How AI Search Is Recommending Pet First Aid and Animal Wound Care: Monthly Trends

Executive Summary

Absorbine (W.F. Young, Inc.) extended its lead as the category leader in AI-driven recommendations for Pet First Aid and Animal Wound Care, reaching 54.6% valid recommendation coverage in September 2026, up from 47.1% in August 2026 and 40.3% in July 2026. The benchmark classifies Absorbine as a significant riser across the three-month series, based on a baseline-to-current gain of 14.3 points. Its lead over second-place Farnam (Central Garden & Pet) widened to 20.2 points in September.

Absorbine was the only brand the benchmark flagged for significant movement across the series on its primary coverage metric, and its related measures moved in the same direction: raw mention presence rate rose from 58.4% to 73.6%, recommended top-three rate rose from 32.6% to 47.2%, and recommended rank-one rate rose from 22.2% to 35.0%. No brand recorded a significant single-month move between August and September, making the latest month quiet even as the three-month series shows the leader's lead widening.

Farnam held second with 34.4% coverage in September, followed by Silver Honey (W.F. Young Brand) at 30.7%. Zymox (Pet King Brands LLC) continued a two-month decline, falling to 9.8% coverage in September from 15.4% in July, with its raw mention presence rate dropping from 17.2% to 9.8% across the same period. The gap between the leader and Zymox widened every month across the series, from 24.9 points in July to 44.8 points in September.

Each monthly run begins with 800 prompt-surface observations (497 unique questions in July 2026; 552 in August 2026; 533 in September 2026) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor in each month; 475 were relevant and 325 were irrelevant in July, 415 relevant and 385 irrelevant in August, and 419 relevant and 381 irrelevant in September. Public metrics are calculated on the 221 qualified observations in July, the 174 in August, and the 163 in September that survive both qualification stages.

Key Findings

Benchmark Context

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

The qualified base used for brand-level percentages shrank from 221 observations in July to 163 in September, a decline of 58 observations across the three months. August's intermediate base of 174 observations continued a downward drift that should be kept in mind when reading rate movements.

Benchmark-Level Metrics

AI Recommendation Trend

Absorbine's Lead Consolidates Across a Three-Month Series

September 2026 held the same rank order as July and August: Absorbine first, Farnam second, Silver Honey third, and Zymox fourth. Absorbine was the only brand whose coverage movement exceeded normal month-to-month variation across the baseline-to-current window; Farnam, Silver Honey, and Zymox each moved within their normal ranges, meaning the category-level shift came primarily from the leader's significant rise combined with Zymox's quieter but consistent decline.

What Changed This Month

Absorbine (W.F. Young, Inc.): Significant Riser Across the Series

Absorbine's valid recommendation coverage rose from 40.3% in July 2026 to 54.6% in September 2026, a gain of 14.3 points that the benchmark flags as significant. Month to month, coverage moved from 40.3% in July to 47.1% in August to 54.6% in September, extending the upward pattern each month without any single month on its own crossing the benchmark's significance flag.

Absorbine's placement quality moved alongside its coverage. Its recommended top-three rate rose from 32.6% in July to 47.2% in September, and its recommended rank-one rate rose from 22.2% to 35.0%, with rank-one placements rising from 49 to 57 on a smaller qualified base. Its raw mention presence rate rose from 58.4% to 73.6%.

The distinction to notice: Absorbine is not merely present more often; it is being recommended, and recommended first, at a higher rate. Its net sentiment rose to 0.8 in September from 0.7 in July.

Highest-priority diagnostic: Which prompts and surface families are driving Absorbine's rank-one placements, and which evidence sources are reinforcing those recommendations?

Farnam (Central Garden & Pet): Steady Gains Within Normal Range

Farnam's coverage rose from 29.9% in July 2026 to 34.4% in September 2026, a gain of 4.5 points that falls within the benchmark's normal month-to-month variation for this brand. Its rank-one rate rose from 7.2% to 12.3% across the series, with rank-one placements rising from 16 to 20 on a smaller qualified base.

Farnam's presence rate rose from 40.7% to 42.9%, a modest gain, while its top-three rate rose from 24.0% to 30.1%. The brand's absolute valid recommendation count fell from 66 in July to 56 in September alongside the smaller observation base, but its share of that base rose.

