Two shops take . The first raises its payment completion rate from 90% to 95%. The second goes from 70% to 73%. Their combined rate drops from 86.0% to 81.8%. The second shop received a much larger share of orders in the second period, and its completion rate was still lower than the first shop’s.
Those shops are fictional. The reversal is the kind of thing a real dashboard can produce when more customers arrive through a channel with a lower completion rate. Before rewriting the checkout or blaming times, check which orders went into the average.
What CoinGate counted
CoinGate reports that 77.42% of 324,631 Litecoin orders completed after the shopper selected the currency and network. The sample covers orders created from September 1, 2025 to August 31, 2026. The provider counts payments later refunded as completed because they were paid first. It also reports a median Litecoin advantage of 10.2 percentage points against the other assets pooled at each eligible merchant. The within-merchant comparison reduces the influence of merchant mix. Shoppers still chose their own payment method, so the figures describe an association within CoinGate’s checkout. CoinGate’s report and methodology.
Compare the same mix of orders
Both periods below contain 10,000 Litecoin selections. Only the split between stores and their individual completion rates change.
| Store | Period 1 | Period 2 |
|---|---|---|
| A | 7,200 / 8,000 (90%) | 3,800 / 4,000 (95%) |
| B | 1,400 / 2,000 (70%) | 4,380 / 6,000 (73%) |
| Combined | 8,600 / 10,000 (86.0%) | 8,180 / 10,000 (81.8%) |
Keep the first period’s mix of 80% Store A and 20% Store B. Applying those weights to the second period’s rates gives 0.80 × 95% + 0.20 × 73% = 90.6%. The raw rate fell by 4.2 percentage points. With the mix fixed, the rate rose by 4.6 points. Use the raw figure for actual outcomes and the fixed-mix figure to see how performance changed within the same groups.
For one store, start with a split you can act on, such as mobile versus desktop or paid ads versus returning customers. Keep the same group definitions and give both periods the same time to finish. Report the number of orders in each group. If a group is absent in one period, show it separately and label the fixed-mix result with the groups it covers.
Find where the orders stop
Record an order ID and timestamps for when the payment options appeared, when the shopper selected LTC and when the invoice reached each subsequent status. Then follow three ratios.
- LTC selections ÷ orders shown the LTC option. This measures how often shoppers choose Litecoin when they can see it. Record later currency switches separately so you can account for the original selection.
- Orders with a detected payment ÷ orders that selected LTC. Count orders that reached
confirmingorpaid, including any refund with evidence of earlier payment. If this falls, test the quote timer, QR code and handoff to a on the affected devices. - Orders your store recorded as paid ÷ orders with a detected payment. If this falls, compare the provider’s order status with your store’s record. A provider status of
paidpaired with an unpaid store order points you toward callback delivery or order matching. An order still inconfirmingbelongs in a separate pending bucket until the reporting cutoff.
Use the order ID to count repeated status notifications once. For a sales report, separately deduplicate retries using your cart or invoice ID. One cart can have an expired invoice and a later paid invoice, which is one recovered sale across two attempts. CoinGate order statuses and payment callback fields. For reconciliation, retrieve the provider’s order record using the List Orders endpoint.
Sources checked November 9, 2026. The two-store example uses synthetic data. Research and drafting used AI assistance. The cover is a conceptual illustration.
