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A report usually answers the questions you already thought to ask. You check whether traffic rose, leads fell, or a campaign hit its target. But the useful clue may sit one level deeper.
A channel can bring in fewer leads overall while producing more qualified ones. A landing page can hold its average conversion rate even as one important audience segment starts to drop off. Neither pattern is obvious from a single headline number.
Give ChatGPT a report with enough detail to compare channels, campaigns, audiences, or time periods. Ask it to hunt for ten surprising patterns, anomalies, or relationships. The number is a way to widen the search, not a requirement to treat every finding as important.
Before you act, check the strongest findings against the source data. A small segment, a tracking change, or a seasonal spike can make a pattern look more meaningful than it is. Look for findings that are both credible and tied to a decision you can make.
Try this prompt (attach your report/data):
Analyze the attached marketing report. Our main goal is [goal], and the decisions this report should inform are [decisions].
Find up to 10 surprising patterns, anomalies, or relationships that a quick read of the headline numbers might miss. Compare segments, channels, campaigns, and time periods where the data allows.
For each finding, show the exact figures and where they appear in the report. Explain why it stands out, one plausible interpretation, and at least one alternative explanation. Flag small samples, missing context, or data quality issues. Do not imply that a relationship is causal without evidence.
Rank the findings by how useful they may be for our decisions. For the top three, suggest the next check I should make before changing our marketing plan. If the report does not support 10 credible findings, return fewer.
The best result is not a list of ten curiosities. It is one or two questions you would have missed that are worth checking next.
Happy prompting!
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