Automating track & trace: connect carriers so AI gives the real delivery status

In almost every webshop a single question accounts for the largest share of customer contact: where is my order. This question, known internationally as WISMO, arises the moment a customer has paid and is waiting for their parcel. The longer the silence around the delivery, the greater the urge to check in. So a large share of incoming emails, chats and calls is not about a problem, but about uncertainty.

The answer to that question rarely sits in the webshop itself. It sits with the carrier: with the courier that scans, transports and delivers the parcel. As long as that information is not available automatically, answering delivery questions stays manual work. This article describes how automating track and trace works and how to connect carriers. It then covers the pitfalls, and how AI gives the real delivery status rather than a guess.

A delivery question seems simple, but handling it is deceptively cumbersome. An agent receives the question and looks up the order in the webshop. There is the tracking code. They paste it into the carrier's website, read the status and retype it into a reply to the customer. That is a series of separate actions that costs minutes per question. With dozens or hundreds of such questions a day, it adds up to a substantial share of working time.

The problem grows the moment a webshop works with multiple carriers. One order goes with one party, the next with another, and each party has its own portal and its own way of showing statuses. So the employee not only has to look things up but also has to choose the right environment each time. That costs mental energy and leads to mistakes, such as a wrong code or an outdated status.

On top of that the information often lags behind reality. A customer who calls because the parcel has not arrived is sometimes told it is on the way. A newer scan already shows a failed delivery attempt. Without current and connected data the organisation answers based on a snapshot that may no longer be accurate.

Step 1: connect the webshop to the service environment

The first step is the foundation: make sure the order data from the webshop is available in the environment where customer questions arrive. Every order has an order number, a customer, products and a shipping method. By connecting that data, the service environment immediately knows which order an incoming question concerns, without anyone having to search.

Step 2: connect the carriers

Next the carriers are connected. One carrier or several? Shipping direct or through a platform? The goal stays the same: each carrier's tracking information flows back to the order automatically. That turns a tracking code from a loose string someone has to look up into a living status attached to the order.

Step 3: link the status to the right customer and order

A raw carrier status is not enough on its own. The value emerges only when that status is inseparably linked to the right customer and order. That way an agent or the AI sees more than 'a parcel is on the way'. This customer is waiting for last week's order, and the latest scan showed a specific event.

Step 4: let AI translate the status into an answer

A carrier speaks in technical statuses and codes. A customer wants an understandable answer. The AI translates the raw status into a clear sentence. On the way and expected on a given day, out for delivery today, or a failed attempt with a follow-up action. The answer then rests on the real data, not on a generic phrasing.

Step 5: handle exceptions separately

Most deliveries go to plan, but the exceptions need attention. A delayed parcel, a failed delivery or a return in transit should not be brushed off with a standard answer. By recognising exceptional statuses, the organisation can pick up these cases separately, for example with a proactive message or a follow-up task for an employee.

Connecting carriers first solves the reactive problem: a question is answered faster and more correctly. But the real gain lies in the next step, where the organisation gets ahead of the question. As soon as delivery data flows in live, an exception can be spotted before the customer asks about it. A parcel running late or a failed delivery attempt can trigger an automatic message that reassures the customer or proposes a new arrangement.

That proactive layer changes the nature of customer contact. Instead of a stream of worried questions, a stream of reassuring updates emerges. The customer does not need to check, because the organisation is already reaching out. That structurally lowers the volume of delivery questions, because the uncertainty that causes the question is removed before it leads to contact.

To make this work it is important to measure which statuses lead to questions and which proactive messages work best. A webshop that sees a certain delay status consistently lead to contact can attach a fixed proactive message to it. That way delivery communication becomes ever more precise, based on what customers actually need.

Webshops rarely work with a single carrier. A domestic order goes differently from an international one, a parcel differently from a letterbox delivery, and large items via yet another party. Each carrier has its own portal, its own status codes and its own way of reporting. For the customer that is invisible, but for customer service it means logging into several systems to answer one simple question.

Automation only truly pays off once that fragmentation is removed. Instead of searching per carrier separately, the status of every shipment comes together in one view that is tied to the right order and customer. The agent or the AI sees at a glance where the parcel is. Which party delivers it makes no difference. That removes the difference between carriers from daily work.

That integrated status view is also the foundation for proactive communication. As soon as a status change comes in, regardless of source, an update can go out to the customer automatically. A delay at one carrier is handled the same way as at another, and the customer notices nothing of the complexity behind it. The result is less manual work, fewer errors and a consistent experience across all shipping partners.

Behind all the technology there is one goal: the customer does not have to ask where their parcel is. When tracking is automated across all carriers, the customer gets the right update at the right moment, without taking any action themselves. Picked up, in transit, out for delivery today. Every step arrives automatically, in plain language and linked to the right order.

That changes the experience fundamentally. Instead of uncertainty and having to search themselves, there is a sense that the shop is watching along and keeping the overview. If a question does come, the AI can answer it directly with the current status, regardless of which carrier holds the parcel. The customer notices nothing of the portals and status codes behind it, and that is exactly the point.

Automating track and trace starts with a solid connection between the webshop, the carriers and the place where customer questions arrive. The delivery status has to be attached to the right customer and order. Only then can AI answer 'where is my order' with real data rather than a guess. Then comes the proactive layer, where the organisation gets ahead of the question.

The building blocks are ready. The integrations connect the webshop and the carriers to the service environment. The page on automating shipping questions shows how delivery questions are handled at scale, and where is my order goes deeper into reducing WISMO. For a broader picture the page on customer service for e-commerce helps.

Want to see how the real delivery status reaches every conversation? Request a demo and discover how AI handles delivery questions based on the actual data from your carriers.