Auto body shop: photo estimate and booking

An auto body shop worked mainly through Instagram and WhatsApp and got dozens of requests a day. Almost every one started the same way: the client sent a couple of photos of a dent or a scratch and asked how much it would cost and when they could drop by. The mechanics had to answer straight from the shop floor, breaking off from painting and panel work. In busy hours the messages piled up, replies lagged, and some clients managed to message the shop next door.

Going through several weeks of chats, we saw that the overwhelming majority of questions come down to a rough estimate from a photo and a booking for an inspection. That needs no mechanic qualification, yet each time it yanks one out of work and breaks the pace in the shop. It also turned out that clients cool off fast: if a clear price range does not arrive in the first minutes, interest fades and the person goes where they got an instant reply. Here the speed of the first answer decides more than the price itself.

We needed an assistant that recognizes a typical kind of damage from a photo and a short description, honestly names a preliminary price range and immediately offers a time for inspection. It was important not to over-promise: a photo estimate is always a range, not a final number, because hidden damage shows only on the lift. The assistant should sound confident but careful, explain that a mechanic will confirm the exact cost, and under no circumstances invent prices out of thin air.

We built an assistant that meets the client on Instagram and WhatsApp, asks for an overall shot and a couple of close-ups and reads the nature of the damage from them. Drawing on a base of the shop's typical jobs and prices, it names a preliminary range and explains what the final figure depends on. Then it shows free windows and books the inspection into the calendar. The tone is friendly and without pressure: the assistant openly warns that a mechanic will confirm the exact sum after inspecting on the lift.

The project took about five weeks. First we gathered examples of damage with real outcomes and sorted them into typical jobs with prices. Then we set up recognition of common cases from photos and tied the price ranges to that base. Separately we wrote honest caveats about hidden damage so the assistant would not over-promise. We connected booking to the calendar, ran the scenario on part of the Instagram inbound, tuned the wording from real dialogs and rolled the assistant out to both channels.

After launch the assistant handles almost all first requests itself. The mechanics are no longer pulled into chats and keep the pace in the shop, while the client gets a clear price range and an offer to book within the first minutes. Thanks to the speed and clarity, noticeably more people now make it from a request to a visit: before, many dropped off at the waiting stage. The average ticket did not slip, because a mechanic still sets the final cost after inspection.