When we talk about reducing fulfillment costs, the first thing we have to understand is that fulfillment is structurally determined long before an item is picked or packed. Ask ten e-commerce operators what their fulfillment cost is, and most will cite a carrier rate. Very few will include dimensional weight surcharges, returns processing, peak-season fees, and the hidden cost of customer service calls triggered by late deliveries.
When all of those costs are properly consolidated, as any rigorous financial analyst would insist, the picture changes dramatically. For small to mid-sized e-commerce businesses shipping fewer than 10,000 orders per month, the true fully-loaded fulfillment cost typically runs between 18% and 28% of revenue. For businesses in the 10,000-100,000 monthly order range, the figure is typically 12-20%. These are not margins most businesses can absorb without a deliberate strategy to reduce them.
The good news, and there is genuine good news here, is that most e-commerce businesses have significant recoverable value sitting untouched in their fulfillment operations.
Continue reading to find out where it is and, more importantly, how to unlock it.
Table of Contents
Fulfillment costs explained: What’s included
Before any cost-reduction strategy can be executed, it must rest on accurate data. Even if it sounds self-evident, many e-commerce merchants overlook it. Fulfillment is not a single expense but a layered structure of costs. To understand where the margin is eroding, one must first clearly separate those layers. They are as follows.
Inbound and receiving costs
This includes freight from the supplier to the warehouse, receiving labour, and quality inspection. These costs are often absorbed into the cost of goods sold and therefore invisible in fulfillment analysis, but they belong here because they are directly driven by order velocity and SKU complexity.
Warehousing and storage
Monthly storage fees, climate control surcharges (if applicable), and the pro-rated cost of warehouse labour for cycle counting, replenishment, and general facility maintenance. For businesses using third-party logistics (3PL) providers, this will typically appear as a line item. For those operating their own facilities, it must be calculated from rent, utilities, and labour overhead.
Pick and pack
The cost per unit of physically retrieving an item, packing it, and preparing it for shipment. In a 3PL context, this is usually a per-pick and per-pack fee. In an owned facility, it is a labour efficiency calculation. This is one of the most variable costs in the stack and one of the most amenable to improvement.
Packaging materials
Boxes, mailers, void fill, tape, labels, and any branded inserts. This line is frequently underestimated, particularly by businesses that use custom or premium packaging. At scale, packaging material costs of 2-4% of revenue are common.
Outbound shipping
Carrier charges, dimensional weight adjustments, fuel surcharges, residential delivery fees, and any accessorial charges. This is the number most businesses have memorised. It is also where the largest absolute savings opportunities typically exist.
Returns processing
The cost of receiving, inspecting, sorting, restocking, or disposing of returned goods. E-commerce return rates range from 20% to 40%, depending on category, and the cost to process a return is often 40-60% of the cost to fulfill the original order. Returns are, therefore, a material cost that must be measured and managed explicitly.
Carrier performance and customer service fallout
Late deliveries, lost parcels, and damaged goods generate customer service contacts, refunds, and reshipments. These indirect costs are rarely attributed to fulfillment but are directly caused by fulfillment failures. Businesses operating at scale should calculate a cost-per-contact and allocate a portion of it to their fulfillment cost stack.
Once these seven layers are properly mapped and quantified, businesses typically discover that their actual fulfillment cost is 20-35% higher than their initial estimate.
That gap is an opportunity, because it represents costs that are now visible and therefore actionable.
1. Transport strategy: How to reduce outbound shipping costs
Dimensional weight and packaging optimisation
Of all the technical aspects of carrier pricing, dimensional weight (DIM weight) is the one that most frequently and most silently inflates shipping costs for e-commerce businesses. Carriers charge based on whichever is greater, the actual weight of a package or its dimensional weight. The practical implication is that lightweight but bulky products are dramatically more expensive to ship than their actual weight would suggest. The strategy response has three components.
First, packaging rightsizing: systematically matching package dimensions to product dimensions as closely as possible. For businesses using a small number of standard box sizes, introducing additional size options, particularly smaller ones, typically reduces dimensional weight charges by 15-25%.
Second, flexible packaging: for soft goods, fashion, and other compressible products, poly mailers and flexible packaging can eliminate the DIM weight problem entirely for eligible shipments.
Third, packaging audits: regularly reviewing the mix of package types used against the product mix being shipped, looking for systematic mismatches.
