interface:
  display_name: "Suede Paid Ads"
  short_description: "Run paid acquisition that pays back"
  default_prompt: "Use $suede-ads on [target]. The user is planning, running, or fixing paid campaigns on Google, Meta, LinkedIn, or X, or weighing whether to run ads at all. Work through campaign structure, audience targeting, bidding, budget pacing, negative keywords, and knowing when to kill an ad, ground every recommendation in evidence the user can check, and return the decisions, the reasoning, and what to measure next."
policy:
  allow_implicit_invocation: true

{
  "skill_name": "suede-ads",
  "evals": [
    {
      "id": 1,
      "prompt": "Help me plan a paid advertising strategy. We're a B2B SaaS tool for HR teams, selling at $99/month per seat. We have $15k/month to spend on ads and want to generate demo requests. Where should we advertise?",
      "expected_output": "Should check for product-marketing.md first. Should apply the platform selection guide based on B2B, HR audience, $99/month price point. Should recommend LinkedIn (B2B targeting by job title/industry), Google Ads (search intent for HR software keywords), and potentially Meta (retargeting). Should recommend campaign structure with naming conventions. Should define audience targeting strategy for each platform. Should set budget allocation across platforms. Should define success metrics and attribution approach. Should recommend starting structure and scaling plan.",
      "assertions": [
        "Checks for product-marketing.md",
        "Applies platform selection guide",
        "Recommends platforms appropriate for B2B HR audience",
        "Recommends campaign structure with naming conventions",
        "Defines audience targeting per platform",
        "Sets budget allocation across platforms",
        "Defines success metrics",
        "Recommends starting structure and scaling plan"
      ],
      "files": []
    },
    {
      "id": 2,
      "prompt": "Our Google Ads CPC is $12 and our cost per lead is $180. Is that good? We're getting about 80 leads/month from a $15k budget.",
      "expected_output": "Should evaluate the metrics in context. Should assess: $12 CPC for B2B (reasonable depending on industry), $180 CPL (depends on LTV — need to compare against customer lifetime value), 80 leads/month from $15k (math checks out). Should apply the campaign optimization framework: check quality score, search term relevance, landing page conversion rate, negative keywords. Should recommend specific optimization levers to reduce CPC and CPL. Should frame performance against industry benchmarks if applicable. Should ask about downstream conversion rates (lead → demo → customer).",
      "assertions": [
        "Evaluates metrics in context",
        "Compares CPL against LTV considerations",
        "Applies campaign optimization framework",
        "Recommends specific optimization levers",
        "Asks about downstream conversion rates",
        "Provides industry context for benchmarking"
      ],
      "files": []
    },
    {
      "id": 3,
      "prompt": "we want to run retargeting ads for people who visited our site but didn't convert. how should we set this up?",
      "expected_output": "Should trigger on casual phrasing. Should apply the retargeting strategies section, specifically the funnel-based approach. Should recommend audience segments: all visitors (broad), pricing page visitors (high intent), blog readers (lower intent), and cart/signup abandoners (highest intent). Should recommend different messaging and offers for each segment. Should address frequency capping to avoid ad fatigue. Should recommend retargeting platforms (Meta, Google Display, LinkedIn). Should include duration windows for each audience.",
      "assertions": [
        "Triggers on casual phrasing",
        "Applies funnel-based retargeting approach",
        "Recommends audience segments by intent level",
        "Recommends different messaging per segment",
        "Addresses frequency capping",
        "Recommends retargeting platforms",
        "Includes audience duration windows"
      ],
      "files": []
    },
    {
      "id": 4,
      "prompt": "Should we advertise on TikTok? We sell accounting software to small businesses. Our current ads are on Google and Meta.",
      "expected_output": "Should apply the platform selection guide for TikTok specifically. Should evaluate TikTok fit for accounting software + small business audience: likely a weaker fit than Google/Meta for this category (lower purchase intent, younger skewing audience, less B2B targeting). Should discuss when TikTok CAN work for B2B (brand awareness, creative content, younger business owners). Should provide an honest recommendation with caveats. Should suggest a small test budget approach if they want to try.",
      "assertions": [
        "Applies platform selection guide for TikTok",
        "Evaluates fit for accounting + small business audience",
        "Provides honest assessment of likely weaker fit",
        "Discusses when TikTok can work for B2B",
        "Suggests small test budget if proceeding",
        "Compares to their existing Google/Meta performance"
      ],
      "files": []
    },
    {
      "id": 5,
      "prompt": "How do we structure our Google Ads campaigns? We have 50+ keywords we want to target for our CRM product.",
      "expected_output": "Should apply the campaign structure and naming conventions framework. Should recommend organizing campaigns by theme/intent (brand, competitor, product features, pain points). Should recommend ad group structure (tightly themed, 5-15 keywords per group). Should define naming conventions for campaigns and ad groups. Should recommend match types strategy. Should include negative keyword lists. Should provide a sample campaign structure.",
      "assertions": [
        "Applies campaign structure framework",
        "Organizes campaigns by theme/intent",
        "Recommends tight ad group structure",
        "Defines naming conventions",
        "Recommends match types strategy",
        "Includes negative keyword lists",
        "Provides sample campaign structure"
      ],
      "files": []
    },
    {
      "id": 6,
      "prompt": "Can you write some ad copy for our Facebook ads? We need headlines and descriptions for 5 different angles.",
      "expected_output": "Should recognize this is an ad creative generation task, not campaign strategy. Should defer to or cross-reference suede-ad-creative, which handles platform-specific ad copy generation with character limits, angle-based variation, and batch generation. May provide brief ad copy framework guidance but should make clear that suede-ad-creative is the right skill for generating ad copy at scale.",
      "assertions": [
        "Recognizes this as ad creative generation",
        "References or defers to suede-ad-creative",
        "Does not attempt bulk ad copy generation using campaign strategy patterns"
      ],
      "files": []
    }
  ]
}

# ABM Playbook (Paid)

Account-based marketing with ads: targeting named accounts on LinkedIn and Meta, accelerating open pipeline, and stitching channels together. ABM ads are a *pipeline influence* motion, not a lead-gen motion — measure accordingly.

## Contents

- When ABM (go/no-go)
- LinkedIn ABM
- ABM on Meta
- Acceleration campaigns (ads against open pipeline)
- Cross-channel orchestration
- Cross-channel UTM remarketing
- Sales orchestration
- Measuring ABM

## When ABM (go/no-go)

Run paid ABM when: target account list ≥ ~1,000 companies (or you accept 1:1/1:few economics), deal size ~$25K+, sales cycle 60+ days, sales and marketing actually aligned on the list, and (for Meta) contact enrichment available.

Skip it when: TAL under ~500 with no enrichment, no first-party data, budget under ~$3K/month, or a short transactional cycle — standard ICP targeting will outperform.

## LinkedIn ABM

Three motions, by list size:

- **1:1** — add the company by name; fully personalized creative for one account.
- **1:few** — up to ~10–20 accounts per campaign, shared pain/industry angle.
- **1:many** — uploaded list (or native targeting), scaled creative.

**List mechanics:**
- LinkedIn needs **300 matched members minimum** to serve; aim for 1,000+ rows (duplicating company names to pad the upload is fine — it dedupes on match). Contact lists match best at scale (LinkedIn suggests ~10K emails); **company lists beat contact lists** for most teams — easier to source, better match rates, less maintenance.
- Cold ABM audiences need ~15K members to deliver reliably.
- **Segment mixed lists.** Left as one audience, LinkedIn over-serves the largest enterprises in the list — accounts have sat at 15% list coverage because the algorithm parked on a few big companies. Split into homogeneous bands (e.g., enterprise / mid-market / SMB) with separate campaigns and budgets.
- List-based targeting typically buys reach materially cheaper than native firmographic targeting, with stronger decision-maker engagement.
- Use the per-company engagement report (Audiences → click into the list) to find under-served priority accounts, then break them into a dedicated campaign.

**Personalized 1:1 creative:** putting the target account's name/logo in the creative can lift CTR ~5–10× over generic ads. **Legal exception: do not run company-name/logo-personalized ads into Germany** — privacy law, not platform policy.

**Frequency capping:** target ~3 impressions/person/week in priority accounts. Mechanic: build a company-engagement audience of accounts that crossed ~500 impressions in the last 7 days and add it as an *exclusion* — it self-rotates accounts out as they cool down. Tune the threshold (300 if fatigue shows, 750 for more pressure).

## ABM on Meta

Meta has no native company targeting — the play is **bring your own matched audience**:

- **The match-rate problem:** raw CRM exports of work emails match under ~5% on Meta. Enrichment providers (identity-graph tools that resolve work identities to personal profiles — e.g., Primer, Metadata, ZoomInfo, Clearbit) raise matches to ~40–85%. Workflow: firmographic criteria → identity-graph match → upload as Custom Audience → target directly or seed a 1% lookalike.
- **Minimum sizes:** account-list audiences ~1,000 companies (5–10K optimal); retargeting slices work down to ~100 accounts; lookalike seeds want 500+.
- Advantage+ **conflicts with strict ABM** — it won't stay locked to your list. Run ABM campaigns manual (or hybrid: manual for the list, Advantage+ for the broad layer).
- Meta's ABM role is cheap **air cover and multi-threading** (reaching the buying committee beyond your champion) while LinkedIn does precision — see the split below.

## Acceleration campaigns (ads against open pipeline)

Ads aimed at accounts already in your pipeline, to speed deals rather than source them:

- Segment the CRM by stage (evaluation / proposal / negotiation), filter to deals worth the spend, upload as an audience, refresh weekly.
- **Use an awareness/reach objective, not conversions** — you're keeping the vendor top-of-mind for the buying committee, not asking in-pipeline accounts to "book a demo" they already booked.
- Creative: case studies, proof, objection-handlers — matched to stage. Budget scales with deal value (larger open deals justify $100–200/day of air cover; stalled deals get a maintenance dose).

