How AI Search Is Recommending Pet Insurance: Monthly Trends

Executive Summary

Pets Best remains the category leader for AI search recommendations in pet insurance, holding 60.6% valid recommendation coverage in September 2026. The lead over the next brand, Spot at 50.4%, stands at 10.2 points. While Pets Best's coverage dipped slightly from 64.1% in July to 60.6% in September, the brand's leadership position stayed intact, with the gap to second place actually narrowing from a 16.0-point lead in July to 10.2 points now because challengers moved up rather than the leader retreating.

September 2026 was a month of significant repositioning. Pumpkin was the strongest upward mover on the baseline-to-current measure, climbing 5.2 points from 27.6% in July to 32.8% in September, with a 6.8-point jump from August marking one of the category's largest single-month gains, trailing only Spot's 7.6-point rebound the same month. MetLife also rose 4.9 points from 31.9% to 36.8% across the period. On the downside, four brands recorded significant declines since July: Figo fell 7.0 points to 22.0%, Embrace dropped 6.0 points to 42.2%, Trupanion declined 5.3 points to 42.8%, and Nationwide slipped 4.6 points to 11.3%.

The month-over-month picture shows a category in motion after August's contraction. Spot rebounded sharply with a 7.6-point gain from 42.8% in August to 50.4% in September, and Pumpkin's 6.8-point rise was also significant. These gains contrast with continued softening at Trupanion, which lost 4.9 points from August to September. The result is a more compressed upper tier, with four brands now clustered between 36.8% and 50.4% coverage, compared with July's wider spread around Pets Best's dominant position.

Each monthly run begins with 800 prompt-surface observations (510 unique questions in July 2026; 569 in August; 574 in September) across the benchmark's defined AI/search surface universe. Of those, all 800 mentioned a tracked brand or competitor in each month; 794 were relevant and 6 were irrelevant in July, versus 797 relevant and 3 irrelevant in August, and 796 relevant and 4 irrelevant in September. The public metrics use the 724 qualified observations in July, 677 in August, and 696 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 surface breadth of six holds across both months, meaning the brand-level metrics below are computed against a consistent set of AI/search surface families even as the total observation count shifted between periods.

Benchmark-Level Metrics

The qualified observation count was 696 in September, between July's 724 and August's 677. August marked the low point in the series, with the September funnel reserving 100 observations versus 120 in August. The September percentages are calculated on a set that is slightly smaller than July's but larger than August's, a detail worth holding when comparing across the three months.

AI Recommendation Trend

Four Brands Cluster Behind the Leader as the Category Compresses

Four brands moved beyond normal month-to-month variation from July to September: Embrace, Figo, Nationwide, and Trupanion all declined significantly, while Pumpkin rose significantly. The remaining five brands moved within expected ranges across the period, meaning the category-level shift came from concentrated declines at multiple established brands offset by gains concentrated in Pumpkin and, from August to September, Spot and MetLife.

What Changed This Month

Pets Best

Pets Best retains the leadership position in September 2026, with valid recommendation coverage of 60.6%, down 3.5 points from 64.1% in July. The decline did not exceed the significance threshold, and the brand rebounded 2.1 points from August's 58.5%, suggesting the August dip was not the start of a sustained slide.

The placement picture is mixed across the period. Top-three recommendation rate fell from 36.3% in July to 31.5% in September, a decline that approached but did not cross the significance threshold. Rank-one placement, however, fell more sharply, dropping 3.3 points from 7.3% to 4.0%, a significant decline. Presence held comparatively firm, with Pets Best mentioned in 83.8% of observations in September versus 86.2% in July, and the brand recorded 422 valid recommendations in September (down from 464 in July but up from 396 in August).

The distinction the reader should notice: Pets Best remains the most visible and most recommended brand in the category, but its hold on the most valuable position, rank one, has weakened meaningfully since July. The brand still leads on raw recommendation frequency, yet the September data shows AI systems less likely to place Pets Best first when they do recommend it.

