Campaign Reporting Checklist
End-of-campaign reporting workflow for marketing managers and demand-gen leads. Covers data collection across paid, organic, and email channels, performance analysis against benchmarks, and stakeholder reporting with documented follow-ups.
Data Collection
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Confirm the campaign KPIs and reporting window
Pull the original campaign brief and confirm the primary KPIs (MQLs, pipeline sourced, ROAS, CPA) plus the exact reporting window. Mismatched windows across GA4, the ad platforms, and the CRM are the most common reason numbers don't reconcile later.
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Audit UTM parameters across campaign links
Check source / medium / campaign / content / term against the team's UTM convention doc. Drift between paid social, paid search, and email — capital letters, spaces, inconsistent campaign names — fragments source-medium reporting in GA4 and breaks attribution.
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Validate GA4 conversion events and pixel firing
Use GA4 DebugView and Tag Assistant to confirm the campaign's conversion events fire on the actual submit, not on email-blur or page-load. Cross-check event counts against Meta Pixel and LinkedIn Insight Tag for the same window — single-digit-percent variance is normal, 5x is a misfire.
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Pull spend and impression data from ad platforms
Export from Google Ads, Meta Ads Manager, LinkedIn Campaign Manager, and any DSP (The Trade Desk, DV360) used. Match attribution windows across platforms — Meta defaults to 7-day click / 1-day view; LinkedIn defaults to 30-day post-click. Document any window differences in the report appendix.
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Export CRM-side pipeline and revenue data
From Salesforce or HubSpot CRM, pull MQLs, SALs, opportunities, and closed-won attributed to the campaign source. Use the campaign object — not free-text source field — to avoid orphaned leads. Note any leads stuck at MQL with no SDR follow-up; that's a routing issue, not a campaign issue.
Performance Analysis
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Compare results against the campaign benchmarks
Benchmark against the original brief's targets and against the trailing four-quarter average for the same channel. A campaign that beats brief targets but underperforms the channel baseline is still a problem worth flagging.
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Calculate ROAS, CPA, and payback period
For B2B, use pipeline-sourced ROAS (opportunity dollars / spend) alongside closed-won ROAS — closed-won lags spend by the sales cycle length. For e-comm, MER (total revenue / total marketing spend) gives a cleaner read than platform-reported ROAS, which double-counts across channels.
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Analyze the conversion funnel for drop-off
Walk the funnel from impression to closed-won: CTR, landing-page conversion rate, MQL-to-SQL conversion, opportunity-to-close. Drop-offs greater than two standard deviations from the channel baseline are the actionable findings — flag these for the recommendations section.
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Rank channels by efficiency and contribution
Build a channel matrix: spend, attributed conversions, CPA, and contribution to total pipeline. Note where last-touch and multi-touch attribution disagree — typically paid search gets credit at last-touch while content / organic carry the assist.
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Flag whether the campaign hit its primary target
This is the headline finding the report opens with. If the campaign missed by more than 15%, the reporting workflow branches to a root-cause analysis before the report goes out.
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Run a root-cause analysis on the miss
For a material miss, isolate whether the gap is upstream (impressions / reach), midstream (CTR / landing-page conversion), or downstream (MQL quality / sales follow-up). Document with platform screenshots and the channel matrix from the prior step. The PMM, demand-gen lead, and an ops partner should sign off on the diagnosis before it goes into the report.
Report Build & Review
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Draft the executive summary and key findings
Lead with the headline number and three to five findings. Executives read the first slide and the recommendations; everything else is appendix. Tie each finding to a specific data point, not a narrative.
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Build channel and funnel visualizations
Standard set: spend vs. pipeline by channel (bar), funnel conversion (waterfall), week-over-week pacing (line), and a CPA / ROAS scatter. Pull from the team's Looker Studio or Tableau template — don't rebuild charts campaign-to-campaign.
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Write actionable recommendations
Each recommendation names an owner, a timeframe, and the metric it should move. "Shift 20% of LinkedIn budget to retargeting next quarter — owned by paid lead, decision by month-end, target: lower CPA by 15%." Vague recommendations like "optimize creative" don't get acted on.
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Run peer review with the demand-gen lead
Demand-gen lead pressure-tests the numbers and the recommendations before anything goes to leadership. Common catches: attribution-window mismatches, double-counted conversions, recommendations that contradict the data.
Collects list
Distribution & Follow-Up
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Distribute the report to stakeholders
Send to CMO, sales leadership, RevOps, and the campaign's PMM. Use the team's standard distribution list rather than ad-hoc Slack DMs — a one-off DM gets lost; a recurring distribution creates the expectation of ongoing accountability.
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Present findings at the next marketing WBR
Five-minute walkthrough at the weekly business review: headline, one chart, the three recommendations. Capture questions from sales and product marketing — they often surface attribution disputes that need resolving before the next campaign.
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Log follow-up actions in the team tracker
Each recommendation becomes a ticket in Asana / Monday / ClickUp with owner, due date, and target metric. Recommendations that don't get logged here don't get done — this is the single biggest gap in most reporting workflows.
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Archive raw data exports and the final report
Save the platform exports, the analysis workbook, and the final deck to the campaign's folder in the DAM or shared drive. Quarterly content audits and annual planning both rely on this archive existing — don't leave the only copy in the analyst's local Downloads folder.
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