Cross-Platform Creative Testing

A/B tests ad creatives across all connected advertising platforms. Creates test variants, monitors performance, determines statistical winners, and applies winning creatives platform-wide.

Safety Guardrails

Read-only by default. This skill:

Analyzes creative performance and outputs recommendations only
Never auto-pauses or promotes variants without explicit flags
Requires --apply flag to make any changes
Generates detailed reports before modifications

Capabilities

Create A/B Tests - Set up multi-variant creative tests across platforms
Monitor Performance - Track CTR, CPC, CVR, ROAS per creative variant
Statistical Analysis - Calculate confidence intervals and significance
Winner Detection - Automatically identify winning variants at threshold
Apply Winners - Promote winning creatives, pause losers
Cross-Platform Sync - Replicate winning concepts to other platforms

Workflow

Step 1: Create Test Configuration

python3 scripts/create_test.py \
  --name "Q1 2026 Hero Image Test" \
  --platforms google,meta,linkedin \
  --variants 3 \
  --metric ctr \
  --confidence 95 \
  --min-impressions 1000 \
  --output test_config.json

Step 2: Upload Creative Variants

python3 scripts/upload_variants.py \
  --test-id test_config.json \
  --variant-a /path/to/hero_v1.png --headline-a "Try Free Today" \
  --variant-b /path/to/hero_v2.png --headline-b "Start Your Trial" \
  --variant-c /path/to/hero_v3.png --headline-c "Get Started Free"

Step 3: Monitor Test Performance

python3 scripts/monitor_test.py \
  --test-id test_config.json \
  --output performance.json

Step 4: Analyze Results

python3 scripts/analyze_results.py \
  --test-id test_config.json \
  --performance performance.json \
  --output analysis.json

Step 5: Apply Winner (Optional)

python3 scripts/apply_winner.py \
  --test-id test_config.json \
  --analysis analysis.json \
  --dry-run

# Remove --dry-run to execute
python3 scripts/apply_winner.py \
  --test-id test_config.json \
  --analysis analysis.json \
  --apply

Common Operations

Quick performance check on active tests

python3 scripts/monitor_test.py \
  --all-active \
  --summary-only

Create headline-only test

python3 scripts/create_test.py \
  --name "Headline Test" \
  --platforms meta \
  --type headline \
  --variants 4 \
  --metric ctr

Create image-only test

python3 scripts/create_test.py \
  --name "Image Test" \
  --platforms google,meta \
  --type image \
  --variants 3 \
  --metric cvr

Generate creative test report

python3 scripts/generate_report.py \
  --test-id test_config.json \
  --format markdown \
  --output creative_report.md

Sync winning creative to other platforms

python3 scripts/sync_winner.py \
  --test-id test_config.json \
  --source-platform meta \
  --target-platforms google,linkedin,tiktok \
  --dry-run

Statistical Methodology

Significance Testing

Uses Bayesian A/B testing with Beta-Binomial model for CTR/CVR:

Prior: Beta(1, 1) - uninformative prior
Posterior: Beta(1 + conversions, 1 + non-conversions)
Winner Probability: Monte Carlo simulation (10,000 draws)
Threshold: Variant wins if P(best) > confidence level

Minimum Sample Size

n = 2 × (Z_α/2 + Z_β)² × p(1-p) / δ²

Where:
- Z_α/2 = 1.96 (95% confidence)
- Z_β = 0.84 (80% power)
- p = expected baseline rate
- δ = minimum detectable effect

Metrics Tracked

Metric	Formula	Use Case
CTR	Clicks / Impressions	Awareness campaigns
CVR	Conversions / Clicks	Conversion campaigns
CPC	Spend / Clicks	Cost efficiency
ROAS	Revenue / Spend	Revenue optimization
CPL	Spend / Leads	Lead generation

Parameters

Parameter	Required	Default	Description
`--name`	Yes	-	Test name for tracking
`--platforms`	No	`all`	Comma-separated platform list
`--type`	No	`full`	Test type: headline, image, video, full
`--variants`	No	`2`	Number of variants (2-5)
`--metric`	No	`ctr`	Primary metric: ctr, cvr, cpc, roas
`--confidence`	No	`95`	Confidence level (90, 95, 99)
`--min-impressions`	No	`1000`	Minimum impressions before analysis
`--max-duration`	No	`14d`	Maximum test duration
`--budget-split`	No	`equal`	Budget allocation: equal, weighted
`--dry-run`	No	`false`	Preview without applying
`--apply`	No	`false`	Execute winner promotion

Scripts Reference

Script	Purpose
`create_test.py`	Create new A/B test configuration
`upload_variants.py`	Upload creative variants to platforms
`monitor_test.py`	Track real-time performance metrics
`analyze_results.py`	Statistical analysis and winner detection
`apply_winner.py`	Promote winner, pause losers
`sync_winner.py`	Replicate winning creative to other platforms
`generate_report.py`	Create detailed test reports
`platform_creative_adapters.py`	Platform-specific creative management