In Europe, these measures carry added urgency. Under the new European Union’s Packaging and Packaging Waste Regulation, e-commerce packaging has become a legal matter. The regulation places limits on excessive empty space in transport packaging and strengthens recyclability requirements across member states. In practical terms, this means that shipping “air” may expose a business to compliance risk and higher Extended Producer Responsibility fees linked to packaging volume and material composition.
Multi-carrier strategy and carrier diversification
Relying on a single carrier is both a commercial and an operational risk. Commercially, it eliminates negotiating leverage, a carrier that knows it holds 100% of your volume has no incentive to offer competitive rates. Operationally, it creates single-point-of-failure exposure: when that carrier experiences network disruptions (which all carriers do), your service levels collapse with it.
A multi-carrier strategy allows a business to route shipments to the carrier that offers the best combination of price and service for each specific shipment’s characteristics. Different carriers hold cost advantages in different regions and service levels. Routing orders dynamically according to geographic strength can reduce average shipping expense.
Algorithmic carrier selection and shipping automation
A multi-carrier strategy is most powerful when it moves beyond manual choice and becomes algorithmic.
Each parcel is assigned to the carrier that delivers the best combination of cost, speed and reliability for that specific shipment. In practice, however, attempting to make that decision manually at scale is unworkable. Modern shipping management platforms integrate directly with a retailer’s order management and warehouse systems. They ingest parcel-level data in real time: weight, dimensions, declared value, destination postcode, required delivery speed, and customer-selected service tier. Simultaneously, they maintain updated carrier rate tables, fuel surcharges, peak adjustments, and service-level agreements. Each parcel becomes a small economic decision, resolved in milliseconds.
2. Warehouse strategy: How to reduce costs through location and layout
Warehouse location and zone optimisation
For businesses operating their own warehouse or selecting a 3PL, the geographic location of the fulfillment facility has a direct and significant impact on outbound shipping costs. This is because the further a package travels from a fulfillment location, the more it costs. A parcel travelling from Hamburg to Madrid may cross no customs barrier, but it still travels 1,800 kilometres. The average ecommerce business ships a significant proportion of its orders to areas that are expensive relative to where its inventory is held.
Many mid-sized merchants still fulfil all European orders from a single warehouse, often in Germany or the Netherlands assuming administrative simplicity offsets transport expenses.
But does it?
If a third of your revenue comes from France, another quarter from Italy, and yet nearly all inventory sits in northern Europe, each order accumulates avoidable transport costs, extending delivery times while depressing conversion rates. Moreover, slower delivery often leads to more WISMO enquiries (“Where is my order?”), which increases customer service workload. It can also increase refund requests if expectations are not met. Both outcomes raise operational cost per order.
Therefore, moving even a portion of inventory to a warehouse closer to high demand can reduce costs significantly. A business whose customer base is geographically distributed (which is most businesses) will pay lower average shipping costs if its warehouses are strategically distributed. When these savings are multiplied across tens or hundreds of thousands of shipments annually, even a partial regionalisation of inventory can produce a measurable and sustained improvement in margin.
The rise of micro-fulfilment centres
The economics of urban last-mile delivery have driven investment in micro-fulfilment centres: smaller, higher-density storage and picking facilities located within or near major urban areas.
Often retrofitted from retail or light industrial space, these sites are designed to serve dense population clusters where last-mile costs are highest. By reducing the distance between inventory and customer, micro-fulfilment compresses both delivery time and transport spend.
While not suitable for every product category, the model highlights how proximity is increasingly priced into competitiveness.
Flex and on-demand warehousing solutions
Flex and on-demand warehousing has matured to offer genuine access to flexible warehousing capacity without long-term lease commitments. For businesses with seasonal or variable volumes, flex warehousing has become a credible and cost-effective option.
How to conduct a warehouse zone distribution analysis
When you evaluate warehouse location, whether for your own facility or a 3PL relationship, you should conduct a zone distribution analysis. Map your historical order data by customer postcode, calculate the average per-order shipping cost from each candidate warehouse location using actual carrier rate cards, and identify the location that minimises weighted average shipping cost across the actual customer distribution.
Warehouse layout and inventory slotting strategy
The physical layout of a warehouse has a direct and measurable impact on pick-and-pack labour cost, which for most e-commerce businesses is the second-largest component of fulfillment cost after outbound shipping. Every metre a picker walks to retrieve an item has a cost. Multiply that cost by the number of picks per day, and the aggregate becomes significant.
