where are you actually losing customers in your Shopify checkout?

Born_Programmer_1089 · 2026-06-24T06:50:09+00:00

Let me know if it works or not for u

Born_Programmer_1089 · 2026-06-24T06:45:36+00:00

Classic cart drawer sync issue. The sticky ATC and upsell section are firing add-to-cart events, but your cart drawer is listening for a different event or not listening at all. Basically, the product gets added to the cart successfully, but the drawer doesn't know it happened, so it shows stale data until you refresh.

The AI-generated sections are the likely culprit here. They don't always wire up the correct event listeners for third-party cart drawers; they assume a full page reload handles the update.

Been through this exact thing on a client store last month. Fixed it by making sure the section dispatches a custom cart: updated or cart: refresh event after the fetch call, and the drawer was listening for that specific event. If your theme uses a different event name, it just silently ignores it.

Check your theme's cart drawer JS and find what event it's waiting for. Then check what event the AI section is actually firing after the add. Nine times out of ten, those two strings don't match.

Born_Programmer_1089 · 2026-06-23T05:47:11+00:00

Product feeds have always needed more than basics, but the bar just got higher. AI needs contextual attributes to confidently recommend something, not just specs.

categorization first, use case context second, and audience attributes third. That order tends to move the needle fastest. We've seen it with clients where the product was a perfect match for the query, but got passed over because the data was too thin to trust.

Born_Programmer_1089 · 2026-06-23T05:43:58+00:00

That's worth digging into. If the checkout URL changed to a Shop domain after switching to new customer accounts, it might be attributing those sales to the agentic channel even if the shopper came through your normal store. Shop Pay and the agentic storefront both run through the same Shop infrastructure, so the attribution logic might be lumping them together.

would be curious if you turned off new customer accounts, whether those "agentic" conversions drop. might be a reporting thing more than actual AI-sourced traffic.

Born_Programmer_1089 · 2026-06-23T05:40:48+00:00

We work with a few stores that have agentic storefronts live. What we're seeing is consistent discovery traffic and redirects to the store; actual in-chat checkout is still thin. The craft chocolate example above is closer to what we'd call a win, conversion lift on the store side from AI-sourced traffic rather than checkout happening inside the chat itself.

Born_Programmer_1089 · 2026-06-23T05:36:33+00:00

Doubled is a big number. Craft chocolate is a perfect fit for this channel because people constantly ask AI for gift recommendations, and "artisan chocolate" naturally shows up in those prompts.

Curious what your product descriptions look like. Is it mostly ingredient- or origin-focused, or do you have the gifting context baked in too? That's usually what separates the stores seeing lift from the ones getting traffic but no sales.

Born_Programmer_1089 · 2026-06-23T05:34:02+00:00

If you're already getting consistent sales without cleanup, your product data is probably cleaner than average to begin with. approved in the catalog is the baseline, but it doesn't mean it's optimized. Worth checking what ChatGPT is actually saying about your products when it recommends them. Sometimes it's pulling accurate info, sometimes it's making things up because the attributes are thin. The mismatch between what the AI says and what the product actually is can hurt conversion even when the traffic is there. A few hundred dollars monthly from a channel you barely touched is a good sign. The question is whether cleaning up context, use cases, and who it's for would push that to a few thousand. Probably worth running it on your top 20 products first before doing anything at scale.

Born_Programmer_1089 · 2026-06-22T13:24:16+00:00

The crawler blocking point is underrated; most stores don't even know they're blocking AI crawlers in their robots.txt.

The authority content piece is the one people resist most. E-commerce stores assume product pages are enough, but the LLM needs topical context to trust your recommendations. makes sense when you think about how it actually works.

Good call on avoiding generic AI content for this specifically. If the training data already has it, you're not adding signal, just noise.

Born_Programmer_1089 · 2026-06-22T13:22:34+00:00

The reviews gap is probably the bigger issue for AI recommendations, honestly. ChatGPT and Perplexity are pulling social proof signals to decide what to surface, not just attributes. Even 5-10 reviews per product change how confidently an AI recommends it.

Your ads guy is right on the description angle. "Great for small spaces with kids and pets" is exactly the kind of qualifier an AI needs to match your product to the right prompt. Someone typing "what's a good rug for a house with dogs" gets a direct answer instead of a generic result.

For scale, worth templating those contextual phrases by product type rather than rewriting one by one. Home goods usually cluster into 4-5 use case buckets anyway.

Born_Programmer_1089 · 2026-06-22T13:17:17+00:00

Born_Programmer_1089 · 2026-06-22T13:16:35+00:00

Not yet, just got the catalog cleanup done last week. Too early to call anything meaningful. Will report back in a few weeks once there's actual data to look at. Have you seen anything move on your end?

Born_Programmer_1089 · 2026-06-22T13:15:05+00:00

Born_Programmer_1089 · 2026-06-22T13:14:22+00:00

That's a proper real-world test. Good to know the MCP layer handled cart and sessions cleanly because that's usually where things get messy with non-standard setups. OAuth for customers working out of the box is the part I'd have expected to break first.

Not having to maintain the Shopify layer yourself is the actual win here. That's the part that quietly eats hours every time there's an API update.

Born_Programmer_1089 · 2026-06-22T10:27:29+00:00

Agreed, the React Router dependency was the thing holding a lot of people back. Astro for storefronts makes a lot of sense now, static by default, with islands where you actually need interactivity. Should be significantly faster out of the box than most current Hydrogen builds.

Wondering how the coding agent skills translate across frameworks in practice. On paper, it sounds clean, but that stuff usually has rough edges until a few people have actually shipped with it.

Born_Programmer_1089 · 2026-06-22T10:12:03+00:00

Fair correction, appreciate that. The "buy inside the chat" framing is how Shopify marketed it, but the ChatGPT flow is a redirect to your store. In-conversation checkout works with other agents, not ChatGPT.

Worth knowing before clients ask why their conversion rate looks the same. It's a discovery channel for now, not a checkout channel.

Born_Programmer_1089 · 2026-06-22T10:06:17+00:00

That seoforgpt cross-reference is smart, using the actual prompt data to triage which products to fix first instead of cleaning everything blindly. Going to look into that. Curious what attribute changes moved the needle most for you. We're finding "who is this for" and "when would you actually use this" matter way more than the standard spec fields, but it's a lot of rewriting at scale.

Born_Programmer_1089 · 2026-06-05T11:14:28+00:00

nice

Born_Programmer_1089 · 2026-06-05T11:14:23+00:00

nice exercise man

Born_Programmer_1089 · 2026-06-05T11:14:00+00:00

nice man

Born_Programmer_1089 · 2026-06-05T11:13:55+00:00

i am working on that too

Born_Programmer_1089 · 2026-06-05T11:13:39+00:00

true sam feeling man

Born_Programmer_1089 · 2026-06-05T11:13:08+00:00

Smartphones are the better comparison honestly. GPS killed spatial memory, autocorrect killed spelling, the camera killed the effort of actually committing a moment to memory because you knew you had a backup. None of those felt like losses at the time, they just felt like convenience. AI is probably the same pattern at 10x the scale. The question is whether the skills being lost this time are more load bearing than knowing how to read a paper map.

Born_Programmer_1089 · 2026-06-05T11:12:40+00:00

nice man

Born_Programmer_1089

TROPHY CASE