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media-plan

Build a paid media plan: channel split, weekly flighting, audiences, reach and frequency.

Skill by indranilbanerjee

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/indranilbanerjee-media-plan

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About

Build a paid media plan: channel split, weekly flighting, audiences, reach and frequency. "plan our Q4 ad budget"

Use cases: marketing, finance

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/media-plan

What's inside

Skill name
media-plan
Description
Build a paid media plan: channel split, weekly flighting, audiences, reach and frequency. "plan our Q4 ad budget"
License
MIT
Instructions
74 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# /digital-marketing-pro:media-plan

## Purpose

Generate a holistic paid media plan that coordinates budget, channels, audiences, creative, and timing across all advertising platforms. Balances reach and efficiency objectives with practical execution constraints to produce a ready-to-implement plan with clear pacing targets and contingency protocols.

## Input Required

The user must provide (or will be prompted for):

- **Campaign dates**: Start date, end date, and any blackout periods or mandatory flight windows
- **Total paid media budget**: Aggregate budget for the campaign period with any channel-specific floors or caps
- **Channels available**: Platforms in consideration — Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, ChatGPT Ads, programmatic display, connected TV, native, audio, out-of-home, etc.
- **Campaign objectives**: Primary and secondary objectives — awareness (reach/impressions), consideration (traffic/engagement), conversion (leads/sales/ROAS)
- **Target audiences with segments**: Audience definitions including demographics, interests, behaviors, custom audiences, lookalikes, and retargeting pools
- **Creative assets available**: Existing ad formats and sizes, video lengths, static variants, and any creative production timelines for new assets
- **Geographic targeting**: Markets, regions, DMAs, or countries to target with any geo-specific budget weighting
- **Competitive spending intelligence**: Known or estimated competitor ad spend, share of voice benchmarks, and auction pressure indicators
- **Historical performance by channel**: Past campaign data — CPC, CPM, CPA, ROAS, conversion rates — by channel and audience segment
- **Seasonality factors**: Demand fluctuations, industry events, holidays, promotional periods, or competitive surges that affect costs or performance

## Process

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.
2. **Assess channel-objective fit**: Evaluate each available channel against campaign objectives using reach capability, targeting precision, cost benchmarks, creative format support, and measurement reliability
3. **Allocate budget across channels**: Distribute budget using efficiency-weighted allocation — factor in historical performance, diminishing returns curves, minimum effective spend thresholds, and strategic importance per channel
4. **Design flight schedule**: Structure campaign timing as continuous, pulsing, or flighting based on objectives, seasonality, and budget — define weekly spend levels and heavy-up periods
5. **Build audience targeting matrix**: Map each audience segment to its optimal channel(s) with targeting parameters, expected reach, estimated frequency, and overlap management between platforms
6. **Plan creative rotation**: Schedule creative variants across channels with rotation frequency, fatigue thresholds (impressions or frequency caps), A/B test windows, and refresh dates for new assets
7. **Define measurement framework**: Establish KPIs per channel, tracking requirements (pixels, UTMs, offline conversion imports), attribution model, and reporting cadence
8. **Set contingency holdback**: Reserve 10-15% of budget as contingency for opportunistic scaling, underperformance reallocation, or emerging platform opportunities — define trigger criteria for deployment
9. **Create platform setup checklists**: Build channel-specific setup checklists covering account structure, campaign naming conventions, tracking implementation, audience uploads, and creative specs
10. **Model reach and frequency estimates**: Project total reach, average frequency, and effective frequency per channel and in aggregate — flag oversaturation or underspend risks
11. **Compile unified media plan calendar**: Assemble all components into a single calendar view showing budget pacing, creative rotation, audience activation, and measurement milestones week by week

## Ads inside AI answers (checked 2026-10-04)

Two surfaces need special handling in any plan. Full sourcing, tracking and feed detail live in `skills/paid-advertising/ads-in-ai-answers.md`; follow it rather than restating numbers from memory.