Highest-priority diagnostic: Which prompt types or AI surfaces drove the decline in rank-one placement from July to September, and which brand took the top spot when Pets Best lost it?

Pumpkin

Pumpkin was the category's strongest riser in September 2026, with valid recommendation coverage climbing 5.2 points from 27.6% in July to 32.8% in September, a significant gain. The August-to-September move was even sharper, with Pumpkin up 6.8 points from 26.0%, one of the largest single-month gains recorded in the current benchmark record, trailing only Spot's 7.6-point rebound in the same month.

The rise was driven by substantially broader presence. Pumpkin's raw mention rate jumped 10.0 points from 40.9% in July to 50.9% in September, a significant increase, and the brand recorded 228 valid recommendations in September (up from 200 in July and 176 in August). Placement quality improved more modestly, with top-three rate moving from 6.5% to 8.9%, a gain that did not reach significance. Rank-one placement actually slipped from 1.8% to 1.3%.

The reader should notice the structure of Pumpkin's gain: the brand became more present across AI answers, appearing in more conversations, but its rise in coverage came from breadth rather than from winning the most coveted top positions. With 9 rank-one placements in September (down from 13 in July), Pumpkin's growth is real but has not yet translated into category-leading placement quality.

Highest-priority diagnostic: Which AI surfaces or prompt types account for Pumpkin's expanded presence, and what evidence sources support its more frequent appearance in recommendations?

Trupanion

Trupanion declined 5.3 points in valid recommendation coverage from 48.1% in July to 42.8% in September, a significant drop. Despite the decline, Trupanion holds third place in September, narrowly ahead of Embrace, whose steeper fall pushed it into fourth. The August-to-September erosion continued, with Trupanion down 4.9 points from 47.7%, leaving the brand with a two-month downward streak.

Presence fell sharply. Trupanion's raw mention rate dropped 10.6 points from 68.4% in July to 57.8% in September, a significant decline, and valid recommendations fell from 348 to 298 across the period. Placement quality tells a more nuanced story: top-three rate eased from 19.3% to 16.0%, but rank-one rate actually rose 2.5 points from 3.7% to 6.2%, a significant improvement. Trupanion recorded 43 rank-one placements in September, up from 27 in July, even as its overall coverage fell.

The key distinction is that Trupanion is being mentioned and recommended in fewer answers overall, yet when AI systems do recommend it, they place it first more often. The brand's problem in September is breadth of consideration, not the quality of its placement when considered. Net sentiment remained strong at 0.7, indicating the decline is not tied to negative framing by AI systems.

Highest-priority diagnostic: Which prompts that previously surfaced Trupanion now omit it entirely, and which competitor captures the mentions Trupanion lost?

Embrace

Embrace declined 6.0 points in valid recommendation coverage from 48.2% in July to 42.2% in September, a significant drop that moved the brand from a near-tie with Trupanion for third place in July into a clearly defined fourth in September, still trailing Trupanion's 42.8%. The decline continued from August, when Embrace sat at 45.5%, giving the brand a two-month downward streak.

The erosion is consistent across presence and placement. Raw mention rate fell 5.9 points from 74.3% to 68.4%, a significant decline, and top-three rate dropped from 18.6% to 13.4%, also significant. Valid recommendations fell from 349 in July to 294 in September. Rank-one placement held comparatively steady, easing just 0.1 points from 2.8% to 2.7%, with 19 rank-one placements in September versus 20 in July.

Embrace's decline is broad-based rather than concentrated in one metric. The brand is less present, less frequently recommended in top-three positions, and slightly less often first in September than it was in July. The stability of rank-one placement suggests AI systems that do lead with Embrace have not changed their view, but fewer answers now feature the brand prominently.

Highest-priority diagnostic: Which evidence sources or prompt categories reduced Embrace's presence and top-three recommendations, and did any specific competitor absorb its lost placements?

