A thousand carriers, a thousand ways to say the parcel is at the depot. Normalising that vocabulary is the entire engineering problem.
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CSV · Excel · JSON · XML · FTP · SFTP · Amazon S3 · Google Cloud
API, JSON feed or CSV, XLSX and JSON files
ScheduleOne-time, monthly, weekly, daily or 3 times a day
TrackingMore pages, filters, fields and a schedule
Built, monitored and repaired by our team
API, JSON feed or CSV, XLSX and JSON files
ScrapeIt runs the collection as a managed service. You name the regions or take the full directory; we build the pipeline with carrier records, coverage and status vocabulary mapped to a normalised lifecycle, raw statuses kept alongside, and hand back CSV, JSON, Excel or a push into your warehouse.
The directory changes steadily rather than constantly, so monthly collection with change records suits most briefs and is what we quote.
We collect published reference data only. No tracking events for third party shipments, no recipient data, no addresses. Requests are paced as part of the service. Everything we deliver is what any visitor can see on TrackingMore, and we collect it legally.
Carrier records carry the carrier name, its identifier on the platform, country or countries of operation, carrier type such as postal, express or last mile, website, and the tracking number formats it uses where documented.
Status vocabulary is collected per carrier as its own rows: the raw status text the carrier emits, and the normalised lifecycle stage we map it to. Both are kept, because the normalisation is an interpretation and a user who disagrees with a mapping needs the original to work from.
The normalised lifecycle is a small deliberate set - information received, in transit, out for delivery, delivered, exception, returned - chosen because a finer scheme cannot be populated consistently across a thousand carriers and a coarser one loses the distinctions people act on.
Coverage fields record which countries and lanes a carrier serves, which is the question most e-commerce operators bring to this data.
Every row carries the collection timestamp, since carrier coverage and naming change more often than people expect.
Coverage overlap analysis answers which carriers are redundant and which are the only option into a market, which is directly useful when negotiating or when planning where to add support.
Tracking number format rules, where documented, support carrier detection - working out which carrier a number belongs to without asking the customer. It is a pattern problem and the documented formats are the raw material.
Carrier change tracking over time shows which operators are added and which disappear, which is a read on consolidation in last mile delivery that is hard to see any other way.
Scope is firm. No tracking events for third party shipments, no recipient information, no addresses. Carrier reference data contains none of that, and we do not build a scraper for other people's shipments.
TrackingMore is a shipment tracking aggregator connecting to a very large number of carriers worldwide - national posts, international express companies, regional couriers and last mile operators - and presenting their tracking under one interface.
The publicly useful asset is the carrier directory. It lists which carriers are supported, where they operate, what their tracking looks like and how each one is identified, and it is substantial enough to be a reference dataset in its own right for anyone building shipping or e-commerce logistics.
The interesting problem underneath is vocabulary. Every carrier describes shipment progress in its own words and its own granularity - one says out for delivery, another says with courier, a third emits a depot scan code with no plain language at all. Mapping those onto a single lifecycle is what an aggregator does, and it is what a dataset built here has to do too.
The carrier section responds directly with a great deal of content. Everything a visitor sees there can be collected: carrier name, platform identifier, countries of operation, carrier type, website and tracking number formats.
Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan detailsThe instinct is to want tracking events. It is the wrong target for two reasons, one practical and one about people.
The practical reason is that tracking events belong to specific shipments and are retrieved per tracking number, which means bulk collection is neither possible nor sensible.
The reason about people is more important. A tracking event is a record of a parcel moving toward a named recipient at an address. Collecting those in bulk builds a dataset about individuals receiving goods, which is personal data regardless of how it was obtained. We do not collect tracking events for shipments that are not the client's own.
What the directory supports is entirely different and entirely legitimate: which carriers serve which countries, how coverage overlaps, which carriers a marketplace or platform needs to support, and how status vocabulary differs across them. For anybody building shipping software that is the reference data the project actually needs.
The fourth point is that vocabulary normalisation is reusable. Built once against a large carrier set, the mapping serves any tracking integration the client builds afterwards, which is usually worth more than any single dataset.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team builds the pipeline, maintains the status normalisation as carriers change their wording, and repairs the collector before your coverage map goes out of date.
You see a sample first, in your format, over the regions you actually ship to, with raw and normalised statuses side by side so you can judge the mapping rather than inherit it.
Still unsure? Write to info@scrapeit.io
No, on two grounds. Practically, events are retrieved one tracking number at a time. More importantly, a tracking event is a record of a parcel moving toward a named recipient, so bulk collection builds a dataset about individuals receiving goods.
Because the normalisation is an interpretation. A user who disagrees with a mapping needs the carrier's original wording to work from, and without it they would have to re-derive the whole thing from scratch.
Because a finer scheme cannot be populated consistently across a thousand carriers - many emit depot codes with no plain language at all. A coarser one loses the distinctions people act on. Six stages is where it holds together.
Coverage decisions. Which carriers serve which countries, where coverage overlaps, which one is the only option into a market, and which a platform needs to support. For anyone building shipping software that is the reference data the project needs.
That is one of the better uses. Where formats are documented they support working out which carrier a number belongs to without asking the customer - a pattern problem for which the documented formats are the raw material.
You share your needs, expectations, and desired timeframe. We'll suggest the best solution based on your request and budget.
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Tell us which sites, which fields and how often. A couple of lines is enough to start.
TrackingMore data from €169/month. Free project assessment, reply within 1 business day.