The foundational principle of warehouse slotting, in other words strategically deciding where to position inventory within a fulfillment facility, is that high-velocity items should be positioned as close to the packing station as possible. This is well understood in theory but inconsistently practiced in reality, because SKU velocity changes constantly and re-slotting requires active management.
ABC analysis for SKU velocity optimisation
A practical starting point is an ABC analysis of SKU velocity: categorising items by their order frequency, with A items being the highest-velocity SKUs, B items medium-velocity, and C items slow-movers. A items should occupy prime picking positions within arm’s reach or minimal walking distance of packing stations. C items can be stored in less accessible locations, such as higher shelves, further zones, because their low frequency means the total distance penalty is small in aggregate.
For businesses experiencing SKU proliferation (a common problem as product ranges expand), periodic slotting audits are essential. A business that last reviewed its warehouse layout eighteen months ago is very likely operating with a suboptimal slot allocation, because the velocity profile of its catalogue will have shifted.
Batch picking vs zone picking: Choosing the most efficient method
The method by which orders are picked has a substantial impact on labour efficiency, and the optimal method depends on order characteristics and warehouse scale.
Single-order picking, where a picker fulfills one order at a time, collecting all items before returning to the pack station, is the simplest method and requires the least coordination, but it is also the least efficient because it results in a large number of individual journeys through the warehouse for the same items.
Batch picking, where a picker collects items for multiple orders simultaneously, then sorts them at the pack station, dramatically reduces travel time but requires sorting capability at the pack station. It is most efficient when order profiles are relatively homogeneous (similar numbers of items per order, similar item sizes).
Zone picking, where the warehouse is divided into zones and each picker is responsible only for their zone, with orders passing between zones as they are fulfilled, works well at higher volumes and greater SKU complexity. It reduces the distance each picker must cover and allows specialisation, but it introduces coordination requirements between zones and requires robust order management software to sequence orders effectively.
For most small-to-mid-sized ecommerce businesses, a well-implemented batch picking system represents the best balance of simplicity and efficiency. Studies consistently show that moving from single-order to batch picking reduces pick-and-pack labour cost by 20-40%, depending on order profile.
The role of Warehouse Management Systems (WMS)
Warehouse management software (WMS) sits at the centre of operational efficiency in a modern fulfillment facility. For businesses currently operating without a WMS, the efficiency gains from implementation typically pay back the investment within six to twelve months. Pick accuracy improvements alone, reducing the cost of mispicks, reshipments, and customer service contacts, often account for a substantial portion of that payback.
For businesses already running a WMS, the relevant question is whether they are extracting its full analytical value. Most WMS platforms generate substantial operational data, such as picks per hour by operative, path efficiency metrics, error rates by SKU or zone, that can be used to identify training needs, layout optimisation opportunities, and staffing patterns.
3. Returns management: Controlling the hidden cost driver
Why returns require a dedicated strategy
Returns management is the most frequently underinvested area of e-commerce operations, and the cost of that underinvestment is considerable. The economics are unforgiving: a return not only costs money to process, it also potentially destroys value in the original product (through handling damage, repackaging cost, or liquidation at below-cost prices), generates a customer service interaction, and eliminates the revenue from the original sale until a replacement is shipped or a refund is issued.
The mistake most operators make is treating returns as a customer service problem rather than a supply chain problem. Customer service teams field the contacts. Warehouse teams process the returns. Finance teams absorb the costs. But no single function owns the end-to-end economics, which means no one is systematically optimising them.
Reducing return rates through root cause analysis
The first priority in returns management is preventing returns from occurring in the first place. This requires honest analysis of why returns are happening.
Returns generally cluster around a small number of root causes: the product did not match its description or images on the website; the product was the wrong size; the product was damaged in transit; the customer simply changed their mind. The distribution between these categories varies by product type, but for most ecommerce businesses, the first two categories – expectation mismatch and sizing – account for 60-75% of returns.
Both are addressable. Expectation mismatch returns can be reduced by improving product content: more detailed descriptions, more comprehensive image sets including scale references, and video content where relevant. Businesses that have invested in improved product photography and description quality typically see return rate reductions of 10-20% on affected SKUs. Sizing returns, particularly acute in fashion, respond well to detailed size guides, fit descriptions (runs small, runs true to size, etc.), and, where budget allows, virtual try-on technology.
