A meaningful share of wedding research has moved to assistants. A family types a question about planning a palace wedding in Udaipur for four hundred guests into ChatGPT or Gemini, and it returns a set of names, a set of considerations and often a rough budget frame. That answer becomes the shortlist, and it is being assembled without anyone visiting a website. The uncomfortable part for planners is that assistants overwhelmingly cite directories, publication listicles and venue pages, because those are the sources structured in a way a model can extract from. Your site, which is a gallery with beautiful images and almost no parseable text, is invisible to the process. This work is about making your expertise legible to a machine reading for facts.
Wedding planning is an unusually strong AEO opportunity and an unusually weak one at the same time, and it is worth understanding why. It is strong because the queries are exactly the shape assistants handle best. A family asking how to plan a three-day wedding at a specific Rajasthan property for four hundred guests in December is posing a multi-constraint question that no search results page answers well, and the assistant will happily synthesise venues, budget frames, timelines and planner names. It is weak because planner websites are the least machine-readable sites in any premium category: image-heavy, text-poor, with the substance living inside galleries and lightboxes that contribute nothing extractable, and with the actual credentials and track record never written down as facts anywhere. So the models fall back on WedMeGood, WeddingWire, ShaadiSaga, publication roundups and venue vendor lists, which is why those sources dominate the answers. There are two consequences worth planning around. First, your own site needs a factual substrate that currently does not exist for most planners: a plainly stated record of venues, destinations, formats, scale bands and years operating. Second, and less comfortably, a large share of the work is off your site altogether, on the third-party sources the models already trust. There is also a real caveat about attribution: when an assistant names you and the family then searches your brand directly, the visit arrives as branded organic or direct traffic with no trace of the assistant, so the channel systematically understates itself. We run this from Powai, Mumbai.






































