creative-testing-framework

Name: creative-testing-framework
Author: indranilbanerjee

507stars91forks

How to install creative-testing-framework?

indranilbanerjee/digital-marketing-pro/creative-testing-framework

$npx -y skills add indranilbanerjee/digital-marketing-pro --skill creative-testing-framework

Installs into the current project.

Summary

Design structured ad creative tests with A/B test plans, multivariate creative strategies, sample size calculations, and iteration cadences. Use when planning creative testing for ads, optimizing creative performance, or building a testing playbook across advertising platforms.

Files · 1

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SKILL.md

1	# /digital-marketing-pro:creative-testing-framework
2
3	## Purpose
4
5	Design a systematic creative testing framework that maximizes learning velocity while maintaining statistical rigor across advertising platforms. Produces a complete testing playbook with variable prioritization, sample size requirements, iteration cadence, and documentation standards for continuous creative optimization.
6
7	## Input Required
8
9	The user must provide (or will be prompted for):
10
11	- Ad platform(s): Where ads are running — Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, programmatic DSPs, Pinterest, X/Twitter, or multi-platform
12	- Creative types available: What formats can be produced — static image, video (short-form/long-form), carousel, text-only, responsive display, HTML5, playable, or collection ads
13	- Monthly ad budget allocated to testing: How much budget is available specifically for creative experimentation vs. proven performers
14	- Current top-performing creative: Description or reference to the best-performing ads currently running, including their key metrics
15	- Learning goals: Which creative elements need optimization — headlines, imagery, CTA copy, video hooks, color palette, offer framing, social proof, format type, or ad copy length
16	- Audience segments for testing: The audience groups available for testing — prospecting, retargeting, lookalike, interest-based, demographic, or custom segments
17	- Campaign objectives: What the ads are optimized for — awareness (impressions/reach), consideration (clicks/video views), or conversion (leads/purchases/ROAS)
18	- Historical creative performance data: Optional — past test results, creative fatigue patterns, seasonal performance variations, and known winners/losers
19	- Brand guidelines constraints: Visual identity rules, messaging restrictions, mandatory disclaimers, or approval bottlenecks that affect creative production speed
20	- Testing timeline: How long the testing program should run — single sprint (2-4 weeks), quarterly roadmap, or ongoing evergreen program
21
22	## Process
23
24	1. Load brand context: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, compliance rules for target markets (`skills/context-engine/compliance-rules.md`), and industry context. Also check for guidelines at `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` — if present, load restrictions and relevant category files. Check for custom templates at `~/.claude-marketing/brands/{slug}/templates/`. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
25	2. Define testing variables: Catalog all testable creative elements — headline copy, body copy length, CTA text and color, hero image subject, image style (photo vs. illustration vs. UGC), video hook (first 3 seconds), video length, ad format (static vs. carousel vs. video), color palette, offer framing (discount vs. value vs. urgency), social proof type (testimonial vs. stat vs. badge), and layout composition.
26	3. Prioritize variables by expected impact and ease: Score each variable on a 2x2 matrix of expected performance impact (high/low) and production effort (high/low). Rank variables so the team tests high-impact, low-effort elements first. Use historical data and platform benchmarks to inform impact estimates where available.
27	4. Design testing matrix: Build the variable-by-variant grid — for each priority variable, define 2-4 variants to test against the current control. Ensure tests are isolated (one variable per test) unless running deliberate multivariate experiments. Map each test to the appropriate audience segment and platform.
28	5. Calculate sample size per variant and minimum budget: Compute the required conversions per variant with `python "${CLAUDE_PLUGIN_ROOT}/scripts/sample-size-calculator.py" --baseline-rate {rate} --mde {mde} --mde-type relative --significance 0.95 --power 0.80` (a "10-20% relative lift" is `--mde 0.10`-`0.20` with `--mde-type relative`; use `--mde-type absolute` if the target is stated in percentage points — the two differ by ~40× at a 5% baseline). Translate sample size into minimum budget per test based on current CPM/CPC rates.
29	6. Define holdout control structure

