AI search for Indian D2C: making your saree, kurti, jewelry brand discoverable

When customers ask ChatGPT 'where can I buy a red silk wedding saree under ₹5000', is your store one of the 5 it recommends? Here's how to find out and fix it.

The problem

Indian D2C buyers under 35 are abandoning Google in favour of ChatGPT for shopping discovery — especially for fashion, jewelry, electronics. The problem: Indian D2C catalogs rarely have the structured data, alt text, or schema.org tagging that AI search engines use to surface products. The result: ChatGPT recommends Amazon, Flipkart, or international brands instead.

Solution: GEOmind for Indian D2C

1. Free static scan of your store's HTML — surfaces missing schema.org, alt text, llms.txt.
2. Connect your store; GEOmind tracks weekly whether ChatGPT/Perplexity/Gemini cite you for buyer-intent queries.
3. PixelAPI auto-fix regenerates alt text in Hindi + English, generates Product schema.org markup, and writes a llms.txt for your domain.
4. Visual GEO via SearchPixel: scores whether your product photos are picked up by ChatGPT Vision and Pinterest Lens.
5. INR pricing with GST invoice — same rules as your other vendors.

Code

curl https://geomind.app/api/visibility/scan-now \
  -X POST -H 'Content-Type: application/json' \
  -d '{"domain":"sareebazaar.in","keyword":"red silk wedding saree under 5000"}'