What you see
A budget cut follows a poor early purchase read, but later reports for the same exposure period show better economics.
Check this first
Compare the result visible when the budget changed with a later read of the same period.
Data needed
- Saved reports for one fixed exposure period at multiple read dates
- Campaign spend, reported purchases, and verified customer status where available
- Dated budget changes, decision reason, and observed purchase delays
Run the check
- #1
Save the report used for the original budget decision.
- #2
Re-read the same exposure period after the account’s usual purchase delay.
- #3
Compare the revised result with the original decision rule.
- #4
Check whether stock, cash, or another constraint justified the cut anyway.
Calculate
For one fixed exposure cohort, compute spend / reported purchases at successive read dates. Keep model-estimated late purchases separate from observed later purchases. Join the dated result to the campaign change log. For acquisition decisions, repeat the check with verified first purchases where linkage exists. Otherwise label the result purchase CPA; it doesn't establish new-customer cost.
Compare groups
- Exposure period
- Read date
- Campaign change date
- Purchase delay and customer status
What a healthy result looks like
Budget decisions use results with known maturity, or explicitly allow for delayed purchases and uncertainty.
When to investigate
Use the account’s observed conversion-delay distribution and the campaign’s decision rule. There is no universal waiting period.
Possible causes
- Recent reports omit purchases that arrive later.
- Decisions are made before the stated test threshold.
Rule out these explanations
- A deliberate stop for stock, cash, or compliance
- A changed attribution model
- Forecasted conversions presented as observed
What to do next
Set an evaluation schedule from actual delay data. Keep the early result, revised result, and decision reason together.
What this check can tell you
A later better result for the same exposure period doesn't prove that keeping the budget higher would have paid off.
Use this check with AI
Run a read-only check for: Campaign budgets are cut before purchase results have matured. First confirm the available sources, columns, row grain, date basis, currency, and customer definition. Use only authorized data. Required inputs: Saved reports for one fixed exposure period at multiple read dates; Campaign spend, reported purchases, and verified customer status where available; Dated budget changes, decision reason, and observed purchase delays. Check: A budget cut follows a poor early purchase read, but later reports for the same exposure period show better economics. Calculate: For one fixed exposure cohort, compute spend / reported purchases at successive read dates. Keep model-estimated late purchases separate from observed later purchases. Join the dated result to the campaign change log. For acquisition decisions, repeat the check with verified first purchases where linkage exists. Otherwise label the result purchase CPA; it doesn't establish new-customer cost. Slice by: Exposure period; Read date; Campaign change date; Purchase delay and customer status. Use this comparison rule: Use the account’s observed conversion-delay distribution and the campaign’s decision rule. There is no universal waiting period. Show the source totals, calculation, unknown groups, missing inputs, and result. Don't invent fields, thresholds, customer matches, or causal effects. Rule out: A deliberate stop for stock, cash, or compliance; A changed attribution model; Forecasted conversions presented as observed. Describe the observed signal separately from possible explanations. If the check is incomplete, state the exact data needed. Make no account or budget changes.
Sources and definitions
- Google: conversion delayLate conversions can change a fixed period’s apparent acquisition efficiency.Read source