Sample AI Readiness Report

In this report

01. Verdict

How ready is Trail Packs NO for AI systems? A score from 0 to 100, based on two things: whether AI names your brand, and what it says about it.

Out of 100 for trail-packs-no.example.com · 110,120 analyzed data points

Trail Packs NO scores 52 out of 100 for AI readiness. Perception is your strongest area at 73, and visibility your weakest at 31, a gap of 42 points. Summit Bags CH is the only competitor you track that AI recommends more often than you. It gets 41.3% of the recommendations that go to the brands you track. You get 35.6%.

Readiness score52

Visibility31

Perception73

050100

02. Technical section

Not part of your score. This section checks whether AI systems can find your pages, read what's on them, and pick up your product facts. Each item that isn't passing comes with its fix.

3 of 6checks pass

3 pass · 2 opportunities · 1 gap · 0 not evaluated

AI systems can read your pages. Three things limit what they can pick up. One needs fixing, and two are worth improving. The fixes are below.

Reach

Can an AI crawler get to your pages at all?

Your site answers AI visitorsGap
AI crawlers are allowed inPass
Every product page can be foundOpportunity

Read

Once there, does it see your content — or an empty shell?

Specs are visible without running scriptsPass

Extract

Can it pull your product facts out and cite them?

Product facts in a format machines readOpportunity
Your product pages could be read end to endPass

Also checked

A guide file for AI systemsPresent

What to do

Your site answers AI visitors
Make sure your site answers non-browser traffic promptly and without a challenge page. If a CDN or firewall is putting bot protection in front of AI crawlers, allow them through — a crawler that gets a challenge sees nothing at all.
Every product page can be found
Publish a sitemap listing every product page and link to it from robots.txt. Without one a crawler only finds the pages you happen to link to from elsewhere, which is rarely all of them.
Product facts in a format machines read
Add structured data — a standard, invisible block of product and price facts — to the product page template, and company detail to the homepage. It is a one-off template change for a developer, and it is the difference between a machine parsing your facts and inferring them.

03. Visibility map

Where does AI recommend Trail Packs NO, and where does it point buyers elsewhere? How often your brand is named when buyers ask AI for advice across your use cases, and how often it comes up first.

Trail Packs NO holds strong ground in 1 of 3 use cases. In Alpine climbing and Everyday commuting, AI names it at most 21% of the time. When it is named, it comes first 74% of the time: most in Multi-day treks (90%), least in Everyday commuting (8%).

Weak ground: 2
Strong ground: 1
Invisible: 0
Data points analyzed: 29,859

Named in, out of 100 answersNamed first

Multi-day treks
Strong ground
72in 100
Named first
90%
- Consumers
  Strong ground
  80in 100
  Named first
  89%
- Professionals and trade
  Strong ground
  62in 100
  Named first
  92%
Alpine climbing
Weak ground
21in 100
Named first
23%
- Professionals and trade
  Strong ground
  34in 100
  Named first
  23%
- Consumers
  Weak ground
  9in 100
  Named first
  25%
Everyday commuting
Weak ground
3in 100
Named first
8%
- Consumers
  Weak ground
  6in 100
  Named first
  10%
- Professionals and trade
  Never named
  0in 100
  Named first
  —

Names you, positively
Names you, neutrally
Names you, negatively
Names you, tone not read
Doesn't name you
Strong ground from 25 in 100
Your average named first, 74%

04. Model split

Do all AI models know Trail Packs NO, or just some? How often each model names your brand, by use case, and where the gaps are.

GPT-5.6 Sol names Trail Packs NO in 93% of Multi-day treks answers; Kimi K3 in 54% — a 39-point split, the widest in the scan. Being found in Multi-day treks depends on which assistant your buyer happened to open.

Mention rate per use case on each AI model
Use case	GPT-5.6 Sol	Claude Opus 5	Claude Sonnet 5	Gemini 3.8 Flash	Muse Spark 1.1	Grok 4.6	Kimi K3	Gap
Multi-day treks	93%	88%	80%	72%	61%	57%	54%	39 points
Alpine climbing	28%	26%	23%	16%	19%	15%	17%	12 points
Everyday commuting	2%	4%	4%	3%	1%	2%	3%	3 points
All use cases	39%	38%	34%	31%	27%	24%	23%	16 points

05. Competitive picture

How your brand stacks up against competitors in AI recommendations, by use case. Competitors you track are named. Every other brand stays anonymous.

Trail Packs NO's share of AI recommendations is highest in Multi-day treks, at 17.1%. The rest of each bar is other brands, shown anonymously.

Trail Packs NO vs Summit Bags CH

They lead

Trail Packs NO clears Summit Bags CH in 1 of the 3 use cases scanned (Multi-day treks), and sits at or below the parity line in the other 2.

