CiteWorks Studio

Primal Pet Foods AI Market Strategy Report - Raw Freeze-Dried and Biologically Appropriate Pet Food

Mark HuntleyBy Mark HuntleyFounder and CEO
11 minutes read

Key Takeaways

  • Primal Pet Foods appeared in 14.29% of qualified AI answers but earned valid recommendation coverage of 10.41%, showing a clear gap between mention and shortlist inclusion.
  • When the brand is recommended, it performs well on quality metrics, with a 2.65 average recommended rank and a 0.8644 net sentiment score across 59 mentions.
  • First-position visibility is the main weakness: Primal Pet Foods earned rank-one placement in just 2 of 413 qualified observations, or 0.48%.
  • Google AI Mode and ChatGPT drive most recommendation activity, while Copilot showed no presence and Gemini and Perplexity contributed little recommendation value.

Answer Capsule

Primal Pet Foods holds a real but narrow position in AI-generated recommendations for raw freeze-dried and biologically appropriate pet food. In September 2026 the brand appeared in 14.29% of qualified AI answers and earned valid recommendation coverage of 10.41%, placing it fourth of seven tracked brands. Its clearest strength is recommendation quality when it does appear, with an average recommended rank of 2.65 and a net sentiment score of 0.8644. Its clearest weakness is scale: it converts presence into recommendations far less often than category leaders, and it holds almost no first-position recommendations. The clearest opportunity is closing the gap between being mentioned and being shortlisted in the category's single active discovery cluster.

Who This Report Is For

This report is written for Primal Pet Foods leadership, brand and growth teams, and retail or distribution partners who need to understand how the brand is positioned when buyers ask AI systems which raw and freeze-dried pet foods to consider.

Report Card

Field

Value

Report type

AI Company Market Strategy Report

Target company

Primal Pet Foods

Category / market studied

Raw Freeze-Dried and Biologically Appropriate Pet Food

Reporting month

September 2026

AI platforms tracked

6 (ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, AI Mode)

Public high-intent clusters

1 active (Best Raw & Freeze-Dried Pet Food Discovery)

AI observations analyzed

413 qualified observations

Competitors tracked

6

Executive Summary

Primal Pet Foods is visible in AI answers but under-recommended relative to its presence. The September 2026 benchmark recorded 59 mentions across 413 qualified observations, a raw mention presence rate of 14.29%, yet only 43 of those observations produced a valid recommendation, a valid recommendation coverage rate of 10.41%. That gap between being named and being chosen is the defining feature of the brand's current AI position.

The brand's framing is strong. Of its 59 mentions, 51 were positive, 8 were neutral, and none were negative, producing a net sentiment score of 0.8644. That places Primal Pet Foods among the more favorably framed brands in the category, ahead of Acana (Champion Petfoods) at 0.8039 and Orijen (Champion Petfoods) at 0.8338, and behind only Stella & Chewy's at 0.8789 and Smallbatch Pets at 1.0 on a much smaller base.

Recommendation depth is where the brand separates from the leaders. Primal Pet Foods recorded a top-three rate of 6.54% and a rank-one rate of 0.48%, meaning it earned first position in just 2 of 413 qualified observations. Orijen (Champion Petfoods) converted 59.81% coverage into a 16.95% rank-one rate over the same period. The brand is being referenced in the same conversations as the category leaders but is rarely the answer the AI system leads with.

The strongest cluster is also the only active cluster. All 413 qualified observations in September 2026 fell into the Brand Recommendation class, covering the Best Raw & Freeze-Dried Pet Food Discovery cluster. Primal Pet Foods earned a 6.54% top-three rate and a 2.65 average recommended rank within it, which indicates that when the brand does enter a shortlist, it tends to land near the top of that shortlist rather than at the bottom.

Platform behavior is uneven. Google AI Mode carried the largest share of the brand's recommendation activity, with a 17.97% valid recommendation coverage rate and 23 valid recommendations, followed by ChatGPT at 14.63% coverage. Copilot produced no mentions at all for Primal Pet Foods in the September dataset, and Gemini and Perplexity produced only marginal presence with no rank-eligible recommendation value.