## Cross-channel orchestration

Default split for B2B ABM: **~60% LinkedIn / ~30% Meta / ~10% other**. LinkedIn buys precision (right person, right company) at $40–70 CPMs; Meta buys presence and committee reach at $10–25. Sequence LinkedIn first to validate the audience, then extend to Meta. Multi-channel ABM consistently and materially outperforms single-channel on engagement and conversion — the channels compound, they don't compete.

## Cross-channel UTM remarketing

The cheapest high-quality audience you can build: retarget one platform's validated clickers on another platform.

1. Tag all paid traffic with consistent UTMs (`utm_source=linkedin`, `utm_source=google&utm_medium=cpc`).
2. On Meta, build a website Custom Audience with the rule **"URL contains `utm_source=linkedin`"** (or `utm_source=google`).
3. Retarget that audience on Meta — LinkedIn-grade audience quality at Meta-grade CPMs (typically 50–70% cheaper reach).

Works in both directions (search clickers → LinkedIn remarketing needs meaningful search volume — worth it above roughly $30K/month search spend). Requires enough source-channel traffic to clear minimum audience sizes. Use a consistent account/campaign token in UTMs so attribution survives the hop.

## Sales orchestration

ABM ads without sales follow-up is billboard spend:

- Pipe ad-engagement signals to the CRM (LinkedIn company-engagement exports, or connectors that sync engagement per account) and treat an engagement spike as a sales trigger — **outreach within ~48 hours** of the spike.
- Route new leads to a shared channel (Slack webhook) with a per-campaign quality reaction (👍/👎) — the cheapest lead-quality feedback loop that exists.
- Hold a monthly sales-marketing session on the list itself: who's engaging, who's dark, who closed — and re-cut the list.
- Expect ~7–10 cross-channel touches before a sales conversation is normal at ABM deal sizes.

## Measuring ABM

Judge ABM on account movement, not CPL:

- **Account penetration** (% of list reached): target ~40–60%.
- **Cost per engaged account** (not per click): ~$100–300 is a workable band.
- **Account → opportunity rate:** ~10–20%.
- **Pipeline influenced:** aim for 3–5× spend; expect win-rate and velocity improvements on engaged vs. non-engaged accounts.
- **Incrementality:** hold out ~20% of the list from ads and compare pipeline formation after 21+ days — the only honest answer to "did the ads do anything?"

---

*Framework lineage: adapted (re-expressed and restructured) from practitioner playbooks, notably Ivan Falco's ads-skills. Thresholds are practitioner-reported starting points — recalibrate against your own accounts.*

# Ad Copy Templates Reference

Detailed formulas and templates for writing high-converting ad copy.

## Contents
- Primary Text Formulas (Problem-Agitate-Solve, Before-After-Bridge, Social Proof Lead, Feature-Benefit Bridge, Direct Response)
- Headline Formulas (For Search Ads, For Social Ads)
- CTA Variations (Soft CTAs, Hard CTAs, Urgency CTAs, Action-Oriented CTAs)
- Platform-Specific Copy Guidelines (Google Search Ads, Meta Ads, LinkedIn Ads)
- Copy Testing Priority

## Primary Text Formulas

### Problem-Agitate-Solve (PAS)

```
[Problem statement]
[Agitate the pain]
[Introduce solution]
[CTA]
```

**Example:**
> Spending hours on manual reporting every week?
> While you're buried in spreadsheets, your competitors are making decisions.
> [Product] automates your reports in minutes.
> Start your free trial →

---

### Before-After-Bridge (BAB)

```
[Current painful state]
[Desired future state]
[Your product as the bridge]
```

**Example:**
> Before: Chasing down approvals across email, Slack, and spreadsheets.
> After: Every approval tracked, automated, and on time.
> [Product] connects your tools and keeps projects moving.

---

### Social Proof Lead

```
[Impressive stat or testimonial]
[What you do]
[CTA]
```

**Example:**
> "We cut our reporting time by 75%." — Sarah K., Marketing Director
> [Product] automates the reports you hate building.
> See how it works →

---

### Feature-Benefit Bridge

```
[Feature]
[So that...]
[Which means...]
```

**Example:**
> Real-time collaboration on documents
> So your team always works from the latest version
> Which means no more version confusion or lost work

---

### Direct Response

```
[Bold claim/outcome]
[Proof point]
[CTA with urgency if genuine]
```

**Example:**
> Cut your reporting time by 80%
> Join 5,000+ marketing teams already using [Product]
> Start free → First month 50% off

---

## Headline Formulas

### For Search Ads

| Formula | Example |
|---------|---------|
| [Keyword] + [Benefit] | "Project Management That Teams Actually Use" |
| [Action] + [Outcome] | "Automate Reports \| Save 10 Hours Weekly" |
| [Question] | "Tired of Manual Data Entry?" |
| [Number] + [Benefit] | "500+ Teams Trust [Product] for [Outcome]" |
| [Keyword] + [Differentiator] | "CRM Built for Small Teams" |
| [Price/Offer] + [Keyword] | "Free Project Management \| No Credit Card" |

### For Social Ads

| Type | Example |
|------|---------|
| Outcome hook | "How we 3x'd our conversion rate" |
| Curiosity hook | "The reporting hack no one talks about" |
| Contrarian hook | "Why we stopped using [common tool]" |
| Specificity hook | "The exact template we use for..." |
| Question hook | "What if you could cut your admin time in half?" |
| Number hook | "7 ways to improve your workflow today" |
| Story hook | "We almost gave up. Then we found..." |

---

## CTA Variations

### Soft CTAs (awareness/consideration)

Best for: Top of funnel, cold audiences, complex products

- Learn More
- See How It Works
- Watch Demo
- Get the Guide
- Explore Features
- See Examples
- Read the Case Study

### Hard CTAs (conversion)

Best for: Bottom of funnel, warm audiences, clear offers

- Start Free Trial
- Get Started Free
- Book a Demo
- Claim Your Discount
- Buy Now
- Sign Up Free
- Get Instant Access

### Urgency CTAs (use when genuine)

Best for: Limited-time offers, scarcity situations

- Limited Time: 30% Off
- Offer Ends [Date]
- Only X Spots Left
- Last Chance
- Early Bird Pricing Ends Soon

### Action-Oriented CTAs

Best for: Active voice, clear next step

- Start Saving Time Today
- Get Your Free Report
- See Your Score
- Calculate Your ROI
- Build Your First Project

---

## Platform-Specific Copy Guidelines

### Google Search Ads

- **Headline limits:** 30 characters each (up to 15 headlines)
- **Description limits:** 90 characters each (up to 4 descriptions)
- Include keywords naturally
- Use all available headline slots
- Include numbers and stats when possible
- Test dynamic keyword insertion

### Meta Ads (Facebook/Instagram)

- **Primary text:** 125 characters visible (can be longer, gets truncated)
- **Headline:** 40 characters recommended
- Front-load the hook (first line matters most)
- Emojis can work but test
- Questions perform well
- Keep image text under 20%

### LinkedIn Ads

- **Intro text:** 600 characters max (150 recommended)
- **Headline:** 200 characters max (70 recommended)
- Professional tone (but not boring)
- Specific job outcomes resonate
- Stats and social proof important
- Avoid consumer-style hype

---

## Copy Testing Priority

When testing ad copy, focus on these elements in order of impact:

1. **Hook/angle** (biggest impact on performance)
2. **Headline**
3. **Primary benefit**
4. **CTA**
5. **Supporting proof points**

Test one element at a time for clean data.

# Audience Targeting Reference

Detailed targeting strategies for each major ad platform.

## Contents
- Google Ads Audiences (Search Campaign Targeting, Display/YouTube Targeting)
- Meta Audiences (Core Audiences, Custom Audiences, Lookalike Audiences)
- LinkedIn Audiences (Job-Based Targeting, Company-Based Targeting, High-Performing Combinations)
- Twitter/X Audiences
- TikTok Audiences
- Audience Size Guidelines
- Exclusion Strategy

## Google Ads Audiences

### Search Campaign Targeting

**Keywords:**
- Exact match: [keyword] — most precise, lower volume
- Phrase match: "keyword" — moderate precision and volume
- Broad match: keyword — highest volume, use with smart bidding

**Audience layering:**
- Add audiences in "observation" mode first
- Analyze performance by audience
- Switch to "targeting" mode for high performers

**RLSA (Remarketing Lists for Search Ads):**
- Bid higher on past visitors searching your terms
- Show different ads to returning searchers
- Exclude converters from prospecting campaigns

### Display/YouTube Targeting

**Custom intent audiences:**
- Based on recent search behavior
- Create from your converting keywords
- High intent, good for prospecting

**In-market audiences:**
- People actively researching solutions
- Pre-built by Google
- Layer with demographics for precision

**Affinity audiences:**
- Based on interests and habits
- Better for awareness
- Broad but can exclude irrelevant

**Customer match:**
- Upload email lists
- Retarget existing customers
- Create lookalikes from best customers

**Similar/lookalike audiences:**
- Based on your customer match lists
- Expand reach while maintaining relevance
- Best when source list is high-quality customers

---

## Meta Audiences

### Core Audiences (Interest/Demographic)

**Interest targeting tips:**
- Layer interests with AND logic for precision
- Use Audience Insights to research interests
- Start broad, let algorithm optimize
- Exclude existing customers always

