Freight logistics: shipment status and intake

A transport and logistics company with a constant flow of cargo and a large client base. Every customer wants to know exactly where their cargo is and when it will arrive, and is used to calling the dispatcher directly for the answer. The status information was already in the accounting system, but only an employee could pull it by hand. As a result, dispatchers, whose real job is planning routes and solving problems on the road, spent half the day answering the same kind of questions by phone.

We broke down the structure of requests over several weeks and saw a clear picture. The bulk of calls was a simple question about status, whose answer was already in the system and did not require the dispatcher to decide anything. At peak hours the line was busy, and clients with a new request or an urgent problem simply could not get through. And the new requests themselves came now to email, now to a messenger, now by phone, and some got lost without a single intake point.

The task split in two. First, to give the client the cargo status automatically, by reference number and at any time of day, so as not to occupy a dispatcher with it. Second, to take new orders in the same window through a clear form and enter them into the system at once, so no request is lost. At the same time the assistant must honestly say when there is no data, rather than inventing the cargo location.

We built an assistant on Telegram as a single window for freight clients. When a person sends a reference number, the assistant queries the accounting system through an integration and returns the current status in real time: where the cargo is, at what stage and the rough timeline. If the client comes with a new order, the same bot collects the route, cargo type and volume and contacts step by step, and then enters a structured request into the CRM. When there is no data for the number or the situation is non-standard, the assistant does not guess but switches the conversation to a live dispatcher.

The project took about a month. First we connected the assistant to the status accounting system via an API, so answers were always taken from the source rather than from copies. Then we described the new request form: which fields are required and how they fit into the CRM. Separately, we walked through the scenarios where the bot is required to hand the dialog to a human. We launched carefully, first on regular clients who ask about status most often, and after a trial we opened the assistant to everyone.

After launch, reference calls about status dropped by about a third, because clients began getting an answer in the chat within seconds and at any time, including nights and weekends. Dispatchers won back time for direct work: planning routes, monitoring trips and dealing with real problems. New requests stopped dissolving between channels, since they now have one entry point and a single format in the CRM. Clients feel calmer: the cargo can always be checked by themselves, without waiting for an answer by phone.