Made by Nacho Appears in 1.2% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
11 minutes read

Key Takeaways

  • Made by Nacho is mentioned in 1.2% of benchmark answers and recommended in 0.34%, leaving a wide gap to leading competitors.
  • Recent monthly data show mentions holding steady while recommendations fell, making the latest month a low point in the series.
  • No conflicting claims were recorded in the reviewed answers, so the first priority is to verify facts and track new mentions as they appear.
  • The recommended work focuses on reviewing owned pages, checking cited third-party sources, and building content around quality and suitability questions.

Answer Capsule

In November 2026, Made by Nacho appeared in 7 of 583 AI answers included in the Cat Food, Litter and Cat Care benchmark (1.20%). It received 2 recommendations (0.34%), with 2 Top 3 placements and 2 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do Made by Nacho mentions, recommendations and placements compare with its Cat Food, Litter and Cat Care peers?

Made by Nacho recorded 7 mentions (1.20%) and 2 recommendations (0.34%) across 583 answers included in the benchmark. Top 3 placements numbered 2; first-place recommendations numbered 2. Framing among its mentions was 5 positive, 2 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Tiki Cat

351

60.21%

223

38.25%

103

17.67%

36

6.17%

2

Dr. Elsey’s

246

42.20%

176

30.19%

111

19.04%

96

16.47%

3

Smalls

239

40.99%

174

29.85%

97

16.64%

73

12.52%

4

Weruva

274

47.00%

168

28.82%

75

12.86%

19

3.26%

5

World’s Best Cat Litter

162

27.79%

105

18.01%

66

11.32%

10

1.72%

6

Pretty Litter

50

8.58%

24

4.12%

17

2.92%

3

0.51%

7

Fussie Cat

17

2.92%

8

1.37%

5

0.86%

4

0.69%

8

Cat Person

17

2.92%

6

1.03%

3

0.51%

2

0.34%

9

Made by Nacho

7

1.20%

2

0.34%

2

0.34%

2

0.34%

10

KitNipBox

3

0.51%

1

0.17%

0

0.00%

0

0.00%

Made by Nacho appears in a small share of the answers reviewed, and its recommendations are rarer still. The placements it does earn tend to sit near the top, which suggests that when an answer does engage with the brand, it engages favorably rather than dismissively. That is a narrow but usable foothold.

The gap to the leading brands is wide, so chasing overall share immediately would be inefficient. The more useful first move is to understand which answer contexts produce the brand's mentions and recommendations, then protect and extend those. A baseline scorecard would record where the brand currently appears and how it is described, giving later work something honest to compare against.

Because the brand's presence is thin, each mention carries weight. A single inaccurate description can shape a large share of what buyers see. That makes verification work disproportionately valuable here, and it should run alongside any effort to widen reach.

What changed since last month

Questions This Section Answers

  • How did Made by Nacho counts and coverage differ across the available monthly snapshots?

Metric

Jul 2026

Aug 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

10 / 681 (1.47%)

13 / 668 (1.95%)

16 / 672 (2.38%)

7 / 665 (1.05%)

7 / 583 (1.20%)

Recommendations

8 / 681 (1.17%)

11 / 668 (1.65%)

11 / 672 (1.64%)

6 / 665 (0.90%)

2 / 583 (0.34%)

Top 3 recommendations

6 / 681 (0.88%)

6 / 668 (0.90%)

8 / 672 (1.19%)

4 / 665 (0.60%)

2 / 583 (0.34%)

#1 recommendations

4 / 681 (0.59%)

4 / 668 (0.60%)

6 / 672 (0.89%)

3 / 665 (0.45%)

2 / 583 (0.34%)

From October 2026 to November 2026, Made by Nacho's mention count stayed at 7, while its recommendation count fell from 6 to 2. The recommendation rate was 0.90% and 0.34% respectively.

The monthly record shows the brand's mentions holding steady between the two most recent samples while recommendations dropped. The earlier months show higher recommendation counts, so the latest figure is a low point in the recorded series rather than a stable level.

The samples differ in size between months, and the answers included are not the same set each time. That limits how much can be read into month-to-month movement. The observed change in recommendations should be treated as a recorded result to investigate, not as evidence that something specific went wrong or that any prior action worked.

A sensible response is to look at the answers behind the recent recommendations and compare them with earlier ones, focusing on how the brand was described and in what context. That review would inform whether the pattern is about wording, placement or simply which questions were asked.

AI recommendation trend

Observed recommendation rate (%), Jul 2026 to Nov 2026

0%0.5%1%1.5%2%Jul 2026Aug 2026Sep 2026Oct 2026Nov 20261.17%Jul 2026: 1.17%1.65%Aug 2026: 1.65%1.64%Sep 2026: 1.64%0.90%Oct 2026: 0.90%0.34%Nov 2026: 0.34%
  • Made by Nacho0.34%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Made by Nacho?

AI answers contained 0 conflicting claims about Made by Nacho: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

No conflicting claims about Made by Nacho were recorded in the answers reviewed, so there is no fact-check queue to work through at present. That is a clean starting position, but it is also a thin one: with so few mentions, the absence of conflicts partly reflects limited exposure rather than confirmed accuracy.

The measurement step should therefore do two things. First, build a visibility comparison that shows where the brand appears relative to competitors and in which kinds of answers. Second, keep a standing list of claims to verify as new mentions appear, so that any description of the brand can be checked against primary sources before it is treated as a problem.

