Data alone doesn’t deliver a package. But it can play a crucial role in ensuring that it arrives reliably.
Whether a purchase is completed depends not only on the product and its price. The delivery options offered also play an important role. According to the DHL E-Commerce Trends Report 2025, 85 percent of online shoppers surveyed in Germany would abandon their purchase if their preferred delivery option were not available.
This presents a clear challenge for online retailers: they must offer shipping options that meet their customers’ expectations while ensuring reliable delivery times. This is particularly challenging in international e-commerce, as different carriers, transport routes, transshipment points, and local delivery networks increase the complexity.
This is where big data comes into play. When shipment information is systematically collected, linked, and analyzed, it becomes easier to identify delays, compare carriers more objectively, and manage shipping processes more effectively.
But what data is truly relevant? How does this data translate into concrete decisions? And what are the limitations of data-driven logistics?
Source: DHL E-Commerce Trends Report 2025.
This article was first published in March 2026 on our previous website.
For its new edition in October 2026, it has been thoroughly updated, expanded in terms of technical content, and supplemented with additional topics.
The Most Important Points at a Glance
Big Data Creates Transparency. Analyzing shipment, transit time, and tracking data reveals where delays or recurring problems occur within international supply chains.
Data Helps Make Better Shipping Decisions. Historical transit times, carrier performance, and current capacity information can help you choose more appropriate shipping options and estimate delivery times more realistically.
Tracking affects the customer experience. Clear status updates and early notifications of any issues help recipients track the shipment of their order.
What Does Big Data Mean in Logistics?
Big Data refers to the collection, processing, and analysis of large volumes of data that vary in structure and are often generated rapidly. In logistics, such data is generated during nearly every step of the process, from goods receipt through sorting to delivery to the recipient.
Three characteristics are often associated with Big Data: volume—the amount of data; velocity—the speed at which data is generated and processed; and variety—the diversity of data sources.
For shipping logistics, for example, shipment scans, timestamps, package dimensions, shipping destinations, carrier information, and historical delivery times are relevant. Depending on data availability, additional information may be included, such as capacity reports or notifications of transportation disruptions.
What matters most is not simply the volume of data. It is the quality of the data, how it is linked, and how it is analyzed that enable meaningful decisions.
Which shipping data is particularly valuable?
Shipment and tracking data document the individual stages of a shipment. Timestamps can show how long packages are processed at a hub or when they are handed over to a delivery partner.
Transit time data broken down by destination country, region, and carrier allow for a comparison of various shipping and delivery options. When doing so, it is important to consider not only average values but also variations and the reliability of delivery.
Shipment volumes and seasonal trends help with capacity planning. Historical volumes can provide insight into the workload to be expected during sales promotions or peak season.
Delivery issues and return data highlight areas where processes can be improved. Recurring address issues, failed delivery attempts, or unusually long return times provide clues as to possible causes.
Individual data points thus come together to form a comprehensive picture that companies can use for their operational and strategic shipping planning.
How Can Big Data Improve Delivery Times?
The greatest benefit is realized when companies use existing information to develop concrete actions. This does not necessarily mean transporting every package faster. Often, it is at least as important to forecast delivery times more realistically and to identify deviations early on.
Forecasting Delivery Times More Accurately
A general estimate of delivery time is often insufficient for international shipping. This is because shipments to different regions within a single country can have varying delivery times, even when using the same carrier.
By analyzing historical delivery data by destination country, region, shipping service, and other relevant factors, you can better identify typical transit times and variations. This allows you to derive more realistic delivery time forecasts.
Such forecasts are often referred to as the Estimated Delivery Date, or EDD for short. Their accuracy depends largely on how up-to-date, complete, and representative the data used is.
Compare Carriers Based on Data
Not every shipping provider is equally suitable for every target market or every type of shipment. That’s why it’s important not to evaluate carriers based solely on their prices.
Actual transit times, delivery reliability, regional coverage, available delivery options, and the quality of tracking data are also relevant criteria.
A multi-carrier strategy makes it possible to deploy different shipping partners to meet the specific requirements of a target market. Data analysis serves as an important basis for decision-making in this process. Which adjustments can actually be automated depends on the integrated systems, available services, and operational conditions.
Detect Bottlenecks and Disruptions Earlier
Delays occur at various points in the supply chain. These include, for example, longer processing times at sorting centers, missing handover scans, or capacity bottlenecks among transportation partners.
Those who systematically monitor such developments can identify notable patterns and explore appropriate measures.
This may involve adjusting capacity planning, utilizing other available shipping services, or notifying affected customers in a timely manner. However, shipments already in transit cannot always be rerouted at will.
Big Data thus improves the basis for decision-making, but it does not replace either the operational infrastructure or the actual capacities of the logistics partners involved.
Tracking as Part of the Customer Experience
The customer journey doesn’t end with the order. Especially with international shipments, customers want to know where their package is, when it’s expected to arrive, and whether they need to take any action themselves.
