Yes. SleekAI reads your products from any post type or e-commerce plugin (WooCommerce, Easy Digital Downloads, or a custom CPT), and you can include attributes like skin type, dietary tag, or plan tier as named context. The bot uses those attributes to filter its recommendation rather than guessing from generic knowledge, which is what keeps the answer accurate when your catalog evolves.

Yes. Multibot lets you run a different chatbot per landing page or campaign, each with its own system prompt, branching logic, and product scope. A skincare brand can run a 'find your moisturizer' quiz on one page and a 'find your serum' quiz on another, both backed by the same catalog but with different tone and depth.

At the end of the conversation, the bot can politely ask for an email to send the result. The full transcript, the recommendation, and any captured attributes are forwarded by webhook to your CRM, ESP, or marketing automation tool. Most teams route into Mailchimp, ConvertKit, Klaviyo, HubSpot, or ActiveCampaign with a tag that reflects the quiz outcome, so follow-up emails can reference the actual result.

Yes. The guideline filter and the system prompt constrain replies to the quiz domain. If a visitor asks an unrelated question, the bot politely steers back to the quiz rather than improvising about adjacent topics. The presets feature surfaces three sample questions so visitors who are not sure how to start the conversation can pick one.

Conversations are stored in your WordPress database with model name, token usage, and page URL, so a partial quiz is visible to marketing the same way a partial cart is to e-commerce. Some teams use that data to spot which question causes the most drop-off and shorten or rewrite it. The full log is also useful for refining the system prompt over time.

Each turn takes a couple of seconds for the model to respond, which is comparable to the page-load delay of a multi-step static quiz between answers. In return the visitor goes through far fewer turns, because the bot can skip irrelevant ones. End-to-end completion time is usually equal or shorter, and completion rates are usually higher because the conversation feels less robotic.

Yes. Use display conditions to show the SleekAI chat to a percentage of traffic, or wire it to your existing experimentation tool. Compare completion rate, captured-email rate, and the downstream conversion of the recommendation. Most brands find the chat lifts captured-email rate because the explanatory result lowers the perceived risk of handing over an address.

Conversations live in your WordPress database, not on a third-party platform. With your own OpenAI, Anthropic, Google, or OpenRouter API key, the data follows that provider's API terms, which by default do not use API content for training. For privacy-conscious brands, that is usually easier to defend than a black-box vendor chatbot.