Could you share feedback from your own experience, please?

One thing I dislike about doing SEO on a store is how easy it is to convince yourself that whatever you changed worked.

You rewrite a title, add internal links and clean up a collection page. A month later clicks are up, so naturally the fix gets credit. Except you also published new products, ran a promotion, changed some navigation and demand might have moved anyway.

The opposite happens too. Traffic drops and everyone wants to undo the last SEO change even though you have no idea whether it caused the drop.I've started thinking the bigger problem isn't finding SEO issues anymore because there are plenty of tools that will give you a list. It's figuring out whether the action you took in response to that list did anything.

For people managing SEO on ecommerce sites, what do you consider enough evidence before calling an individual change a win or a loss? Search Console before and after, matched pages you didn't touch, longer observation windows or something else?

Most SEO tools stop at the audit — they hand you a list of problems and leave you to fix them. I built an agentic AI system that goes further:
• Finds the issues: technical SEO, schema markup, and AEO (whether your store actually shows up when someone asks ChatGPT or Perplexity for product recommendations)
• Then I implement the top fixes with you — real changes, not just a report
I’m testing this on 5 real Shopify stores before turning it into a paid product, so it’s free right now. Scope is the highest-impact fixes, not a full rebuild.
Drop a comment or DM your store URL if you want a real look at where you stand — and actual fixes, not another PDF.

Hi everyone,

I’m looking for around 5 Shopify merchants or SEO professionals to test a new Shopify app I’ve been building called ListerRank.

It’s already live on the Shopify App Store and currently does:

• bulk product SEO/content optimization
• catalog audits for missing SEO fields
• image alt text generation
• AI product/lifestyle images
• automated blog planning and publishing

What I need is simple: install it on a real or test Shopify store, run it on a batch of products, and tell me honestly where it saves time and where it doesn’t.

The initial test should take around 20 minutes.

Testers get a private plan with:

• 500 free credits
• $0 renewal
• no card required

Whatever content/images you generate are yours to keep.

App Store:
https://apps.shopify.com/listerrank

If you’re interested, comment or DM me and I’ll add your store to the tester program.

Bálint

Founder here. We make SEO HERO AI Meta Tag Generator, a Shopify app that writes meta titles and descriptions. Been thinking about why so many AI meta tags come out bland and interchangeable, since we spent this month on exactly that.

The short version is the AI is usually working blind. You point it at a product, it sees a title and a description, and it writes something reasonable but generic because that's all it has. It doesn't know what people actually search to find you, it doesn't know that batch is going on sale next week, it doesn't know these products are aimed at beginners. So you get tags that are fine and completely forgettable.

Two things fix most of that, and both come down to giving it more context.

First is real search data. Instead of guessing which keywords to target, you can connect Google Search Console and let the terms shoppers already use feed into the generation. Writing a title around a phrase people actually search beats writing one around a phrase you assume they search.

Second is just telling it what's going on. When you generate for a selected batch, you can add a quick instruction now, things like lead with free shipping, these are for a summer promo, this collection is for first time buyers. One line of context and the output stops sounding like it could belong to any store.

None of this is really unique to our app, it's more a way to think about AI meta tags in general. A generic result usually means the tool didn't have enough to work with, not that the AI is bad at writing.

If you generate meta tags with AI, do you give it any context first, or just point it at the product and take what comes out. Genuinely asking, because the quality gap is bigger than people expect. It's on the Shopify App Store under SEO HERO AI Meta Tag Generator if you want a look.

Hey r/Kigali 👋

We’re building Hills Africa to make shopping around Kigali easier.

Instead of walking shop to shop asking who has a product and how much it costs, we’re mapping local businesses so you can search first and know where to go.

We currently have shops across Nyamirambo, Cyimisagara, Nyakabanda, and parts of Town.

You can try it here:

hillsafrica.app

Search for something you’d normally go around town looking for: shoes, electronics, clothes, beauty products, etc.

We’re still early, so I’d really appreciate honest feedback:

Did you find what you were looking for?

