Advanced logistics technology is no longer optional for enterprise ecommerce stores. According to a McKinsey report, 93% of shippers plan to increase their technology investments by 2026 — and if you are not doing that yourself, you risk falling behind.
We’re not just talking about automated box sealers in your 3PL warehouse. Modern systems leverage machine learning (ML) and artificial intelligence (AI) to gather insights for each step of your supply chain and enhance operational efficiency.
Let’s uncover what exactly shipping analytics are, which metrics you should track, and how ecommerce businesses can become more competitive by implementing this technology.
Key highlights:
- Shipping analytics are visual interpretations of raw logistics data that provide strategic insights for businesses, helping them identify inefficiencies, improve decision-making, and enhance customer satisfaction.
- Legacy shipping technology cannot keep up with rising customer expectations, shrinking delivery timelines, and complex carrier networks.
- Companies that implement modern shipping analytics software gain a competitive edge over those that don’t.
- Shipium is a modern technology platform that leverages shipping data to reduce transit times, lower costs, and improve SLA compliance.
What is shipping data analytics?
Shipping data analytics is the process of collecting, analyzing, and interpreting logistics data to improve delivery efficiency. Instead of relying on manual tracking or guesswork, enterprise businesses use real-time analytics tools to gain visibility into:
- Carrier performance: Which carriers are meeting their on-time delivery service level agreements (SLAs)?
- Shipping costs: Where are you overspending — on parcels, surcharges, or inefficiencies?
- Delivery reliability: Are delays caused by specific carriers, locations, or service levels?
- Customer satisfaction: How often do late shipments lead to returns or complaints?
How parcel shipping analytics benefit your fulfillment operations
Parcel shipping logistics are increasingly complex. Carrier networks have expanded, fulfillment timelines are lower than ever, and customer expectations keep rising. At the same time, legacy technology fails to keep pace, limiting its customer’s visibility and capacity to make informed decisions.
Modern systems leveraging parcel shipping analytics can help solve these challenges. By turning raw data into visual graphics, they bring benefits such as::
- Cost savings: Pinpointing areas to optimize cost by breaking down expenses like freight rates, fuel surcharges, and carrier fees.
- Reliable decision-making: Allowing logistics teams to monitor shipping performance in real time. Instead of relying on historical reports, live shipping dashboards help managers address delays on the go using precise information.
- Enhanced customer satisfaction: Helping businesses identify high-risk shipments before they fail to meet deadlines. Predictive shipping analytics ensure on-time deliveries and fewer “Where is my order?” (WISMO) calls.
What to include in your shipping analytics dashboard
Without precise key performance indicators (KPIs), businesses struggle to identify the root causes of delivery inefficiencies, risking making uninformed decisions that drive up costs and hurt customer satisfaction.
See the main shipping metrics and reports to include in your dashboard:
1. Total on-time delivery performance
Ecommerce shipping delays lead to missed SLAs, chargebacks, and lost revenue. Case in point: according to a Körber Supply Chain report, over 67% of customers have experienced shipment delays in the past six months, with 84% stating they wouldn’t shop in the same store again after one poor experience.
That’s why tracking on-time delivery rates should be a priority — it’s a key competitive differentiator for your business.
Use shipping analytics software to monitor delivery performance metrics such as:
- Total percentage of on-time deliveries (OTD%): The number of shipments that arrive within the promised timeframe. A declining OTD% signals carrier inefficiencies, fulfillment delays, or poor rate shopping choices, all of which impact customer satisfaction and costs. When tracking this indicator, businesses can get insights to improve carrier selection, inventory positioning, or even last-mile delivery strategies.
- Delivery speed by carrier and mode: Transit time for different ecommerce shipping options (Ground, Economy, Overnight etc.). This metric helps businesses identify if they’re using the right service for each shipment. For example, if 80% of peak season shipments were delivered in four days or less using Ground or Economy methods, a possible insight is that you don’t need to overpay for premium shipping when standard options can achieve the same results in this case.
- Failure points by region: The geographical locations where shipments most frequently fail to meet their SLAs. Some areas can have higher delay risks due to weather, customs processing, or difficulty accessing last-mile routes. Knowing where issues occur helps operators reroute shipments or adjust delivery promises accordingly.
