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Post campaign analysis closes a completed campaign's observation window before comparing results with targets. Follow a worked export, spreadsheet formulas and a reconciled contribution review.
Post campaign analysis compares a completed campaign's mature outcomes with its original targets and reconciled costs. Close the observation window for every eligible prospect before judging the result. Then record what to repeat, change or stop, with a named owner for the next action.
Write down the campaign entry period, qualifying action, attribution rule and follow-up window. Keep the original target version. Changing the target after seeing results turns a closeout into a moving comparison.
For this example, a fictional US equipment supplier compares Alpha and Beta. Qualified prospects entered during April 2026. Each gets a first-order window covering the 60 calendar days following qualification, starting the next day and ending on the qualification date plus 60 days, inclusive. The final review takes place July 31, after every window has closed.
An earlier snapshot can help the team manage follow-up. It belongs in campaign dashboards, with a provisional label. The completed-campaign review answers a different question: what did the agreed cohort produce within its agreed time?
Use one row per qualified prospect for this first-order example. Campaign membership is exclusive, and each prospect has at most one first order. For repeat-order analysis, keep a separate order register so prospect counts are not multiplied by purchases.
The table is the Cohort sheet, columns A through F, rows 2 through 7. Dates are in 2026; store them as actual dates. Empty order-date cells are blank, and zero revenue means no recorded first order.
| Prospect | Campaign | Qualified date | First order date | Revenue (USD) | COGS (USD) |
|---|---|---|---|---|---|
| A1 | Alpha | April 1 | April 25 | 18,000 | 10,800 |
| A2 | Alpha | April 5 | June 1 | 12,000 | 7,200 |
| A3 | Alpha | April 10 | 0 | 0 | |
| B1 | Beta | April 15 | May 10 | 20,000 | 10,000 |
| B2 | Beta | April 20 | 0 | 0 | |
| B3 | Beta | April 30 | July 5 | 10,000 | 6,000 |
Check the campaign IDs against the approved campaign list. Reconcile costs separately to advertising charges, supplier invoices and any required accruals. Use the same treatment of production and event costs in both campaigns.
In G2, calculate the end of the prospect's window:
=C2+60
In H2, mark whether the first order falls inside that window:
=COUNTIFS(D2,">"&C2,D2,"<="&G2)
Fill both formulas through row 7. Microsoft documents COUNTIFS as counting rows where all supplied criteria are met. Here, the blank order dates do not meet the positive date thresholds.
The window ends are May 31, June 4, June 9, June 14, June 19 and June 29, respectively. H contains 1, 1, 0, 1, 0 and 0. B3's July 5 order is real, but outside its June 29 cutoff.
Put the campaign name in A2 of a separate summary sheet. Count eligible first orders in B2 and sum their revenue in C2:
=COUNTIFS(Cohort!$B$2:$B$7,$A2,Cohort!$H$2:$H$7,1)
=SUMIFS(Cohort!$E$2:$E$7,Cohort!$B$2:$B$7,$A2,Cohort!$H$2:$H$7,1)
For eligible COGS, replace the sum range E with F. Microsoft's SUMIFS reference confirms the sum range comes first, followed by the criteria pairs. Keep all ranges the same size.
Covirage is not affiliated with Microsoft.
First recover the approved plan. The contribution definition here is revenue minus COGS minus campaign spend, before other selling expenses and corporate overhead. Keep that boundary consistent; contribution and gross margin answer different cost questions.
| Campaign | Target orders | Target revenue (USD) | Target COGS (USD) | Budget (USD) | Target contribution (USD) |
|---|---|---|---|---|---|
| Alpha | 3 | 36,000 | 22,500 | 7,500 | 6,000 |
| Beta | 2 | 24,000 | 12,500 | 6,500 | 5,000 |
| Total | 5 | 60,000 | 35,000 | 14,000 | 11,000 |
Alpha's target contribution is 36,000 minus 22,500 minus 7,500 = $6,000. Calculate the actuals using eligible outcomes and the reconciled spending register:
| Campaign | Eligible orders | Eligible revenue (USD) | Eligible COGS (USD) | Actual spend (USD) | Actual contribution (USD) |
|---|---|---|---|---|---|
| Alpha | 2 | 30,000 | 18,000 | 8,000 | 4,000 |
| Beta | 1 | 20,000 | 10,000 | 6,000 | 4,000 |
| Total | 3 | 50,000 | 28,000 | 14,000 | 8,000 |
If this actual table starts in A1, contribution in F2 is:
=C2-D2-E2
Total spending equals budget, but the campaign set misses target orders by 3 minus 5 = -2 and revenue by 50,000 minus 60,000 = -$10,000. Contribution misses by 8,000 minus 11,000 = -$3,000. Alpha overspends by $500, while Beta underspends by $500; the company total conceals both variances.
The prospect export contains $60,000 of first-order revenue. Subtract B3's $10,000 outside the window to reach $50,000 eligible revenue. Likewise, $34,000 of exported COGS minus $6,000 outside the window equals $28,000 eligible COGS. The financial bridge is 50,000 minus 28,000 minus 14,000 = $8,000.
Now assign follow-up work. Alpha's owner should explain its cost overrun; Beta's owner should examine the delayed purchase before deciding whether the follow-up window fits its sales process. Equal contribution does not mean equal causes. The marketing campaign analysis report covers how to present the findings for a decision meeting.
Bring your target sheet, campaign costs and dated prospect and sales exports. Covirage maps the columns, and its tools compute and check target-versus-result and contribution comparisons; the external AI model explains the results with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data.
See revenue driver analysis for the supporting business context.
Run the final review after the agreed sales observation window has closed for the last eligible prospect and the relevant costs are available. Earlier reviews can be useful, but label them provisional. Choose the window before inspecting results and apply it consistently across comparable campaigns.
Keep the original targets, campaign cost records, qualified prospect export and dated sales outcomes. Use stable campaign and prospect identifiers, plus order identifiers when repeat orders exist. Finance should provide net revenue, relevant costs and adjustments so the outcome totals can be reconciled.
Count sales inside the agreed observation window in the main comparison. Show later sales in a separate follow-up view. If the business adopts a longer window for future reviews, document that definition change and restate earlier comparisons where necessary.