Food and FMCG queries increasingly start on LLMs: 'best Indian spice brands', 'organic protein powder India', 'how to use asafoetida in cooking'. AEO for FMCG is engineering recipes, ingredient pages, use-case guides and product pages for LLM extraction. The category has an unusual advantage here, which is that recipe and ingredient content is already the most structured content on the internet and answer engines lean on it heavily. A properly marked-up recipe with quantities, timings and method is exactly the shape a model wants to quote. The disadvantage is that dietary and nutritional questions make models cautious, so they lean toward sources they can verify, which puts consistent brand entity data, label-accurate nutritional facts and third-party mentions at the centre of the work rather than at the edge.
FMCG LLM queries fall into repeating shapes: category best-of, where to buy, how to use, ingredient-specific, dietary questions such as gluten-free or vegan variants, and nutritional questions such as the protein content of a product. Recipe markup and direct-answer structure are the two biggest on-page levers, and content with proper Recipe markup is cited at materially higher rates than the same information written as unstructured prose. Underneath the on-page work sit three off-site realities. Dietary and nutritional claims are treated cautiously by models, so facts that match the physical label exactly and are stated in a single unambiguous place get used while vague marketing language gets skipped. Entity consistency matters because a brand whose founding year, city and product range disagree across its own schema, its business profile and press listings is one a model will hedge away from. And third-party inclusion is decisive for category questions, since a query about the best brands in a category is answered largely from pages that already compare brands rather than from any single brand's own site.
