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.
交互式模型
估算符合条件案件涉及的购买价值
这是一个简单的风险敞口模型，并非节省承诺。它用平均购买价值乘以每月符合条件的证据请求数量。
预计每月风险敞口
$749.50
$14.99 × 50 件
实际退款、适用资格、证据、决定和留存收入均会有所不同。
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.