**Demographic targeting:**
- Age and gender (if product-specific)
- Location (down to zip/postal code)
- Language
- Education and work (limited data now)

**Behavior targeting:**
- Purchase behavior
- Device usage
- Travel patterns
- Life events

### Custom Audiences

**Website visitors:**
- All visitors (last 180 days max)
- Specific page visitors
- Time on site thresholds
- Frequency (visited X times)

**Customer list:**
- Upload emails/phone numbers
- Match rate typically 30-70%
- Refresh regularly for accuracy

**Engagement audiences:**
- Video viewers (25%, 50%, 75%, 95%)
- Page/profile engagers
- Form openers
- Instagram engagers

**App activity:**
- App installers
- In-app events
- Purchase events

### Lookalike Audiences

**Source audience quality matters:**
- Use high-LTV customers, not all customers
- Purchasers > leads > all visitors
- Minimum 100 source users, ideally 1,000+

**Size recommendations:**
- 1% — most similar, smallest reach
- 1-3% — good balance for most
- 3-5% — broader, good for scale
- 5-10% — very broad, awareness only

**Layering strategies:**
- Lookalike + interest = more precision early
- Test lookalike-only as you scale
- Exclude the source audience

---

## LinkedIn Audiences

### Job-Based Targeting

**Job titles:**
- Be specific (CMO vs. "Marketing")
- LinkedIn normalizes titles, but verify
- Stack related titles
- Exclude irrelevant titles

**Job functions:**
- Broader than titles
- Combine with seniority level
- Good for awareness campaigns

**Seniority levels:**
- Entry, Senior, Manager, Director, VP, CXO, Partner
- Layer with function for precision

**Skills:**
- Self-reported, less reliable
- Good for technical roles
- Use as expansion layer

### Company-Based Targeting

**Company size:**
- 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5000+
- Key filter for B2B

**Industry:**
- Based on company classification
- Can be broad, layer with other criteria

**Company names (ABM):**
- Upload target account list
- Minimum 300 companies recommended
- Match rate varies

**Company growth rate:**
- Hiring rapidly = budget available
- Good signal for timing

### High-Performing Combinations

| Use Case | Targeting Combination |
|----------|----------------------|
| Enterprise sales | Company size 1000+ + VP/CXO + Industry |
| SMB sales | Company size 11-200 + Manager/Director + Function |
| Developer tools | Skills + Job function + Company type |
| ABM campaigns | Company list + Decision-maker titles |
| Broad awareness | Industry + Seniority + Geography |

---

## Twitter/X Audiences

### Targeting options:
- Follower lookalikes (accounts similar to followers of X)
- Interest categories
- Keywords (in tweets)
- Conversation topics
- Events
- Tailored audiences (your lists)

### Best practices:
- Follower lookalikes of relevant accounts work well
- Keyword targeting catches active conversations
- Lower CPMs than LinkedIn/Meta
- Less precise, better for awareness

---

## TikTok Audiences

### Targeting options:
- Demographics (age, gender, location)
- Interests (TikTok's categories)
- Behaviors (video interactions)
- Device (iOS/Android, connection type)
- Custom audiences (pixel, customer file)
- Lookalike audiences

### Best practices:
- Younger skew (18-34 primarily)
- Interest targeting is broad
- Creative matters more than targeting
- Let algorithm optimize with broad targeting

---

## Audience Size Guidelines

| Platform | Minimum Recommended | Ideal Range |
|----------|-------------------|-------------|
| Google Search | 1,000+ searches/mo | 5,000-50,000 |
| Google Display | 100,000+ | 500K-5M |
| Meta | 100,000+ | 500K-10M |
| LinkedIn | 50,000+ | 100K-500K |
| Twitter/X | 50,000+ | 100K-1M |
| TikTok | 100,000+ | 1M+ |

Too narrow = expensive, slow learning
Too broad = wasted spend, poor relevance

---

## Exclusion Strategy

Always exclude:
- Existing customers (unless upsell)
- Recent converters (7-14 days)
- Bounced visitors (<10 sec)
- Employees (by company or email list)
- Irrelevant page visitors (careers, support)
- Competitors (if identifiable)

# B2B Paid Playbook

Cross-platform operating rules for B2B paid acquisition — where sales cycles run 2–24 months, in-platform conversions mislead, and lead *quality* matters more than lead cost. Use this alongside the platform playbooks ([Meta decision system](meta-decision-system.md), [LinkedIn](linkedin-b2b-playbook.md), [Google Search](google-search-playbook.md), [ABM](abm-playbook.md)).

## Contents

- The Demand Lifecycle (5 stages, past the funnel)
- Budget by stage
- Leading vs. lagging signals
- Unit economics: breakeven CPL and CPC
- Kill rules
- The optimize-to-quality trap (and the offline conversion loop)
- Lead quality scoring (Urgency / Budget / Fit)
- The scaling quadrant
- Measurement maturity check
- Channel selection

## The Demand Lifecycle (5 stages, past the funnel)

TOFU/MOFU/BOFU stops at conversion. B2B revenue doesn't — closed-lost deals, open pipeline, and existing customers are all addressable with ads. Plan across five stages:

| Stage | Outcome | Buyer awareness | Typical offers | KPIs |
|-------|---------|-----------------|----------------|------|
| **Create** | Build affinity & trust | Unaware / Problem-aware | Educational content, POV | Cost per consumption, blended cost/opp |
| **Capture** | Convert in-market buyers | Solution / Product-aware | Demos, trials | Pipe-to-spend, direct cost/opp |
| **Accelerate** (sales-led) / **Activate** (product-led) | Close open deals faster / convert free users | Product / Offer-aware | Case studies, webinars, events | Pipeline velocity, paid signups |
| **Revive** | Restart closed-lost | Offer-aware | Incentivized demos, guided trials | SQOs created, cost/SQO |
| **Expand** | Grow existing accounts | Most aware | Referral programs, new-feature content | Expansion revenue, influenced SQOs |

**Build bottom-up for fastest ROI**: Expand → Revive → Accelerate/Activate → Capture → Create. The bottom stages are cheap, small-audience, and quick to pay back; Create is the biggest and slowest investment. Most teams build top-down and burn months waiting for ROI.

## Budget by stage

| Stage | Budget size | Time to ROI | Difficulty |
|-------|------------|-------------|------------|
| Create | High | 90+ days | High (needs strong content + POV) |
| Capture | Moderate | <45 days | High (expensive, competitive) |
| Accelerate/Activate | Low | Tracks sales cycle | Low |
| Revive | Low | <45 days | Low |
| Expand | Low | <60 days | Medium (small audiences) |

Weight by motion: product-led skews budget to Create + Capture; sales-led with a small TAM skews to Create + Accelerate. The stage with the most *pipeline* isn't automatically the stage that deserves the most *budget* — fund where pipeline share exceeds budget share and the audience is under-penetrated.

## Leading vs. lagging signals

You can't optimize on closed-won when deals close in 6 months. Split every stage's metrics:

- **Leading** (moves in <1 month — optimize on these): CTR, engagement, CPL, cost per qualified lead, accounts reached
- **Lagging** (moves in >1 month — the truth, reviewed monthly/quarterly): pipe-to-spend, influenced revenue, time-to-close, expansion revenue

The leading metric must demonstrably correlate with the lagging one — a proxy metric worth optimizing is measurable, moveable, not an average, and hard to game. If CPL falls while pipeline doesn't move, the proxy broke; fix the proxy, not the ads.

## Unit economics: breakeven CPL and CPC

Derive targets from deal math, not platform benchmarks:

- **Breakeven CPL** = average deal size × lead-to-close rate. ($3,000 ACV × 10% close = $300 CPL.)
- **Breakeven CPC** = target CPL × landing page conversion rate. ($300 CPL × 5% LP conversion = $15 CPC.)

Set the actual target below breakeven by your required margin. Every kill rule and scaling decision keys off this number.

## Kill rules

Two hard rules that remove emotion from pausing decisions:

- **Non-performer rule** (new ads, any time): pause once an ad has spent **2–3× target CPL with zero conversions**. Target CPL $300 → kill at $600–900 spent, no conversions.
- **Maintenance rule** (ads past ~7–14 days): pause when an ad's CPL runs **1.5–2× over target**. Target $300 → kill at $450–600 CPL.

These aren't statistically rigorous — they're repeatable, cheap to apply, and better than deciding by mood. Never pause a producer without a replacement staged (see the swap rules in the [Meta decision system](meta-decision-system.md)).

## The optimize-to-quality trap (and the offline conversion loop)

Smart bidding optimizes toward whatever you call a "conversion." Feed it raw form-fills and it will buy you cheap junk form-fills — CPL improves while pipeline dies. The fix, in order:

1. **Close the offline conversion loop.** Push CRM stage changes (MQL → SQL → opportunity → closed-won) back to the ad platforms — GCLID + offline import on Google, CAPI lifecycle events on Meta, conversion API on LinkedIn. This is the single highest-impact move in a B2B ad account: the algorithm starts buying pipeline instead of form-fills.
2. **Value conversions differently.** A demo request is not an ebook download.
3. **Until offline data flows, keep a human reading lead quality weekly** — job titles and companies, not just CPL.

Reconcile platform-reported conversions against the CRM monthly. When they disagree, **the CRM wins**.

## Lead quality scoring (Urgency / Budget / Fit)

The platform can't see lead quality — score it yourself and rank ads by it:

- **Urgency** (0–3): 0 browsing → 3 burning need with timeline
- **Budget** (0–3): 0 none/no authority → 3 approved and ready
- **Fit** (0–3): 0 not ICP → 3 perfect ICP

Whoever runs the sales calls scores each lead (max 9) and logs it against the originating ad. After ~20 scored calls, **rank ads by average quality score, not CPL or CTR** — the ad with the best CPL is regularly the one producing 3/9 leads. Scale the high-score ads; kill variations whose average drops below ~5.