Trail Packs NO vs Outdoor Packs CA

You lead

Trail Packs NO clears Outdoor Packs CA in 2 of the 3 use cases scanned (Multi-day treks and Alpine climbing), and sits at or below the parity line in the other 1.

06. Whitespace

Which buyer questions could Trail Packs NO still win, because no brand owns them yet? Buying questions across your use cases where no brand — you included — is named in even half the AI answers. Whoever earns the mention there first takes the ground.

Choosing an approach in Alpine climbing is the biggest open question — 3.2% of all answers — and no brand is named in more than 28% of them.

06.1

Of all answers sit on open ground: 78.7%
Open questions big enough to chase: 10
Already led by Trail Packs NO: 2
Most any brand reaches in one: 47%

Open question — 10 in all, the biggest namedTrail Packs NO is already the most-named brand

Choosing an approachAlpine climbing
3.2%
Trail Packs NO is named in 20% of its answers, the strongest brand in 28%.
Fit for intended useAlpine climbing
3.2%
Trail Packs NO is named in 14% of its answers, the strongest brand in 27%.
Choosing an approachEveryday commuting
3.0%
Trail Packs NO is named in 2% of its answers, the strongest brand in 38%.
Finding providers for this useEveryday commuting
2.5%
Trail Packs NO is named in 3% of its answers, the strongest brand in 42%.
Fit for intended useEveryday commuting
2.5%
Trail Packs NO is named in 2% of its answers, the strongest brand in 44%.
Changing providers for this useAlpine climbing
2.3%
Trail Packs NO is named in 19% of its answers, the strongest brand in 27%.
Finding providers for this useAlpine climbing
2.3%
Trail Packs NO is named in 15% of its answers, the strongest brand in 28%.
Changing providers for this useEveryday commuting
2.2%
Trail Packs NO is named in 3% of its answers, the strongest brand in 42%.
Fit for intended useMulti-day treks
0.2%
Trail Packs NO is named in 46% of its answers, the strongest brand in 46%.
Choosing an approachMulti-day treks
0.1%
Trail Packs NO is named in 47% of its answers, the strongest brand in 47%.

Size of the questionTrail Packs NOStrongest brand

07. Perception

What AI says about your brand when it mentions you: your overall reputation, broken down by use case, and how professional buyers see you. You can hold every finding against reality and fix what's wrong or thin.

Overall brand reputation

Known for: Value and quality; 07.2
Praised for: Reputation, net +49; 07.2
Criticized for: Value, net -32; 07.2

07.1

Data points on your brand: 11,686
Overall tone: +46
Positive: 61%
Negative: 15%

AI talks about Trail Packs NO more positively than negatively: net +46 across 11,686 answers.

07.2

Reputation

Quality

Innovation

Service

Value

AI is most positive about reputation (+49) and most negative about value (-32).

Reputation per use case

07.3

Use case	Data points	Net	Praised for	Criticized for
Multi-day treks	2,459	+81	Quality (net +75)	—
Alpine climbing	673	-21	Reputation (net +1)	Quality (net -65)
Everyday commuting	87	+44	Reputation (net +52)	Value (net -33)

Your reputation reads strongest in Multi-day treks (net +81) and weakest in Alpine climbing (net -21).

07.4

Multi-day treks

Quality

Reputation

Value

ServiceNot discussed in any answer naming the brand

InnovationNot discussed in any answer naming the brand

Alpine climbing

Reputation

Innovation

Value

Quality

ServiceNot discussed in any answer naming the brand

Everyday commuting

Reputation

Quality

Innovation

Service

Value

Net, in points: more negative ← 0 → more positive

The most positive reading is quality in Multi-day treks (+75). The most negative is quality in Alpine climbing (-65).

Against your purchased competitors

07.5

Trail Packs NO (you)Summit Bags CHOutdoor Packs CA

Brand	Data points	Overall	Reputation	Quality	Value	Service	Innovation
Trail Packs NO(you)	11,686	+46	20%	18%	6%	8%	9%
Summit Bags CH	12,821	+20	16%	21%	0%	15%	15%
Outdoor Packs CA	9,180	+1	0%	0%	21%	0%	0%

AI credits Trail Packs NO most for reputation, in 20% of the answers naming it. That is ahead of every competitor slot on this chart — the nearest, Summit Bags CH, is credited for it in 16%.

07.6

Brand	Trade data points	Overall	Service
Trail Packs NO(you)	1,016	+42	-3
Summit Bags CH	1,161	+21	+50
Outdoor Packs CA	772	+1	-53

Among professional buyers, Trail Packs NO is seen at least as positively as every competitor you track, at net +42, and Summit Bags CH is the only one praised for service.