This gives the client a priority order grounded in what answers actually say, rather than in assumptions about what buyers are told.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Made by Nacho should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

No disputed topics were supplied for this part of the analysis, so there is nothing to adjudicate between competing descriptions. The useful work here is preparatory: agreeing which brand facts are approved, where they come from, and who confirms them.

With that in place, page briefs can be drafted conditionally, marked as pending verification until the underlying facts are confirmed against current primary sources. Any apparent conflict should first be checked for entity, date and source differences, since those often explain discrepancies without anyone being at fault.

This keeps the website work honest. Briefs describe what a page should say once facts are settled, rather than asserting a correction before the evidence supports one.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Made by Nacho?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://cats.com/made-by-nacho-cat-food-review

2

2

0

https://felineliving.net/made-by-nacho-cat-food-review/

2

2

0

https://catfoodadvisor.com/reviews/made-by-nacho-kibble-dry/

1

1

0

https://catfoodadvisor.com/reviews/made-by-nacho-shreds/

1

1

0

https://catster.com/nutrition/made-by-nacho-cat-food-review/

1

1

0

https://chewy.com/made-by-nacho-bone-broth-infused-cage/dp/756478

1

1

0

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

A small set of review and retailer pages was selected for review because they relate to the brand in captured answers. None of them is linked to a conflicting claim, and citation alone does not show that a page influenced an answer. Their current contents still need checking before any request is considered.

The proposed work is a focused source review: read each page as it stands today, note how the brand is described, and identify anything that is clearly out of date or inaccurate against approved facts. Where a genuine issue exists, a polite evidence-backed request can follow. Where the page is accurate, the decision is to leave it alone and record why.

This protects relationships with publishers and keeps requests credible.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Made by Nacho website pages should receive review briefs?

Company website page

Citation appearances in all captured answers

Benchmark answers citing the page

Recommending answers citing the page

https://madebynacho.com/blogs/from-nacho-s-deck/nacho-s-lifelong-vet-shares-her-tips-on-cat-hydration

1

1

0

https://madebynacho.com/collections/cat-food-toppers

1

0

0

https://madebynacho.com/products/cuts-in-gravy-variety-pack

1

1

1

https://madebynacho.com/products/flaked-chicken-beef

1

1

0

The company's website was cited 4 times across 4 distinct page addresses; the table shows 4 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

The brand's own site was cited across a handful of distinct pages, including product pages and a hydration article. Only one of those pages appears in answers that also recommend the brand, so most owned citations are not currently accompanying an endorsement.

Page briefs should use approved facts and the questions buyers actually ask, rather than restating marketing copy. Each brief would specify the page's purpose, the facts it may state, the questions it should answer and the evidence behind any claim. Existing coverage should be checked before proposing new pages, since some questions may already be addressed.

The aim is to make priority pages clearer and more citable, not to flood the site with new content.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Made by Nacho?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

Is Nacho cat food high quality?

2

2

1

Is Made by Nacho good cat food?

1

1

1

What kind of broth can I give my cat?

1

1

0

hydrating cat food

1

1

0

name brand cat food

1

1

0

what is flaked cat food

1

1

0

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions cluster around quality and suitability, with a secondary group about broth, hydration and flaked food formats. The brand was mentioned in answers to most of these questions and recommended in a couple, which suggests the quality questions are the most productive ground to build on.

Proposed content briefs would address these buyer questions directly, using approved facts and plain explanations of ingredients, formats and feeding. Each brief should first check whether the site already answers the question well; where it does, the work is refinement rather than a new page.

These observations are recorded answer activity, not search demand, so the briefs should be treated as hypotheses to test against the site's own evidence.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Made by Nacho work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month establishes the baseline: a scorecard of current visibility, a scoped register of claims to verify with named owners, and a shortlist of pages and sources worth reviewing. Each record needs an evidence requirement and a review status so nothing sits unresolved.

The second month turns confirmed findings into page briefs and, where justified, publisher requests. Confirmed edits, no-change decisions, requests sent and responses received are tracked separately, so the client can see what was done versus what was merely proposed.

The third month adds buyer-question content briefs and a fresh scorecard. Completed work is reported separately from measured answer outcomes, and the comparability limits between samples are stated plainly rather than glossed over.

Methodology

Questions This Section Answers

  • How are Made by Nacho answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 583 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 5426 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Jul 2026

681

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Aug 2026

668

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Sep 2026

672

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Oct 2026

665

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Nov 2026

583

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

The visibility figures rest on answers that met the benchmark's inclusion rules, and the exact collection dates for the original answers have not been verified. A recommendation requires both an endorsement and positive wording, and top placements sit inside recommendations rather than adding to them.

Answers can mention several companies, so company counts cannot be summed to find distinct answers. Sentiment describes answer wording, not customer satisfaction. The citation analysis covers a wider set of captured answers than the benchmark, and cited pages still need independent checking.

Monthly samples differ, so comparisons show how recorded results changed, not why.

Our first three priorities

First, verify before correcting. With no conflicting claims recorded, the immediate task is to agree approved brand facts and a standing check for new mentions, so any future discrepancy can be assessed against primary sources rather than acted on immediately.

Second, review the selected external pages as they stand today and decide, page by page, whether a request is warranted. Accurate pages should be left alone and the decision recorded.

Third, draft buyer-question briefs around quality and suitability, checking existing site coverage first. These three strands give the client a defensible base before any effort to widen visibility, and they keep proposed work clearly separate from measured outcomes.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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