Damage-in-transit returns are a packaging and carrier problem. If a category of product is generating above-average damage returns, the root cause is almost always either insufficient protective packaging or carrier handling characteristics for that package profile. Both are fixable.
Improving returns processing efficiency
For returns that do occur, processing cost is heavily influenced by the degree to which the returns process is automated and standardised. A well-designed returns portal, one that requires customers to categorise their return reason, print a pre-paid label, and receive an automated confirmation, costs a fraction of a returns process handled through customer service email.
More importantly, a returns portal generates structured data on return reasons, which can then be fed back into the root cause analysis described above. This creates a feedback loop that, over time, drives down return rates while simultaneously reducing the cost of processing the returns that do occur.
Reverse logistics optimisation through 3PL partnerships
For businesses at sufficient scale, reverse logistics optimisation through 3PL by consolidating return flows across multiple merchants, standardising inspection processes, using established carrier contracts, and strategically positioning return hubs closer to key customer markets can meaningfully improve the economics of returns.
4. Technology and automation in fulfilment optimisation
The technology stack for fulfillment optimisation
The technology infrastructure that supports fulfillment optimisation has six core components, and understanding how they interrelate is essential for making investment decisions.
Order Management System (OMS). The OMS is the system of record for orders. It receives orders from sales channels, manages order status, and routes orders to fulfillment locations. For multi-channel businesses or those with multiple fulfillment nodes, the OMS ensures orders are fulfilled from the optimal location.
Warehouse Management System (WMS). As described above, the WMS directs operations within the fulfillment facility. Integration between OMS and WMS is essential. Orders must flow automatically from one to the other without manual intervention.
Carrier Management. Predictive algorithms evaluate carrier performance histories, live capacity data, transit time windows, and cost models to dynamically assign the optimal shipping partner at checkout, balancing speed, cost, and delivery reliability at scale.
Returns Management Platform. A dedicated returns management platform manages the customer-facing returns portal, generates return labels, tracks returns in transit, and routes returned inventory to the appropriate disposition.
Analytics and Reporting. The ability to measure fulfillment performance across the dimensions described throughout this article – cost per order by component, carrier performance by zone, return rates by product and reason, pick accuracy – requires either a purpose-built analytics layer or the discipline to extract and analyse data from the operational systems above. Businesses that invest in this analytical capability consistently outperform those that do not, because they can identify problems early and quantify the impact of improvements.
Demand Forecasting & Replenishment. Time-series analysis and regression-based forecasting engines translate vast datasets into automated replenishment triggers, ensuring stock levels remain optimized without overstocking or stockout risk.
Measuring fulfilment cost performance in 2026
The final element of any fulfillment cost reduction programme is the measurement framework.
The core metrics are:
- Fulfillment cost per order
- Carrier cost per shipment,
- Average order cycle time from placement to delivery
- Pick accuracy rate
- Return rate by product category and return reason
- Cost per return processed.
These metrics should be reviewed at least monthly. For a complete set of logistics KPIs to measure in 2026, read the full article here.
eLogy begins when the customer hits “Buy.”
90% of e-commerce businesses lose money on hidden logistics friction. eLogy automates your touchpoints and turns your fulfillment into a high-conversion engine by slashing shipping errors and delivering 24/48h.
- 360° view Dashboard: Integrated logistics management. Monitor shipments and inventory in real time with advanced reports and visibility through every stage of the order fulfillment process.
- Automatically Generate Shipping Documents
An AI-driven software that orchestrates shipments, generates shipping labels, validates addresses, manages returns, and optimizes orders — with no errors and no waste. - SmartShip™ AI: eLogy’s algorithm automatically selects the best-performing carrier for a specific zip code and package type in real-time.
- Real-Time Data Integrity: eLogy bridges the “Information Gap” by ensuring tracking updates move faster than the package, neutralizing WISMO before it starts.
- Strategic Fulfillment: With warehouses across Europe, eLogy keeps your stock closer to customers, reducing the tracking timeline.
- Integrated Communication: eLogy has built-in WhatsApp and Call Center workflows.
- Proactive “Push” Notifications: send automatic notifications via Email and WhatsApp. By telling the customer where the package is before they feel the need to ask, you eliminate the ticket before it’s born.
Ready to transform your fulfillment into a competitive advantage?
