Looker Studio Charts Showing Incorrect Totals: How to Audit the Data
When Looker Studio charts show incorrect totals, the wrong number can come from the source data, the aggregation, the blending, a calculation or a filter. Each layer can change the total, so the goal is to identify which layer introduced the wrong value before changing anything.
Table of Contents
- 01.Where a total can go wrong
- 02.What to check first
- 03.Source data vs aggregation
- 04.Duplicate rows from blending
- 05.Calculated metrics
- 06.Filters and granularity
- 07.How to test the fix
- 08.How to validate the final result
Where a total can go wrong
A total is the result of source data passing through aggregation, blending, calculation and filtering. Any of those layers can change the value. The wrong total is not always a chart problem. It can be the correct total for a wrong configuration, which is why you have to trace the value through each layer.
| Layer | What can go wrong | How to check |
|---|---|---|
| Source data | Values differ from expectation | Compare with the source platform total |
| Aggregation | Sum vs average vs count | Confirm the metric aggregation type |
| Blending | Join duplicates rows | Test each source separately |
| Calculation | Calculated metric mis-aggregated | Check the calculated field aggregation |
| Filtering | Filter excludes or includes wrong rows | Remove filters and compare |
What to check first
- Compare the chart total with the source platform total for the same period.
- Confirm the metric aggregation type, sum, average or count.
- Remove all filters and compare the unfiltered total.
- For blended charts, test each source separately before the blend.
- For calculated metrics, confirm the calculated field aggregation.
Source data vs aggregation
The first check is whether the source platform itself shows the same total. If the source total differs from your expectation, the report is correct and the data is the issue. If the source total matches your expectation but Looker Studio differs, the problem is in aggregation, blending, calculation or filtering. Confirm the aggregation type, because a metric that should be a sum can default to an average or a count, which changes the total entirely.
Duplicate rows from blending
Blended data is a frequent cause of inflated totals. When a join key matches multiple rows, the blend duplicates rows and the total multiplies. A cost total that is double or triple the expected value often comes from a one-to-many join. Test each source in a separate chart first. If each source shows the correct total but the blend inflates it, the join is duplicating rows. Blending problems are covered in the guide on Looker Studio blended data not matching.
Calculated metrics
A calculated metric can produce a wrong total when its aggregation does not match the intent. A ratio calculated as a sum of ratios differs from a ratio of sums. Confirm how the calculated field aggregates. If the calculated field aggregates incorrectly, the total is mathematically wrong even though each row looks right. Calculated field problems are covered in the guide on Looker Studio calculated field not working.
Filters and granularity
A filter can exclude rows that should be included, or include rows that should be excluded, changing the total. Remove all filters and compare the unfiltered total. Granularity also matters. A chart grouped by day shows a different total than the same chart grouped by campaign, because of how rows aggregate. Confirm the chart granularity matches the total you expect.
How to test the fix
- 1.Confirm the source platform total matches your expectation.
- 2.Confirm the metric aggregation type is correct.
- 3.For blended charts, confirm each source total is correct before the blend.
- 4.Remove filters and confirm the unfiltered total is correct.
How to validate the final result
The total is correct when it matches the source platform for the same period, aggregation and filter set, and blended charts do not inflate due to duplicate joins. If the total is correct unfiltered but wrong filtered, the filter logic is the cause, not the data.
Frequently Asked Questions
Why is my Looker Studio total double the expected value?
A blended data join is duplicating rows. When a join key matches multiple rows, the blend multiplies the total. Test each source separately first. If each source total is correct but the blend doubles it, the join is the cause.
Why does my total not match the source platform?
Check the aggregation type, the date range and the filters. A metric that should be a sum can default to an average or a count. Remove filters and compare the unfiltered total with the source platform for the same period.
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Related Guides
Looker Studio Blended Data Not Matching: How to Find Join and Aggregation Problems
Blended data mismatches usually come from join keys, granularity, aggregation or null values in the join dimension. Test each source separately before blaming the blend.
Looker Studio Metrics Are Duplicated: How to Find the Cause
Duplicated metrics usually come from blended joins, duplicate source rows, aggregation or multiple sources pulling the same metric. This is a reporting problem, not a duplicate conversion tracking problem.
Looker Studio Calculated Field Not Working: Common Formula and Data Problems
A calculated field that fails usually breaks on a missing field, a type mismatch, null values, aggregation or syntax. Simplify the formula and test one operation at a time to isolate the failing part.