Recommendation Intelligence Research™

The State of AI Recommendations in Pets

We asked one AI model 20 high-intent pet shopping questions, 20 times each. Then we checked the same thing we checked in beauty, supplements, and coffee, and pets gave a different, sharper answer.

Atom Foundry · June 2026 · Fourth in the Recommendation Intelligence Research™ series
4,000
Recommendations
405
Distinct brands
20
Shopping intents
400
Prompt-runs
How we measured it

Methodology, up front

Same method as the first three reports, so all four are directly comparable. Everything below is computed from real captured responses. Nothing is estimated or projected.

Category: Pets
Model: one model (gpt-4o-mini)
Intents: 20 high-intent prompts
Runs per intent: 20
Prompt-runs total: 400
Recommendations captured: 4,000

Recommendation Share™

A brand's share of all recommendations captured. The whole field sums to 100 percent.

Recommendation Frequency™

In what percent of the 400 prompt-runs the brand appeared at least once.

Recommendation Position™

Average rank in the answer when the brand appeared. Lower is better.

Marketplaces are not brands. Retailers and marketplaces (Chewy, Petco, Amazon, PetSmart, Frisco) were separated out and excluded from the brand-level analysis. The contest measured here is between single brands and their own stores. A note on pets: the biggest food names (Purina, Royal Canin, Hill's, Taste of the Wild) are not in our store index, so they appear off-index and stay out of the correlation. One brand, Wellness, was dropped from the on-index set after we found its name had auto-matched to an unrelated health-directory domain; we report it off-index rather than attach a wrong store. Other limits: one model, one category, one point in time. Each intent ran 20 times. Brands map to the real stores we measure where a match exists; the rest are off-index, never invented.
Who AI recommends

The pet recommendation leaderboard

Top 20 brands by share of voice across all 4,000 recommendations, with retailers excluded. The last column is each brand's real AI Commerce Score™ from our index. Note how many of the most recommended names are either off-index or sit deep in the red.

#Brand Share™ Freq™ Pos™ AI Commerce Score™
1 Blue Buffalo 2.8%
 27.8% 3.9 30AI Invisible
2 PetFusion off-index 2.7%
 25.0% 4.2 —Off-index
3 Purina Pro Plan off-index 2.7%
 26.8% 3.4 —Off-index
4 Merrick 2.5%
 24.8% 6.5 42AI Invisible
5 Wellness off-index 2.3%
 22.8% 5.0 —Off-index
6 Royal Canin off-index 2.1%
 20.8% 1.6 —Off-index
7 Hill's Science Diet off-index 2.1%
 20.5% 1.9 —Off-index
8 PetSafe off-index 2.1%
 20.5% 4.0 —Off-index
9 Vet's Best off-index 1.9%
 18.8% 5.9 —Off-index
10 Taste of the Wild off-index 1.8%
 18.0% 6.7 —Off-index
11 BarkBox off-index 1.5%
 15.3% 6.2 —Off-index
12 Zesty Paws off-index 1.4%
 14.3% 3.4 —Off-index
13 Canidae 1.2%
 11.5% 7.0 44AI Invisible
14 Burt's Bees 1.0%
 10.0% 4.9 34AI Invisible
15 Big Barker off-index 1.0%
 10.0% 1.3 —Off-index
16 Ruffwear 1.0%
 10.0% 4.7 66Low
17 Wellness CORE off-index 1.0%
 9.8% 5.3 —Off-index
18 KONG 1.0%
 9.5% 3.2 66Low
19 Orijen 1.0%
 9.5% 3.3 14AI Invisible
20 Petmate off-index 0.9%
 8.8% 4.3 —Off-index
The central finding

In pets, being recommended is if anything a sign of a worse store

In the first three categories the relationship between recommendation and readiness was zero. Pets is different. Here the correlation between Recommendation Frequency™ and AI Commerce Score™ is r = -0.366 (n = 39), a weak but marginally significant negative relationship. The more often AI recommends a pet brand, the slightly worse its store tends to be. Each dot is a single-brand store.