Farnam is gaining ground steadily without a single month that the benchmark flags as unusual, holding second place as the leader pulls away.

Highest-priority diagnostic: Which prompt clusters are Farnam winning or losing to Absorbine, and where does Farnam take rank-one placement?

Silver Honey (W.F. Young Brand): Coverage Rose Despite a Smaller Base

Silver Honey's coverage rose from 25.3% in July 2026 to 30.7% in September 2026, a gain of 5.4 points. Its rank-one rate rose from 5.9% to 10.4%, with rank-one placements rising from 13 to 17 even as its qualified base shrank. Its top-three rate rose from 19.5% to 25.8%.

Silver Honey's raw mention presence rate rose modestly from 33.9% to 36.8%, and its net sentiment held at 0.9, one of the highest positive sentiment scores in the category, trailing only Zymox's 1.0.

Silver Honey's gains came from being recommended within a similar presence footprint, meaning the brand converted a higher share of its appearances into valid recommendations.

Highest-priority diagnostic: Which surfaces are converting Silver Honey's presence into valid recommendations, and is this concentration durable?

Zymox (Pet King Brands LLC): Two-Month Decline in Presence

Zymox's valid recommendation coverage fell from 15.4% in July 2026 to 9.8% in September 2026, a decline of 5.6 points. Its raw mention presence rate fell from 17.2% to 9.8%, a 7.4-point drop across the series. Absolute present count fell from 38 to 16, and valid recommendation count fell from 34 to 16.

Zymox's decline is a presence story, not a sentiment story: its net sentiment rose to 1.0 in September from 0.9 in July, and its average recommended rank improved to 1.5. When Zymox is recommended, it is recommended favorably and early, but it is surfacing far less often.

The benchmark does not establish why presence declined. The category-level gaps widened every month between Zymox and each of the other three brands, with the Absorbine-Zymox gap growing from 24.9 points in July to 44.8 points in September.

Highest-priority diagnostic: Which prompts and surfaces stopped surfacing Zymox, and which competitor appears in its place when it is absent?

The Gap Between the Leader and the Trailing Brands Widened Every Month

The three largest gaps in the category each widened in every month of the series. The gap between Absorbine and Zymox grew from 24.9 points in July to 44.8 points in September. The gap between Farnam and Zymox grew from 14.5 to 24.6 points. The gap between Silver Honey and Zymox grew from 9.9 to 20.9 points.

Zymox fell further behind all three brands in every successive month. The benchmark does not establish why.

Buyer-Intent Interpretation

In September 2026, all 163 qualified observations fell into the Brand Recommendation cluster. There were zero qualified observations in the Pricing & Value or Multi-Brand Comparison clusters. The public benchmark can currently speak to which brand AI systems recommend, but it cannot yet answer questions about how AI positions brands on price, value, or direct comparison. The evidence on those commercial questions remains outside the qualified set.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

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

Report-Specific Interpretation Notes

• The qualified benchmark set shrank from 221 observations in July 2026 to 163 in September 2026; percentages are calculated on these smaller denominators. For Absorbine, the valid recommendation count held flat at 89 while its coverage rate rose from 40.3% to 54.6%, illustrating how a shrinking denominator can raise a rate even without a matching gain in the underlying count.
• Differences between the months' funnels (497 vs. 533 unique questions; 475 vs. 419 relevant prompts) mean part of the change may reflect what was asked, not just how brands answered.
• The series analysis classified Absorbine as a significant riser across the baseline-to-current window, while the September month itself was quiet, with no brand posting a significant single-month move.
• All four tracked brands appear in the benchmark, and small observation counts for some brands warrant caution in interpreting their rates.

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 raise questions that the benchmark alone cannot answer. Which high-intent prompts is each brand winning? When a brand loses a recommendation, which competitor takes its place? What attributes do AI systems associate with each brand, and which external sources are shaping those associations? For a brand like Zymox, the question is why a brand with strong sentiment and average rank lost presence in consecutive months. For Absorbine, the question is which specific prompts and evidence sources are compounding its rank-one advantage.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It identifies the specific content, sources, and surfaces that drive recommendation outcomes for one brand.

Request an AI visibility audit