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Type

creative-testing-framework

507stars91forks

View on GitHub

How to install creative-testing-framework?

indranilbanerjee/digital-marketing-pro/creative-testing-framework

$npx -y skills add indranilbanerjee/digital-marketing-pro --skill creative-testing-framework

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# /digital-marketing-pro:creative-testing-framework
2
3	## Purpose
4
5	Design a systematic creative testing framework that maximizes learning velocity while maintaining statistical rigor across advertising platforms. Produces a complete testing playbook with variable prioritization, sample size requirements, iteration cadence, and documentation standards for continuous creative optimization.
6
7	## Input Required
8
9	The user must provide (or will be prompted for):
10
11	- Ad platform(s): Where ads are running — Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, programmatic DSPs, Pinterest, X/Twitter, or multi-platform
12	- Creative types available: What formats can be produced — static image, video (short-form/long-form), carousel, text-only, responsive display, HTML5, playable, or collection ads
13	- Monthly ad budget allocated to testing: How much budget is available specifically for creative experimentation vs. proven performers
14	- Current top-performing creative: Description or reference to the best-performing ads currently running, including their key metrics
15	- Learning goals: Which creative elements need optimization — headlines, imagery, CTA copy, video hooks, color palette, offer framing, social proof, format type, or ad copy length
16	- Audience segments for testing: The audience groups available for testing — prospecting, retargeting, lookalike, interest-based, demographic, or custom segments
17	- Campaign objectives: What the ads are optimized for — awareness (impressions/reach), consideration (clicks/video views), or conversion (leads/purchases/ROAS)
18	- Historical creative performance data: Optional — past test results, creative fatigue patterns, seasonal performance variations, and known winners/losers
19	- Brand guidelines constraints: Visual identity rules, messaging restrictions, mandatory disclaimers, or approval bottlenecks that affect creative production speed
20	- Testing timeline: How long the testing program should run — single sprint (2-4 weeks), quarterly roadmap, or ongoing evergreen program
21
22	## Process
23
24	1. Load brand context: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, compliance rules for target markets (`skills/context-engine/compliance-rules.md`), and industry context. Also check for guidelines at `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` — if present, load restrictions and relevant category files. Check for custom templates at `~/.claude-marketing/brands/{slug}/templates/`. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
25	2. Define testing variables: Catalog all testable creative elements — headline copy, body copy length, CTA text and color, hero image subject, image style (photo vs. illustration vs. UGC), video hook (first 3 seconds), video length, ad format (static vs. carousel vs. video), color palette, offer framing (discount vs. value vs. urgency), social proof type (testimonial vs. stat vs. badge), and layout composition.
26	3. Prioritize variables by expected impact and ease: Score each variable on a 2x2 matrix of expected performance impact (high/low) and production effort (high/low). Rank variables so the team tests high-impact, low-effort elements first. Use historical data and platform benchmarks to inform impact estimates where available.
27	4. Design testing matrix: Build the variable-by-variant grid — for each priority variable, define 2-4 variants to test against the current control. Ensure tests are isolated (one variable per test) unless running deliberate multivariate experiments. Map each test to the appropriate audience segment and platform.
28	5. Calculate sample size per variant and minimum budget: Compute the required conversions per variant with `python "${CLAUDE_PLUGIN_ROOT}/scripts/sample-size-calculator.py" --baseline-rate {rate} --mde {mde} --mde-type relative --significance 0.95 --power 0.80` (a "10-20% relative lift" is `--mde 0.10`-`0.20` with `--mde-type relative`; use `--mde-type absolute` if the target is stated in percentage points — the two differ by ~40× at a 5% baseline). Translate sample size into minimum budget per test based on current CPM/CPC rates.
29	6. Define holdout control structure

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6 picks

Type