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Do not choose a free shipping threshold by adding a fixed percentage to average order value. Choose a candidate that protects order contribution, then test its effect on contribution per eligible visit. This captures customers who add items, customers who buy because of the offer, and customers who receive free shipping even though they would have purchased anyway.
For an ecommerce manager in Qatar or the Gulf, the question is not whether customers like free shipping. It is which orders the business can deliver under that policy without buying revenue out of its own margin. Geography, bulky goods and returns can change the answer. Removing the visible shipping charge does not remove the operational cost.
Start with order economics, not the average basket
Define order contribution as net product revenue after discounts, less product and relevant variable costs, plus shipping fees collected, less picking, packing and delivery costs. Include a realistic allowance for returns and failed delivery when orders have not fully matured. Do not subtract a cost inside product contribution and then count it again in fulfilment.
Shopify’s free shipping guide emphasizes clear minimum-spend conditions, geographical coverage and exclusions for heavy goods. That is operating guidance from a platform provider, not evidence that a particular threshold will work for your store. Use your invoices and basket distribution rather than importing conversion assumptions from another market.
At a 30% pre-fulfilment contribution margin, QAR 5 picking and packing, and QAR 20 delivery, a QAR 200 order with free shipping contributes 200 × 30% − 5 − 20 = QAR 35. This validates that individual order under the assumptions. It does not establish that the policy creates incremental profit across the store.
Separate three customer responses
- Customers who would already buy: the store may lose the shipping fees they would have paid, particularly when their baskets already exceed the threshold.
- Customers who add products: compare contribution from those additions against lost shipping revenue and any additional weight or handling cost.
- Customers induced to purchase: count their entire order contribution, including any change in acquisition or return costs.
For example, adding QAR 40 of products at a 30% contribution margin creates QAR 12 before fulfilment. If the offer removes a QAR 12 shipping charge, the addition only replaces the lost revenue before any extra packaging cost. A bigger basket is not evidence of improvement. Moving into a more expensive weight band can make the outcome worse.
This differs from recommending useful complementary products: the intervention changes the cost of completing a purchase, not merely the products shown. Also examine checkout friction to establish whether unexpected shipping fees are the underlying problem.
A hypothetical example: calculate the whole store
Assume two comparable groups, each with 10,000 eligible visits. Pre-fulfilment contribution is 30%, including assumed product cost, variable payment fees and a returns allowance. Picking and packing costs QAR 5 per order and delivery QAR 20. Advertising spend and fixed costs do not differ between groups. These are teaching assumptions, not results from an actual store.
| Measure | QAR 12 shipping on every order | Free shipping from QAR 200 |
|---|---|---|
| Eligible visits | 10,000 | 10,000 |
| Orders | 300 | 340 |
| Average basket | QAR 160 | QAR 190 |
| Product revenue | QAR 48,000 | QAR 64,600 |
| Shipping fees collected | QAR 3,600 | QAR 960 |
| Total order contribution | QAR 10,500 | QAR 11,840 |
| Contribution per visit | QAR 1.05 | QAR 1.184 |
In the offer group, assume 260 qualifying orders averaging QAR 210 and 80 non-qualifying orders averaging QAR 125. This produces QAR 64,600 of revenue and a QAR 190 average basket despite the QAR 200 threshold. The average across all orders is not the average among qualifying orders.
Baseline contribution is 48,000 × 30% + 3,600 − 300 × 25 = QAR 10,500. Under the offer it is 64,600 × 30% + 960 − 340 × 25 = QAR 11,840. The illustrative improvement is QAR 1,340, approximately 12.8%, before any new costs omitted from the assumptions. This is arithmetic, not a statistical verdict; real visit and order data are needed to quantify uncertainty.
Test without confusing the customer
Extract basket distributions, margins and delivery costs by zone over a representative operating period. Select one or two thresholds that are easy to explain. Define whether the threshold applies after discounts, which products are excluded and how split shipments are handled. Check the entire purchase journey so the advertising promise agrees with the checkout.
If testing customer groups, keep each customer’s policy consistent throughout the experiment and honour the offer shown at checkout. Measure conversion and contribution per visit, not contribution per order alone: the latter can increase while fewer customers buy. When the offer puts pressure on shared fulfilment capacity, customers outside the offer may also be affected.
Decision limits and stop signals
Monitor actual delivery cost, split shipments, returns, failed delivery, complaints and stockouts. Break results down by region and product type; averages can hide persistent losses on bulky items. Improving delivery-route density may be more useful than raising the threshold beyond customers’ natural needs.
Do not scale an offer whose apparent gain depends on an optimistic returns allowance or a margin assumption that does not match the new baskets. Set the improvement required to justify operational complexity and the acceptable harm limits in advance. Test one clear policy, let its costs mature, and expand only when contribution per visit improves without service deterioration. Free shipping is a pricing instrument, not an independent growth objective.
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