Review marketing performance, generate reports and move from a summary into project, campaign or product data.
No account needed: move from a results overview into campaign context.
A report is most useful when you can investigate what sits behind it. Start with a shared reporting context, narrow the question and carry the relevant evidence into a task or a report comment.
Choose the project, source and period. Check whether purchases and conversion value cover the same scope as spend. Allow for reporting and attribution delays before comparing the latest period with a more complete earlier one.
Start with the project overview and inspect the campaign or product behind a change. Compare related metrics rather than one isolated number. A rise in cost with fewer purchases suggests a question to investigate; it does not yet explain the cause.
Bring the project summary, campaign results and commentary into a report. Keep the same source and period as the results view. Distinguish completed actions from upcoming tasks; when a finding needs investigation, move into a task with its data context.
Bring results from connected sources into one place. Compare appropriate periods and interpret differences with measurement models and data availability in mind.
Prepare a report for your team or client. Data, commentary and relevant tasks connect an assessment of the situation to a decision about next steps.
Open a campaign or product, review its related task and ask AI for help with the analysis. A hypothesis still needs verification against the sources.
Cost, purchases and conversion value describe different parts of performance. Without margin, returns and other relevant business data, they cannot establish profit. Use the available metrics precisely and make missing inputs visible.
An owner may need the project overview; a specialist may need campaign or product detail. Add a short explanation of the change and the planned next step. Reporting becomes more useful when the reader knows what requires attention.
Two systems can differ in attribution, time zone or the time a conversion is recorded. Verify the source and reporting period before treating a discrepancy as a campaign problem. Keep these limits alongside the interpretation.
Yes. The product experience connects project results with campaign and product views. Use those views to narrow an observation and retain the relevant context when moving into a task or the next check.
Start with the source, period and metric definition. Check attribution and data freshness before drawing a conclusion. Different reporting rules can produce different figures without proving that either campaign execution or data collection has failed.
AI can help interpret the available context and suggest checks. Treat explanations as hypotheses until supported by evidence. A correlation or a generated suggestion is not proof of what caused a performance change.
Choose one project and a reporting period with sufficiently complete data.
Find a material change and inspect the campaign or product behind it.
Record the finding, the next check and the evidence needed to close the task.
Choose a process, connect its source and review the first result. Find package and add-on details in pricing.
