Food & Beverage covers businesses that produce or sell food and drinks: specialty grocers, spice and coffee merchants, fresh produce delivery, regional products and supermarkets. AI assistants are asked where to buy a product, how to judge its quality and what a label means. Their answers combine producers' and shops' own pages with official sources on labels, origin and food safety, encyclopedic references and customer reviews.
What changed in September 2026
- Answers analyzed 1'500 (▼ 17% vs August 2026)
- First domain lesvergersdegally.com (4.87 per 100 answers), replacing economie.gouv.fr
- First platform Trustpilot (1.87 per 100 answers)
Months compared: September 2026 and August 2026. The platforms that rose and fell the most are listed just below.
Biggest movers in September 2026
Rises
Trustpilot1.67 to 1.87+0.20 pt
Falls
Wikipedia2.28 to 0.07-2.21 pt
Most cited domains in AI answers, Food & Beverage
9 of the 10 most cited domains in Food & Beverage (lesvergersdegally.com, thespicehouse.com and pause-fruitee.fr) do not appear among the 50 most cited domains of the whole panel.
How to read it: each bar is a domain; its length is its number of citations per 100 answers over the selected period and filters.
Domains ranked by citations per 100 answers, all periods combined.
| Rank | Rank change | Domain | Citations | per 100 answers | Share of citations | 12 months |
|---|---|---|---|---|---|---|
| 1 | Up 1 | 256 | 6.32 | 1.47% | Trend: 14.00 in Jul 2026, 4.87 in Sep 2026, high 14.00. | |
| 2 | Down 3 | 200 | 4.94 | 1.15% | Trend: 6.40 in Jul 2026, 4.20 in Sep 2026, high 6.40. | |
| 3 | Up 1 | 174 | 4.30 | 1.00% | Trend: 5.20 in Jul 2026, 4.33 in Sep 2026, high 5.20. | |
| 4 | Up 10 | 164 | 4.05 | 0.94% | Trend: 6.53 in Jul 2026, 4.60 in Sep 2026, high 6.53. | |
| 5 | Unchanged | 154 | 3.80 | 0.88% | Trend: 7.73 in Jul 2026, 3.07 in Sep 2026, high 7.73. | |
| 6 | Down 11 | 148 | 3.65 | 0.85% | Trend: 4.53 in Jul 2026, 2.80 in Sep 2026, high 4.53. | |
| 7 | Down 2 | 119 | 2.94 | 0.68% | Trend: 3.67 in Aug 2026, 3.53 in Sep 2026, high 3.67. | |
| 8 | Up 12 | 116 | 2.86 | 0.67% | Trend: 4.80 in Jul 2026, 3.00 in Sep 2026, high 4.80. | |
| 9 | Up 3 | 112 | 2.77 | 0.64% | Trend: 2.89 in Aug 2026, 4.00 in Sep 2026, high 4.00. | |
| 10 | out of top | 105 | 2.59 | 0.60% | Trend: 7.73 in Jul 2026, 2.61 in Aug 2026, high 7.73. | |
| 11 | Up 1 | 104 | 2.57 | 0.60% | Trend: 2.93 in Jul 2026, 2.73 in Sep 2026, high 2.93. | |
| 12 | Down 1 | 95 | 2.35 | 0.55% | Trend: 2.78 in Aug 2026, 3.00 in Sep 2026, high 3.00. | |
| 13 | Down 15 | 89 | 2.20 | 0.51% | Trend: 3.11 in Aug 2026, 2.20 in Sep 2026, high 3.11. | |
| 14 | new | 89 | 2.20 | 0.51% | Trend: 5.33 in Jul 2026, 3.27 in Sep 2026, high 5.33. | |
| 15 | Up 1 | 88 | 2.17 | 0.50% | Trend: 2.50 in Aug 2026, 2.87 in Sep 2026, high 2.87. | |
| 16 | Down 6 | 81 | 2.00 | 0.46% | Trend: 2.50 in Aug 2026, 2.40 in Sep 2026, high 2.50. | |
| 17 | Up 2 | 76 | 1.88 | 0.44% | Trend: 2.11 in Aug 2026, 2.53 in Sep 2026, high 2.53. | |
| 18 | out of top | 72 | 1.78 | 0.41% | Trend: 4.53 in Jul 2026, 2.11 in Aug 2026, high 4.53. | |
| 19 | out of top | 70 | 1.73 | 0.40% | Trend: 3.87 in Jul 2026, 2.28 in Aug 2026, high 3.87. | |
| 20 | new | 68 | 1.68 | 0.39% | Trend: 4.13 in Jul 2026, 2.47 in Sep 2026, high 4.13. |
Rankings are rebuilt from monthly rankings: the counts at the end of a list can be minimums. Industry: the business of the analyzed website, classified by Sorank. Data since July 2026. Rank change: rank in the September 2026 monthly list against August 2026 (new: absent from the August 2026 list). A dash: fewer than 1'000 answers in one of the two months in this scope, or absent from the September 2026 list. 12 months: monthly rate per 100 answers; gaps when the domain is out of the monthly list, hollow points for months under 1'000 answers.
