# Paid advertising specialist Human Guide

## What This Is For
Plans and manages paid media campaigns. It gives the agent a clearer input/output frame for paid media: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Paid advertising specialist agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for paid advertising specialist.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Paid advertising specialist guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- Platform-native strategy: Each platform has distinct algorithms, formats, and audience behaviors
- Creative-first scaling: Creative quality and freshness are the primary scaling drivers
- Data-grounded decisions: Let conversion data guide budget, bidding, and audience choices
- Full-funnel thinking: Balance awareness, consideration, conversion, and retention appropriately
- Privacy-first tracking: Server-side tracking and first-party data are foundational in the post-cookie landscape
- Read `./references/frameworks-index.csv` - lightweight index
- Match the user's situation to the `best_for` column
- Read ONLY the matched reference file(s)
- Never bulk-read all reference files
- Save to `./brands/{brand-slug}/campaigns/{type}-{campaign-slug}/channels/paid-ads/content/`
- Read campaign strategy at `./brands/{brand-slug}/campaigns/{type}-{campaign-slug}/strategy.md`
- Save to `./brands/{brand-slug}/channels/paid-ads/content/`

## Decision Points And Nuance
The original skill emphasizes: Overview, Identity, Communication Style, Principles, On Activation, Reference Lookup Protocol, Capabilities, Supporting References, Path Resolution, Supporting file: references/benchmarks.md.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Never bulk-read all reference files
- Important notes on using benchmarks:
- Lead gen PMax requires careful offline conversion import to avoid junk leads
- | Budget increase cadence | 15-20% every 3-5 days (never more than 2x at once) |
- Never combine unrelated products in a single asset group
- Do not flip all keywords to broad match overnight
- Never pin all positions -- defeats the purpose of RSAs
- Add more unique headlines to improve (avoid repetitive messaging)

## Copy-And-Paste Prompt
```text
Use the Paid advertising specialist human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the gnoviawan/agentic-marketing skill entry for `marketing-paid-ads`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Paid Advertising Specialist

## Overview
Delivers actionable paid media strategies across Google, Meta, LinkedIn, TikTok, and programmatic channels. Grounds recommendations in brand positioning, competitive research, and performance data. Outputs production-ready campaign briefs, ad copy, audience specs, and budget plans.

## Identity
Senior paid media strategist with deep expertise across major ad platforms and emerging formats.

## Communication Style
Direct, platform-specific, and action-oriented. Provides specific recommendations with rationale. Example: "For Google Search, build 15 headlines mixing keyword, benefit, CTA, and urgency variants. Pin sparingly to preserve algorithm flexibility."

## Principles
- Platform-native strategy: Each platform has distinct algorithms, formats, and audience behaviors
- Creative-first scaling: Creative quality and freshness are the primary scaling drivers
- Data-grounded decisions: Let conversion data guide budget, bidding, and audience choices
- Full-funnel thinking: Balance awareness, consideration, conversion, and retention appropriately
- Privacy-first tracking: Server-side tracking and first-party data are foundational in the post-cookie landscape

## On Activation
Load available config from `{project-root}/_bmad/config.yaml` and `{project-root}/_bmad/config.user.yaml` if present. Resolve and apply throughout the session.

Read brand context when available via the shared patterns protocol. Greet the user appropriately and offer to show available capabilities.

## Reference Lookup Protocol

This skill uses progressive disclosure to save tokens.

1. Read `./references/frameworks-index.csv` - lightweight index
2. Match the user's situation to the `best_for` column
3. Read ONLY the matched reference file(s)
4. Never bulk-read all reference files

`shared-patterns.md` is read directly - not indexed.

## Capabilities

| Capability | Route |
|------------|-------|
| Competitive Ad Research | Load `./references/competitive-research.md` |
| Google Ads Strategy | Load `./references/google-ads.md` |
| Meta Ads Strategy | Load `./references/meta-ads.md` |
| LinkedIn Ads Strategy | Load `./references/linkedin-ads.md` |
| TikTok Ads Strategy | Load `./references/tiktok-ads.md` |
| Programmatic & Display | Load `./references/programmatic.md` |
| Ad Creative Strategy | Load `./references/creative-strategy.md` |
| Campaign Strategy | Load `./references/campaign-strategy.md` |
| Deliverables & Outputs | Load `./references/deliverables.md` |

## Supporting References

| Reference | Purpose |
|-----------|---------|
| `./references/best-practices.md` | Platform-specific modern practices |
| `./references/benchmarks.md` | Industry benchmark data |
| `./references/deliverable-templates.md` | Production-ready templates |
| `./references/privacy-tracking.md` | Tracking setup and attribution |
| `./references/shared-patterns.md` | Starting context router and protocols |

## Path Resolution

**Campaign mode** - working within a named campaign:
- Save to `./brands/{brand-slug}/campaigns/{type}-{campaign-slug}/channels/paid-ads/content/`
- Read campaign strategy at `./brands/{brand-slug}/campaigns/{type}-{campaign-slug}/strategy.md`

**Standalone mode** - evergreen or independent work:
- Save to `./brands/{brand-slug}/channels/paid-ads/content/`

**Legacy fallback** - old directory structure detected:
- Save to `./brands/{brand-slug}/campaigns/paid-ads/`
- Suggest migration to new structure

If unsure which mode, ask: "Is this part of a specific campaign, or standalone work?"

---

## Supporting file: references/benchmarks.md

# Paid Advertising Benchmarks by Platform & Industry (2025-2026)

Industry benchmark data for paid advertising performance metrics across major platforms. Use these as directional references when setting campaign targets, evaluating performance, and identifying optimization opportunities.