Figo

Figo declined 7.0 points in valid recommendation coverage from 29.0% in July to 22.0% in September, the largest baseline-to-current drop in the category and a significant move. The August-to-September change was minimal at 0.2 points, indicating the bulk of Figo's decline happened in August, when coverage fell 6.8 points from 29.0% to 22.2%.

Presence fell sharply. Figo's raw mention rate dropped 9.1 points from 46.6% in July to 37.5% in September, a significant decline, and valid recommendations fell from 210 to 153. Placement quality weakened as well: top-three rate fell from 6.6% to 3.2%, a significant drop, while rank-one placements slipped from 16 to 9, taking the rate from 2.2% to 1.3%, a decline that did not reach significance.

The category view shows Figo's competitive position eroding on multiple fronts. The brand fell 12.2 points behind Pumpkin since July, reversing a 1.4-point lead into a 10.8-point deficit, and fell 14.8 points behind MetLife, widening from a 2.9-point gap. Figo's net sentiment held at 0.7, so the change is about how often AI systems surface the brand, not how they frame it when they do.

Highest-priority diagnostic: Which prompts that recommended Figo in July now omit it, and what changed in the underlying evidence sources those AI systems draw upon?

Spot and MetLife

Spot rebounded strongly in September. Valid recommendation coverage rose 7.6 points from 42.8% in August to 50.4%, a significant gain that returned the brand to its July level of 49.3% and moved Spot from fourth to second place. Raw mention presence rose 5.1 points from 69.5% to 74.6% across the period, and rank-one rate improved from 2.2% in August to 4.0%. Spot's rank-one rate of 4.0% in September now matches Pets Best, suggesting the brand is winning first position as often as the leader even while trailing on overall coverage.

MetLife also gained ground, with coverage rising 4.9 points from 31.9% in July to 36.8% in September. The August-to-September move was sharper at 6.1 points, a significant gain. MetLife's presence rose 8.3 points from 49.2% to 57.5% across the period, though top-three and rank-one rates both declined, indicating the brand's growth came from broader inclusion rather than stronger placement. With no single competitor absorbing these gains, the September picture suggests AI systems broadened the set of brands they present as viable options.

Highest-priority diagnostic for Spot: Which surfaces restored Spot's coverage in September, and does the rise in rank-one placements reflect new evidence sources or a return of prior ones?

Highest-priority diagnostic for MetLife: Which prompt categories drove MetLife's expanded presence, and why did placement quality decline even as coverage rose?

Buyer-Intent Interpretation

All qualified observations in July, August, and September 2026 fell into the Brand Recommendation cluster. The public benchmark did not capture qualified observations in the Pricing & Value or Multi-Brand Comparison clusters in any of the three months, so the current analysis speaks to which brands AI systems recommend, not how they frame price or conduct head-to-head comparisons. Those commercial questions remain open for company-level analysis, and the category's comparatively high share of factual and pricing-shaped responses in September suggests some of those answers may not have met the qualification bar for inclusion.

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 September 2026 qualified observation count (696) sits between July (724) and August (677); percentage movements across all three months should be read with these differing denominators in mind.
• Brands with smaller valid recommendation counts warrant care: AKC recorded 86 valid recommendations and Nationwide 79 in September, so percentage movements for both should be read with the small count in mind.
• The benchmark separates raw collection from qualified analysis; all percentages above use the qualified denominator.
• Movement across months or between consecutive months identifies changes worth investigating; it does not by itself establish cause.
• Directional analysis is reported as up or down points between months, not as an evaluation of brand performance.

Next Step

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

Beneath the aggregate percentages sit the questions that drive strategy: which high-intent prompts a brand wins, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers. The September 2026 movements for Pumpkin, Trupanion, Embrace, and Spot each raise specific diagnostic questions that only prompt-level inspection can answer.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy.

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