- **ChatGPT Ads: plan it as a test line, funded from the contingency reserve (step 8).**
  - Before any budget is committed, check two prerequisites:
    1. The Measurement Pixel **and** the server-side Conversions API are both live and deduplicated (pixel `event_id` = API `id`).
    2. The target countries have been confirmed inside the brand's own Ads Manager.
  - The developer surface is primary-documented at [developers.openai.com/ads](https://developers.openai.com/ads). Launch dates and country rollout are secondary-sourced; label them "reported, unverified" in the plan.
  - Custom Audiences are unavailable in the EEA and Switzerland, so EU/CH lines carry no audience tactics.
  - In the measurement framework (step 7), state the attribution window next to the line: the Reporting API default is 30-day click / 1-day view.
- **Google AI Mode: not a separate line item.**
  - Google reaches AI Mode inventory through **AI Max for Search, AI Max for Shopping, and Performance Max** ([blog.google](https://blog.google/products/ads-commerce/google-marketing-live-search-ads/), 20 May 2026).
  - Budget it inside those lines, and say in the plan that no AI-Mode-specific reporting is documented.
  - Do not schedule Business Agent for leads ("coming months") or Direct Offers upgrades ("coming soon") as live flights until the account shows them.

## Output

A structured paid media plan containing:

- **Channel allocation table**: Budget amount, percentage share, and strategic rationale for each channel with minimum and maximum spend guardrails
- **Flight schedule with weekly budget waves**: Week-by-week spend plan showing ramp-up, steady state, heavy-up, and wind-down phases per channel
- **Audience targeting matrix**: Segment-by-channel-by-creative mapping showing targeting parameters, expected reach, frequency caps, and overlap management
- **Creative rotation calendar**: Asset schedule per channel with rotation dates, fatigue thresholds, A/B test windows, and refresh milestones for new creative
- **Reach and frequency estimates**: Projected reach, average frequency, and effective frequency per channel and in aggregate with confidence ranges
- **Measurement framework**: KPIs per channel, tracking requirements, attribution model, reporting cadence, and data integration points
- **Platform setup checklists**: Channel-specific implementation checklists covering account structure, naming conventions, tracking, audiences, and creative specs
- **Contingency budget plan**: Reserve amount, deployment trigger criteria (over/underperformance thresholds), and reallocation decision framework
- **Competitive spending comparison**: Estimated share of voice, auction overlap indicators, and competitive pressure assessment by channel
- **Daily/weekly pacing targets**: Spend and performance pacing benchmarks for in-flight monitoring with acceptable variance thresholds
- **Cross-channel synergy map**: Retargeting flows between channels, sequential messaging paths, and audience progression logic from awareness to conversion
- **Risk scenarios with budget reallocation triggers**: Defined scenarios (platform outage, CPM spikes, underperformance, budget cuts) with pre-approved reallocation responses

## Before it goes to the client

Run the zero-context review in `/digital-marketing-pro:check` (`--goldfish`). `goldfish-review.py` packs the deliverable, the brief and the brand profile into one file and nothing else, flags money figures and benchmark rates that nothing in the brief or profile supports, and writes the prompt for a reviewer that sees only that file. Answer each finding in the document itself (state the assumption for the client to confirm, cite the source, or cut the figure) before it is sent.

## Agents Used

- **media-buyer** — Channel allocation, budget pacing, auction dynamics, platform setup, reach/frequency modeling, competitive spending analysis, and creative rotation planning
- **marketing-strategist** — Objective-channel alignment, audience strategy, cross-channel synergy design, contingency planning, and measurement framework architecture

From indranilbanerjee/digital-marketing-pro, MIT.

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Last commit (this folder)
Oct 9, 2026 (21 days ago)
Last release
Jul 29, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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media-plan skill. Agent Mart. https://agentmart.dev/skills/indranilbanerjee-media-plan (last updated 2026-10-24)