Candle customers do not ask if you sell candles. They ask whether the Tobacco Vanilla scent is too smoky for a bedroom, whether the 8oz tin gives a true 45 hour burn, whether the soy wax is single-origin or a blend, and whether the scent is sweetened with vanillin or natural vanilla absolute. Those are specific catalog questions tied to your scent notes, wax sourcing, and burn-test data. Generic chatbots trained on candle category copy give vague answers and miss the conversion.

SleekAI maps directly into the WooCommerce attributes most candle shops use. Scent family (woody, floral, gourmand, fresh), top and base notes, wax type (soy, paraffin, coconut blend, beeswax), vessel size, and burn time each live as product attributes in wp_term_taxonomy or postmeta. SleekAI's data mapper reads the active variant at answer time, so a Tobacco Vanilla 8oz question quotes the 8oz variant's actual burn time, price, and stock count.

The other half of candle support is the gift conversation. Customers ask which scent suits a baby shower, which travel tin works for office desks, which collection makes a strong Mother's Day bundle. Those answers tie to scent metadata, gift-bundle product groupings, and seasonal availability. SleekAI exposes all that to the model so the bot recommends from your in-stock catalog, not from a generic candle-gifting blog.

Candle buying is a sensory decision made without smelling. Customers shop online based on note descriptions, burn time claims, and wax sourcing language. A vague answer from a generic chatbot kills the trust that a small candle brand spends years building.

Tobacco Vanilla described as warm and cozy means nothing. Tobacco Vanilla described as pipe tobacco leaf on top, vanilla absolute heart, tonka amber base, with a 40 to 45 hour burn in the 8oz tin made from single-origin Iowa soy at 9 percent fragrance load tells the customer everything. SleekAI delivers the second version because it reads the exact postmeta, attribute, and product description fields the candle maker uses to organize the catalog.

The bot answers like the maker would behind the booth at a craft fair, except the chat is open at 11pm when most candle shopping happens. The maker sees a log of which scents drive the most questions, which feeds the next collection's direction and which scents deserve sample-size promotion. Gift-giving customers feel safe choosing a scent for a friend because the bot can explain the notes in plain language.

Returning customers get instant answers about which collection their favorite scent moved into. The whole experience reflects the care that went into the candle itself, which is the difference between a casual buyer and a regular.