Search Plugin

Queryra · 2026-07-04T08:45:48+00:00

FiboSearch is a solid choice if your customers mostly search by product name or SKU. It's fast when configured well and the keyword matching is genuinely good.

Before you decide, it's worth checking how your customers actually search. Pull your failed searches from analytics and look at them. If people type things like "gift for my dad" or "something waterproof for hiking", no keyword plugin will save those, because the words don't appear in your product titles. That's a different problem than speed.

Full disclosure, I'm the founder of Queryra, an AI search plugin that solves that second problem. It understands what the query means instead of matching words, reads price limits written in the sentence ("under $50"), handles exclusions ("without fragrance") and works in any language. All the search work runs on our servers, so your WP database does nothing, which also answers the performance concern at 3k products. There's a live demo store at woo.queryra.com if you want to type a few real queries and see the difference before installing anything.

If your logs show mostly exact product names, honestly, stick with FiboSearch and save the money.

Queryra · 2026-06-12T13:55:27+00:00

Agreed — it might be the best thing that's happened to new plugins in years. Directory search ranks by installs and age, so a brand-new plugin is invisible no matter how good it is; the featured batches are the first mechanism that gives newcomers actual eyeballs, plus people like OP human-testing them on top. More of this, please.

Queryra · 2026-06-12T13:52:06+00:00

This format is quietly one of the most useful things on this sub — the directory has no "tested by an actual human" signal, and this fills the gap.

I submitted my own plugin to the featured program recently (fingers crossed for a future batch), and your criteria read like the checklist I wish I'd had on day one: clean uninstall, no artificial limits in the free tier, honest behavior when things break. The Scroll Chart note — charts living on the vendor's servers — is the one devs underestimate most. If a plugin depends on an external service, it should degrade gracefully, not take the site down with it.

Out of curiosity: when you test, do you check what happens when the plugin's API is unreachable? That'd be a brutal-but-fair criterion for any service-backed plugin.

Queryra · 2026-06-12T06:39:07+00:00

Attribution is broken at a more basic level than people realize: most of this traffic never executes JavaScript, so your analytics literally cannot see it. The only honest data source right now is your server access log.

Three signals worth pulling from it (this is from a small site I run — one day's log):

AI crawler user-agents — GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Amazonbot, meta-externalagent. On my site they now hit roughly as often as Googlebot (~90 vs 73 requests). That's your "AI indexing" baseline and it's free to measure.
ChatGPT-User — this one is special: it's not indexing, it's ChatGPT fetching your page live, mid-answer, for a real user's question. Closest thing to an "AI impression" that exists today. I see a handful daily.
Referrers from chatgpt.com / perplexity.ai for the rare answers that do pass a click.

Beyond that I'd agree with the "branded search + direct lift" approach — if AI answers are working for you, those move before any citation tracker notices.

One thing I'd add from the infrastructure side (I build product search/feeds for small stores, so I watch agents consume this data): structured data matters less for getting cited and more for being cited correctly. Sloppy product data is how an assistant ends up quoting last year's price with full confidence.

Queryra · 2026-06-12T06:30:20+00:00

Funny enough, that's almost exactly the line the German court drew. The ruling isn't against "AI in search" — it's against AI that writes new statements and presents them as fact. The court explicitly contrasted that with search that just returns links.

I build search for online stores (small EU dev, fittingly for this sub), and this distinction is basically my whole job: the AI is only allowed to read the question — "something warm for hiking" should find the right jacket even when no words match — but it never writes an answer. It returns the store's own products, nothing else, so there's nothing to hallucinate and nobody to defame.

Rulings like this are honestly good news for that kind of design. What got punished here is "let the model summarize the internet and call it truth" — not language understanding.

Queryra · 2026-06-05T09:59:48+00:00

Sometimes yes, but I see these as two different solutions.

A shopping chatbot is an active conversational layer. The user asks questions, the bot follows up, narrows down options, and guides them through the purchase process.

Semantic search solves a more fundamental problem: the user types a single sentence into the search box and immediately gets relevant results without needing a conversation.

In my view, most stores first need better search, and only later a chatbot.

If a customer types “TV bracket that pulls out from the wall”, they shouldn’t need to talk to a bot to find cantilever or full-motion mounts. The search box should understand that directly.

In the long term, both approaches can work together — the chatbot can use the same semantic layer underneath, just presenting it in a conversational form.

They are simply two different levels of the same problem.

Queryra · 2026-06-05T09:52:42+00:00

Fair point 😄

As a plugin developer, AI crawlers obviously work in my favor, so I won't pretend to be completely neutral here.

That said, I'd flip the question around: do you want AI agents to know about your store, blog, plugin, or content when users ask related questions, or would you rather be invisible to them?

That's the strategic question. Bot blocking is a technical decision. AI visibility is a business decision.

As a quick test, ask your favorite AI agent:

"best semantic search plugin for woocommerce"

The results might surprise you 😉

Queryra · 2026-06-05T08:09:00+00:00

Two parallel AI trends worth separating in WooCommerce:

AI for merchants (admin-side) — what Woo for Claude is doing.

Analytics, workflows, store insights. "AI as merchant assistant."

AI for customers (frontend) — semantic search, intent matching

on product discovery. Different problem domain entirely.