The clearest gap is conversion, not awareness. Primal Pet Foods is present in roughly one in seven qualified AI answers but is shortlisted in roughly one in ten. Closing that distance, particularly on Copilot and in first-position placements, is the most direct path to stronger recommendation-stage visibility in this category.

What Primal Pet Foods Is Winning

Primal Pet Foods holds a genuine quality advantage in how it is framed when it appears. A net sentiment score of 0.8644 across 59 mentions, with zero negative mentions recorded, indicates that AI systems describe the brand in favorable or neutral terms rather than as a cautionary comparison point. That is a meaningful asset in a category where several brands carry at least one negative mention.

The brand also converts efficiently when it does enter a shortlist. Its average recommended rank of 2.65 is the second-best among tracked brands, behind only Orijen (Champion Petfoods) at 2.46 and ahead of Stella & Chewy's at 2.76. When Primal Pet Foods earns a recommendation, it typically lands in the top three rather than deeper in the list.

Google AI Mode is the strongest platform signal. The brand recorded 23 valid recommendations there, a 17.97% coverage rate, and a 10.16% top-three rate, making it the single largest contributor to the brand's recommendation footprint. ChatGPT is the second-strongest surface, with 6 valid recommendations and a 14.63% coverage rate.

Where Primal Pet Foods Has the Clearest AI Visibility Gaps

The primary gap is recommendation conversion. Primal Pet Foods appeared in 14.29% of qualified observations but earned a valid recommendation in only 10.41%. That 3.88-point difference represents mentions where the brand was named as context, comparison, or background rather than as a recommended option. Orijen (Champion Petfoods) shows the opposite pattern, converting an 85.96% presence rate into 59.81% recommendation coverage, a much tighter relationship between being seen and being chosen.

First-position placement is the sharpest weakness. Primal Pet Foods earned rank-one status in 2 of 413 qualified observations, a 0.48% rate. Stella & Chewy's earned 41 rank-one placements, a 9.93% rate, and Orijen (Champion Petfoods) earned 70, a 16.95% rate. The brand is competing for shortlist inclusion but is almost never the answer an AI system leads with when a buyer asks for a single best option.

Copilot is an absent surface. Primal Pet Foods recorded zero mentions across the 29 Copilot observations in the September dataset. Champion Petfoods, by contrast, recorded a 68.97% presence rate and a 20.69% valid recommendation coverage rate on the same platform. That is a platform-specific gap where a competitor is being recommended and Primal Pet Foods is not appearing at all.

Gemini and Perplexity contribute almost nothing to the brand's recommendation position. Gemini produced 4 mentions and 1 valid recommendation with no rank-eligible value. Perplexity produced 5 mentions and 2 valid recommendations, also with no rank-eligible value. Both surfaces are effectively neutral for the brand today, which means the recommendation footprint is concentrated almost entirely in Google AI Mode and ChatGPT.

Biggest Opportunity

The single clearest opportunity is converting existing presence into shortlist placement in the Best Raw & Freeze-Dried Pet Food Discovery cluster. Primal Pet Foods is already being mentioned in roughly one in seven qualified AI answers, which means the retrieval layer is finding the brand. The gap is in the recommendation layer, where the brand is named but not selected.

Because the brand's average recommended rank is 2.65 when it does earn a recommendation, the underlying framing is already strong. The work is not to repair a negative narrative but to make the brand's evidence easier for AI systems to retrieve and cite as a recommended option rather than a referenced one. That means strengthening the owned and third-party source layer around the specific discovery prompts where the brand currently appears without being shortlisted.

Competitive Landscape

Questions This Section Answers

  • Who leads AI recommendations in raw and freeze-dried pet food, and where does Primal Pet Foods rank?
  • How does Primal Pet Foods compare with Orijen and Stella & Chewy's on top-three and rank-one placement?
  • Why is Primal Pet Foods' average recommended rank stronger than its shortlist frequency?