Discover our complete list of 40 ecommerce supply chain analytics to track.
2. Shipment cost breakdown
Shipping is one of the largest operational expenses for most businesses, yet many lack visibility into where their money is going. Without fully loaded rate shopping, for example, ecommerce stores can face many hidden carrier fees. In fact, according to a Flock Freight report, companies with over $1 billion in revenue spent an average of $2.3 million on unexpected less-than-truckload (LTL) accessorial fees in 2023 alone.
Add cost-related metrics in your shipping dashboard to break down expenses like fuel surcharges, address correction fees, and DIM weight adjustments and understand where to eliminate what is unnecessary for your operation. Examples of metrics to track include:
- Total shipping costs: The total amount spent on all shipping-related activities, including freight, parcel, inbound, and outbound transportation. A good way to understand if your company is doing well is to compare these rates to industry benchmarks. Clothing and fashion, for example, have higher shipping costs relative to revenue, while electronics have lower percentages due to product characteristics, standard shipping methods per industry and pricing strategies.
- Cost per package (CPP): The total shipping cost divided by the number of shipments. Tracking CPP over time helps businesses identify cost trends, negotiate better carrier contracts, and spot gaps in fulfillment.
- Inbound shipping costs: The total price of receiving inventory from suppliers or manufacturers. Inbound freight affects stock availability and production schedules. Tracking these costs helps businesses negotiate better supplier terms, optimize for consolidated shipments, and reduce replenishment delays.
- Outbound shipping costs: The cost of shipping products to customers. Analyzing outbound costs helps businesses balance speed and cost-effectiveness while meeting SLA commitments.
- Hidden fee impact: The percentage of shipping costs coming from accessorial charges, DIM weight fees, and other surcharges. This data helps businesses identify the most costly surcharges and adjust packaging, service selection, or contracts to minimize fees.
- Freight cost per weight or volume: The total cargo expenses divided by the pounds or cubic feet of shipments. This metric provides visibility into your costs based on shipment size, helping businesses optimize packaging options and carrier choices.
3. Decision visibility report
A decision visibility report consists of detailed graphs and analyses that help companies make better shipping choices — whether it’s carrier selection, service level compliance, or cost trade-offs.
Depending on your business needs, you can track:
- Rate shopping win/loss data: How often a lower-cost option was available but not selected. Tracking this information helps businesses understand whether they are making cost-effective shipping decisions without sacrificing service quality.
- Label execution insights: The relationship between labels generated vs. actual shipments sent. This metric helps you detect order fulfillment inconsistencies, such as labels printed but not scanned for pickup, which can prevent upstream shipment delays.
- Carrier performance benchmarking: How each carrier performs on on-time delivery, cost, and service level adherence over time. Tracking this information helps shippers determine if contracted carriers are meeting their SLAs or if it’s time to renegotiate agreements.
All this shipping data can equip operators with the insights they need to fine-tune their processes. But to really capitalize on this valuable information, companies need the right technology partner to present data in a way that drives informed decision-making.
Meet Shipium, a modern shipping technology platform that helps enterprise retailers optimize fulfillment through its automation and analytics tools.
Unlike legacy shipping software, Shipium’s customizable decision visibility reports integrate with your entire fulfillment stack, including TMS, WMS, and OMS platforms. Using our flexible reporting tools, you gain full transparency into their operations while making data-driven adjustments in real time.
Discover all you can do with the Shipium Analytics Suite.
Challenges when implementing a new shipping data hub
Despite the availability of advanced tools for data analytics in the shipping industry, implementing and managing this technology still presents challenges.
Fragmented shipping data
Many enterprise shippers rely on a multi-carrier network and third-party logistics companies, each with its own tracking systems, making it difficult to get a unified view of shipping performance. This fragmentation creates data silos, making it complex for logistics leaders to get a unified performance overview.
