Marketing & search · Practical guide

Avoid counting overlapping report exports twice

Two exports overlap, and combining them adds some observations twice. The final report looks stronger than either source.

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What to change

Establish the unique reporting key before appending files. Depending on the export, that key may include the period, page, event and selected dimensions. Ask the analyst to preserve source filenames and compare overlapping rows before deciding whether they are duplicates or separate observations. A fixed fictional test example with known overlap provides a useful acceptance test and avoids exposing production records while the merge logic is corrected.

A worked example

Illustrative example

Illustrative test: Two fictional exports share one known row; the combined report counts it once. Two exports may overlap for the last week of a month. The analyst marks one known repeated row in a fictional sample and preserves its source filenames. The agreed merge counts that observation once while retaining a separate row that happens to share the same total. The practice can reproduce the combined figure and understand why a row was removed, rather than accepting an unexplained reduction after an automated cleanup.

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What this means for your practice

Combining two files can inflate a report if their date ranges overlap. Ask your analyst what makes a row unique before appending the exports. Depending on the report, that may involve its date, page, event and other selected categories. Keep the source filenames so any overlap can be traced. A small fictional example with one deliberately repeated row makes the proposed treatment easy to review without exposing operational records. Do not remove rows merely because their totals look identical; separate observations can legitimately share the same number. The finished calculation should preserve valid activity while explaining each removed duplication, with enough information for another analyst to reproduce the result.

How to check the result

The result is reproducible and preserves an explanation for every removed overlap.

A mistake to avoid

Dropping rows based on identical totals alone can remove valid separate observations.

Turn reading into a next step

Your action checklist

Work through these checks with your team or supplier. Tick the ones you have resolved and leave unknowns open.

Checks to discuss

Record what you know, what is still missing and the answer you need from your team or supplier.

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Further reading

These sources provide background for the topic. The practice examples and checklist are illustrative planning suggestions from Kay & Co.

Related guides

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