Most cited platforms in AI answers, Food & Beverage
Trustpilot is the platform AI cites most in Food & Beverage (1.86 per 100 answers), though less than across all sectors over the same months (2.13).
How to read it: each bar is one of the tracked platforms; its length is its number of citations per 100 answers over the selected period.
| Rank | Rank change | Platform | per 100 answers | 12 months |
|---|---|---|---|---|
| 1 | Up 1 | 1.86 | Trend: 2.27 in Jul 2026, 1.87 in Sep 2026, high 2.27. | |
| 2 | Down 10 | 1.76 | Trend: 3.87 in Jul 2026, 0.07 in Sep 2026, high 3.87. | |
| 3 | Up 2 | 0.64 | Trend: 1.47 in Jul 2026, 0.40 in Sep 2026, high 1.47. | |
| 4 | Down 2 | 0.59 | Trend: 1.20 in Jul 2026, 0.33 in Sep 2026, high 1.20. | |
| 5 | Down 2 | 0.57 | Trend: 0.67 in Jul 2026, 0.33 in Sep 2026, high 0.72. | |
| 6 | Up 3 | 0.54 | Trend: 0.67 in Jul 2026, 0.53 in Sep 2026, high 0.67. | |
| 7 | Up 1 | 0.44 | Trend: 1.33 in Jul 2026, 0.33 in Sep 2026, high 1.33. | |
| 8 | Up 4 | 0.30 | Trend: 0.27 in Jul 2026, 0.40 in Sep 2026, high 0.40. | |
| 9 | Down 1 | 0.23 | Trend: 0.67 in Jul 2026, 0.07 in Sep 2026, high 0.67. | |
| 10 | Up 2 | 0.12 | Trend: 0.13 in Jul 2026, 0.20 in Sep 2026, high 0.20. |
Rank change: rank among the platforms cited in September 2026 against August 2026 (new: not cited in August 2026). A dash: fewer than 1'000 answers in one of the two months in this scope, or not cited in September 2026. 12 months: monthly rate per 100 answers, hollow points for months under 1'000 answers.
AI models compared
AI assistants do not agree on the first source in Food & Beverage: ChatGPT cites economie.gouv.fr first; Gemini cites epices-roellinger.com first; Perplexity cites lesvergersdegally.com first.
How to read it: left, how the citations split between the five models; right, each model's citations per 100 answers, month by month.
First source of each AI model in Food & Beverage
| Model | First source | per 100 answers | Second source |
|---|---|---|---|
| 9.85 | |||
| 9.48 | |||
| 9.19 |
Typical food and drink prompts
Food prompts usually pair a product with a criterion: origin, quality grade, delivery, price or intended use.
- "where to buy pure maple syrup online", "best online spice shop for saffron"
- "weekly fruit basket delivery for the office", "organic vegetable box delivered in Lyon"
- "difference between PDO and PGI", "what does the organic label guarantee"
- "coffee roaster selling single-origin beans", "gourmet food gift for clients"
Some of these requests come from companies rather than households. Office managers looking for fruit deliveries or corporate gift boxes ask AI assistants for supplier shortlists, a type of prompt where specialists have a real chance against large grocers.
Producers, regulators, grocers: where food answers come from
Producers and specialist shops carry much of the weight on purchase prompts. A spice merchant explaining vanilla grades, an orchard selling direct or a maple syrup importer describing colour classes gives the model the precise information it needs to recommend a seller.
