RefundHalt Research · July 2026
App refund exposure report: a transparent 2026 revenue model
How much purchase value sits behind time-limited refund evidence requests? This report provides a reproducible model with no invented customer outcomes and no hidden assumptions.
互動式模型
估算符合條件案件涉及的購買價值
這是簡單的曝險模型，不是節省承諾。它會將平均購買價值乘以每月符合條件的證據申請數量。
估算每月曝險金額
$749.50
$14.99 × 50 件
實際退款、適用資格、證據、決定與守住的營收都可能不同。
Key finding
Exposure grows linearly with eligible case volume
For an app with a $14.99 average purchase, each eligible case represents $14.99 of purchase value under review. Ten cases represent $149.90, 50 represent $749.50, and 100 represent $1,499.00. These values describe exposure, not guaranteed retained revenue.
| Eligible cases per month | Average purchase | Modeled exposure |
|---|---|---|
| 10 | $14.99 | $149.90 |
| 50 | $14.99 | $749.50 |
| 100 | $14.99 | $1,499.00 |
Methodology
The model uses one equation: monthly purchase-value exposure equals eligible cases received in the month multiplied by average purchase value.
- An eligible Apple case is a CONSUMPTION_REQUEST that asks the developer for consumption information.
- An eligible Google case is a chargeback for which Google sends a PendingRefundReviewNotification.
- The default $14.99 input is illustrative and matches RefundHalt’s monthly software price. Replace it with your own average purchase value.
- The model does not estimate approval rate, decline rate, chargeback fees, taxes, store fees, or downstream lifetime value.
How to interpret the model
The useful comparison is not modeled exposure versus guaranteed savings. The useful comparison is the cost of consistently answering eligible requests versus the value of even one purchase that might otherwise lack developer evidence. At a $14.99 purchase value, one such purchase equals RefundHalt’s $14.99 monthly plan price, but the store may still grant the refund.
Track your own received requests, response timeliness, store outcomes, and purchase values. Replace the model with observed cohort data as your ledger grows. RefundHalt records Apple and Google outcomes in one place so that analysis is possible without blending modeled and real results.
Primary sources and limitations
Store documentation establishes the response windows and eligible workflows. The scenarios and calculations are RefundHalt’s original model. Last verified July 17, 2026.