Weekly Performance Digest
A skill for producing publication-ready weekly Google Ads performance reports.
What this skill does
Given two weeks of campaign data (this week vs. last week, plus same week last month for MoM context), produces a digest with:
- Executive summary (3 sentences)
- Key metrics table with WoW and MoM comparisons
- Campaign highlights (top 3 + bottom 3)
- Anomalies and flags
- Prioritized action items for next week
Output is plain-language, non-technical - sendable directly to stakeholders.
Required inputs
- This week's campaign data (last 7 days)
- Last week's data (the 7 days before that)
- Same week last month (for MoM comparison; optional but recommended)
- Known changes context - any new campaigns, paused ads, budget shifts, creative updates the user made
Required columns
For each period:
- Campaign name
- Spend, Impressions, Clicks, CTR, CPC
- Conversions, CPA, Conv. rate
- Conv. value / Revenue (if tracked)
- ROAS (if tracked)
Workflow
Step 1: Validate data alignment
Both periods must have:
- Same set of campaigns (or note any added/removed)
- Same column structure
- Comparable date ranges (7 days each)
If a campaign was added or removed between periods, note it explicitly - comparisons across asymmetric periods are misleading.
Step 2: Compute aggregates and deltas
Account-level totals (this week vs. last week):
| Metric | Formula |
|---|---|
| WoW change % | (this - last) / last × 100 |
| MoM change % | (this - same_week_last_mo) / same_week_last_mo × 100 |
Flag any metric where:
- WoW change > ±15% (notable)
- MoM change > ±25% (significant trend)
Step 3: Identify campaign highlights
Top 3 performers: ranked by absolute conversion or revenue gain WoW Bottom 3 performers: ranked by absolute drop in conversions OR CPA spike
For each, write a 1-sentence "what changed and why" - tied to the data, not speculation. If the cause isn't clear from the data, say so:
"Generic Search lost 18 conversions WoW (down 22%). Cause unclear from current data - recommend checking search terms report."
Step 4: Anomaly detection
Flag campaigns where:
- Spent >20% of weekly budget with zero conversions
- CPA jumped >25% WoW
- Conv. rate dropped >20% WoW
- IS lost to budget jumped >10 percentage points
For each anomaly, include:
- Campaign name
- The specific metric that moved
- Possible cause (if obvious from data)
Step 5: Action items
3–5 specific, prioritized tasks for next week. Each item:
- Action: what to do (specific, not "review the account")
- Expected impact: estimated dollar/conversion result
- Owner: who should do it (PPC manager, designer, dev, client-side, etc.)
Examples:
- "Add 12 negative keywords to Generic Search campaign (saves est. $400/week)"
- "Investigate landing page conversion rate drop on Brand campaign - possible site change last week"
- "Increase Long Tail campaign budget from $500/day to $700/day - IS lost to budget = 35%, est. +18 conversions/week"
Output format
Read references/digest-template.md for the full template.
A markdown response structured as:
# Google Ads Weekly Digest - [Date Range]
## Executive Summary
[3 sentences: spend, conversions, CPA, ROAS this week + biggest win + biggest concern]
## Key Metrics
[Table: Metric | This Week | Last Week | WoW Δ | Last Month Same Week | MoM Δ]
## Campaign Highlights
### Top performers
- [Campaign A]: [what changed]
- [Campaign B]: [what changed]
- [Campaign C]: [what changed]
### Bottom performers / concerns
- [Campaign X]: [what changed]
- [Campaign Y]: [what changed]
- [Campaign Z]: [what changed]
## Anomalies
[Bulleted list of campaigns + metric movements meeting flag thresholds]
## Action Items for Next Week
1. [Action] - Impact: [estimate] - Owner: [role]
2. ...
If the user says this is for a stakeholder presentation, generate a Word doc using the docx skill. If they say "for my dashboard," generate a markdown response and offer to also create an Excel workbook with the data tables.
Output style requirements
This is the most reader-facing skill in the set. Style matters:
- Use actual numbers, not vague descriptions. Not "spend was up significantly" - say "$42,300, up 18% WoW."
- Plain language, not PPC jargon. Replace "CPA" → "cost per conversion" on first use, can use the abbreviation after.
- Frame metrics in business impact. "CPA dropped $8" → "We're acquiring customers $8 cheaper this week, saving ~$1,600 at current volume."
- Don't editorialize beyond what the data supports. "Strong week" is fine if numbers warrant it; "incredible breakthrough" is not.
- Active voice. "We launched a new campaign" beats "A new campaign was launched."
What this skill must NOT do
- Don't use PPC jargon without translation. Recipients may not be PPC experts.
- Don't speculate about causes you can't substantiate. "CPA might have spiked because of seasonality" - only say this if you have data showing it. Otherwise, "CPA spiked; cause unclear, recommend investigation."
- Don't pad. If the week was uneventful, say so in 3 sentences and move on.
- Don't recommend more than 5 action items. Stakeholders won't read more than that.
- Don't invent metrics. If the user didn't include ROAS data, don't compute or report ROAS.
- Don't write headers or sections that have nothing to say. Better to skip a section than say "no anomalies this week" with bullet padding.
Reference files
references/digest-template.md- full reference template with examplereferences/style-guide.md- language and framing rules with do/don't examples