Revenue impact analysis

Revenue impact analysis in Reveal Transactions turns error frequency into financial priority. After Error analysis shows which decline reasons appear most often, these views show which reasons put the most revenue at risk.

In the UI, related charts are titled Error Impact on Revenue. You can switch between an averaged (by occurrence) view and a by: Last Occurrence view.

To open them, select Transactions, open Performance, then select the Error Distribution tab and open the Error Impact on Revenue charts.

Average revenue impact

Average revenue impact estimates the typical transaction value associated with each error type (financial impact averaged by occurrence).

Why it matters: Frequency and value often disagree. If 3DS authentication failures average $300 per declined transaction while insufficient-funds errors average $75, the rarer 3DS failures may deserve earlier attention. Combine this with segments from Drill down into auth and decline rates—for example high-value 3DS failures in one Customer Country—to decide what to fix first.

Last seen error (last occurrence)

Last occurrence impact tracks the final error associated with an order when customers attempt multiple payments and then abandon. It answers: which error was present when the sale was ultimately lost?

Why it matters: Intermediate errors can mislead. Consider a $500 order where the customer:

1. Hits a 3DS authentication failure
2. Retries and gets insufficient funds
3. Abandons after Do Not Honor

All three errors occurred, but Do Not Honor was the last error before the lost sale. Last-occurrence impact prioritizes the breaking points in the payment flow, not only every error that appeared along the way.

Example: prioritizing two errors

| Error | Share of declines | Avg impact | Last-occurrence volume at risk | | --- | --- | --- | --- | | Insufficient Funds | 35% | $60 | $12,000 | | Soft decline / Do Not Honor | 12% | $220 | $40,000 |

Insufficient Funds is more common, but Do Not Honor dominates last-occurrence revenue at risk. A payments team might improve messaging and alternate-method prompts for soft declines first, while still monitoring Funding Type patterns for insufficient funds.

How to use both metrics together

Combine average impact and last-occurrence impact to:

• Prioritize error types by business cost, not only count
• Design retry rules that protect high-value attempts
• Optimize flows for segments where expensive errors cluster
• Inform payment routing and risk settings with evidence
• Improve customer communication at the failure points that precede abandonment

Apply the same Performance filters and grouping dimensions you use elsewhere—Funding Type, geography, 3DS Flow, Gateway Account, and related parameters—so revenue impact stays tied to a clear population. For the full list of normalized codes, see Standard error codes.