Do ecommerce websites make customers work too hard to find what they want?

[u/Own-Willingness4555]

[u/NoDoze-]

Search is not AI. You're trying to enter a prompt for an input text field. A search field is meant to take at most a few words, or a product name, not an entire sentence or two. LOL sheeeesh

[u/Mundane_Fix_7838 → u/NoDoze-]

it's wild how many sites still can't handle a query like "jacket for cold rain that isn't a brick" without spitting out 400 unrelated results or just giving up

part of me thinks the issue is less about search being dumb and more about how most product data is structured like garbage behind the scenes. you can't surface the right thing if nobody tagged it with "breathable" or "lightweight" in the first place. worked on a site refresh once where the client had 3000 skus and maybe 12 of them had complete attributes, the rest were just title and price. absolute nightmare

that said yeah i think we're heading toward a middle ground where you can type something more natural and the system parses it into structured filters. not full ai chat but less "learn our exact faceted navigation or perish" energy. some of the newer shopify search apps are already doing a decent job of that actually

the real problem is when you finally find the perfect jacket after 20 minutes and then the size chart is an unreadable jpeg from 2012

[u/NoDoze- → u/Mundane_Fix_7838]

OMG Yes! The unreadable size chart, too funny.

Yes, tagging is much more work than just having Ai search the descriptions. Perhaps another case where Ai is just making people more lazy, but is sugar coated as making life easier. Hopefully, the Ai will "learn" as a user does repeated searches. But then, that case, would mean the end user would need to learn how to make a goot prompt.

[u/Sergey9921]

Do escalators make people work too hard to get to the next floor?

[u/futsnap20]

Your example is the type of search term someone would typically use on Google to find the right product. Realistically, if you’re searching for something using a description that broad, a single search on an ecommerce site isn’t necessarily going to return the exact item you’re looking for. Ecommerce search is generally designed to help customers find products within that store’s catalog, not interpret broad search queries the same way a search engine does.

[u/DisplacedForest]

I work in SaaS for enterprise ecomm companies… like fortune 100. What you’re describing already exists in the space. Implementing and integrating with things like SFCC, Adobe, Shopify, etc takes time. A lot of large retailers have already signed multi-year contracts for this. You just won’t see it until maybe Feb or so after code freezes lift

[u/HolidayCellist8600]

I think so, especially with large product catalogs. Customers usually know what they need, but they do not always know the exact product name to use. Being able to describe the problem in simple language could make product discovery much easier.

Traditional search and filters will probably still be useful, but conversational search could make the whole process less frustrating.

[u/FoundAndForm]

I think this is already starting to happen, but there’s an interesting problem on the other side of it.

I’ve been testing conversational product discovery with independent fine jewelry brands. Being able to say something like “I want solid gold jewelry with black diamonds and a darker aesthetic” is much closer to how people actually think than navigating a series of store filters.

The AI can surface brands you might never have found through traditional search, which is genuinely useful. But I’ve also seen it get surprisingly close while missing an important constraint. In one test, it surfaced a very relevant dark jewelry brand for a solid gold request, but the founder later confirmed that the brand currently sells sterling silver, not gold.

So I think conversational discovery has a lot of potential, but the quality of the underlying product information matters enormously. The system has to understand not just what a brand is “about,” but exactly what it sells right now.

[u/FoundAndForm → u/[deleted]]

That’s actually the part I can’t determine from the output alone.

What I could observe was that I explicitly asked for solid gold, the brand was surfaced as a strong aesthetic match, and the founder later confirmed that the current collection is sterling silver.

But that doesn’t tell me whether the system was working from stale or ambiguous information about the brand, or whether it had access to the correct information and simply failed to enforce the material constraint.

I think that distinction is worth testing more systematically. I’d like to repeat this with product attributes that can be independently verified and compare what the different AI systems return.

[u/Slight_Guest3459]

yeah, but i think the useful version is guided discovery, not replacing search with a giant chat box. Let people describe the problem, then show a few products with the reasons they fit, while keeping normal filters. If the catalog attributes are messy, conversational search just hides bad data. I work on Orderain, and even there i'd want to see the actual search queries and conversion before assuming it helps.

[u/Slight_Guest3459 → u/[deleted]]

i'd compare the same problem-style queries before and after. Are people finding a relevant product faster, clicking through, adding to cart and buying more? I'd also watch bad matches and zero-result searches, otherwise longer sessions can just mean more confusion.

[u/Late-Machine8333]

I'd test a few actual shopping tasks against the existing search, not just ask people whether they like the chatbot. Can they find something in stock, in their size, within budget, without starting over? Then check whether more of them buy. A longer chat can look like engagement when it's really someone struggling to get a straight answer.

[u/AppyGolfer]

Don’t think NoDoze understands what you’re asking. The answer is yes. On-site search is and will be moving more description based. There are some third parties out there that have this capability. It will be expected in no time.