## The scaling quadrant

Route scaling tactics by your actual constraint:

| | Low effort | High effort |
|---|---|---|
| **High budget** | **Audiences** — bigger audiences, more segments, more frequency | **Geography** — new countries/regions (localization work) |
| **Low budget** | **Ads** — new creative, angles, formats | **Objectives & bids** — change objective or bid strategy to buy cheaper |

- Have budget but no time → work the top row (audiences, then geo).
- Need scale but capped on budget → work the bottom row (better creative and cheaper bidding free up money).

## Measurement maturity check

Before scaling spend, score yourself 1–3 on each: blended pipeline dashboard; per-channel dashboard; conversion tracking (1 = none, 2 = pixel only, 3 = offline conversions flowing); web analytics; a documented, agreed attribution process. Under ~6/15, fix visibility before adding budget — you're flying blind and every optimization is a guess. Fix the lowest score first.

## Channel selection

Five channel families: paid social, paid search, **paid review listings** (G2, Capterra, Software Advice — often skipped, high intent), programmatic (display, audio, CTV, native), and sponsorships (newsletters, podcasts, events, creators). Evaluate on four axes: can you actually target your ICP; media cost (CPC/CPM); reach at your targeting; platform policy for your industry.

Before committing to a new channel, **run a ~$100 test campaign** to learn its real CPC/CPM for your targeting — platform estimates and published benchmarks are consistently wrong for specific ICPs.

---

*Framework lineage: several operating rules in this file are adapted (re-expressed, restructured, and extended) from practitioner playbooks, notably Ivan Falco's ads-skills. Benchmarks and thresholds are practitioner-reported starting points — always recalibrate against your own account's first 30 days.*

# Conversion Tracking Setup

How to set up conversion tracking pixels across ad platforms. This guide covers installation, event configuration, and validation — everything a marketer needs to ensure ad spend is properly attributed.

---

## Why This Matters

Without conversion tracking:
- Ad platforms can't optimize for your actual goals
- You're flying blind on ROAS and CPA
- Retargeting audiences can't be built
- You'll waste budget on impressions that don't convert

Get tracking right before spending a dollar on ads.

---

## Platform Pixels Overview

| Platform | Pixel/Tag Name | Events API | Key Events |
|----------|---------------|:----------:|------------|
| **Google Ads** | Google tag (gtag.js) | Enhanced Conversions | purchase, sign_up, generate_lead |
| **Meta** | Meta Pixel + CAPI | Conversions API | Purchase, Lead, ViewContent, AddToCart |
| **LinkedIn** | Insight Tag | Conversions API | conversion (URL or event-based) |
| **TikTok** | TikTok Pixel | Events API | Purchase, ViewContent, AddToCart, CompleteRegistration |
| **Twitter/X** | Twitter Pixel | - | Purchase, SignUp, Download |

---

## Google Ads

### Install the Google tag

Add to every page, in `<head>`:

```html
<script async src="https://www.googletagmanager.com/gtag/js?id=AW-XXXXXXXXX"></script>
<script>
  window.dataLayer = window.dataLayer || [];
  function gtag(){dataLayer.push(arguments);}
  gtag('js', new Date());
  gtag('config', 'AW-XXXXXXXXX');
</script>
```

Replace `AW-XXXXXXXXX` with your Conversion ID from Google Ads > Tools > Conversions.

### Set up conversion actions

In Google Ads > Goals > Conversions > New conversion action:

| Conversion | Category | Value | Count |
|-----------|----------|-------|-------|
| Purchase | Purchase | Dynamic (order value) | Every |
| Sign up / Lead | Sign-up | Fixed ($X estimated value) | One |
| Demo request | Lead | Fixed ($X estimated value) | One |
| Free trial start | Sign-up | Fixed ($X estimated value) | One |

### Fire conversion events

```javascript
// Purchase
gtag('event', 'conversion', {
  'send_to': 'AW-XXXXXXXXX/CONVERSION_LABEL',
  'value': 99.00,
  'currency': 'USD',
  'transaction_id': 'ORDER-123'
});

// Lead / Sign up
gtag('event', 'conversion', {
  'send_to': 'AW-XXXXXXXXX/CONVERSION_LABEL',
  'value': 50.00,
  'currency': 'USD'
});
```

### Enhanced Conversions

Sends hashed first-party data (email, phone) to improve attribution after cookie restrictions. Enable in Google Ads > Goals > Settings > Enhanced conversions.

```javascript
gtag('set', 'user_data', {
  'email': 'user@example.com',      // auto-hashed by gtag
  'phone_number': '+11234567890'
});
```

### Google Tag Manager alternative

If using GTM instead of inline gtag.js:
1. Install GTM container on all pages
2. Create Google Ads conversion tags in GTM
3. Set triggers for conversion events (form submissions, purchases)
4. Use the Data Layer to pass dynamic values (order amount, transaction ID)
5. Test with GTM Preview mode before publishing

---

## Meta (Facebook/Instagram)

### Install the Meta Pixel

Add to every page, in `<head>`:

```html
<script>
  !function(f,b,e,v,n,t,s)
  {if(f.fbq)return;n=f.fbq=function(){n.callMethod?
  n.callMethod.apply(n,arguments):n.queue.push(arguments)};
  if(!f._fbq)f._fbq=n;n.push=n;n.loaded=!0;n.version='2.0';
  n.queue=[];t=b.createElement(e);t.async=!0;
  t.src=v;s=b.getElementsByTagName(e)[0];
  s.parentNode.insertBefore(t,s)}(window, document,'script',
  'https://connect.facebook.net/en_US/fbevents.js');
  fbq('init', 'YOUR_PIXEL_ID');
  fbq('track', 'PageView');
</script>
```

Replace `YOUR_PIXEL_ID` from Meta Events Manager.

### Standard events

```javascript
// View a product or key page
fbq('track', 'ViewContent', {
  content_name: 'Pro Plan',
  content_category: 'Pricing',
  value: 29.00,
  currency: 'USD'
});

// Lead capture (form submit, demo request)
fbq('track', 'Lead', {
  content_name: 'Demo Request',
  value: 50.00,
  currency: 'USD'
});

// Purchase
fbq('track', 'Purchase', {
  value: 99.00,
  currency: 'USD',
  content_type: 'product',
  contents: [{ id: 'pro-plan', quantity: 1 }]
});

// Add to cart (e-commerce)
fbq('track', 'AddToCart', {
  content_ids: ['SKU-123'],
  content_type: 'product',
  value: 49.00,
  currency: 'USD'
});
```

### Conversions API (CAPI)

Server-side tracking that works alongside the pixel. Required for accurate tracking after iOS 14+ and cookie restrictions.

Set up via:
- **Direct integration** — send events from your server to Meta's API
- **Partner integrations** — Shopify, WooCommerce, Segment, etc. have built-in CAPI support
- **Conversions API Gateway** — Meta's managed solution via AWS

Key: send the same events from both pixel (browser) AND CAPI (server), with a shared `event_id` for deduplication.

### Aggregated Event Measurement

Required for iOS 14+ tracking. In Events Manager > Aggregated Event Measurement:
1. Verify your domain
2. Configure and prioritize your top 8 events in order of business importance
3. Purchase should typically be #1, Lead #2

---

## LinkedIn

### Install the Insight Tag

Add to every page, before `</body>`:

```html
<script type="text/javascript">
  _linkedin_partner_id = "YOUR_PARTNER_ID";
  window._linkedin_data_partner_ids = window._linkedin_data_partner_ids || [];
  window._linkedin_data_partner_ids.push(_linkedin_partner_id);
  (function(l) {
    if (!l){window.lintrk = function(a,b){window.lintrk.q.push([a,b])};
    window.lintrk.q=[]}
    var s = document.getElementsByTagName("script")[0];
    var b = document.createElement("script");
    b.type = "text/javascript";b.async = true;
    b.src = "https://snap.licdn.com/li.lms-analytics/insight.min.js";
    s.parentNode.insertBefore(b, s);})(window.lintrk);
</script>
```

### Conversion tracking

LinkedIn supports two methods:

**URL-based**: Fires when someone visits a specific URL (e.g., `/thank-you`).
Set up in Campaign Manager > Analyze > Conversion Tracking > Create Conversion.

**Event-based**: Fire manually on specific actions:

```javascript
window.lintrk('track', { conversion_id: YOUR_CONVERSION_ID });
```

### LinkedIn CAPI

For server-side tracking, LinkedIn offers a Conversions API. Set up via partner integrations (Segment, Tealium) or direct API calls. Deduplicates with the Insight Tag automatically when configured correctly.

