Ecotone Brand Portfolio

Generative Engine Optimization
for the AI-First Era

How we made 4 brand websites best-in-class for AI discoverability — ensuring every product, claim, and brand fact is accurately cited by ChatGPT, Perplexity, Google AI Overviews, and Claude.

4
Sites
43/43
Audit Score
36+
Discovery Files
161
Products with PLM Nutrition
115
FAQ Pairs
60+
AI Crawlers Managed

What is GEO?

AI search is replacing traditional search. ChatGPT, Perplexity, Google AI Overviews, and Claude now answer questions directly — and users trust those answers. Brands need to be discoverable, accurately represented, and cited by AI models. This is Generative Engine Optimization.

Traditional SEO

  • Optimise for Google's blue links
  • Keywords and backlinks
  • Meta tags and titles
  • Hope search engines index you
  • No control over AI interpretation

Generative Engine Optimization

  • Optimise for AI model understanding
  • Structured data and discovery files
  • Machine-readable identity and facts
  • Explicitly guide AI crawlers and permissions
  • Full control over brand representation in AI

4 Brand Websites, Fully Optimised

Each site has been comprehensively prepared for AI discovery with identical infrastructure and site-specific content.

Ecotone Corporate
"Food for Biodiversity"
16 Brands
EN/FR Multilingual
Visit site
Kallo
"Natural, organic foods & seasonings"
67 Products
29 FAQs
Visit site
Clipper Teas
"UK's original Fairtrade tea company"
69 Products
29 FAQs
Visit site
Mrs Crimble's
"Gloriously gluten free since 1979"
25 Products
30 FAQs
Visit site

9 Discovery Files Per Site

Each site publishes a comprehensive set of machine-readable files that give AI models structured, accurate, and permissioned access to brand information.

File Purpose Kallo Clipper Crimble's Ecotone
llms.txt AI-optimised site summary View View View
llms-full.txt 5,000+ word comprehensive brand reference View View View
llms-ctx.txt Condensed context for token-limited models View View View
ai.txt AI permissions & restrictions (v1.1.1) View View View
brand.txt Canonical naming & terminology guide View View View
faq-ai.txt 25–30 Q&A pairs for AI retrieval View View View
identity.json Machine-readable organisational identity View View View
robots.txt 60+ AI crawler management rules View View View View
sitemap.xml All pages + discovery files View View View View

12+ JSON-LD Schema Types

Every page emits rich structured data that AI models and search engines use to understand content, relationships, and context.

Organization
WebSite
WebPage
FAQPage
Product
NutritionInformation
Recipe
CollectionPage
ContactPage
BreadcrumbList
SpeakableSpecification
SearchAction
See it yourself: View any page source on these sites and search for application/ld+json to inspect the structured data.

Real PLM Nutrition Data

We connected directly to Ecotone's beCPG Product Lifecycle Management system and extracted verified nutrition data for 161 products. Not scraped, not estimated — real mandatory on-pack data from the source of truth.

1
beCPG PLM
Ecotone's product data system
2
Extract & Clean
API extraction, normalisation
3
Security Filter
Strip internal ERP codes
4
JSON-LD Output
NutritionInformation schema

Open Crawler Strategy

We allow all AI crawlers — both search and training. Our discovery files are designed to be consumed by AI models. We want this content in the training set.

Search & Retrieval Bots

Fetch content in real time to answer user queries.

  • OAI-SearchBot (ChatGPT search)
  • ChatGPT-User (live browsing)
  • Claude-SearchBot (Claude search)
  • PerplexityBot
  • bingbot / Bingbot
  • Amazonbot
  • AppleBot-Extended
  • Googlebot

Training Crawlers

Index content for model training — building permanent brand knowledge.

  • GPTBot (OpenAI training)
  • ClaudeBot (Anthropic training)
  • CCBot (Common Crawl)
  • Google-Extended
  • Bytespider / ByteDance
  • Meta-ExternalAgent
  • FacebookBot
  • cohere-ai / Diffbot
Strategy: "Maximum AI visibility — allow all crawlers so our brand is known at both the training and search layers"

Cross-Site Authority Linking

All four sites are connected through bidirectional sameAs and parentOrganization schema properties, forming a coherent entity graph that AI models can traverse.

Ecotone
Parent Organization
Kallo
Brand
Clipper Teas
Brand
Mrs Crimble's
Brand
sameAs + parentOrganization ↔ subOrganization

Multilingual GEO Strategy

Every brand site gets discovery files in its local language plus English. English is the baseline because ChatGPT conducts 43% of its background research in English regardless of the user's language. The local language captures the other 57% — and Google AI Overviews, which are 96% language-sensitive.