02550751000%5%10%15%20%25%30% Blue Buffalo: 27.8% frequency, score 30Merrick: 24.8% frequency, score 42Canidae: 11.5% frequency, score 44Ruffwear: 10.0% frequency, score 66Burt's Bees: 10.0% frequency, score 34Orijen: 9.5% frequency, score 14KONG: 9.5% frequency, score 66Acana: 5.5% frequency, score 57Kurgo: 5.5% frequency, score 61Benebone: 5.0% frequency, score 79Catit: 5.0% frequency, score 38World's Best Cat Litter: 5.0% frequency, score 52Ollie: 5.0% frequency, score 51West Paw: 5.0% frequency, score 63PetPlate: 5.0% frequency, score 49The Farmer's Dog: 5.0% frequency, score 58Nylabone: 5.0% frequency, score 48Nom Nom: 5.0% frequency, score 49Just Food For Dogs: 4.3% frequency, score 62A Pup Above: 3.3% frequency, score 53Solid Gold: 3.0% frequency, score 14Zee.Dog: 2.0% frequency, score 51Greenies: 1.8% frequency, score 55Orvis: 1.3% frequency, score 56Zignature: 1.3% frequency, score 50Outward Hound: 1.0% frequency, score 48Pawstruck: 0.8% frequency, score 72Petlibro: 0.5% frequency, score 51Casper: 0.5% frequency, score 73Petcube: 0.5% frequency, score 64Litter-Robot: 0.5% frequency, score 62Brentwood Home: 0.5% frequency, score 69Spot and Tango: 0.3% frequency, score 56L.L. Bean: 0.3% frequency, score 68Vivo: 0.3% frequency, score 41Hello Fresh: 0.3% frequency, score 56Earth Animal: 0.3% frequency, score 56Advantage: 0.3% frequency, score 37Diggs: 0.3% frequency, score 61 Blue BuffaloBurt's BeesBeneboneRuffwearCanidaeMerrickOrijenKONG Recommendation Frequency™ (percent of prompts) AI Commerce Score™
Highly (85+)
Moderately (70 to 84)
Low (50 to 69)
AI Invisible (under 50)
The pet-food establishment dominates on fame. Blue Buffalo (27.8 percent of prompts, score 30), Merrick (24.8 percent, score 42), and Purina Pro Plan (26.8 percent, not even in our index) win the most recommendations while their stores are weak or absent. Meanwhile the best-built stores in the set, Benebone (79), Casper (73), and Pawstruck (72), barely appear at all.

This is the clearest inversion we have measured. The legacy food giants AI grew up on dominate the answers, and the modern direct-to-consumer brands building the most readable stores are the ones it overlooks. The average AI Commerce Score™ across all on-index recommended brands is just 52.7.

Four categories now. Beauty came in at r = 0.17, supplements at r = -0.015, coffee at r = 0.019, and pets at r = -0.366. Across more than 16,000 recommendations, recommendation frequency is never positively related to store readiness. In three categories the link is zero; in pets it tilts negative. Being recommended is a sign of fame, not of a better store.
What maps to a real store

Brands, not retailers

Pets is the most marketplace-driven category we have measured. Retailers like Chewy, Petco, and Amazon took 7.1 percent of recommendations, more than in beauty, supplements, or coffee. And only 19.8 percent of recommendations map to a single-brand store we measure, the lowest share yet.

19.8%
of recommendations map to a single-brand store we actually measure (on-index)
7.1%
go to retailers and marketplaces, separated out and kept entirely out of the brand analysis

Two things drive that low on-index share. So much of pet commerce runs through Chewy and Petco rather than brand stores, and the biggest brands of all, Purina, Royal Canin, and Hill's, are not in our index. They are recommended on pure brand fame, not because an agent read and rated their store.

What it means

Visibility is not recommendation, and recommendation is not readiness

Today AI recommends from memory. It reaches for the names it saw most during training, which in pets means the legacy food giants, even when their stores are weak or absent and the best modern stores go unnamed. That bias is baked in, and it is temporary. As AI shopping moves from recalling names to live retrieval and agents that browse, compare, and check out, the advantage shifts to the stores an agent can actually read, trust, and act on.

That is the gap this research exposes and the one the Recommendation Intelligence Framework™ is built to close: AI Readability, AI Understanding, AI Trust, Recommendation Intelligence, and Decision Confidence. The brands coasting on fame today are the ones with the most to lose when the model changes. The modern brands building readable, trustworthy, machine-legible stores now are the ones that keep the recommendation when memory stops being enough.

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