---

## TikTok

### Install the TikTok Pixel

Add to every page, in `<head>`:

```html
<script>
  !function (w, d, t) {
    w.TiktokAnalyticsObject=t;var ttq=w[t]=w[t]||[];
    ttq.methods=["page","track","identify","instances","debug","on","off",
    "once","ready","alias","group","enableCookie","disableCookie","holdConsent",
    "revokeConsent","grantConsent"],ttq.setAndDefer=function(t,e)
    {t[e]=function(){t.push([e].concat(Array.prototype.slice.call(arguments,0)))}};
    for(var i=0;i<ttq.methods.length;i++)ttq.setAndDefer(ttq,ttq.methods[i]);
    ttq.instance=function(t){for(var e=ttq._i[t]||[],n=0;
    n<ttq.methods.length;n++)ttq.setAndDefer(e,ttq.methods[n]);return e};
    ttq.load=function(e,n){var r="https://analytics.tiktok.com/i18n/pixel/events.js",
    o=n&&n.partner;ttq._i=ttq._i||{},ttq._i[e]=[],ttq._i[e]._u=r,
    ttq._t=ttq._t||{},ttq._t[e]=+new Date,ttq._o=ttq._o||{},
    ttq._o[e]=n||{};var s=document.createElement("script");
    s.type="text/javascript",s.async=!0,s.src=r+"?sdkid="+e+"&lib="+t;
    var a=document.getElementsByTagName("script")[0];
    a.parentNode.insertBefore(s,a)};
    ttq.load('YOUR_PIXEL_ID');
    ttq.page();
  }(window, document, 'ttq');
</script>
```

### Standard events

```javascript
// View content
ttq.track('ViewContent', {
  content_id: 'pro-plan',
  content_type: 'product',
  content_name: 'Pro Plan',
  value: 29.00,
  currency: 'USD'
});

// Complete registration / sign up
ttq.track('CompleteRegistration', {
  content_name: 'Free Trial'
});

// Purchase
ttq.track('Purchase', {
  content_id: 'pro-plan',
  content_type: 'product',
  value: 99.00,
  currency: 'USD',
  quantity: 1
});

// Add to cart
ttq.track('AddToCart', {
  content_id: 'SKU-123',
  content_type: 'product',
  value: 49.00,
  currency: 'USD'
});
```

### Events API (server-side)

TikTok's Events API works like Meta's CAPI — send the same events from your server for better attribution. Use `event_id` for deduplication with browser pixel events.

### Advanced Matching

Pass hashed user data for better attribution:

```javascript
ttq.identify({
  email: 'user@example.com',       // auto-hashed
  phone_number: '+11234567890'
});
```

---

## Validation Checklist

After installing any pixel, verify before going live:

### Browser-side checks

- [ ] Pixel fires on every page (check via browser extension)
- [ ] Conversion events fire at the right moment (after confirmed action, not on button click)
- [ ] Event parameters contain correct values (currency, amount, content IDs)
- [ ] No duplicate events firing on the same action
- [ ] Events fire on both desktop and mobile

### Platform-side checks

- [ ] Events appear in the platform's event manager/diagnostics
- [ ] Test conversions show correct values
- [ ] Event match quality is acceptable (Meta: score > 6)
- [ ] Server-side events are deduplicating with browser events (not double-counting)

### Debugging tools

| Platform | Tool |
|----------|------|
| Google | Google Tag Assistant, Chrome DevTools Network tab |
| Meta | Meta Pixel Helper (Chrome extension), Events Manager Test Events |
| LinkedIn | Insight Tag Validator in Campaign Manager |
| TikTok | TikTok Pixel Helper (Chrome extension), Events Manager |
| All | GTM Preview Mode (if using Google Tag Manager) |

---

## Common Mistakes

- **Firing purchase events on button click instead of confirmed payment** — always fire on the success/thank-you page or after server confirmation
- **Missing deduplication between pixel and server events** — without a shared `event_id`, you'll double-count conversions
- **Not testing on mobile** — many pixels break on mobile browsers or in-app webviews
- **Hardcoded test values** — remove test transaction amounts before going live
- **Forgetting to exclude internal traffic** — your team's visits inflate conversion data
- **Installing pixels without consent management** — GDPR/CCPA require user consent before firing tracking pixels in applicable regions
- **Pixel installed but no conversion actions created** — the pixel collects data, but the ad platform won't optimize without defined conversion actions

---

## When to Use Server-Side Tracking

Browser-only tracking is increasingly unreliable due to:
- iOS 14+ App Tracking Transparency
- Third-party cookie deprecation
- Ad blockers (30%+ of tech audiences)

**Use server-side (CAPI/Events API) when:**
- Running Meta or TikTok ads (strongly recommended)
- Your audience is tech-savvy (higher ad blocker usage)
- You need accurate purchase/revenue attribution
- You're spending >$5K/month on any platform

**Server-side is optional when:**
- Running Google Ads only (Enhanced Conversions covers most gaps)
- Low ad spend / testing phase
- B2B with LinkedIn only (Insight Tag is still reliable)

# Google Search Playbook (B2B)

Intent-first operating rules for Google Ads: where to spend first, how to structure the account, when to loosen match types, and how to keep smart bidding pointed at revenue instead of junk form-fills. For RSA generation mechanics, see [rsa-output-spec.md](rsa-output-spec.md).

## Contents

- The intent ladder
- Brand bidding (and the pause test)
- Capture before you create
- Account structure
- Keywords and match types
- Negative keywords
- The weekly search-terms ritual
- Bidding by conversion volume
- Offline conversions
- Quality Score and landing pages
- PMax for B2B
- Benchmarks and the weekly scorecard

## The intent ladder

Spend opens rung by rung — each tier unlocks only after the one below proves it converts to *pipeline*:

1. **Brand** — "they want you" (brand name, brand + pricing/login). Cheapest clicks, highest conversion. Always on.
2. **High-intent non-brand** — ready to buy ("cold email software," "best CRM for agencies"). The profit center; most budget lives here.
3. **Competitor** — evaluating alternatives ("[competitor] alternative/vs"). Higher CPC, lower CVR; run selectively with dedicated comparison pages.
4. **Problem-aware** — has the problem, isn't shopping ("how to scale outbound"). Longer payback; only after tiers 1–2 work.
5. **Demand-gen/awareness** — broad, Display, YouTube. Last, with spare budget only.

**Don't skip rungs.** Broad spend before high-intent proof is how B2B accounts burn budgets with nothing in the CRM.

## Brand bidding (and the pause test)

Bid on brand by default — if you don't, competitors will, and you pay in lost deals rather than clicks. The exception: if you're the only bidder and organic owns the whole SERP, test pausing brand and watch **total brand conversions (paid + organic)**, not just paid. If total holds, you were cannibalizing yourself; if it drops, turn it back on. Cap brand budget — it rarely needs much, and shared budgets let brand eat everything (see below).

## Capture before you create

Search **harvests existing demand**; it cannot create demand. If your category has near-zero search volume, say so and put the budget upstream (LinkedIn/Meta/YouTube) instead of forcing keywords nobody types. Demand creation happens on social; Search is where you catch it landing.

## Account structure

Minimum viable split — each with an **independent budget**:

- **Brand** (own budget — never shared)
- **Non-brand high-intent** (one campaign, themed ad groups by solution)
- **Competitor** (own budget and messaging — its CPC/CVR economics are different)
- **Remarketing** (separate from Search)

Why independent budgets: in a shared budget the cheapest, highest-converting campaign (always brand) starves the ones you actually need data from. The account looks profitable on paper and is blind everywhere that matters.

- **Themed ad groups, not SKAGs:** 5–15 closely related keywords sharing one intent, answerable by one promise. If two keywords need different landing pages or value props, split the group. 2–3 RSAs per ad group.
- **Consolidation rule:** a campaign that can't reach ~15–30 conversions/month can't feed smart bidding — merge it. Fewer, better-fed campaigns beat elaborate structures in low-volume B2B.
- **Default settings to flip on every new Search campaign:** turn OFF Search Partners and Display Network until proven; set location targeting to **"Presence"** (people physically in the target geo — the default "presence or interest" serves people merely interested in it); remember language targeting keys off the user's Google interface language, not the query language.
- **Don't compete with yourself:** the same keyword at the same match type in multiple ad groups splits your data and bids against your own account. Use negatives to route each query to exactly one home.

## Keywords and match types

Source keywords from how **buyers describe the problem** (sales-call language, your own search-terms report, competitor ad copy) — not how you describe the product. A keyword with 50 searches/month and clear intent beats one with 5,000 and mixed intent. Tag every keyword by intent tier.

**Match-type progression — in this order:**

1. Start high-intent terms on **Phrase + Exact** (Exact still matches close variants; Phrase is the B2B workhorse), manual CPC or Max Conversions while volume is low.
2. Mine the search-terms report weekly (ritual below).
3. Introduce **Broad only after**: 30+ conversions/month in the campaign, AND smart bidding live, AND a tight negative list. Broad without all three is a donation to Google.

## Negative keywords

Starter lists to apply at build time:

- **Universal junk:** free, cheap, jobs, salary, hiring, career, intern, student, course, tutorial, training, certification, pdf, template, reddit, wiki, login (except in brand campaigns)
- **Research intent:** "what is," "how to," "examples," "meaning," "definition"
- **Category collisions:** terms your category shares with an unrelated one (selling sales-engagement? negative "employee engagement")
- **Your brand as a negative in non-brand campaigns** — routes brand traffic to the brand campaign where it belongs

**Match-type mechanics gotcha:** negative broad requires ALL its words present (any order) — negative broad "free trial" does **not** block "free" alone. Negative phrase blocks in-order phrases; negative exact blocks only that exact query. Most accidental over-blocking and under-blocking traces to this.

**Don't over-negative:** every negative narrows reach, and it compounds fast at B2B volumes. Negative the clearly wrong, not the merely uncertain — an ambiguous term deserves more data before it's cut.

## The weekly search-terms ritual

Once a week per campaign, three passes:

1. **Waste:** terms with spend (3+ clicks) and zero conversions → negative the irrelevant ones.
2. **Winners:** converting search terms that aren't keywords yet → add as Exact/Phrase in the right ad group.
3. **Drift:** broad/phrase matches pulling adjacent-but-wrong meanings → tighten the match type or negative the drift.

