SEO report example: from source metrics to client actions.

Start by working through the actions in order: confirm project details; state the reporting period; write a concise executive summary; order detailed sections by client importance. Each action should leave an audit trail in the report, even if that trail is only a short note about the date range, selected property, filtering decision, or page group under review. This prevents the next report from using a different definition by accident and makes unusual movements easier to investigate. When several people contribute to reporting, the same checklist also reduces interpretation differences between team members.

After collecting the figures, compare the headline result with the underlying dimensions. Look for concentration, such as one page producing a large share of clicks, or one source accounting for a material portion of sessions. Then review whether the movement is broad or isolated. This step turns a generic metric summary into analysis that a client can use, while keeping the explanation anchored to the data supported by MetricFlow: Search Console performance, GA4 activity, stored report metrics, generated summaries, and PDF exports.

A report for an ecommerce project could summarize a rise in organic clicks, identify the collection pages contributing to that movement, and recommend reviewing high-impression product queries. A strong report would state the measured result, name the source, describe the supporting detail, and then suggest a review or optimization step. It would not imply causation merely because two metrics moved during the same period. If an important dimension is unavailable, the report should say so and avoid filling the gap with an unsupported assumption.

A polished layout cannot compensate for vague definitions or claims that are not supported by the figures shown. Before publishing, ask whether another reader could reproduce the interpretation from the figures shown. Check that dates match, units are clear, percentages are calculated consistently, and recommendations are proportionate to the evidence. This final quality check is especially important when generated wording is used: MetricFlow can create summaries and recommendations from structured report data, but the report owner should review that wording before sharing it with a client.

Start by working through the actions in order: group KPIs by source; compare matching periods; inspect supporting dimensions; avoid universal benchmark claims. Each action should leave an audit trail in the report, even if that trail is only a short note about the date range, selected property, filtering decision, or page group under review. This prevents the next report from using a different definition by accident and makes unusual movements easier to investigate. When several people contribute to reporting, the same checklist also reduces interpretation differences between team members.

After collecting the figures, compare the headline result with the underlying dimensions. Look for concentration, such as one page producing a large share of clicks, or one source accounting for a material portion of sessions. Then review whether the movement is broad or isolated. This step turns a generic metric summary into analysis that a client can use, while keeping the explanation anchored to the data supported by MetricFlow: Search Console performance, GA4 activity, stored report metrics, generated summaries, and PDF exports.

If sessions increase but engagement rate falls, the report can inspect landing pages and traffic sources before deciding whether the change represents weaker visit quality. A strong report would state the measured result, name the source, describe the supporting detail, and then suggest a review or optimization step. It would not imply causation merely because two metrics moved during the same period. If an important dimension is unavailable, the report should say so and avoid filling the gap with an unsupported assumption.

A benchmark from another website, industry, or tracking setup may not be an appropriate target for the client being reported. Before publishing, ask whether another reader could reproduce the interpretation from the figures shown. Check that dates match, units are clear, percentages are calculated consistently, and recommendations are proportionate to the evidence. This final quality check is especially important when generated wording is used: MetricFlow can create summaries and recommendations from structured report data, but the report owner should review that wording before sharing it with a client.

Start by working through the actions in order: show the four core GSC metrics; review top queries; review top pages; tie recommendations to observed opportunities. Each action should leave an audit trail in the report, even if that trail is only a short note about the date range, selected property, filtering decision, or page group under review. This prevents the next report from using a different definition by accident and makes unusual movements easier to investigate. When several people contribute to reporting, the same checklist also reduces interpretation differences between team members.

After collecting the figures, compare the headline result with the underlying dimensions. Look for concentration, such as one page producing a large share of clicks, or one source accounting for a material portion of sessions. Then review whether the movement is broad or isolated. This step turns a generic metric summary into analysis that a client can use, while keeping the explanation anchored to the data supported by MetricFlow: Search Console performance, GA4 activity, stored report metrics, generated summaries, and PDF exports.