08. Monday plan

Tasks ranked by impact, starting with your weakest area. Each one links to the finding behind it, who should handle it, and what fixing it should improve.

3 to start this week. 4 more follow, in the same order. Your verdict puts visibility at 31, your weakest area, so the list starts there.

This week

ranks 01 to 03 · all three move visibility

Publish content that owns “Choosing an approach” in Alpine climbing

Open ground — the strongest brand reaches only 28% of its answers. You appear in 20%.

Hand to whoever owns your content. Worth 3.2% of this scan's question volume, and whoever earns the mention first takes uncontested territory. Evidence: §6 Whitespace

Publish content that owns “Fit for intended use” in Alpine climbing

Open ground — the strongest brand reaches only 27% of its answers. You appear in 14%.

Hand to whoever owns your content. Worth 3.2% of this scan's question volume, and whoever earns the mention first takes uncontested territory. Evidence: §6 Whitespace

Publish content that owns “Choosing an approach” in Everyday commuting

Open ground — the strongest brand reaches only 38% of its answers. You appear in 2%.

Hand to whoever owns your content. Worth 3.0% of this scan's question volume, and whoever earns the mention first takes uncontested territory. Evidence: §6 Whitespace

Then, in this order

4 tasks, each one line. Open one to see the finding behind it, who to hand it to, and what it should move.

Perception

1 task · score 73

Technical section

3 tasks

09. Methodology footprint

What was measured, and how much of it. Which AI models were asked, how much was analyzed, and anything the scan could not cover.

All 7 AI models were asked the same set of questions, producing 110,120 data points.

AI models scanned: 7
Data points analyzed: 110,120

The models on the panel

GPT-5.6 SolClaude Opus 5Claude Sonnet 5Gemini 3.8 FlashGrok 4.6Muse Spark 1.1Kimi K3

The use cases and buyers covered, in data points

Multi-day treks · any buyer — 6,063Alpine climbing · any buyer — 5,673Everyday commuting · any buyer — 5,661Everyday commuting · consumers — 2,094Multi-day treks · professionals and trade — 2,079Everyday commuting · professionals and trade — 2,076Alpine climbing · consumers — 2,073Alpine climbing · professionals and trade — 2,070Multi-day treks · consumers — 2,070

Scanned Sep 16, 2026 — the answers are a snapshot of that date.

This scan completed 99% of its planned answers — every section above, and the data-point count, is computed from the answers that arrived.

Every fact behind those three numbers, printed here rather than filed behind a click.

Models on the panel: GPT-5.6 Sol, Claude Opus 5, Claude Sonnet 5, Gemini 3.8 Flash, Grok 4.6, Muse Spark 1.1 and Kimi K3
Use cases and buyers covered: Every use case you typed was scanned against every buyer you picked, and against questions written for no particular buyer — 9 combinations in all, each scored on its own rather than pooled: Multi-day treks · any buyer, 6,063 data points, Alpine climbing · any buyer, 5,673 data points, Everyday commuting · any buyer, 5,661 data points, Everyday commuting · consumers, 2,094 data points, Multi-day treks · professionals and trade, 2,079 data points, Everyday commuting · professionals and trade, 2,076 data points, Alpine climbing · consumers, 2,073 data points, Alpine climbing · professionals and trade, 2,070 data points and Multi-day treks · consumers, 2,070 data points.
One data point: One recorded verdict about one AI answer for one brand. Each answer is read once for every brand this check tracks, which is why the count rises with competitor slots while the answer count does not.
Scanned: Sep 16, 2026. The answers are a snapshot of that date.
How we asked: Every question went out as a bare user message with no system prompt of ours — we measure what the model already believes about your brand, not how it responds to our prompting, and we never search the web on your behalf. All 7 models were asked the identical set, so a gap between them is theirs, not an artefact of asking them different things.
How the scan is drawn: The scan asks the buying questions your buyers ask, without naming any brand, and asks about your brand itself, angle by angle. Every question is written for what you sell, who buys it and where, from the answers you gave when you set up the check.
Why a re-scan compares: The panel is pinned to dated model snapshots and a slice of questions is deliberately re-asked, so a re-scan measures movement in the models rather than drift in our method.

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Purchase

Purchased: Sep 16, 2026, 1:00 PM
Scan started: Sep 16, 2026, 1:40 PM
Scan finished: Sep 16, 2026, 2:09 PM
Amount: $12,950

What the price pays for

Technical section

Full technical audit, run on your domain only

Included

You paid for the visibility scan: every question asked across all 7 AI models, for your brand and each competitor you added. The technical section is included context and carried no price.