## Bidding by conversion volume

| Conversions/month (campaign) | Strategy |
|---|---|
| 0–15 | Manual CPC or Maximize Conversions (no target) |
| 15–30 | Maximize Conversions |
| 30+ stable | Target CPA — set at or slightly above your trailing 30-day actual |
| Real revenue values flowing back | Target ROAS |

Rules of thumb: smart bidding needs ~30 conversions in 30 days per campaign to learn. Set tCPA near actuals — an aggressively low target chokes delivery (Google just stops bidding). Move targets in **±10–15% steps and wait 1–2 weeks**; every change restarts learning, so don't panic-edit inside the learning window. Budget mechanics: campaigns can spend up to **2× daily budget** in a day (Google balances monthly — single-day overspend is normal); a budget-capped campaign that's converting often *lowers* its CPA when you raise the budget, because constrained smart bidding underperforms.

## Offline conversions

The single highest-impact move in a B2B Google account: **import CRM outcomes** (SQL, opportunity, closed-won) back into Google via GCLID + offline conversion import or a native CRM integration, with real deal values. Until then, smart bidding optimizes to form-fills and buys you junk (see the optimize-to-quality trap in [b2b-paid-playbook.md](b2b-paid-playbook.md)). B2B clicks close in 60–180 days — in-platform conversion counts will never tell the truth on their own. Reconcile against the CRM monthly; the CRM wins.

## Quality Score and landing pages

QS (1–10, per keyword) = expected CTR + ad relevance + landing page experience. Low QS means paying more for the same position — **fix the weak component before raising the bid.** Landing page rules that move it: message match (page headline echoes the ad's promise and the query — not a generic homepage); one job and one CTA per page; speed; proof above the fold. **Form length is an intent gate:** short forms buy volume at lower quality, longer qualified forms buy fewer/better — match it to what you're feeding back as the conversion event.

## PMax for B2B

Value ranking: **brand Search > high-intent non-brand Search > remarketing > PMax > broad demand-gen.** PMax earns budget only after the cheaper, clearer wins are maxed. Never run it as the first campaign, on weak tracking, or on tiny budgets.

Guardrails when you do run it: account-level **brand exclusions** (or it cannibalizes brand Search and claims the credit); audience signals from first-party data; negative keywords from day one; offline conversions imported *before* scaling it; check the CRM quality of PMax leads by campaign — if they convert to pipeline at half the rate of Search leads, PMax is cheap-looking and expensive-in-reality. Google auto-generates a bad video if you don't supply one.

## Benchmarks and the weekly scorecard

B2B SaaS Search ranges (wide on purpose — anchor to your own first 30 days): brand CTR 8–20%, CVR 15–40%; non-brand high-intent CTR 2–6%, CVR 3–10%, CPC $8–40+, CPL $80–400+; competitor terms run higher CPC and lower CVR than non-brand.

Weekly scorecard — exactly eight numbers: spend · leads · CPL · lead→SQL rate (from CRM) · SQLs · cost per SQL · Search impression share · top wasted search terms. Diagnostic: **Search Lost IS (budget)** vs **Lost IS (rank)** tells you whether you're capped by money or by Ad Rank — different problems, different fixes. If the eight are healthy and trending right, the account is healthy.

---

*Framework lineage: adapted (re-expressed and restructured) from practitioner playbooks, notably Ivan Falco's ads-skills. Benchmarks are practitioner-reported starting points — recalibrate against your own account.*

# LinkedIn B2B Playbook

Operational rules for LinkedIn Ads: bidding, audience sizing, scaling triggers, benchmarks, and format-specific tactics. LinkedIn is the precision channel — highest-quality B2B targeting at the highest cost, so the operating discipline is about not wasting that precision.

## Contents

- Bidding progression
- Audience sizing rules
- Job functions vs. job titles
- Audience splitting rules
- Penetration-based scaling
- Benchmarks by funnel stage
- Thought leader ads (TLAs)
- Campaign group build order
- Format notes (document, conversation, CTV)
- Retargeting setup (non-retroactive!)
- Account audit shortlist

## Bidding progression

1. **Week 1:** launch on automated bidding / maximum delivery. Don't touch it — you're buying CPC data.
2. **Week 2+:** switch to manual CPC set **~20% below the average CPC** the automated phase produced. This reliably cuts CPC without killing delivery.
3. **Exceptions:** small retargeting/ABM audiences stay on automated (manual underdelivers on small pools); reset to automated for a week whenever you change objective; audiences under ~10K may never spend their full budget at any bid.

Scheduling note: LinkedIn's ad day resets at UTC midnight. Professional activity peaks weekday mornings–early afternoon in the audience's timezone; dayparting there stretches limited budgets.

## Audience sizing rules

- **Cold prospecting:** 50K–300K members. Minimum ~15K per cold campaign.
- **Too-narrow failure mode:** hyper-narrow audiences spike CPMs several-fold and stall delivery entirely — budget won't spend at any bid. If it's not spending, the audience is usually too small, not the bid too low.
- **Tiny TAM (<~30K addressable):** skip the TOF/BOF split — run one campaign that saturates the whole audience with all funnel layers.
- **Retargeting:** audiences of roughly 1K–5K per segment (site visitors, 50%+ video viewers) are workable; below ~300 won't deliver.

## Job functions vs. job titles

Title targeting is precise but small and expensive. **Job function + seniority** targeting typically triples the addressable audience with materially cheaper reach at similar engagement — at the cost of a weekly "negative title" exclusion pass for the first ~2 months (like negative keywords: exclude irrelevant titles as they show up in demographics).

Platform gotchas:
- **Job-title targeting and seniority targeting are mutually exclusive** — you can't stack them. Entry-level exclusions only work under function/seniority targeting.
- The **Business Development function includes many CEOs, CMOs, and managing directors.** Don't blanket-exclude BD if you sell to the C-suite — filter with seniority exclusions instead.
- Leave **Audience Expansion OFF** (it quietly spends a meaningful share of budget on out-of-ICP members) and **Audience Network OFF** for B2B lead gen.

## Audience splitting rules

Split priority: **intent > persona > region/company size > seniority.**

- **Region:** keep the US separate (most expensive market — grouped with cheaper regions, it eats the budget). DACH needs localized ads; UK/Canada/Australia group fine; Nordics/Netherlands run fine in English. Never group an expensive market with small ones.
- **Company size:** segment by employee count (not revenue — LinkedIn's revenue data is estimated). Start with two bands, not three. Left unsegmented, LinkedIn over-serves the extremes (small companies and very large ones) and underserves mid-market — splitting forces fair distribution.

## Penetration-based scaling

Audience penetration (reached ÷ audience size) is the scaling trigger, not spend:

- 30-day penetration **<25%** → room to raise budget on this audience.
- **25–35%** → hold; let penetration accumulate before adding spend.
- **~35%+** = healthy saturation → scale horizontally (new audiences), not vertically.
- Expect diminishing returns: doubling budget grows penetration ~50–70%, not 100%.
- One campaign at 35%+ penetration beats three campaigns at 12% each — consolidate before multiplying.
- **Spend rising but reach flat (frequency climbing)?** Either competitors outbid you or ad quality is dragging your auction price. Strong ads → raise budget/bids; weak ads → fix creative first, more money just buys the same people again.

## Benchmarks by funnel stage

Practitioner-reported B2B SaaS ranges — recalibrate on your own account. **Careful:** for engagement-objective and thought-leader campaigns, LinkedIn's reported "CTR" includes social actions; judge traffic on **click-through to landing page (CTRTLP)** specifically.

| Metric | Cold / TOF | MOF | BOF/retargeting |
|---|---|---|---|
| CTRTLP | 0.30–0.55% | 0.55–0.80% | 0.80–1.30% |
| CPM | $33–65 typical | — | — |
| CPC | $8–22+ | — | lower |
| Cost per lead (Lead Gen Form) | — | $50–200 | — |
| Cost per website form fill | — | — | $200–500 |

Other useful bars: lead-gen form fill rate >8% (below = form too long, offer weak, or audience too cold); cost per SQL should stay under ~$500 (enterprise ACVs tolerate $300–500+ CPLs; SMB needs $50–150); video view rate >40%, completion 8–15% for horizontal; expect return data to lag 3–6 months.

## Thought leader ads (TLAs)

Ads promoted from a person's profile rather than the company page — currently the platform's biggest efficiency arbitrage:

- TLAs typically deliver **~3–6× the CTR of company-page ads** at a fraction of the CPC.
- **Non-employee/creator TLAs often outperform employee TLAs** — partnerships with niche creators are worth 30–50% of TLA budget if available.
- **Organic-first pipeline:** posts that hit ~2–3% organic CTR are your TLA candidates — the audience already voted.
- **The 72-hour edit:** organic reach concentrates in a post's first ~3 days. Let it run organic, then edit the post to add the CTA/product mention and promote it as a TLA — you capture organic credibility first, then convert it to demand gen.
- Auction insight: single-image ads face the most auction competition. Document, conversation, and TLA formats often buy cheaper reach purely because fewer advertisers use them — format diversification is a *bidding* tactic, not just creative variety.

## Campaign group build order

Add groups in ROI order, funding each before the next: **1. Product value** (direct response on your core offer) → **2. Remarketing** → **3. Content** (only content that can't be consumed in-feed — it must earn the click) → **4. Social proof** (case studies, testimonials) → **5. Thought leadership** (slowest payback, add last). Group-budget optimization tends to favor cheap audiences and video — don't mix enterprise with SMB or static with video in one group.

