analyzing-marketing-campaign
Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metr…
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技能内容
Marketing Campaign Analysis
Automated analysis of multi-channel marketing campaign data from BigQuery.
Data Source
Query data from BigQuery using the bigquery:execute_sql tool.
Location: marketing-analytics-483823.marketing.campaign_performance
Schema:
| Column | Type | Description |
|--------|------|-------------|
| date | DATE | Campaign date |
| campaign_name | STRING | Campaign identifier |
| channel | STRING | Marketing channel |
| segment | STRING | Customer segment |
| impressions | INTEGER | Ad impressions (NULL for Email) |
| clicks | INTEGER | Number of clicks |
| conversions | INTEGER | Number of conversions |
| spend | FLOAT | Marketing spend in dollars |
| revenue | FLOAT | Revenue generated in dollars |
| orders | INTEGER | Number of orders |
Required Input
The user must specify a week to analyze. Accept formats like:
- "Dec 9-15" or "December 9-15, 2024"
- "2024-12-09 to 2024-12-15"
- "week of Dec 9" or "last week"
If the date range is ambiguous, ask the user to clarify before querying.
Querying Data
Always filter by date range—never pull the entire table. Example query structure:
SELECT
channel,
SUM(impressions) as impressions,
SUM(clicks) as clicks,
SUM(conversions) as conversions,
SUM(spend) as spend,
SUM(revenue) as revenue,
SUM(orders) as orders
FROM `marketing-analytics-483823.marketing.campaign_performance`
WHERE date BETWEEN '2024-12-09' AND '2024-12-15'
GROUP BY channel
Adjust the query as needed for the specific analysis (e.g., group by segment, include daily breakdown).
Data Quality Check
- Check for NULL values (Email channel won't have impressions)
- Verify no negative values in numeric columns
- Flag anomalies (e.g., conversions without clicks)
Funnel Analysis
Calculate per channel:
- Click Through Rate (CTR) = clicks / impressions × 100
- Conversion Rate (CVR) = conversions / clicks × 100
Compare to user-provided benchmarks, report difference in percentage points. If benchmarks not provided, use:
| Channel | CTR | CVR |
|---------|-----|-----|
| Facebook_Ads | 2.5% | 3.8% |
| Google_Ads | 5.0% | 4.5% |
| TikTok_Ads | 2.0% | 0.9% |
| Email | 15.0% | 2.1% |
Efficiency Analysis
Calculate per channel:
- Return On Ad Spend (ROAS) = revenue / spend
- Cost Per Acquisition (CPA) = spend / conversions
- Net Profit = revenue - Total Costs
- Total Costs = spend + (orders × Shipping Cost) + (revenue × Product Cost %)
- Defaults: Shipping Cost = $8/order, Product Cost = 35% of revenue
Compare to user-provided targets. Defaults:
- Target ROAS: 4.0x minimum
- Max CPA: $50
Output Format
Present results as tables with status indicators:
Funnel Analysis Table:
| Channel | CTR Actual | CTR Benchmark | CTR Diff | CVR Actual | CVR Benchmark | CVR Diff |
Efficiency Analysis Table:
| Channel | ROAS | Status | CPA | Status | Net Profit | Status |
Status indicators:
- ROAS: "[OK] Above" if >= target, "[X] Below" if < target
- CPA: "[OK] Below" if <= max, "[X] Above" if > max
- Net Profit: "[OK] Positive" if > 0, "[X] Negative" if <= 0
Follow each table with brief channel-by-channel interpretation.
Budget Reallocation
If user asks about budget reallocation, read references/budget_reallocation_rules.md for the complete decision framework including eligibility rules, performance-based actions, and constraints.
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L3/updated_marketing_skill/analyzing-marketing-campaign/SKILL.md同一个仓库里的其他技能
同名技能的其他版本
有 2 个不同仓库或目录里都有叫 analyzing-marketing-campaign 的技能。它们内容并不相同,别混用:
- https-deeplearning-ai/sc-agent-skills-files — Analyze weekly marketing campaign performance data across channels. Use when analyzing mul