Orijen (Champion Petfoods) holds dominant recommendation power in this category, with Stella & Chewy's as the strongest challenger and Acana (Champion Petfoods) as the third brand with meaningful shortlist presence. Primal Pet Foods sits in the second tier, ahead of Instinct Pet Food and Champion Petfoods on recommendation rate but well behind the top three on both top-three and rank-one placement.

Brand

Top-3 rate

Rank-1 rate

Avg recommended rank

Sentiment

Orijen (Champion Petfoods)

26.63%

16.95%

2.46

0.8338

Stella & Chewy's

19.37%

9.93%

2.76

0.8789

Acana (Champion Petfoods)

14.04%

0.48%

3.49

0.8039

Primal Pet Foods

6.54%

0.48%

2.65

0.8644

Instinct Pet Food

4.84%

0.24%

3.21

0.8214

Champion Petfoods

1.21%

0.48%

2.00

0.6585

Smallbatch Pets

0.97%

0.48%

3.14

1.0000

Average recommended rank covers rank-eligible recommendations only.

Primal Pet Foods ranks fourth by top-three rate and shares the fourth-lowest rank-one rate in the tracked set. Its average recommended rank of 2.65 is the second-best in the table, which shows that the brand's problem is frequency of shortlist entry rather than position quality once it enters.

Prompt Evidence

Google AI Mode / Best Raw & Freeze-Dried Pet Food Discovery Prompt: "What is the healthiest dog food for a dog?" Result: Primal Pet Foods appeared within the recommendation set and earned rank-eligible placement, contributing to its strongest platform coverage rate of 17.97%.

ChatGPT / Best Raw & Freeze-Dried Pet Food Discovery Prompt: "best dog food" Result: The brand was mentioned and earned a valid recommendation in a subset of runs, with a 14.63% coverage rate and no first-position placements recorded on this surface.

Copilot / Best Raw & Freeze-Dried Pet Food Discovery Prompt: "dog food brands" Result: Primal Pet Foods did not appear in any of the 29 Copilot observations, while Champion Petfoods recorded a 68.97% presence rate on the same surface.

Perplexity / Best Raw & Freeze-Dried Pet Food Discovery Prompt: "raw dog food" Result: The brand appeared in 5 of 53 Perplexity observations with 2 valid recommendations, but earned no rank-eligible placement, indicating presence without recommendation depth.

What CiteWorks Studio Would Do Next

Questions This Section Answers

  • What phases would close the gap between mentions and recommendations for Primal Pet Foods?
  • Which prompts and evidence layers would be prioritized to move from mention to shortlist?

Phase 1: AI Market Discovery Audit Map every prompt where Primal Pet Foods is mentioned but not recommended, and identify which competitors take the shortlist slot in each case.

Phase 2: Recommendation Readiness Plan Prioritize the discovery prompts with the highest commercial intent where the brand already has presence, and define the evidence needed to move from mention to shortlist.

Phase 3: Owned Answer Layer Buildout Strengthen the brand's own pages and structured content so AI systems can retrieve clear, citable answers about what Primal Pet Foods is, who it is for, and why it belongs in a raw and freeze-dried shortlist.

Phase 4: Citation and Authority Layer Development Build the third-party source footprint, including retailer, review, and editorial sources, that AI systems appear to draw on when forming recommendations in this category.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track presence, valid recommendation coverage, top-three rate, rank-one rate, and sentiment by platform each month to confirm whether the conversion gap is closing.

Why This Matters

AI systems are now where a meaningful share of buyer shortlists are formed. A brand that is mentioned but not recommended is visible without being chosen, which is a weaker position than it appears in a presence-only metric. Primal Pet Foods currently sits in that position: favorably framed, frequently referenced, and rarely the answer an AI system leads with.

The next move is not broader awareness. It is targeted correction of the prompt, page, and citation layers that determine whether the brand is retrieved as a recommended option or merely referenced as background. That work is specific, measurable, and directly tied to the gap between the brand's 14.29% presence rate and its 10.41% recommendation coverage.