Official sources appear as soon as a label, an origin or a safety issue is involved. In France, the agriculture ministry and INAO (the body that manages designations of origin) are references, and the economy ministry's consumer pages cover labelling and pricing rules. For English-language prompts, agencies such as the FDA play a similar role.
Supermarkets and large grocers are cited for availability and price, Wikipedia for definitions and product history, and review platforms like Trustpilot for delivery services. Facebook, Reddit and TripAdvisor show up for local shops, markets and farm visits.
Origin and labels: the claims AI wants to verify
Food is an industry of claims: organic, artisanal, local, single origin, protected designation. AI models handle these words with caution and look for an official reference that defines them. A product page that names the exact label, the certifying body and the origin of the raw ingredient is easier to cite than one that only says "authentic" or "premium".
Precision also protects the brand. When a page states an origin or a label that an official register can confirm, the model can repeat it with confidence. When the claim is vague, the answer may hedge or recommend a competitor whose claims are documented.
Precision counts more than brand awareness
A small producer can be named next to a national grocer if its pages state what the model needs: origin, label, ingredients, shelf life, delivery area and minimum order. Visibility in food answers depends less on fame than on these details.
Delivery zones deserve special care. Many prompts include a place ("in Paris", "in Belgium", "anywhere in Europe"), and a shop that does not say where it delivers is easy to leave out. The same goes for business customers: a page for companies, with order frequency and invoicing terms, matches those prompts directly.
Practical steps for food and drink businesses
- On every product page, state origin, label or designation, ingredients, allergens, shelf life and storage conditions in plain text.
- Name the certifying body for each label you use (organic, PDO, PGI) and keep certificates current on a dedicated page.
- Publish delivery zones, lead times and minimum order clearly, with a separate page for business orders if you serve companies.
- Write buying guides that explain quality grades in your category (spice grades, coffee processing methods, syrup colour classes), the content models quote for "how to choose" prompts.
- Collect reviews about freshness and delivery on an independent platform, and keep your listings on TripAdvisor and local directories accurate if you run a shop or a farm open to visitors.
- Treat GEO (Generative Engine Optimization) as a seasonal task: before Christmas and other gifting peaks, check which shops AI assistants recommend for your products and update your pages ahead of time.
Frequently asked questions
Why do AI assistants cite government websites for food questions?
Because many food questions involve rules: what a label guarantees, what a designation of origin covers, how products must be labelled or stored. Ministries of agriculture, food safety agencies and the bodies that manage designations are the most reliable sources for those definitions. Brands appear next to them when their pages state claims the official source can confirm.
Can a small food producer be recommended by ChatGPT or Perplexity?
Yes, especially on precise prompts. A request for "dark maple syrup delivered in France" or "office fruit basket delivery in Brussels" is better matched by a specialist page than by a supermarket. Clear product details, stated delivery zones, independent reviews and mentions in food media or local press all increase the chances of being named.
Do labels like organic or PDO matter for AI visibility?
They help when they are documented. AI models tend to repeat claims they can verify, and recognised labels have public definitions and registers. Naming the label, the certifying body and the product's origin on your page makes the claim usable in an answer. Vague wording such as "artisanal" or "premium" carries little weight on its own.
Which websites do AI assistants cite for Food & Beverage businesses?
lesvergersdegally.com (6.32 citations per 100 answers), economie.gouv.fr (4.94) and thespicehouse.com (4.30), across 4'050 answers from ChatGPT, Claude, Gemini, Grok and Perplexity about Food & Beverage businesses since July 2026.
Which platforms do AI assistants cite in Food & Beverage?
Trustpilot (1.86 citations per 100 answers), Wikipedia (1.76) and YouTube (0.64).
Method and sources
387'471 answers from ChatGPT, Claude, Gemini, Grok and Perplexity, from August 2025 to September 2026, to the questions Sorank asks every week to follow its clients' visibility (88% of them in French). A citation is a source domain given in an answer; the rate is the number of citations per 100 answers. Data snapshot of 2 October 2026.
Full methodology · Raw data (JSON)
How to cite this page: Sorank Data, “Websites AI cites most in Food & Beverage (Sep 2026)”, data.sorank.com, data snapshot of 2 October 2026.
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