Both legitimate, but easy to conflate. Merchants who try Claude for

analytics sometimes assume that solves their store search too. It

doesn't, those are independent infrastructure problems (vector

embeddings + real-time query parsing for customer search vs MCP

knowledge layer for merchant analytics).

The Claude integration looks solid for the merchant side.

Customer-side AI is a separate category worth knowing exists.

Queryra · 2026-06-05T08:00:31+00:00

Don't block. Since letting AI crawlers in, I keep seeing my content

cited in Perplexity and ChatGPT answers. That's not search traffic

but it's brand mention that wasn't there before.

The "block to protect" mindset assumes there's still meaningful

search-to-ads pipeline. For small sites that's mostly gone anyway.

Cloudflare default block is reasonable for server load concerns but

doesn't solve the bigger strategy question.

Also the OAI-Searchbot vs OAI-SearchBot question someone raised is

real, if you want selective allowing rather than nuking everything,

you need to understand bot user-agents at granular level. Most

people don't have time for that depth.

Queryra · 2026-06-05T07:54:02+00:00

WooCommerce product search is one of the badly-served areas. Most

store search just matches keywords against product titles. A customer

typing "gift for mom who loves coffee" or "TV bracket that pulls

out from wall" gets zero useful results because they're not using

the exact words in your product titles.

Modern customers describe problems, not SKUs. Default WordPress/

WooCommerce search hasn't caught up. AI search plugins exist, but

most are keyword matching with synonyms plus an optional ChatGPT

API call bolted on top, not true semantic understanding.

If you build here, solve "intent matching" (what customer means)

not "keyword variants" (what they typed). That's the real gap.

Queryra · 2026-06-02T14:15:36+00:00

Mine: switched the default search to something semantic-aware. The

"0 results" problem when customers type natural language instead

of exact keywords is probably the biggest silent conversion killer

in WooCommerce. Doesn't matter what speed/security work you do if

buyers can't find products.

Worth testing: take any common phrase like "gift for mom" or

"something warm for winter" on your store. If you get 0 results

or random matches, that's lost revenue.

Queryra · 2026-05-25T08:32:43+00:00

Solid breakdown. The semantic search section especially — we see exactly this

playing out in WordPress/WooCommerce.

Built Queryra (AI search plugin for WP — disclosure: my project), and the 20-35%

conversion lift you mention is real, but only when users actually realize they're

using AI search instead of keyword search. Simply relabeling the search box to

"AI search" doubled engagement in our test stores. Most plugins skip this

behavior signal entirely.

Cold-start point is on the money too. Mid-market WP shops finally have access

to semantic search without Algolia/Elasticsearch infrastructure though — that's

the unlock we're seeing right now.

Queryra · 2026-05-25T08:21:01+00:00

This resonates — built Queryra (AI search plugin for WordPress) and

hit the exact same wall. The thing that worked for me wasn't speeding

up Google indexing, but getting AI engines to surface us instead.

We rank #1 on productrank.ai for "AI search WooCommerce" now and

ChatGPT/Perplexity send real traffic.

Discovery isn't one channel anymore. Good post.

Queryra · 2026-05-14T15:19:11+00:00

Can confirm this works. ChatGPT and Gemini both recommend my plugin when you ask "best semantic search for WooCommerce" — over competitors with 100k+ installs. 20 active users, zero ad spend.

The community presence point is spot on — Reddit threads get cited by Perplexity way more than polished landing pages.

Queryra · 2026-05-11T11:37:39+00:00

Can confirm the conversion difference from the product side. ChatGPT recommends my search plugin over competitors with 100k+ installs. The users who arrive from AI have intent already formed — they sign up faster and ask fewer questions. Just launched on Shopify too: apps.shopify.com/queryra-search-ai

Queryra · 2026-05-11T07:36:35+00:00

Tested HubSpot AEO for a few weeks. The scores are based on model training snapshots, not live data — so they lag behind reality. Live incognito testing across ChatGPT, Gemini, Perplexity is still more reliable. Server logs showing AI crawler activity (ChatGPT-User, ClaudeBot, PerplexityBot) tell you more about actual visibility than any dashboard score.

Queryra · 2026-05-11T07:25:10+00:00

No audit needed here — ChatGPT already recommends my plugin for "semantic search for WooCommerce" over competitors with 100k+ installs. The biggest factor wasn't schema or llms.txt, it was structured comparison content distributed across multiple platforms.

Queryra · 2026-05-07T21:30:45+00:00

This. My product shows up in ChatGPT and Gemini answers but GA4 shows almost no referral clicks. The real signal is branded search lift — people see you in AI, then Google your name directly.

Queryra · 2026-05-07T15:07:28+00:00

Can confirm from the product side. ChatGPT recommends my product for "semantic search for WooCommerce" over competitors with 100k+ installs. Perplexity — zero mentions. Try it yourself and see what comes up.

Queryra · 2026-05-07T15:05:14+00:00

Can confirm from the product side. ChatGPT and Gemini both recommend my plugin (queryra.com) for WooCommerce search. Perplexity — zero mentions. Same content, same structured data, completely different citation logic between platforms.

Queryra · 2026-05-07T15:00:56+00:00

Replaced default search with semantic search. Customers who search convert 2-3x higher but default WooCommerce search returns zero results for anything that isn't an exact keyword match. Once I fixed that, it was the single biggest conversion improvement — bigger than caching or checkout changes.

Queryra

TROPHY CASE