# Paid Search

> Plan or diagnose paid-search campaigns with intent segmentation, current match behavior, bidding, creative, landing-page alignment, tracking, and test controls. Use when launching or restructuring search advertising and when spend must be tied to measurable acquisition outcomes.

- Skill: `majesticlabs-dev/paid-search` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majesticlabs-dev/paid-search`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majesticlabs-dev/paid-search/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: majesticlabs-dev (https://skillmd.com/u/majesticlabs-dev)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/majesticlabs-dev/paid-search

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# Paid Search

## Boundary

Create a strategy, not a platform guarantee. Verify current product behavior and policies before giving platform-specific instructions. Do not invent benchmarks, competitor claims, or expected returns.

## Required Inputs

- Business model, offer, audience, geography, and acquisition goal
- Budget, margin, conversion value, sales cycle, and risk tolerance
- Existing account, query, creative, landing-page, and conversion data
- Current official platform documentation and policy constraints

## Workflow

1. Verify current campaign types, match behavior, bidding, measurement, and policy rules.
2. Audit conversion definitions, attribution, consent, and tag quality before optimizing bids.
3. Segment campaigns by intent, economics, geography, and landing-page promise.
4. Build keyword and negative-keyword hypotheses from real queries and buyer language.
5. Choose exact, phrase, broad, or keywordless reach based on control, data, and automation readiness.
6. Create evidence-safe ads and message-matched landing-page requirements.
7. Choose bidding from data volume and business value, then define budget guardrails.
8. Set search-term, creative, landing-page, and incrementality review cadence.

## Output

1. **Verification date and platform assumptions**
2. **Campaign and intent architecture**
3. **Keyword, negative, audience, and creative plan**
4. **Bidding, budget, tracking, and guardrails**
5. **Experiment and optimization backlog**

## Quality Gate

- Official current docs support platform-specific claims.
- Primary conversions represent business value.
- Benchmarks are sourced, dated context only.
- Automation has measurement and spend safeguards.

## Reference

Read [current-platform-checks.md](references/current-platform-checks.md) before implementation.