WooCommerce Pre-Orders adds product meta keys like _wc_pre_orders_enabled, _wc_pre_orders_availability_datetime, _wc_pre_orders_fee, and _wc_pre_orders_when_to_charge, plus a dedicated wc-pre-ordered order status that flows through to wc_actions for charge-on-release. SleekAI maps those fields into the bot's system message alongside line items, so a shopper asking when their copy of a new title arrives gets the same date the product page shows.

That turns release-date and charge-timing questions into one-shot answers. A shopper asks when the May 30 album drops, the bot reads _wc_pre_orders_availability_datetime and the configured charge mode (upfront, on release, or on shipping) and explains exactly what will happen to their card. If a pre-order is already placed, the bot reads the order status wc-pre-ordered and the line items to confirm the position in the queue.

Display conditions can scope the bot to single product pages with _wc_pre_orders_enabled=yes and to My Account, so the bot only fires on contexts where pre-order logic actually applies. Conversation logs capture each ask with model name and token usage, useful when product teams want to feed common questions back into saved presets or detect a release date that needs to be updated because the meta says one thing and customers are hearing another.

Pre-orders are unusually high-anxiety transactions. The shopper is paying for something they cannot hold yet, often weeks out, with charge timing that is not always obvious from the checkout flow. Every detail that is unclear (when does it ship, when does the card run, is there a fee) generates a support ticket.

On a quiet store that is fine. On a launch week, the inbox doubles and the team ends up answering the same three questions for ten days straight. WooCommerce Pre-Orders already structures the data.

The release date is right there as _wc_pre_orders_availability_datetime, the charge mode is _wc_pre_orders_when_to_charge, and the order status flips through wc-pre-ordered into wc-processing once the press date arrives. The problem is that this structure lives in the database, not in the customer's head. A chatbot that reads the same fields answers each question with the exact configured value, in the same tone the store would use, without the team having to type the reply.

Generic chatbots cannot do this. They have a vague training-data idea of what a pre-order is, but no clue what your release date is or whether the customer's card runs today. They will either hedge to the point of uselessness or invent a date, which is worse.

The variable mapping closes that gap. It also lets the bot stay honest at the moments that matter most, like the morning a release date slips and the team needs the bot to reflect the new value the second the meta updates.