Product finder chatbot for your store
SleekAI reads your products, attributes, and ACF fields directly, asks two or three qualifying questions, and recommends the right SKU with stock and price. Plug in OpenAI, Anthropic, Google, or OpenRouter and pay the API directly with your own key.
Faceted filters lose the shopper who doesn’t know the vocabulary
Most product finders are a stack of filters that only work if the visitor already knows the words your catalog uses. A first-time buyer types “something quiet for a small apartment” into the search box and gets nothing, because your attributes say “55 dB” and “compact footprint”. The mismatch is the leak, and it shows up as session bounces no analytics tool ever attributes to bad navigation.
SleekAI replaces the filter wall with a conversation grounded in the same WooCommerce or custom-post-type catalog. You map products, taxonomies, variations, stock meta, and any ACF attribute into the prompt context via the data-source wizard.
The bot asks two or three qualifying questions, then names two or three SKUs with a one-line reason each. Bring your own OpenAI, Anthropic, Google, or OpenRouter key and pay the model provider directly at their rates.
Features
Attribute-aware
Maps the shopper’s plain-language goal onto the attributes, taxonomies, and meta keys you have already tagged. Two or three qualifying questions is usually enough to land on the right shelf.
Stock and price honest
Variation stock and price live in postmeta and flow into the prompt unchanged. The bot quotes what your shop quotes today, not a cached snapshot from last week’s catalog export.
Answers from your data
Map post titles, content, post meta, taxonomies or a WP_Query into the instruction, and the bot answers from what your site actually publishes.
Where it helps
Specialty retail
Outdoor, audio, and hobby shops where the catalog is wide and the buyer vocabulary varies. The bot translates “single-wall bivy under 1 kg” into the right shelf without forcing the shopper to learn the filter UI.
Configurable products
Mattresses, bikes, and furniture where two or three qualifying questions matter more than browsing.
Repeat questions
Answer the questions visitors ask every day from the pages and posts where you already answer them.
How SleekAI runs a product finder
Map the catalog
Include products, taxonomies, variation stock, and any ACF or attribute fields shoppers reference. Skip the meta keys nobody searches for, since token cost adds up across a wide catalog.
Map your data
Choose the posts, fields, taxonomies or users the bot should know and reference them in the instruction.
Place on shopping templates
Display conditions show the bot on shop, category, and single-product templates and hide it on the blog and home page. The shopper meets it the moment they enter a buying flow.
Set display conditions
Decide which pages, post types, roles or logged-in states show the chatbot.
Why a finder bot beats a filter wall
Filter-based discovery optimises for visitors who already know the vocabulary of your catalog. The serious cyclist knows what “single-wall” means; the first-time buyer doesn’t. As stores expand into adjacent customer segments, that vocabulary mismatch becomes the leak, and it shows up as session bounces no analytics tool ever attributes to navigation.
A conversational interface sidesteps the problem because the shopper describes the goal in their own words and the bot maps that description onto attributes you have already tagged. The other lever is trust. A recommendation with a one-line reason beats a list of twelve unranked results because it does the comparison work the shopper would otherwise outsource to a third-party blog or YouTube review.
The ancillary win is operational. Every miss is a logged query that points at a missing category, an unclear product title, or an attribute that needs to be tagged. None of that data exists in a static facet UI.
Over a quarter, the logs become a merchandising backlog you can actually prioritise, and the questions that used to vanish into the bounce rate now show up as concrete content and tagging work.
The bot also keeps merchandising honest. When a recommendation can’t be grounded, the right behaviour is to say so and escalate rather than improvise, which is the difference between a finder shoppers come back to and one that loses their trust the first time it invents an SKU.
Frequently asked questions
Does the bot read live WooCommerce stock?
Yes. Stock status and per-variation stock live in postmeta, so they flow into the prompt the same as any other field. The bot can answer “is the medium in stock” or “which colour ships fastest” if you include the relevant meta keys. Keep the field list lean to control token cost, since wide catalogs add up quickly when you include every attribute.
Can it recommend across multiple categories at once?
Yes. You can scope the WP_Query that feeds context to a parent taxonomy or to the whole shop, and the system prompt tells the bot how many SKUs to surface per reply. Most teams cap it at two or three picks with a one-line reason each, which keeps the chat scannable and avoids the wall-of-results pattern shoppers came to the chat to avoid.
Will it invent products that don’t exist?
Only if you let it. A tight system prompt tells the bot to refuse rather than guess, and the grounding context only includes products you have actually published.
Does it work with variable products?
Yes. WooCommerce variations are children of the parent product in wp_posts with their own postmeta for price, stock, and attributes. SleekAI can include the relevant variation data in the prompt so the bot can answer per-size and per-colour questions without a separate integration.
Can I show different bots on different shop sections?
Yes. Multibot lets you run a tuned bot per category or template, and display conditions decide which bot loads where.
Can it work without WooCommerce?
Yes. Any post type works. Custom catalogs built on ACF or Meta Box flow through the same data-source wizard, and the bot doesn’t care whether the products are WooCommerce SKUs or custom post type entries.
Which AI providers does it support?
OpenAI, Anthropic, Google and OpenRouter, plus custom OpenAI-compatible endpoints. You bring your own API key and the provider bills you directly.
Where does the chatbot get its answers?
From the WordPress data you map into its instruction: post titles and content, post meta, ACF and Meta Box fields, taxonomies, terms, users and user meta, or a WP_Query. Values resolve on every request.
Pricing
Explore our flexible licensing options tailored to your needs. Upgrade your license anytime to access more features, or opt for a lifetime license for ongoing value, including lifetime updates and lifetime support. Our hassle-free upgrade process ensures that our platform can grow with you, starting from whichever plan you choose.
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What’s included
SleekAI
SleekByte
SleekMotion
SleekPixel
SleekView
SleekRank
SleekTrack