For ecommerce and D2C
Product pages AI can recommend.
Shoppers ask AI for gift ideas, comparisons and “does it run small?”. Omnishown keeps your storefront code clear, structured and quotable, release after release.
- Product facts in structured data
- Comparison and FAQ content
- Checked on every theme or code change
Omnishown Check
2 passed, 1 has a fix ready
- SEOTitle and descriptionPassed
- AEOStructured dataPassed
- GEOFAQ answers on /menuFix ready
Every release can quietly cost you a recommendation.
Specs buried in images
Size, material and price live in a graphic. A shopper's AI cannot read a graphic, so it recommends a product whose page it can read.
Thin product pages
A title, a photo and a price. No answer to the questions shoppers actually have: fit, care, delivery, returns.
Theme updates undo the basics
A new template drops the product schema or the canonical tag. Nobody notices until sales dip.
Make product facts machine-readable.
Product, offer, availability and review markup (schema.org) tells search and AI exactly what a page sells and for how much. Omnishown checks it is present and correct on every release.
- Product and offer structured data
- Consistent titles and descriptions across the catalogue
- Canonical tags that stop duplicate variants competing
application/ld+json
Facts a machine can read
- Business
- Sweet Crumbs, custom cakes
- Area
- Gachibowli, Hyderabad
- Hours
- Daily, 9:00 to 21:00
- Ordering
- Same-day on request
Example business, not a real customer.
Answer what shoppers ask before they buy.
“Does it run small?” “Is it machine washable?” “Can I return it?” Omnishown proposes FAQ and spec content as pull requests, and you confirm every fact, because only you know your product.
- FAQ blocks on product and category pages
- Clear delivery and returns copy as real text
- Headings that match shopper questions
Omnishown: add FAQ answers to /menu
Pull request #14
See when AI names your brand.
Omnishown Watch tracks the shopping questions that matter to you and records whether your brand is named, so you know which products and categories need attention.
- Track brand and category questions
- Named or not named, per question
- Trend over time with Omnishown Diff
| Buyer question | ChatGPT | Perplexity | Gemini |
|---|---|---|---|
| Custom birthday cake in Gachibowli today? | Named | Named | Not named |
| Eggless bakery near Kondapur? | Not named | Named | Not named |
| Best bakery for corporate orders in Hyderabad? | Named | Not named | Named |
Honest limits for stores.
- Omnishown reviews storefront code that lives in a GitHub repository, such as a custom or headless storefront. Hosted store platforms whose code you cannot reach are not supported yet.
- It does not manage product feeds, marketplaces or ads.
- Tracking AI shopping surfaces is not part of the plan today. Omnishown Watch tracks the questions you choose.
Questions, answered plainly
Still unsure? Join the pilot and ask us directly. We'll answer before you connect anything.
Does Omnishown work with my store platform?
If your storefront or theme code is in a GitHub repository, tell us about it in the pilot form. Supported setups are being set with the first clients.
Will it edit my products?
No. Omnishown reviews and proposes changes to code in your repository. Product data in a separate system is outside its reach.
Can it handle a large catalogue?
Catalogue-scale handling is one of the things we will test with pilot sites. We would rather prove it than promise it.
Tell us how your store is built.
Join the pilot and we will say honestly whether Omnishown fits your storefront.
- No card, no commitment
- Every fix arrives as a pull request you approve
- Planned pricing from ₹2,999 per site per month