Someone with a cracked MacBook Pro screen wants to know what the repair costs, how long it takes, and whether you have the part in stock. A generic chatbot that asks for a name and quotes a flat 'we charge a $49 diagnostic fee' loses the lead because the customer is pricing three repair shops and Apple's service. SleekAI reads your service tiers, parts inventory, and turnaround times from WordPress and quotes the specific repair honestly, with mail-in and in-shop options both surfaced.

The example chat shows the difference. A 2020 MacBook Pro 13-inch with a cracked screen gets quoted at $329 for the screen replacement, with the part in stock and a 1 to 2 business day turnaround. The bot asks the right questions: model year, whether the touch ID or trackpad is affected, and whether there's any liquid damage history. Those questions matter because a 2018 MacBook Pro 15-inch is a different repair than a 2020 13-inch, and a unit with prior liquid damage may have logic board corrosion that changes the conversation entirely.

Booking captures the device scope. Make, model, year, IMEI or serial if the customer has it, symptoms, and any prior repair history save into WordPress against the work order. The tech who picks up the repair Tuesday morning already knows it's a 2020 MacBook Pro 13-inch with a cracked screen, no liquid damage history, and the customer chose in-shop pickup. The repair goes from a 4-hour cold intake to a 90-minute scoped repair, and the customer gets a 'ready for pickup' text by 2 PM.

Computer repair is a price-sensitive, comparison-shopped trade. A customer with a cracked MacBook Pro screen is calling three local shops, Apple's mail-in service, and an authorized AASP within the same hour. A generic chatbot that says 'we charge a $49 diagnostic fee, bring it in' loses every comparison because the competitor's chatbot quoted $329 with parts in stock.

Model-aware quoting matters because the customer's question is concrete (how much for my exact laptop), and a real answer wins the booking. Repair shops running SleekAI find that walk-in conversion goes up because the customer already knows the price, the turnaround, and the part availability before they leave the house. The tech's queue shifts from cold intake (where 30 minutes per ticket goes to re-discovering what the customer wanted) to scoped repairs (where the bench time goes to actual work).

Same-day cutoff times set correctly mean customers show up at 9 AM instead of 4 PM expecting a same-day finish, which protects the bench schedule. Mail-in service becomes a real revenue line because the bot can scope the repair without the customer having to ship the unit first. Computer repair shops have to compete with Apple's mail-in service and Best Buy's Geek Squad on price and trust, and the chatbot is where that competition lives, before the customer ever walks in the door.