Overseas warehouse vs. self-delivery: How to choose the most suitable cross-border e-commerce logistics model for you?

  1. Overview of two logistics models
    Overseas warehouse model
    Overseas warehouse refers to the storage facilities that cross-border e-commerce sellers pre-lease or build in the target market country, and transport the goods in batches to overseas warehouses for storage in advance. When an order is generated, the goods are shipped directly from the local warehouse to the consumer.

Self-delivery model
Self-delivery (direct mail) means that after receiving the order, the seller directly ships from the domestic warehouse or supplier, and delivers the goods to overseas consumers through international express, postal parcels, etc.

  1. Core comparison dimensions
    Comparison items Overseas warehouse Self-delivery
    Delivery time 1-5 days (local delivery) 7-30 days (international transportation)
    Logistics cost Large initial investment, low unit cost Small initial investment, high unit cost
    Capital occupation High (need to prepare inventory) Low (delivery according to order)
    Inventory risk High (need to predict sales) Low (flexible adjustment)
    Return and exchange processing Convenient (local processing) Complex (international return)
    Applicable products Heavy, standardized, hot-selling products Light and small items, non-standard products, long-tail products
  2. Selection strategy guide
    Suitable for choosing overseas warehouses:
    Product characteristics: products weighing more than 500g and large in size (can significantly reduce logistics costs)

Sales performance: SKUs with stable monthly sales of more than 100 orders (reduce inventory risks)

Market positioning: high-end markets focusing on “fast delivery” (such as developed countries such as Europe, the United States, Japan, etc.)

Promotion plan: Prepare to participate in platform promotions (such as Amazon Prime Day)

Suitable for self-delivery:
New market testing: just entering a new country market, sales are unstable

Special products: customized products, seasonal products or long-tail products

Funding restrictions: start-ups have tight cash flow and cannot afford large quantities of inventory

Regulatory risks: the target market’s customs policies are changeable (to avoid inventory retention)

IV. Hybrid model recommendations
Mature sellers can adopt a hybrid strategy of “overseas warehouse + self-delivery”:

80% of hot-selling products are stored in overseas warehouses to ensure the experience of the main products

20% of long-tail products are self-delivered to reduce inventory pressure

Use third-party overseas warehouse services (such as FBA) to reduce initial investment

V. Decision-making flow chart
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Start

Analyze product characteristics (weight/size/value)

Evaluate sales data (average daily order volume/growth rate)

Calculate cost comparison (head-mile + warehousing vs. direct mail unit price)

Consider capital turnover capacity

Evaluate target market consumer time efficiency expectations

→ High time efficiency demand & stable sales → Choose overseas warehouses
→ Low time efficiency tolerance & uncertain sales → Choose self-delivery

Implement and continuously monitor (evaluate the model effect once a month)
VI. Risk Warning
Risks of overseas warehouses:

Risk of unsalable inventory (it is recommended to purchase inventory insurance)

Changes in local regulations (such as EU VAT policy)

Out-of-control warehouse management costs (need to strictly monitor turnover rate)

Risks of self-delivery:

Logistics time fluctuations (select at least 3 backup logistics providers)

High return rate (reserve 15-20% return cost space)

Risk of customs detention (ensure that the declared information is accurate and complete)

It is recommended that sellers re-evaluate logistics strategies every quarter and adjust the model combination based on sales data, changes in logistics costs and market environment. In the early stage, you can test the two models in small batches and make the final decision based on actual data.

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