How do I install the Analyzing Marketing Campaign skill?

Run npx skillmds@latest add datawhalechina/analyzing-marketing-campaign in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Analyzing Marketing Campaign free to use?

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Who published Analyzing Marketing Campaign?

datawhalechina (@datawhalechina) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Analyzing Marketing Campaign by datawhalechina

Name: Analyzing Marketing Campaign
Rating: 4.2 (5 reviews)
Author: datawhalechina

Analyzing Marketing Campaign

Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.

File contents

Marketing Campaign Analysis

Automated analysis of multi-channel marketing campaign data.

Input Requirements

Expects campaign data in CSV format with these columns:

date: Campaign date
campaign_name: Campaign identifier
channel: Marketing channel
segment: Customer segment
impressions: Ad impressions (empty for Email channel)
clicks: Number of clicks
conversions: Number of conversions
spend: Marketing spend in dollars
revenue: Revenue generated in dollars
orders: Number of orders

Data Quality Check

Check for missing values and empty cells (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 and provide brief interpretation for each channel. If benchmarks are not provided, use these historical values:

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 %)
- Unless user specifies different values, use:
  - Shipping Cost: $8 per order
  - Product Cost: 35% of revenue

Compare to user-provided targets. If not provided, use these defaults:

Target ROAS: 4.0x minimum
Max CPA: $50

Output Format

Present results as tables with status indicators:

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 highlighting key insights and recommended actions.

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.

---name: analyzing-marketing-campaigndescription: Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.---# Marketing Campaign AnalysisAutomated analysis of multi-channel marketing campaign data.## Input RequirementsExpects campaign data in CSV format with these columns:- **date**: Campaign date - **campaign_name**: Campaign identifier- **channel**: Marketing channel- **segment**: Customer segment- **impressions**: Ad impressions (empty for Email channel)- **clicks**: Number of clicks- **conversions**: Number of conversions- **spend**: Marketing spend in dollars- **revenue**: Revenue generated in dollars- **orders**: Number of orders## Data Quality Check1. Check for missing values and empty cells (Email channel won't have impressions)2. Verify no negative values in numeric columns3. Flag anomalies (e.g., conversions without clicks)## Funnel AnalysisCalculate per channel:- **Click Through Rate (CTR)** = clicks / impressions × 100- **Conversion Rate (CVR)** = conversions / clicks × 100Compare to user-provided benchmarks, report difference in percentage points and provide brief interpretation for each channel. If benchmarks are not provided, use these historical values:| 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 AnalysisCalculate 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 %) - Unless user specifies different values, use: - **Shipping Cost**: $8 per order - **Product Cost**: 35% of revenueCompare to user-provided targets. If not provided, use these defaults:- **Target ROAS**: 4.0x minimum- **Max CPA**: $50## Output FormatPresent 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 <= 0Follow each table with brief channel-by-channel interpretation highlighting key insights and recommended actions.## Budget ReallocationIf user asks about budget reallocation, read `references/budget_reallocation_rules.md` for the complete decision framework including eligibility rules, performance-based actions, and constraints.

Frequently asked questions