Output Format

Test Configuration JSON

{
  "test_id": "ct_2026011801",
  "name": "Q1 2026 Hero Image Test",
  "created_at": "2026-01-18T10:00:00Z",
  "status": "running",
  "platforms": ["google", "meta", "linkedin"],
  "type": "full",
  "primary_metric": "ctr",
  "confidence_level": 95,
  "min_impressions": 1000,
  "max_duration_days": 14,
  "variants": [
    {
      "id": "A",
      "name": "Control",
      "headline": "Try Free Today",
      "image_url": "https://your-cdn.com/creatives/hero_v1.png"
    },
    {
      "id": "B",
      "name": "Variant B",
      "headline": "Start Your Trial",
      "image_url": "https://your-cdn.com/creatives/hero_v2.png"
    }
  ],
  "budget_split": {
    "A": 50,
    "B": 50
  }
}

Analysis Results JSON

{
  "test_id": "ct_2026011801",
  "analyzed_at": "2026-01-25T10:00:00Z",
  "status": "winner_found",
  "winner": "B",
  "confidence": 97.3,
  "platforms": {
    "google": {
      "variants": {
        "A": {
          "impressions": 12500,
          "clicks": 375,
          "conversions": 45,
          "spend": 187.50,
          "ctr": 3.0,
          "cvr": 12.0,
          "cpc": 0.50
        },
        "B": {
          "impressions": 12500,
          "clicks": 500,
          "conversions": 65,
          "spend": 187.50,
          "ctr": 4.0,
          "cvr": 13.0,
          "cpc": 0.375
        }
      },
      "winner": "B",
      "confidence": 98.5,
      "lift": {
        "ctr": 33.3,
        "cvr": 8.3,
        "cpc": -25.0
      }
    },
    "meta": {
      "variants": {
        "A": {
          "impressions": 18000,
          "clicks": 540,
          "conversions": 54,
          "spend": 270.00,
          "ctr": 3.0,
          "cvr": 10.0,
          "cpc": 0.50
        },
        "B": {
          "impressions": 18000,
          "clicks": 720,
          "conversions": 79,
          "spend": 270.00,
          "ctr": 4.0,
          "cvr": 11.0,
          "cpc": 0.375
        }
      },
      "winner": "B",
      "confidence": 99.1,
      "lift": {
        "ctr": 33.3,
        "cvr": 10.0,
        "cpc": -25.0
      }
    }
  },
  "aggregate": {
    "winner": "B",
    "confidence": 97.3,
    "total_impressions": 61000,
    "lift": {
      "ctr": 33.3,
      "cvr": 9.5,
      "cpc": -25.0
    },
    "recommendation": "Promote Variant B across all platforms. Expected +33% CTR improvement."
  }
}

Platform-Specific Notes

Google Ads

Creates Responsive Search Ads for headline tests
Responsive Display Ads for image tests
Asset-level reporting available
Ad rotation: Optimize or Rotate Evenly

Meta Ads

Uses Dynamic Creative for testing
A/B test framework built-in
Automatic placements recommended
Breakdown by creative element

LinkedIn Ads

Sponsored Content A/B testing
Single image, carousel, video formats
Member traits for audience splits
Conversion tracking via Insight Tag

X Ads

Promoted Tweets with variants
Image, video, carousel formats
Engagement objectives for CTR
Website conversion tracking

Reddit Ads

Link ads and text ads
Subreddit targeting splits
Conversion pixel for CVR
API v3 creative management

TikTok Ads

In-Feed ads, TopView, Spark
Video-first creative testing
Custom audiences for splits
TikTok Pixel for conversions

Amazon Ads

Sponsored Products/Brands/Display
Custom headline tests
ASIN-level performance
Attribution for conversions

Best Practices

Test one element at a time - Isolate headlines, images, or CTAs
Ensure statistical significance - Wait for min impressions before deciding
Use realistic budgets - Don't starve variants with low spend
Match audiences - Ensure fair comparison with same targeting
Document learnings - Track what works for future campaigns
Consider seasonality - Account for weekly/monthly patterns
Iterate on winners - Use insights for next round of tests
Cross-platform sync - Apply learnings across all platforms

Environment Variables

Required environment variables:

# Platform Connection IDs

# Platform Account IDs
GOOGLE_ADS_CUSTOMER_ID
META_AD_ACCOUNT_ID
LINKEDIN_AD_ACCOUNT_ID
TWITTER_AD_ACCOUNT_ID
REDDIT_AD_ACCOUNT_ID
TIKTOK_ADVERTISER_ID
AMAZON_ADS_PROFILE_ID

# Google Ads specific
GOOGLE_ADS_DEVELOPER_TOKEN
GOOGLE_ADS_LOGIN_CUSTOMER_ID

# Database for test tracking
DATABASE_URL

Error Handling

Error	Cause	Solution
`INSUFFICIENT_DATA`	Not enough impressions	Extend test duration or increase budget
`NO_WINNER`	Variants too similar	Increase minimum detectable effect
`UPLOAD_FAILED`	Creative rejected by platform	Check format/size requirements
`TEST_EXPIRED`	Max duration reached	Analyze current data or restart
`VARIANT_PAUSED`	Platform paused underperformer	May indicate quality issues
`SYNC_FAILED`	Cross-platform sync error	Check target platform credentials

Integration with Other Skills

ad-copy-generation - Generate headline variants for testing
cross-platform-launcher - Deploy winning creatives to new campaigns
multi-channel-reporting - Include test results in reports
budget-optimizer - Allocate more budget to winning creatives

About this skill

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