answers, and a sixth holds an entry called “king kong”.
counted · 50 vendorsAll 27 of HubSpot's recommendations have the same verb, which is create. None is categorised as fixing, reclaiming or retiring anything you already have, and two high-priority items target the single most unwinnable question on your panel.
read from the portalYour dashboard reports one visibility number. It averages four engines that were not given equal numbers of runs, so it is not a fact about your market. It is a fact about how HubSpot allocated its budget.
Split it and the picture inverts. On Google's engines you are the most-named encoder company of the fifty we counted. On Perplexity you are third. On ChatGPT you are barely present, and outside one territory you are not present at all.
| Engine | Answers | You were named | Rate | Rank | Who leads |
|---|---|---|---|---|---|
| Gemini Flash 3.5 | 609 | 350 | 57.5% | #1 | Netzer Precision |
| Gemini Flash 2.5 | 1,165 | 496 | 42.6% | #1 | Netzer Precision |
| Perplexity | 1,774 | 444 | 25.0% | #3 | HEIDENHAIN, 31.7% |
| ChatGPT | 1,753 | 89 | 5.1% | ~#10 | Renishaw, 26.4% |
ChatGPT answered without searching the web at all in 842 of its 1,753 answers. Not truncated, not failed. Long, confident answers written from memory. In those 842 answers, Netzer was named zero times.
The other engines behave differently when they answer from memory. Perplexity names you in 19% of its unsearched answers, Gemini 3.5 in 25%. Their models know who you are. ChatGPT's does not.
| Engine | How it answered | Answers | You were named | Rate |
|---|---|---|---|---|
| ChatGPT | searched the web | 911 | 89 | 9.8% |
| ChatGPT | answered from memory | 842 | 0 | 0.0% |
| Perplexity | answered from memory | 63 | 12 | 19.0% |
| Gemini Flash 3.5 | answered from memory | 40 | 10 | 25.0% |
An absolute encoder reports its true position at power-on without searching for it. Half the time, so does ChatGPT. And it has no position for Netzer at all.
This separates two problems that look identical on a dashboard. Publishing better pages fixes the searched half. It does nothing for the unsearched half, which is a question of how widely you are written about on the sources these models are built from. Different budget, different people, different timescale.
netzerprecision.com is the single most-cited domain in the entire dataset, with 2,680 citations, ahead of heidenhain.com and renishaw.com. The engines open your site more often than anyone else's.
And one time in three, they read it and never say your name.
Perplexity · 11 July 2026 · "Which industrial automation encoders suit surgical robotics manufacturers?"
In its source list: netzerprecision.com/applications/surgical/
"Surgical robotics manufacturers prioritize compact absolute encoders… | Absolute Magnetic (e.g., AksIM-2) | Compact, off-axis design for space-constrained joints; robust against EMI from nearby motors. |"
Your surgical applications page was opened. AksIM-2 is an RLS product. Your page was in the source list. A competitor's part number was in the sentence.
| Engine | Answers citing you | Cited and named you | Cited, named someone else | Share |
|---|---|---|---|---|
| Perplexity | 701 | 412 | 289 | 41.2% |
| Gemini Flash 2.5 | 751 | 495 | 256 | 34.1% |
| Gemini Flash 3.5 | 412 | 332 | 80 | 19.4% |
| ChatGPT | 81 | 79 | 2 | 2.5% |
| All four engines | 1,945 | 1,318 | 627 | 32.2% |
Being in the source list is not being in the sentence. Being named is not being recommended.
We counted fifty vendor names against every one of the 5,301 answers: yours, your fifteen real tracked competitors, and thirty-four more that appear in your own citation data. That gives each question a number, which is how many company names the engines put in a typical answer to it.
It predicts your score almost perfectly.
Across 251 answers to the failure-causes question, all fifty vendors together were named 35 times. Across 251 answers to the space question, 1,217 times. That is a 35-fold difference in whether the answer has room for a company at all.
Perplexity · "What are the most common causes of encoder failure in high-precision applications?"
"In high-precision applications, the most common causes of encoder failure are mechanical misalignment (specifically shaft run-out or a bent shaft), contamination … bearing wear due to vibration, and electrical noise interfering with signal integrity. … | Shaft Run-Out / Bent Shaft | The single most common cause… [6]."