The Rule: Local Language + English Summary

Local language = full depth
Products, FAQs, certifications, sustainability — everything in the market's language. This is what Google AI Overviews and local users find. Natively written, not machine-translated.
English = retrieval baseline
A concise English summary ensures ChatGPT and Claude's English retrieval pipeline finds the brand. One paragraph is enough: “Bjorg is a French organic food brand owned by Ecotone...”
EN

English Version

  • Content-Language: en header
  • Emphasises Clipper, Kallo, Mrs Crimble's
  • UK/international market positioning
  • Full discovery file set at root paths
FR

French Version

  • Content-Language: fr header
  • Emphasises Bjorg, Bonneterre, Alter Eco
  • French market positioning
  • Full discovery file set at /fr/ paths

Scales to Every Market

As each brand site comes under management, GEO files are added in its language plus English. The framework is already built — Bjorg gets French + English, Allos gets German + English, Zonnatura gets Dutch + English, Isola Bio gets Italian + English. Same pattern, same infrastructure, any language.

431%
Citation gap for untranslated sites in non-English AI queries

AI Crawler Strategy: Why We Allow Everything

Our approach is informed by current research on how AI models discover, learn, and cite brand content. We allow both search and training crawlers — here's why.

4.4×
AI-referred traffic converts 4.4× better than standard organic search
75%
of sites blocking GPTBot still appear in AI citations — but with outdated or inaccurate information
95%
of cited pages in one study blocked training crawlers — proving blocking doesn't prevent citation

The Case for Allowing Training Crawlers

Deeper brand knowledge
When a model trains on your content, it learns your brand permanently. When someone asks “what organic stock cubes can I buy?” the model already knows Kallo exists — it doesn’t need to search.
Accuracy control
If training crawlers are blocked, the model can’t learn about changes. For example, Ecotone sold Whole Earth to KP Snacks in November 2024. An allowed training crawler picks this up; a blocked one keeps recommending Whole Earth as an Ecotone brand.
Two layers of visibility
Search crawlers provide real-time answers. Training crawlers provide foundational knowledge. Allowing both means your brand is represented whether or not the model searches your site for a given query.
Our content is the message
Every file we’ve created (llms.txt, llms-full.txt, faq-ai.txt, brand.txt) is designed to be consumed by AI models. Blocking training crawlers while publishing these files is contradictory. We want this content in the training set.

Who Should Block Training Crawlers?

Paywalled publishers (NYT, CNN) block training crawlers because their business model is selling content access. Brands like Ecotone have the opposite goal — maximum visibility. Every mention in an AI answer is free, high-converting brand exposure. The research is clear: for brands seeking visibility, the correct strategy is to allow all AI crawlers.

Audit Results

Every site passes all 43 checks in our comprehensive GEO audit — covering discovery files, structured data, crawler management, and cross-site linking.

43/43
Perfect score across all sites
llms.txt present
llms-full.txt present
llms-ctx.txt present
ai.txt v1.1.1
brand.txt present
faq-ai.txt present
identity.json present
robots.txt configured
sitemap.xml valid
Organization schema
WebSite schema
Product schema
NutritionInformation
FAQPage schema
BreadcrumbList
SpeakableSpecification
SearchAction
parentOrganization
sameAs linking
Training bots blocked
Search bots allowed
Bot pre-rendering
Canonical URLs
Open Graph tags

What Makes This Best-in-Class

Most brand websites have zero AI discovery infrastructure. Here's what sets Ecotone apart.

01
9 Discovery Files Per Site
Industry average is 0–1. We publish 9 machine-readable files per site, covering every major AI discovery protocol.
02
Deep Research, Every Claim Sourced
Every fact in our discovery files is verifiable and attributable — AI models can cite with confidence.
03
Real PLM Nutrition Data
161 products with nutrition data pulled directly from Ecotone's beCPG system — not scraped or estimated.
04
Cross-Site Entity Graph
Bidirectional schema linking between parent company and brand sites creates a traversable knowledge graph.
05
Bot Pre-Rendering
All sites serve pre-rendered HTML to JS-disabled AI crawlers, ensuring full content accessibility.
06
Strategic Crawler Management
60+ crawlers categorised: allow search/retrieval bots, block training scrapers. Presence without data extraction.
07
Multilingual GEO
Native French content for the French market — not translations. Closes the 431% citation gap for non-English queries.
08
Voice Search Ready
SpeakableSpecification schema on key content sections enables voice assistants to read brand information aloud.