API-based shipping analytics systems like Shipium solve this challenge by automating data collection and integration in real time. Instead of using manual uploads or disconnected spreadsheets, API-driven platforms pull freight data directly from carrier APIs, TMS, WMS, and ERP systems, ensuring that:
- All data points are centralized in one platform
- Shipping metrics are always up-to-date
- Businesses can set up automated alerts when performance drops, costs spike, or delays occur — rather than reacting after the occurrence
Internal resistance to new technologies
Many logistics teams are used to manual tracking, and shifting to an analytics-driven approach may feel overwhelming or too complicated. However, companies that rely on outdated reporting methods fall behind competitors that use analytics to leverage operational insights.
Focus on these key arguments to get buy-in for investments in modern shipping analytics software:
- Data analyses reduce operational costs without compromising performance: During peak season 2024, businesses using Shipium’s real-time carrier selection and cost modeling tools saw an average 9% reduction in shipping costs, with a full 16% decrease in Cost per Package (CPP). Instead of relying on static contracts and pre-set preferences, our customers used merit-based, data-driven selection models to reduce costs while maintaining delivery reliability.
- New tech insights provide supply chain agility: Macro-environmental changes can happen at any moment, impacting supply chain management and delivery speed. Using our shipping data analysis tools, Shipium customers achieved a 95.4% on-time delivery rate during busy seasons despite carrier capacity issues and compressed timelines. Also, 30.48% of all their shipments were delivered in 4 days or less, and 79.5% of those were shipped via a cheaper Ground or Economy method rather than a more expensive expedited option.
Read our complete 2024 numbers recap and see how Shipium can help your business achieve the same results.
How to get started with effective shipping data analysis
Getting started with shipping analytics requires the right approach — one that integrates data seamlessly into daily operations and decision-making. This is how to do it:
1. Integrate and centralize your tools in a single shipping dashboard
Without centralized data and automation, you waste time compiling reports instead of acting on insights. Identify relevant data sources such as your TMS, OMS, or customer relationship management (CRM). Then, use API-driven shipping analytics tools to automatically update data in real time. By integrating all data sources into a single information hub, you can eliminate human errors and reporting delays.
2. Use predictive analytics for better decision-making
Traditional reporting is reactive — companies only see problems after they occur. Predictive analytics flips this model by forecasting delays, cost spikes, and carrier issues before they happen. Leverage machine learning and AI-driven analytics to:
- Identify patterns of shipments at risk of missing delivery windows and reroute them proactively
- Predict peak season cost fluctuations and adjust rate shopping rules accordingly
- Optimize carrier selection dynamically, reducing dependency on underperforming partners
- Determine which fulfillment center should process optimal insights to reduce transit times
The Green Mountain Benchmark Report predicts that, in 2025, AI tools will enable retailers to reduce out-of-stock incidents by up to 30%. By analyzing historical sales data, seasonality patterns, and real-time market trends, these systems accurately forecast demand for many different SKUs across channels.
3. Foster a data-driven culture in your organization
Even with the best shipping analytics tool, businesses won’t see results unless teams actively use the data to make decisions. For data analyses to be effective, logistics teams must regularly review key metrics, adjust strategies based on trends, and integrate all of that into their daily operations.
To ensure company-wide adoption of shipping data analytics:
- Make it accessible — choose user-friendly tools with intuitive dashboards
- Provide training for the use of the new technology
- Incentivize data-driven performance, creating department goals that are tied to your shipping metrics
Why Shipium is your go-to shipping analytics software
The key to higher operational performance is integrating data into your daily operations — so you aren’t just reacting to problems but proactively minimizing them.
With Shipium as your end-to-end logistics platform, you get real-time analytics, predictive modeling, and intelligent automation to enhance efficiency and maintain delivery promises to customers. We bring to the table:
- Fulfillment engine: Use an ML-powered time-in-transit model to route orders to the optimal fulfillment center based on inventory availability, customer proximity, and carrier performance, reducing transit times and costs.
- Simulation: Run what-if analyses on carrier selection, transit times, and costs, allowing businesses to test different shipping strategies before making operational changes.
- Carrier selection: Automate rate shopping and carrier assignment, ensuring every shipment is optimized for cost and speed based on real-time performance data.
- Analytics suite: Choose from several pre-configured product modules or build your own dashboards with our team to centralize your most relevant shipping data and gain strategic insights into your operation.
Request a demo and see how Shipium helps you leverage shipping analytics to take your fulfillment process to the next level.