Core Metrics

Metric

Value

Mentions

59

Valid recommendations

43

Top 3 recommendation count

27

Rank #1 recommendation count

2

Average recommended rank

2.65

Positive mentions

51

Neutral mentions

8

Negative mentions

0

Raw mention presence rate

14.29%

Valid recommendation coverage

10.41%

Top 3 recommendation rate

6.54%

Rank #1 recommendation rate

0.48%

Net sentiment score

0.8644

Strongest cluster by recommendation behavior

Best Raw & Freeze-Dried Pet Food Discovery

Strongest platform by recommendation behavior

Google AI Mode

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Primal Pet Foods in September 2026, that calculation is (51 × 1 + 8 × 0 + 0 × -1) / 59, which produces a score of 0.8644.

This matters because unclassified mention counts are misleading. A brand that appears 59 times could look strong on a presence metric alone, but that number says nothing about whether the brand was recommended, referenced neutrally, or raised as a caution. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal events, and counting them as if they were produces a distorted picture of competitive position.

Classified sentiment is required before interpreting AI visibility. Primal Pet Foods benefits from a clean sentiment profile with no negative mentions, which means its gap is a conversion problem rather than a reputation problem. That distinction changes the remediation strategy entirely.

Sentiment by Platform

Questions This Section Answers

  • Which AI platforms frame Primal Pet Foods most favorably?
  • On which platforms is Primal Pet Foods mentioned without being recommended?

Platform

Mentions

Positive

Neutral

Negative

Sentiment Score

Readout

Google AI Mode

28

27

1

0

0.9643

Strongest public recommendation signal

ChatGPT

7

6

1

0

0.8571

Present and recommended, no first-position placements

Perplexity

5

3

2

0

0.6000

Present as context, not recommendation

Gemini

4

1

3

0

0.2500

Positive, but sample too small

Copilot

0

0

0

0

N/A

No public presence in this packet

AI Overviews

15

14

1

0

0.9333

Present, but not recommendation-led

Methodology

  1. This report is a benchmark-based analysis of Primal Pet Foods within the Raw Freeze-Dried and Biologically Appropriate Pet Food category, produced from the September 2026 LLM Authority Index AI Market Discovery dataset.
  2. The reporting window is September 2026, with July 2026 and August 2026 used as comparison months where the benchmark provides them.
  3. Six AI surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. All six were represented in the September 2026 qualified set.
  4. The September 2026 run began with 800 prompt-surface observations and 565 unique questions, of which 704 were relevant and 96 were irrelevant to the vertical.
  5. The public denominator is 413 qualified observations, which is the figure used for all brand-level rates in this report.
  6. Seven brands were tracked: Primal Pet Foods, Orijen (Champion Petfoods), Stella & Chewy's, Acana (Champion Petfoods), Instinct Pet Food, Champion Petfoods, and Smallbatch Pets.
  7. One public cluster was active in September 2026, the Best Raw & Freeze-Dried Pet Food Discovery cluster, covering consideration-stage brand recommendation prompts. The Pricing & Value and Multi-Brand Comparison clusters carried zero qualified observations in the public series.
  8. A mention is counted when a brand appears anywhere in a qualified AI answer, regardless of whether it was recommended.
  9. A valid recommendation is counted only when the dataset marks the brand as a recommended option with rank eligibility. Neutral references, comparison anchors, and listed-only appearances are not counted as valid recommendations.
  10. Top-three rate and rank-one rate are calculated against the 413 qualified observations, not against the brand's own mention count.
  11. Average recommended rank covers rank-eligible recommendations only. A brand with no rank-eligible recommendations is shown as N/A.
  12. The benchmark records movement and placement, not causation. Month-over-month changes identify where attention is warranted but do not by themselves establish why a change occurred.

See Where AI Is Recommending Your Brand

The public benchmark shows where Primal Pet Foods stands in AI-generated recommendations across the category. A company-level AI visibility audit maps the specific prompts, surfaces, competitors, and evidence sources behind those numbers, and turns them into a prioritized plan for closing the gap between being mentioned and being recommended.

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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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