A page with increasing impressions but stable clicks can be highlighted for title, description, intent, or content review rather than labelled a failure. A strong report would state the measured result, name the source, describe the supporting detail, and then suggest a review or optimization step. It would not imply causation merely because two metrics moved during the same period. If an important dimension is unavailable, the report should say so and avoid filling the gap with an unsupported assumption.

Do not describe average position as a single fixed ranking for every user, location, device, and query. Before publishing, ask whether another reader could reproduce the interpretation from the figures shown. Check that dates match, units are clear, percentages are calculated consistently, and recommendations are proportionate to the evidence. This final quality check is especially important when generated wording is used: MetricFlow can create summaries and recommendations from structured report data, but the report owner should review that wording before sharing it with a client.

Start by working through the actions in order: label GA4 metrics clearly; inspect leading landing pages; review generated summaries; edit recommendations to match professional judgment. Each action should leave an audit trail in the report, even if that trail is only a short note about the date range, selected property, filtering decision, or page group under review. This prevents the next report from using a different definition by accident and makes unusual movements easier to investigate. When several people contribute to reporting, the same checklist also reduces interpretation differences between team members.

After collecting the figures, compare the headline result with the underlying dimensions. Look for concentration, such as one page producing a large share of clicks, or one source accounting for a material portion of sessions. Then review whether the movement is broad or isolated. This step turns a generic metric summary into analysis that a client can use, while keeping the explanation anchored to the data supported by MetricFlow: Search Console performance, GA4 activity, stored report metrics, generated summaries, and PDF exports.

A reviewed summary might state that organic visibility and measured sessions increased while engagement varied by landing page, then recommend examining the weakest high-traffic pages. A strong report would state the measured result, name the source, describe the supporting detail, and then suggest a review or optimization step. It would not imply causation merely because two metrics moved during the same period. If an important dimension is unavailable, the report should say so and avoid filling the gap with an unsupported assumption.

Generated text should not introduce numbers, causes, or outcomes that are absent from the stored report metrics. Before publishing, ask whether another reader could reproduce the interpretation from the figures shown. Check that dates match, units are clear, percentages are calculated consistently, and recommendations are proportionate to the evidence. This final quality check is especially important when generated wording is used: MetricFlow can create summaries and recommendations from structured report data, but the report owner should review that wording before sharing it with a client.

Start by working through the actions in order: review the report in the application; check the PDF dates and project name; scan tables for clipping or missing values; share only the approved export. Each action should leave an audit trail in the report, even if that trail is only a short note about the date range, selected property, filtering decision, or page group under review. This prevents the next report from using a different definition by accident and makes unusual movements easier to investigate. When several people contribute to reporting, the same checklist also reduces interpretation differences between team members.

After collecting the figures, compare the headline result with the underlying dimensions. Look for concentration, such as one page producing a large share of clicks, or one source accounting for a material portion of sessions. Then review whether the movement is broad or isolated. This step turns a generic metric summary into analysis that a client can use, while keeping the explanation anchored to the data supported by MetricFlow: Search Console performance, GA4 activity, stored report metrics, generated summaries, and PDF exports.

A consultant can generate a report, review the AI-assisted wording, export the final PDF, and use it during a client meeting or send it through their normal communication process. A strong report would state the measured result, name the source, describe the supporting detail, and then suggest a review or optimization step. It would not imply causation merely because two metrics moved during the same period. If an important dimension is unavailable, the report should say so and avoid filling the gap with an unsupported assumption.

PDF export does not remove the need to verify source-property selection, date ranges, and generated recommendations. Before publishing, ask whether another reader could reproduce the interpretation from the figures shown. Check that dates match, units are clear, percentages are calculated consistently, and recommendations are proportionate to the evidence. This final quality check is especially important when generated wording is used: MetricFlow can create summaries and recommendations from structured report data, but the report owner should review that wording before sharing it with a client.