How AI Search Is Recommending Cat Food, Litter and Cat Care: Monthly Trends

Executive Summary

Across the two-month tracking window from July 2026 to August 2026, Tiki Cat has held the category lead throughout, extending its valid recommendation coverage from 60.2% to 63.0%. Weruva remains in second position, with coverage rising from 43.8% to 48.9%; the gap between the two brands narrowed from 16.4 points to 14.1 points.

August 2026 was a quiet month for the category: all ten tracked brands are classified as stable, with no brand's movement exceeding normal month-to-month variation. Weruva was the strongest upward mover, with valid recommendation coverage rising 5.1 points from 43.8% to 48.9%. Smalls also advanced 4.2 points to 46.3%. The largest decline came from Dr. Elsey's, which fell 3.5 points to 27.5%. Other movement included Pretty Litter and World's Best Cat Litter, both down 1.7 points, and Cat Person, down 0.1 points.

These changes extend the pattern already established in July: Tiki Cat and Weruva continue to lead the category, and Dr. Elsey's continues to lose ground relative to the top of the field. The category recorded 668 qualified observations in August 2026, compared with 681 in July 2026.

Each monthly run begins with 800 prompt-surface observations (582 unique questions in July, 630 in August) across the benchmark's defined AI/search surface universe. Of those, all 800 mentioned a tracked brand or competitor in both months; 781 were relevant and 19 were irrelevant in both months. The public metrics use the 681 qualified observations in July and 668 qualified observations in August that survive both qualification stages.

Key Findings

Benchmark Context

The benchmark separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

Benchmark-Level Metrics

AI Recommendation Trend

Tiki Cat Holds the Lead as the Upper Tier Tightens

Tiki Cat extended its lead in August 2026, reaching 63.0% valid recommendation coverage, up from 60.2% in July 2026. The gap between Tiki Cat and the next brand, Weruva, narrowed to 14.1 points as Weruva closed ground from 43.8% to 48.9%. No brand's movement this month exceeded normal month-to-month variation; the category-level change reflects a combination of several smaller movements across the field.

Weruva and Smalls posted the largest gains this month, and Dr. Elsey's recorded the largest decline, but all ten tracked brands remain classified as stable within their normal range of month-to-month movement.

What Changed This Month

Tiki Cat Extends Its Lead

Tiki Cat's valid recommendation coverage rose 2.8 points from 60.2% in July to 63.0% in August. Its top-three rate reached 44.2% (295 prompts), up from 43.2% (294 prompts) in July, and its rank-one rate rose to 15.1% (101 prompts), up from 13.2% (90 prompts). Raw mention presence also rose to 71.3% from 69.6%.

The brand's lead over Weruva narrowed from 16.4 points to 14.1 points, even as Tiki Cat's own coverage grew.

Next inspection: Which specific prompts drove the rank-one gains in August, and did they cluster on particular surfaces or question types?

Weruva Posts the Largest Gain

Weruva's valid recommendation coverage rose 5.1 points from 43.8% in July to 48.9% in August, the largest increase among tracked brands this month. Its raw mention presence rose 5.2 points to 57.6%, and its top-three rate improved 3.6 points to 32.8%. Rank-one coverage rose from 2.5% (17 prompts) to 3.6% (24 prompts).

The gain lifts Weruva to a 14.1-point gap behind Tiki Cat, putting it clearly ahead of Smalls at 46.3% and Dr. Elsey's at 27.5%.

Next inspection: What changed in the prompts where AI systems surfaced Weruva as a recommendation, and which surfaces contributed the largest share of the 5.1-point rise?

Smalls Gains Ground

Smalls rose 4.2 points from 42.1% in July to 46.3% in August, holding third position in the category. Its top-three rate climbed 2.5 points to 36.1% (241 prompts), while its raw mention presence rose 3.1 points to 48.0%. Notably, Smalls' rank-one rate fell 3.5 points to 22.3% (149 prompts), down from 25.8% (176 prompts) in July.

Smalls now trails Weruva by 2.6 points, a wider gap than in July when the difference was 1.7 points.

Next inspection: Why did rank-one placements decline while overall coverage and top-three presence rose, and which competing brand captured the displaced first positions?

Dr. Elsey's Slips Further

Dr. Elsey's valid recommendation coverage fell 3.5 points from 31.0% in July to 27.5% in August. Raw mention presence declined 3.1 points to 31.4%, and the rank-one rate fell 2.8 points to 13.6% (91 prompts).

The category data show a widening gap between Dr. Elsey's and the brands above it: the difference between Dr. Elsey's and Weruva moved from -12.8 points in July to -21.4 points in August, and versus Smalls from -11.1 to -18.8 points.

Next inspection: Which prompt categories or surfaces drove the 3.5-point decline, and which competitors gained the recommendation credit Dr. Elsey's lost?

Notable Gaps Continue to Widen

The distance between Pretty Litter and Weruva has grown across the two-month window, moving from -37.0 points to -43.8 points. This pattern is consistent with the widening separation recorded between Dr. Elsey's and the category's top two brands, described above.

Next inspection: Whether the widening gap reflects changes in where AI systems surface mid-tier brands, or shifts in the prompts themselves toward established options.

Buyer-Intent Interpretation

In August 2026, all 668 qualified observations fell into the Brand Recommendation cluster. There were no qualified observations in the Pricing & Value or Multi-Brand Comparison clusters. The public benchmark therefore measures discovery-and-consideration behavior well, but it cannot yet answer questions about price positioning, value perception, or head-to-head comparison outcomes in this category.

Brand Opportunity Summary

The benchmark identifies where attention is warranted across the brand set; a company-level analysis is needed to explain why individual brands move as they do.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations capturing the query, the AI surface used, the recommendation outcome, any rank or position, sentiment, and citations where exposed. Company-level analysis can go deeper into prompt patterns, competitor presence, surface-level variance, and evidence sources. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the CiteWorks Studio AI Industry Market Discovery research program. Key links:

• AI Industry Market Discovery
• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Movement in this report is directional. A change between months identifies where attention is warranted, but it does not by itself establish the cause of that change.
• Small counts matter. Brands like KitNipBox (5 valid recommendations) and Cat Person (6 valid recommendations) can show large percentage swings from very few prompts.
• The qualified denominator (668 observations in August) differs from the raw collection (800 prompt-surface observations). Brand-level percentages are calculated within the qualified set.
• No brand's movement this month exceeded normal month-to-month variation. The category is best read as stable, with several mid-tier shifts worth continued observation.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

The aggregate percentages in this report sit on top of individual prompt-level decisions. Which high-intent queries are won or lost, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers are all questions that the monthly benchmark surfaces but cannot answer on its own.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. Instead of tracking a single percentage, you can see the specific queries and surfaces where your brand wins, loses, or is absent, and what the AI systems say about you.

Request an AI visibility audit