## Format notes

- **Document ads:** always 1080×1350 portrait (4:5). 5–7 slides: hook → pain → shift → solution → differentiators → CTA. The classic mistake is making the "solution" slide generic category requirements and the "differentiator" slide a rehash — slide N must add what slide N-1 couldn't. Big standalone stat slides (one number, source small) carry these.
- **Conversation ads:** subject 2–4 words; 3–5 short lines per message; specific numbers beat vague benefit claims; lead with a soft CTA ("see how it works") over "book a demo"; route the primary CTA to a Lead Gen Form, not a scheduling link. Benchmarks: 35–50%+ open rate, 2–5% CTR.
- **CTV:** Brand Awareness objective only, auto-bid only, ~$50/day minimum, limited geos. Completion metrics are meaningless (forced view). Only worth it above roughly $15K/month total spend — below that it cannibalizes measurable-signal budget.

## Retargeting setup (non-retroactive!)

**LinkedIn retargeting audiences only start collecting from the moment you create them.** Create every retargeting audience you might ever want (site visitors, video viewers, ad engagers, lead-form openers, company page visitors) **before launch** — data you didn't capture is gone permanently.

Cross-channel: tag paid-search traffic with UTMs and build LinkedIn (and Meta) retargeting audiences from it — see the [ABM playbook](abm-playbook.md) for the mechanic.

## Account audit shortlist

The highest-frequency findings when auditing LinkedIn accounts, in order: Audience Expansion left on · Audience Network left on · audiences too small to deliver · fewer than 4 active ads per campaign · campaigns under ~10 results/week (starved — consolidate) · stale creative (3+ months old) · no retargeting audiences created · lead quality never reconciled against CRM · brand/geo budget mixing · everything on automated bidding forever.

---

*Framework lineage: adapted (re-expressed and restructured) from practitioner playbooks, notably Ivan Falco's ads-skills. Benchmarks are practitioner-reported starting points — recalibrate against your own account.*

# Meta Decision System (B2B)

A quantified kill/keep/scale engine for Meta ads. Every threshold derives from one anchor number, so decisions become arithmetic instead of vibes. Pairs with the strategy-level Meta playbook in SKILL.md (creative-as-targeting, creative volume) — this file is the *operating* layer.

## Contents

- TCPL: the anchor variable
- The ad-count ceiling
- Two-campaign structure (Scaling / Testing)
- Stage 1: delivery check (day 7)
- Stage 2: quality evaluation (weekly)
- Graduation criteria
- Fatigue detection
- Swap rules
- Creative production math
- Scaling protocol
- Weekly cadence
- Lead forms and social amnesia
- Advantage+ transition
- Benchmarks and seasonality

## TCPL: the anchor variable

TCPL = **Target Cost Per Qualified Lead** (qualified = meets your ICP bar, not just a form-fill). Set it one of three ways:

1. **From deal math (best):** TCPL = target cost per demo × qualified-lead-to-demo rate. ($2,000/demo × 0.28 = $560.)
2. **From history:** TCPL = trailing 30-day CPL(qualified) × 0.80 — a 20% improvement is achievable through operational cleanup alone (killing zero-QL ads, graduating winners). Once you have both, use whichever is tighter.
3. **New account:** target CAC × qualified-lead-to-customer rate, or a placeholder from your ACV tier; replace with method 2 after 30 days.

Every rule below is expressed in multiples of TCPL. Review TCPL monthly.

## The ad-count ceiling

More active ads than your budget can feed = every ad starves and nothing gets a fair read.

**Ceiling = (daily budget × 14) / (2 × TCPL)** — i.e., over a 14-day evaluation window, each ad needs at least 2× TCPL of spend to be judged.

$1,000/day at $500 TCPL → ceiling of 14 ads; run **6–10** (winners + 2–3 test slots). At the ceiling, launching a new test requires killing something first.

## Two-campaign structure (Scaling / Testing)

Run two CBO campaigns over the **same audience**:

- **Scaling campaign (~80% of budget)** — holds only graduated, proven ads.
- **Testing campaign (~20%)** — holds new concepts and iterations, with its own protected budget.

Why: inside a single CBO, proven ads always starve new ads — tests never get enough spend to be judged. Why not ABO for testing: equal forced distribution keeps spending on ads Meta has already deprioritized. The separation is *budget protection*, not audience segmentation.

**Image-first validation:** launch new concepts as statics first; only produce the video/carousel/UGC version after the image passes the checks below. Exception: concepts that are inherently video (testimonial, demo, UGC).

## Stage 1: delivery check (day 7)

CBO's spend allocation is itself a signal — Meta pre-screens your ads. At day 7 for each test ad:

- **Fair share test:** minimum expected spend = (campaign daily budget ÷ active ads) × 7 × 0.5. Below that → **kill** (Meta actively deprioritized it). Zero spend → kill immediately.
- **Ongoing:** if an ad has spent ≥ 1× TCPL lifetime AND averaged under ~$10/day over the last 7 days → kill. (The lifetime-spend gate stops you from killing ads CBO simply hasn't explored yet.)

When iterating on a delivery-killed ad, change the **hook/visual/format only** — the audience never got far enough for copy or CTA to matter.

## Stage 2: quality evaluation (weekly, rolling 14-day data)

Run in order; stop at the first triggered action:

1. **Data gate:** spend < 3× TCPL → **wait** (not enough signal). At true cost-per-QL = target, 3× TCPL of spend should produce ~3 qualified leads; zero QLs at that spend is ~5% probability — so judging at 3× gives ~95% confidence without wasting budget (2× has a 13% false-negative rate; 5× overpays for certainty).
2. **Zero pixel leads** at ≥3× TCPL → **swap and abandon the concept** (don't iterate a dead concept).
3. **Quality check** (the layer Meta can't see — requires your CRM):
   - Pixel leads but zero qualified → swap; keep the format, change the angle.
   - Qualified rate <40% → swap; the ad attracts the wrong people. Add ICP-filtering language. (At 40% QL rate, true cost per QL is 2.5× the pixel CPL you see in Ads Manager — two ads identical in-platform can differ 60%+ in real cost.)
   - 40–60% → monitor one more week. ≥60% → proceed.
4. **Cost check:** cost per QL ≤ TCPL → candidate winner. 1–1.5× TCPL → monitor (normal variance). >1.5× TCPL → swap (structural underperformance, not noise).

## Graduation criteria (Testing → Scaling)

Graduate only when **all** are true: ≥5 qualified leads · qualified rate ≥60% · cost per QL ≤ TCPL · running ≥14 days · ≥1 QL in the last 7 days.

## Fatigue detection

Frequency bands by campaign type (safe / warning / critical):

| Campaign type | Safe | Warning | Critical |
|---|---|---|---|
| Cold prospecting | 1.0–2.5 | 2.5–4.0 | >4.0 |
| Retargeting | 2.0–4.0 | 4.0–6.0 | >6.0 |
| ABM (small audiences) | 2.0–5.0 | 5.0–8.0 | >8.0 |

Other signals, in urgency order: CTR down 20%+ from baseline over 7 days; CPM up 30%+ over 2 weeks (leading indicator — moves before CTR); ad relevance rankings "below average"; CPA up with stable targeting.

For **scaling-campaign ads**, apply a deliberately stricter bar than the general bands — these ads carry ~80% of spend, so fatigue there costs the most: warning at frequency 3.0–3.5 or cost +20% → start 2 iterations now (they take ~14 days to be ready); swap at >3.5, cost +40%, or >1.5× TCPL for 2 weeks.

**Lifespan expectations (B2B):** statics 14–28 days; short video and carousels 21–35; UGC/testimonial 28–42. Small B2B audiences build frequency fast — plan refresh every 14–21 days.

**Retire (don't iterate)** when CTR drops 30%+ from peak or frequency crosses the campaign type's critical band above — the concept is exhausted, not the execution.

**Rotation without resetting learning:** never edit creative inside a performing ad — that resets the learning phase. Launch new ads alongside existing ones, or spin up a new ad set with the same targeting. Pausing doesn't reset; editing does.

## Swap rules

**Never pause without a replacement.** Keep 2–3 iterations staged; replacement live within 7 days, immediately for critical fatigue. If the pipeline is empty, redirect the budget to proven ads rather than leaving a zombie running. What to change depends on why it died: delivery kill → hook/visual; quality kill → angle and ICP language; cost kill → offer and audience; fatigue → fresh execution of the same proven concept.

## Creative production math

- **Test throughput** ≈ (monthly budget × 0.20) ÷ (3 × TCPL), per month. Delivery kills free budget early, so actual throughput runs ~1.5–2× the base rate.
- **Win rates:** iterations on winners ~25%; brand-new concepts ~10%; blended ~1 in 6. To get N winners, plan ~6× N tests.
- **Minimum proven-ad inventory** ≈ monthly budget ÷ $5,000 — each proven B2B ad absorbs roughly $5K/month before fatiguing. **You cannot scale budget ahead of creative supply**; if proven ads < minimum, fix the creative deficit before raising budget.
- **Iteration priority** when refreshing a winner (ranked by impact): 1. hook (changes who stops) → 2. visual treatment → 3. format → 4. body copy/CTA.

## Scaling protocol

Scale only when all: proven-ad count meets the next budget level's minimum; account frequency <3.0; cost per QL ≤ TCPL for 2+ consecutive weeks; 3+ replacements staged.

- **Rate:** +20% every 5 days. Never +30% or more in one move — that resets learning.
- **Rollback trigger:** cost per QL >1.5× TCPL after a scale step → cut budget 20–30% immediately, stabilize 2 weeks, resume at +10% per week.
- **Hitting the wall** (account-wide average frequency >3.5 — an account-level *scale* guardrail, distinct from the per-ad fatigue bands above): expand lookalikes 1% → 2–3%, add new seed audiences, test broad, activate cross-channel UTM audiences (see [ABM playbook](abm-playbook.md)), re-open remarketing.

