West Paw Appears in 68.5% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
9 minutes read

Key Takeaways

  • West Paw has strong mention and recommendation rates in the dog toys and pet enrichment category, with very little negative framing.
  • The main opportunity is not visibility alone, but improving first-place placement and overall prominence in answers.
  • Several pricing claims need primary-source verification before any website or publisher corrections are proposed.
  • Priority work includes reviewing high-citation pages, updating key site pages, and building content around durable-toy and breed-specific buyer questions.

Answer Capsule

In November 2026, West Paw appeared in 359 of 524 AI answers included in the Dog Toys and Pet Enrichment Products benchmark (68.51%). It received 251 recommendations (47.90%), with 177 Top 3 placements and 48 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 West Paw mentions, recommendations and placements compare with its Dog Toys and Pet Enrichment Products peers?

West Paw recorded 359 mentions (68.51%) and 251 recommendations (47.90%) across 524 answers included in the benchmark. Top 3 placements numbered 177; first-place recommendations numbered 48. Framing among its mentions was 286 positive, 73 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Kong Company

414

79.01%

300

57.25%

220

41.98%

199

37.98%

2

West Paw

359

68.51%

251

47.90%

177

33.78%

48

9.16%

3

Outward Hound

255

48.66%

155

29.58%

85

16.22%

36

6.87%

4

Chuckit!(brand of Petmate/Doskocil Mfg)

231

44.08%

134

25.57%

75

14.31%

20

3.82%

5

Nylabone

202

38.55%

120

22.90%

57

10.88%

18

3.44%

6

BarkBox(parent: Bark Inc)

69

13.17%

17

3.24%

7

1.34%

5

0.95%

West Paw sits near the top of this category in AI answers, with strong mention and recommendation rates and almost no negative framing. That is a solid base to defend rather than a problem to fix. The gap worth noting is placement depth: it is named often but leads far less often than the category leader, so prominence, not presence, is the open opportunity.

The agency would treat this as a positioning brief. We would map which question types produce a first-place answer for West Paw and which stop at a mention, then build page and content briefs aimed at the questions where it is named but not chosen.

What changed since last month

Questions This Section Answers

  • How did West Paw counts and coverage differ across the available monthly snapshots?

Metric

Aug 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

425 / 641 (66.30%)

447 / 645 (69.30%)

398 / 610 (65.25%)

359 / 524 (68.51%)

Recommendations

410 / 641 (63.96%)

429 / 645 (66.51%)

391 / 610 (64.10%)

251 / 524 (47.90%)

Top 3 recommendations

285 / 641 (44.46%)

300 / 645 (46.51%)

290 / 610 (47.54%)

177 / 524 (33.78%)

#1 recommendations

19 / 641 (2.96%)

18 / 645 (2.79%)

30 / 610 (4.92%)

48 / 524 (9.16%)

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

From October 2026 to November 2026, West Paw's mention count fell from 398 to 359, while its recommendation count fell from 391 to 251. The recommendation rate was 64.10% and 47.90% respectively.

The November sample shows fewer mentions and a notably lower recommendation rate than October, while first-place finishes rose. These are separate selected samples, so the movement describes what was recorded, not a cause. The comparability limit matters here: a different answer total does not explain the shift in counts or rates.

For the client, the practical reading is to watch the recommendation rate and placement mix together rather than reacting to one month. The agency would keep the monthly scorecard running and flag any pattern that persists across samples before recommending changes.

AI recommendation trend

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

0%20%40%60%80%Aug 2026Sep 2026Oct 2026Nov 202663.96%Aug 2026: 63.96%66.51%Sep 2026: 66.51%64.10%Oct 2026: 64.10%47.90%Nov 2026: 47.90%
  • West Paw47.90%

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 West Paw?

AI answers contained 5 conflicting claims about West Paw: 0 critical, 1 high, 1 medium, 3 low. Of these, 1 was 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.

The fact-check list is small but not trivial: one high-priority conflict and several lower ones, mostly around pricing for named products. These ratings order the verification work; they do not show that West Paw or any publisher got something wrong. A price conflict can simply reflect different dates or editions.

The agency would build a visibility comparison alongside a scoped fact-review register, giving each disputed claim an owner, a primary-source check and a status. That lets the client fix what is genuinely wrong and leave ambiguous items out of the correction queue.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about West Paw should be verified before proposed page edits?

Review topic

Severity

Recorded AI claim A

Recorded AI claim B

West Paw Jive Ball price

low

~$22

$21.95

West Paw Zogoflex Tux price range

low

$18–$25

$20–$25

Qwizl price

low

$26.95

$26.99

Qwizl price

medium

$26.95

$21.95

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.

The disputed topics cluster around prices for the Jive Ball, the Tux and the Qwizl, with one medium-severity conflict on Qwizl pricing. Both recorded claims are AI answer text, not confirmed company facts, so the first job is to establish the entity, the date and the source behind each figure before anyone drafts a correction.