Thorough, well sourced, and it contains no supplier at all. You score zero here because the answer has no vendor-shaped slot in it, not because your content is weak.
| Question shape | Questions | Names per answer | Your mean score | Zeros |
|---|---|---|---|---|
| Selection: Which… / Who… / best… / top… / Compare… | 14 | 2.83 | 36.2% | 0 |
| Information: How do… / Why… / What causes… / What should… | 7 | 0.29 | 3.7% | 4 |
A third of your prompt set asks questions that barely name a supplier at all. Changing the verb is free and worth thirty points. Changing the page costs money and is worth ten.
Because the reporting is blended and nobody was watching per engine, a very large event passed without comment. Between the first week of May and the first week of June 2026, your Perplexity visibility fell from 48.2% to 9.5%. It recovered only to about 25%. Your citations on Perplexity fell in step, which rules out a counting glitch. The engine genuinely stopped surfacing your pages.
The last run completed on 16 July 2026 and access had already ended on 15 July, two months ago. Nothing has been observed since. Whether the May collapse has returned is currently unknown, and there is no instrument running that would tell you.
Ten of your 21 questions are medical or surgical. Three slots are space, covering two distinct questions. The space questions are the ones you win, and they show what a fully earned answer looks like. Gemini Flash 3.5 named you in every one of 87 space answers. Medical is the bigger half of the panel and you are strong there on Gemini, mid on Perplexity, and absent on ChatGPT.
Perplexity · "Who produces space qualified rotary encoders?" · your best question, 87%
"| Netzer Precision | Develops contactless capacitive absolute rotary encoders (e.g., VLS family, Space GEO) tested per ESA/NASA standards for GEO, LEO, and deep-space missions [4][5][10]. |"
The engine did not describe you with adjectives. It named a product family, a product, and a qualification standard, because your space pages publish all three. That is the mechanism, and it already works on part of your site.
The contrast is the diagnosis. Your VLS-80 page carries TML and CVCM outgassing figures, TID and SEE radiation data, Parylene and Polyimide coatings, and three named standards. Your MRI and magnetic-immunity page says "Immunity to Magnetic". It sits at 3% across 251 answers.
1,457 domains were cited in answers to your questions. The top of that list is where your category's answers are actually assembled from, and several of the biggest entries are channels you have not claimed.
surgicalroboticstechnology.com was cited 569 times. Celera Motion holds a full company profile there, with six news items and a video. You have one news item and no profile. The site's own footer reads "Add Your Company". YouTube was cited 1,197 times.
Every share-of-voice figure on your dashboard is measured against sixteen names someone typed in. Those sixteen account for 62% of all competitor name-appearances in your own data, so 38% of the competition comes from vendors the dashboard cannot see at all.
| Tracked, but barely present | Presence | Untracked, but real | Presence |
|---|---|---|---|
| POSITAL | 1.9% | Gurley | 9.6% |
| Sensata | 1.5% | NUMERIK JENA | 8.0% |
| TAMAGAWA SEIKI | 0.6% | MACCON | 7.6% |
| Novotechnik | 0.1% | Lika Electronic | 6.9% |
| BOGEN | 0.0%, zero in 5,301 | maxon | 4.5% |
| "king kong" | junk entry | Micronor | 1.7% |
Five of sixteen slots hold vendors under 2%, and a sixth holds a junk entry. Gurley alone is named more often than four tracked names combined. Which means competitors mentioned = 0 has always meant "none of our sixteen", never "no vendor appeared". Location tags are split three ways as well, across US, United States and DE, with the same question tracked under two of them.
Twenty-seven recommendations are sitting in your portal, generated for 20 May to 19 June, all still marked NEW. Every single one carries the same action category: CREATE_CONTENT.
Two of the high-priority items are "Create an educational article on encoder failure causes" and "Create a how-to guide on preventing encoder failures". Both target the one question on your panel where fifty vendors are named 35 times in 251 answers. The tool cannot see that, because it measures your absence and never measures the category's.
To be fair to the tool, it picked good surfaces. Thirteen of the 27 point at LinkedIn, Reddit and YouTube, which is the same direction as our own Tier 3 below. The problem is narrower than "it only tells you to blog", and it is not fixable by using the tool harder: it has one verb. It cannot say repair the FAQ markup that fails to parse, add product schema, rewrite the page sitting at 3%, claim the directory profile a competitor already holds, retire an unwinnable question, or fix the competitor list that distorts every number on its own dashboard. Those are six of our ten actions, and no setting in the tool will produce them.
The tool has one verb, and it is create. Six of our ten actions need a different one.
Tier 1 costs nothing and we are certain of it. Tier 3 is the largest opportunity and the least certain. Do them in this order.