Clear tracking provides transparency. It makes shipment events easy to follow and reduces uncertainty between the time of order and delivery.
However, a long list of technical status updates alone does not make for a good customer experience. What matters most is that information is presented in an understandable way and displayed as consistently as possible across different shipping partners.
From Shipment Tracking to Proactive Communication
Instead of merely responding to customer inquiries, shipping information can be used to communicate early on when discrepancies are detected.
For example, if a required delivery status is missing or a projected delivery time is exceeded, this may warrant a targeted review or notification.
This requires reliable data and appropriate communication processes. After all, a missing scan does not automatically mean that a shipment has been lost.
Ultimately, what matters most to the customer is that the information remains transparent and that announced delivery times are met as reliably as possible.
ONE Tracking: Unified Shipment Visibility Across Carriers
PARCEL.ONE connects various international delivery partners within a single, centralized shipping solution. With ONE Tracking, shipment information from different carriers is consolidated and made available through a unified tracking process.
This eliminates the need for merchants to use a separate tracking system for each delivery partner. The centralized overview makes it easier to track shipment status and investigate any discrepancies.
This standardization is particularly important in cross-border e-commerce, as the carriers involved use different systems and status messages.
HUB.ONE: Where Digital Data Meets Physical Logistics
Data analytics only realize their full potential when they are linked to logistics processes that can actually be implemented. This is precisely where HUB.ONE comes in.
As a “Hub as a Service,” HUB.ONE integrates physical package handling with digital shipment information. This includes, among other things, the intake and consolidation of packages, scanning, measurement, sorting, relabeling, and handoff to connected transport and delivery networks.
During shipment processing, data is generated regarding the identity, weight, dimensions, and processing status of the packages. This information can be used to control sorting, validate shipping data, and support downstream processes.
The data is also valuable for operational planning. Information on shipment volumes and destination regions can help better assess capacity requirements and efficiently organize the flow of goods.
In this way, HUB.ONE demonstrates that modern package logistics consists of more than just software or physical infrastructure. Only the interplay of both levels enables end-to-end, controllable processes.
How PARCEL.ONE Uses the Information for International Shipping
While HUB.ONE supports the operational processing and handoff of shipments, PARCEL.ONE connects international carriers and shipping services within a single, centralized solution.
Shipment data, routing rules, and information from the participating partners form the basis for selecting suitable shipping options and for a standardized labeling and tracking system.
For retailers, this reduces the need to coordinate numerous carrier integrations and shipping processes individually. At the same time, it creates a foundation for evaluating shipping decisions more transparently and based on concrete performance data.
Which metrics help optimize delivery performance?
If you want to improve delivery times using data, you shouldn’t focus solely on the average transit time.
An important metric is the actual transit time from the defined shipment start time to delivery. In addition, on-time delivery rates show what percentage of shipments were delivered within the announced time window.
The variation in transit times is also relevant. Two carriers may achieve similar average values but differ significantly in terms of reliability.
Other helpful indicators include the processing time between individual scans, the rate of successful first-time deliveries, and the frequency of shipments with an unresolved status.
To ensure reliable comparisons, starting and ending points, measurement periods, and shipment groups must be defined consistently. Otherwise, seemingly clear-cut figures may lead to incorrect conclusions.
Key Performance Indicators (KPIs) in Shipping Logistics
Frequently Asked Questions About Big Data in Logistics
What Is Big Data in Logistics?
Big Data refers to the processing and analysis of large and diverse sets of data generated, among other things, during transportation, sorting, and delivery. This data can be used to gain insights for managing and optimizing logistics processes.
How can big data improve delivery times?
By analyzing transit times, shipment events, and carrier data, it is possible to identify common delays, improve forecasts, and select the most appropriate shipping options more effectively. Whether transit times are actually reduced depends on the measures taken as a result.
What role does predictive analytics play in shipping?
Predictive analytics uses historical and, where applicable, current data to estimate future trends. These include, for example, estimated delivery times, capacity requirements, and the risk of delivery delays.
Why is consistent tracking important in international shipping?
International shipping often involves multiple transportation and delivery partners. A unified tracking system consolidates their information and makes it easier for merchants and recipients to track the progress of a shipment.
Conclusion: Data makes shipping logistics easier to manage
Big Data can play a key role in making international delivery processes more transparent, predictable, and reliable. What matters is not the volume of information collected, but the ability to use it to make concrete decisions.
For online retailers, this means evaluating carriers not only based on price, but also taking into account their actual performance and the expectations of recipients. At the same time, tracking information must be presented in a clear and understandable way, and operational processes must be continuously reviewed.
To this end, PARCEL.ONE combines digital shipping management with an international carrier network and its own operational infrastructure. This lays the foundation not only for mapping shipping processes but also for specifically refining them.
Intelligently manage international shipping processes.
Anyone who wants to serve different target markets needs reliable information and a shipping solution that makes this data operationally usable.