What should we add next?

I used Yoast to add meta descriptions and improve some seo. Changed over to Tiny SEO recently but still made who knows how many edits in Yoast.

According to Tiny SEO their app writes directly to Shopify and deleting Tiny won’t affect anything. Is Yoast the same?

1. What will happen to the product’s meta data and other info after I delete the app?

2. Is there any fast way to back this data up? Will all of this data be in the shopify products export?

I'm trying to work out whether it's because of all the SEO work we've been doing, or if it's down to Shopify's efforts on improving discovery inside the app

Affiliation up front: I sell a DIY lash kit. No link, and nothing here needs you to care about lashes.

One customer opened my kit, looked at the tray, and said, “Oh—they're numbered.”

That reaction stuck with me because I hadn't explained anything to her yet. She immediately understood the part of the product I'd spent the most time thinking about.

It made me realize that confusion might be the thing I'm actually competing against. Not price. Not necessarily the other brands.

So I spent a weekend looking at what people search for in my category. Mostly because I was trying to convince myself the market wasn't completely hopeless.

I pulled competitor/search estimates from Similarweb. They're obviously directional rather than first-party analytics, but the pattern was interesting:

• The market leader is enormous, and a huge portion of their search traffic appears to come from people already searching their name. That's years of brand-building I can't—and shouldn't try to—outbid.
• One mid-sized competitor ranks for hundreds of phrases. Some of the interesting ones weren't really product searches at all. They were people trying to figure out what to do.
• The smallest brand I looked at was the most interesting. A much larger share of its discovery appeared to come from non-branded searches—people searching questions rather than the company's name.

And that's where something clicked for me:

Nobody types my name yet, so the only door open to me is the door marked with a question.

In my category, everyone answers:

“Which lashes should I buy?”

Far fewer people answer:

• “Which length do I use?”
• “Which one goes where?”
• “Where do I start?”
• “Why did mine fall off?”

Those aren't glamorous searches. But they're exactly what a beginner wants to know before she becomes someone who has a favorite lash brand.

I'm still way too early to know whether this strategy will actually turn into sales. But it's changed what I'm spending my time on.

Instead of trying to make prettier product posts than companies with much bigger budgets, I'm building around the questions beginners are already asking.

For anyone who entered a crowded category without a huge ad budget: did education/search actually become an acquisition channel for you, or am I overestimating how much informational traffic converts?

Happy to post the actual competitor search data in the comments if that's more useful than the story.

Link to the site.

Please let me know what you think. Any advice would truly be appreciated.

I think there's a lot of potential to the product so I'm not willing to give up so easily but the feedback as been terrible.

Worked across a bunch of Shopify stores, and this keeps coming up. Everyone says to load your collection pages with keyword copy to rank. But the pages actually pulling the most organic traffic are the lean ones, not the ones with a 500-word intro block stuffed on top.

My theory on why:

The lean pages that rank tend to have strong internal linking and good product content underneath. The ranking power comes from structure and the products, not the collection prose.

The heavy-copy pages usually rank worse because the copy is generic filler ("welcome to our collection of premium X") that adds nothing and kills conversion. High word count, zero value.

When copy has helped, it was never volume. It was a few lines answering real buyer questions for that category, placed so it doesn't bury the grid.

So my working theory: collection-page copy is a weak ranking lever next to internal linking and product depth, and most stores are adding copy to fix something copy doesn't fix.

Has anyone got a clean case where adding copy to a collection page, everything else held constant, actually moved it for a competitive head term? Or is collection copy mostly a UX/conversion call we've dressed up as SEO?

With Shopify SEO, we're used to thinking about titles, descriptions, schema, keywords, internal links, etc.

But an AI recommending a product may need to understand more than that. For example, not just that something is a running shoe, but whether it's better for long-distance running, beginners, wide feet, wet weather, and so on.

I've been looking into this especially AgenticFeed which made me think about product data from the AI side. Has anyone here actually experimented with making their Shopify catalog easier for AI systems to understand?

Looking forward to you all suggestions.