Yes. Frame size and colour are usually WooCommerce product variations, and SleekAI reads those plus the parent product attributes in the same request. Geometry charts that live in ACF or custom fields are mapped through the data-source wizard. The bot can quote 'the 54cm Journeyer in Spruce Green is in stock' from the same data the product page uses, so there is no separate catalog sync to maintain through spring rush.

If you track service in a booking plugin like LatePoint or Bookly, or in a custom 'service ticket' post type, SleekAI reads the open count and your configured lead-time rules. The bot can say 'tune-ups are running 5 to 7 days this week' rather than a generic 'usually about a week'. As tickets close the answer shifts on its own, which keeps the bot honest during the May rush when turnaround can double overnight.

Yes. Multibot lets you scope a bot to a product category or URL pattern. A road-bike bot can lean into fit and aero questions, the gravel bot can focus on tyre clearance and bikepacking, and the MTB bot handles suspension setup. Shared brand voice and service info live in a common knowledge pool so you only edit policy in one place. Display conditions support 28+ rules including taxonomy term, role, and URL pattern.

Used bikes are usually a separate WooCommerce category or a custom post type with condition notes and a single quantity. SleekAI reads both. The bot can quote 'we have one used Marin Nicasio in size M, photos on the listing' from the same data your floor sales staff uses. For trade-in intake, you can wire the bot to a custom form that captures brand, model year, and condition before the rider visits.

All conversation logs stay in the WordPress database with model name, token usage, and the page URL the chat happened on. Nothing routes through a Sleek-hosted server, just browser to WordPress to your chosen API. That makes spring-rush capacity planning easier because you can see which categories drive the most pre-purchase chats and which service questions repeat enough to deserve a dedicated FAQ entry.

If you use LatePoint, Bookly, Amelia, or a similar plugin, SleekAI can read available slots and link the customer to the booking page with the right service preselected. For more control you can wire a small REST endpoint that creates the booking directly from the chat. Most shops start with the link approach and graduate to direct booking once the chat volume justifies the dev time.

E-bike questions are mostly about battery range, charge time, motor brand, and replacement battery cost. Those values live in product meta or ACF fields on the bike CPT. SleekAI quotes them directly so 'how far will the Tero 3.0 go on a charge' gets a real number from the manufacturer spec rather than a generic 'depends on terrain' deflection. Battery service questions can be routed to a dedicated e-bike technician contact if you have one.

The widget loads asynchronously and only fetches context when a rider actually starts chatting, so the bot has no impact on first-paint or Lighthouse scores. Compute cost scales with conversations, not pageviews. Bring-your-own API keys means there is no per-message markup, so a 4x traffic spike does not blow up the support budget. Most shops budget the same way they budget for tubes, by expected season volume.