The agency would verify current primary sources, then prepare conditional page briefs only where a real inconsistency is confirmed. Where dates or variants explain the gap, we would record a no-change decision rather than force an edit.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for West Paw?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://chewy.com/ca/west-paw-zogoflex-toppl-tough-treat/dp/1000104311?gad_campaignid=21002931069&gad_source=1&gbraid=0AAAAApnr0YiOhK30KMUgBVfsAqIPXH2lM

1

1

1

https://dogtuff.com/products/west-paw-tux

1

1

1

https://fleacircuspetsupplies.com.au/west-paw-toppl-treat-dispensing-dog-toy

1

1

1

https://nytimes.com/wirecutter/reviews/best-dog-toys/

80

38

1

https://businessinsider.com/guides/pets/best-dog-toys-aggressive-chewers

40

35

1

https://citylinevet.com/veterinary-blog/dog-toys-for-chewers/

20

17

1

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.

The citation review points to a small set of third-party pages, with the Wirecutter and Business Insider guides appearing most often in answers that mention West Paw. A page linked to a conflicting claim is not necessarily its cause, and citation alone does not show influence, so these are review candidates rather than targets.

The agency would check the current contents of the shortlisted pages, then prepare evidence-backed requests only where a specific, verifiable issue exists. Requests would be framed as corrections or clarifications, with responses tracked separately from confirmed edits.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed West Paw 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://westpaw.com/

7

6

1

https://westpaw.com/collections/puzzle

3

3

3

https://westpaw.com/collections/dog-toys

2

2

0

https://westpaw.com/blogs/scoop/guaranteed-tough-durable-dog-toys

1

1

1

https://westpaw.com/blogs/scoop/indestructible-dog-toys

1

1

0

https://westpaw.com/blogs/scoop/safest-dog-toys-0

1

1

1

https://westpaw.com/collections/fetch-toys

1

1

0

https://westpaw.com/pages/chew-vs-play

1

1

1

The company's website was cited 24 times across 15 distinct page addresses; the table shows 8 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.

West Paw's own site is cited across a modest set of pages, with the homepage and the puzzle collection drawing the most appearances. The puzzle collection is notable because its citations also appear in recommending answers, which makes it a sensible first candidate for a page brief. A cited page is not automatically one that accompanied a recommendation.

The agency would draft briefs for the priority pages using approved facts and real buyer questions, checking existing coverage before proposing anything new. Each brief would name the reviewer and the evidence needed before publication.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for West Paw?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

What is the most popular dog toy right now?

5

4

4

What to give a dog that destroys everything?

4

4

4

What are the best toys for Labradors?

6

4

3

What is the best dog toy on the market?

4

4

3

What are the best toys for Bernese dogs?

3

3

3

What are the best toys for a large dog?

3

3

3

What are the best toys for bernese dogs?

4

3

3

What is the best food dispensing toy for dogs?

3

3

3

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

The recorded questions are practical: durable toys for heavy chewers, breed-specific picks for Labradors and Bernese, food-dispensing options and general best-toy queries. West Paw is mentioned in most of these answers and recommended in many, so the opportunity is depth and consistency rather than filling an obvious gap. These observations are not search volume or proof of missing content.

The agency would turn the strongest questions into buyer-content briefs, checking what the site already covers first. Where coverage exists, the brief would sharpen it; where it does not, we would propose a new page with approved facts.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed West Paw 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 scorecard, a scoped fact-review register and a page and source shortlist, each with an owner and evidence requirement. The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately.

The final month delivers buyer-content briefs and a fresh scorecard. Completed work is reported separately from measured answer outcomes, and no visibility gain is promised; the samples and their comparability limits stay visible throughout.

Methodology

Questions This Section Answers

  • How are West Paw 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 524 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 4923 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

Aug 2026

641

6

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

Sep 2026

645

6

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

Oct 2026

610

6

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

Nov 2026

524

6

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

Reliable results for July 2026 are unavailable. This is a gap in the history, not a result of zero.

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

The monthly samples differ, so comparisons show how recorded results changed, not why. Recommendation requires both endorsement and positive wording, and placement counts sit inside recommendations rather than adding to them. Answers can name several companies, so company counts do not sum to distinct answers.

Cited pages and disputed claims still need independent verification, and sentiment describes answer wording rather than customer satisfaction. The missing July results are a gap, not a zero.

Our first three priorities

First, verify the high-priority pricing conflict and the related lower-severity items against current primary sources, keeping ambiguous matches out of the correction queue. Second, prepare page briefs for the homepage and puzzle collection, where citations already appear alongside recommendations, using approved facts and buyer questions.

Third, review the most-cited third-party guides for current accuracy before any publisher request, and build buyer-content briefs around the durable-toy and breed questions. Each step has a named reviewer, and completed work will be reported separately from measured answer outcomes.

/ Learn More

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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