u/yolosollo — reddlx

Our app scores a product page against competitor and keyword data, rewrites it, and publishes it back to the store

The app reads the competitors currently ranking for a product, the queries people search around it, and keyword demand with volume and CPC. It scores the merchant's existing page against that, rewrites the whole thing, generates the product images, and pushes it live to the store in one click. After publish it follows rankings and traffic so the merchant can see whether the rewrite moved anything.

The point is that a merchant can do this across a full catalogue rather than hand writing a handful of pages. The same research set also produces the ads, social posts and emails.

It is live at brandybee.ai. Happy to go into how the research side is put together.

reddit.com

u/yolosollo — 2 days ago

▲ 1 r/ShopifyPros

We built a tool that researches competitors and search demand, then rewrites and publishes your product pages

It pulls the competitors ranking for a product, what people are actually searching around it, and keyword demand with volume and CPC. Then it scores your current page, rewrites it in full, generates the product photos, and publishes it back to your store in one click. Once it is live it tracks rankings and traffic and tells you what to fix next.

So the page is built on what the market is actually searching for, and you can run it across a whole catalogue instead of hand writing ten pages and stopping there. The same research also writes the ads, social posts and emails.

It is live at brandybee.ai. Happy to answer anything about it.

reddit.com

u/yolosollo — 2 days ago

▲ 10 r/ShopifyApps+1 crossposts

Built a Shopify app that rewrites product page SEO and pushes it live, instead of leaving you a list of things to fix by hand

We just launched this, and the pattern we built it around is one you see on almost every Shopify store: the theme fills the meta title with "Product Name - Store Name", the description is whatever the supplier sent, half the images have no alt text, and the products sit uncategorized with no GTIN. Every one of those is a known fix. None of them get done, because doing them across 300 products by hand is a week of work that never gets scheduled.

What it checks per page: meta title and description, keyword coverage, content depth, image alt text, and the structured data underneath. Is the product schema there and actually parsing, is there a GTIN, is availability declared, is the product categorized, are the required attributes complete.

What it does before writing: pulls the competitors' pages ranking for that product, what people are actually searching for around it, and keyword demand with volume and CPC. So the rewrite targets what's actually winning that query rather than generic advice.

Then it rewrites the page, generates product images with alt text, and pushes it live to your store in one click. After that it tracks your keyword rankings and what your competitors change.

https://apps.shopify.com/brandybee

Happy to get into detail on how the scoring works, and I'd love to hear your feedback.

u/yolosollo — 8 days ago

▲ 6 r/EcommerceCircle+3 crossposts

We made the AI research the market before it writes the product page, instead of writing from a prompt. The difference was bigger than we expected

Disclosure first: we built this and it just launched, so read it with that in mind. But the lesson is useful whether or not you ever touch our tool.

Most AI tools in ecommerce write product copy from a prompt and a brand name. You get fluent text that says nothing specific about your market, because the model has nothing to work with except your product title and a tone instruction.

We went the other way. The AI does research before it writes a word:

Pulls your competitors' pages for the same product
Reads the actual search results for that product
Gets keyword demand, search volume and CPC
Scores your existing page against all of it and lists what's weak

Only then does it write. So the page gets built around what's actually ranking in your category instead of what a model guesses sounds good.

After that it generates the product images, publishes the page back to the store, and tracks rankings and traffic so you can tell whether any of it worked.

The part that surprised us most: the research step matters more than which model you pick. Same model, run with and without the competitive and search context, produces output that isn't in the same league. Almost all of our work has gone into what we feed the model, not into prompting it better. If you're building anything similar, that's where I'd spend the time.

It's at https://brandybee.ai and there's a free plan if you want to run it on your own store. Happy to go into detail on any part of how it works.

u/yolosollo — 8 days ago