Naive sales view
$291
what simple order-level reporting might suggest
Recognized outcome
$527
commercial result after explanation-layer reconciliation
Cash refunded
$103
cash that actually left the business
Value preserved
$284
value retained through exchanges or credit
Synthetic case scoreboard
Which cases create the biggest trust problem?
| Case | Scenario | Naive sales | Recognized | Cash refunded | Value preserved | Risk |
|---|---|---|---|---|---|---|
| C-1001 | Late full refund after return receipt | $107 | $95 | $85 | $0 | High |
| C-1002 | Exchange upsell with extra charge | $50 | $188 | $0 | $160 | High |
| C-1003 | Store credit exchange with replacement order | $28 | $132 | $0 | $118 | Medium |
| C-1004 | Order edit and partial refund after support save | $106 | $112 | $18 | $6 | Medium |
Case deep dive
C-1002 — exchange upsell with extra charge
Preserved value
$160
plus $28 additional charge
2026-03-05
Original order captured at $236.80 all-in cash collected.
2026-03-09
Customer requested a size swap instead of a refund.
2026-03-10
$160 of value moved into exchange credit, then the replacement order collected an additional $28 upsell delta.
Why this matters
Naive reporting makes this case look like lost sales.
The explanation layer shows the opposite: most value stayed in the business and the customer even spent more.
Case deep dive
C-1001 — late full refund after return receipt
Cash refunded
$85
delayed against original sale period
2026-03-03
Original order closed normally with $192.00 collected.
2026-03-07
Return opened, but no money moved yet.
2026-03-10
Refund posted after warehouse receipt, creating a delayed dashboard drop that ops experienced as confusing and sudden.
Why this matters
The drop is real, but the timing is the story.
This is the classic period mismatch case. The explanation summary matters almost as much as the amount.
Method
What the report computes
Original order anchor, downstream event timeline, naive sales view, recognized outcome, cash refunded, value preserved, and a plain-English explanation.
Why it matters
Built to be shown before product exists
If operators, agencies, or bookkeepers immediately say “yes, this is exactly the confusion we explain manually,” the wedge is strong enough to continue into real sample collection.
Next step
Use it as a discovery prop
Run walkthroughs, capture reactions manually, and only then decide whether to build integrations or a wider workflow product.