## Weekly cadence

- **Monday — decision day:** pull rolling 14-day data; run Stage 2 on every test ad; run the fatigue check on every scaling ad.
- **Wednesday — launch day:** launch new tests into freed slots; run Stage 1 on ads that hit day 7.
- **Friday — scaling day:** apply scale steps or rollbacks.
- **Monthly:** creative library audit + TCPL review.

## Lead forms and social amnesia

The #1 B2B Meta lead-quality problem: frictionless auto-filled forms produce leads who don't remember converting ("social amnesia"). **Intentional friction = awareness = quality:**

- Use **Higher Intent** form type (adds a review step), not More Volume.
- **Require work email** — it can't auto-fill from the Facebook profile, forcing a conscious act. This is the single biggest quality lever.
- Add 1–3 multiple-choice qualification questions (4+ spikes abandonment), ordered easiest → hardest.
- Confirmation message sets expectations for what happens next (combats amnesia at the follow-up stage).

Lead form vs. landing page: LP converting ≥5% → use the LP; LP under ~2% → lead form; demo/trial offers → LP; content/webinar → form.

## Advantage+ transition

Manual is where you learn; Advantage+ is where you earn. Transition a campaign to Advantage+ only after: a proven offer, a validated audience, and **~50 conversions/week** on the optimization event (the learning-phase exit bar — budget needed ≈ target CPA × 50 ÷ 7 per day). If you can't hit 50/week on the target event, optimize a higher-volume event up-funnel and retarget converters. Advantage+ conflicts with strict ABM (you can't lock it to a list) — see the [ABM playbook](abm-playbook.md). Watch Campaign Score directionally (70+ healthy, <50 = fighting the algorithm) but never trade lead quality for score.

## Benchmarks and seasonality

B2B SaaS Meta ranges (practitioner-reported; recalibrate on your own first 30 days): CTR 1.0–1.5% (red flag <0.8%); CPM $10–20 (red flag >$25); CPL (form) $20–50 (red flag >$75); landing page CVR 8–12%. Seasonality: Q1 CPMs are the year's lowest (scale aggressively); Q4 runs +60–80% (consider reducing B2B spend and banking budget for January).

---

*Framework lineage: this decision system is adapted (re-expressed, reconciled, and restructured) from practitioner operating systems, notably Ivan Falco's ads-skills. All thresholds are starting points — recalibrate against your own account.*

# Platform Setup Checklists

Complete setup checklists for major ad platforms.

## Contents
- Google Ads Setup (Account Foundation, Conversion Tracking, Analytics Integration, Audience Setup, Campaign Readiness, Ad Extensions, Brand Protection)
- Meta Ads Setup (Business Manager Foundation, Pixel & Tracking, Domain & Aggregated Events, Audience Setup, Catalog, Creative Assets, Compliance)
- LinkedIn Ads Setup (Campaign Manager Foundation, Insight Tag & Tracking, Audience Setup, Lead Gen Forms, Document Ads, Creative Assets, Budget Considerations)
- Twitter/X Ads Setup (Account Foundation, Tracking, Audience Setup, Creative)
- TikTok Ads Setup (Account Foundation, Pixel & Tracking, Audience Setup, Creative)
- Universal Pre-Launch Checklist

## Google Ads Setup

### Account Foundation

- [ ] Google Ads account created and verified
- [ ] Billing information added
- [ ] Time zone and currency set correctly
- [ ] Account access granted to team members

### Conversion Tracking

- [ ] Google tag installed on all pages
- [ ] Conversion actions created (purchase, lead, signup)
- [ ] Conversion values assigned (if applicable)
- [ ] Enhanced conversions enabled
- [ ] Test conversions firing correctly
- [ ] Import conversions from GA4 (optional)

### Analytics Integration

- [ ] Google Analytics 4 linked
- [ ] Auto-tagging enabled
- [ ] GA4 audiences available in Google Ads
- [ ] Cross-domain tracking set up (if multiple domains)

### Audience Setup

- [ ] Remarketing tag verified
- [ ] Website visitor audiences created:
  - All visitors (180 days)
  - Key page visitors (pricing, demo, features)
  - Converters (for exclusion)
- [ ] Customer match lists uploaded
- [ ] Similar audiences enabled

### Campaign Readiness

- [ ] Negative keyword lists created:
  - Universal negatives (free, jobs, careers, reviews, complaints)
  - Competitor negatives (if needed)
  - Irrelevant industry terms
- [ ] Location targeting set (include/exclude)
- [ ] Language targeting set
- [ ] Ad schedule configured (if B2B, business hours)
- [ ] Device bid adjustments considered

### Ad Extensions

- [ ] Sitelinks (4-6 relevant pages)
- [ ] Callouts (key benefits, offers)
- [ ] Structured snippets (features, types, services)
- [ ] Call extension (if phone leads valuable)
- [ ] Lead form extension (if using)
- [ ] Price extensions (if applicable)
- [ ] Image extensions (where available)

### Brand Protection

- [ ] Brand campaign running (protect branded terms)
- [ ] Competitor campaigns considered
- [ ] Brand terms in negative lists for non-brand campaigns

---

## Meta Ads Setup

### Business Manager Foundation

- [ ] Business Manager created
- [ ] Business verified (if running certain ad types)
- [ ] Ad account created within Business Manager
- [ ] Payment method added
- [ ] Team access configured with proper roles

### Pixel & Tracking

- [ ] Meta Pixel installed on all pages
- [ ] Standard events configured:
  - PageView (automatic)
  - ViewContent (product/feature pages)
  - Lead (form submissions)
  - Purchase (conversions)
  - AddToCart (if e-commerce)
  - InitiateCheckout (if e-commerce)
- [ ] Conversions API (CAPI) set up for server-side tracking
- [ ] Event Match Quality score > 6
- [ ] Test events in Events Manager

### Domain & Aggregated Events

- [ ] Domain verified in Business Manager
- [ ] Aggregated Event Measurement configured
- [ ] Top 8 events prioritized in order of importance
- [ ] Web events prioritized for iOS 14+ tracking

### Audience Setup

- [ ] Custom audiences created:
  - Website visitors (all, 30/60/90/180 days)
  - Key page visitors
  - Video viewers (25%, 50%, 75%, 95%)
  - Page/Instagram engagers
  - Customer list uploaded
- [ ] Lookalike audiences created (1%, 1-3%)
- [ ] Saved audiences for common targeting

### Catalog (E-commerce)

- [ ] Product catalog connected
- [ ] Product feed updating correctly
- [ ] Catalog sales campaigns enabled
- [ ] Dynamic product ads configured

### Creative Assets

- [ ] Images in correct sizes:
  - Feed: 1080x1080 (1:1)
  - Stories/Reels: 1080x1920 (9:16)
  - Landscape: 1200x628 (1.91:1)
- [ ] Videos in correct formats
- [ ] Ad copy variations ready
- [ ] UTM parameters in all destination URLs

### Compliance

- [ ] Special Ad Categories declared (if housing, credit, employment, politics)
- [ ] Landing page complies with Meta policies
- [ ] No prohibited content in ads

---

## LinkedIn Ads Setup

### Campaign Manager Foundation

- [ ] Campaign Manager account created
- [ ] Company Page connected
- [ ] Billing information added
- [ ] Team access configured

### Insight Tag & Tracking

- [ ] LinkedIn Insight Tag installed on all pages
- [ ] Tag verified and firing
- [ ] Conversion tracking configured:
  - URL-based conversions
  - Event-specific conversions
- [ ] Conversion values set (if applicable)

### Audience Setup

- [ ] Matched Audiences created:
  - Website retargeting audiences
  - Company list uploaded (for ABM)
  - Contact list uploaded
- [ ] Lookalike audiences created
- [ ] Saved audiences for common targeting

### Lead Gen Forms (if using)

- [ ] Lead gen form templates created
- [ ] Form fields selected (minimize for conversion)
- [ ] Privacy policy URL added
- [ ] Thank you message configured
- [ ] CRM integration set up (or CSV export process)

### Document Ads (if using)

- [ ] Documents uploaded (PDF, PowerPoint)
- [ ] Gating configured (full gate or preview)
- [ ] Lead gen form connected

### Creative Assets

- [ ] Single image ads: 1200x627 (1.91:1) or 1080x1080 (1:1)
- [ ] Carousel images ready
- [ ] Video specs met (if using)
- [ ] Ad copy within character limits:
  - Intro text: 600 max, 150 recommended
  - Headline: 200 max, 70 recommended

### Budget Considerations

- [ ] Budget realistic for LinkedIn CPCs ($8-15+ typical)
- [ ] Audience size validated (50K+ recommended)
- [ ] Daily vs. lifetime budget decided
- [ ] Bid strategy selected

---

## Twitter/X Ads Setup

### Account Foundation

- [ ] Ads account created
- [ ] Payment method added
- [ ] Account verified (if required)

### Tracking

- [ ] Twitter Pixel installed
- [ ] Conversion events created
- [ ] Website tag verified

### Audience Setup

- [ ] Tailored audiences created:
  - Website visitors
  - Customer lists
- [ ] Follower lookalikes identified
- [ ] Interest and keyword targets researched

### Creative

- [ ] Tweet copy within 280 characters
- [ ] Images: 1200x675 (1.91:1) or 1200x1200 (1:1)
- [ ] Video specs met (if using)
- [ ] Cards configured (website, app, etc.)

---

## TikTok Ads Setup

### Account Foundation

- [ ] TikTok Ads Manager account created
- [ ] Business verification completed
- [ ] Payment method added

### Pixel & Tracking

- [ ] TikTok Pixel installed
- [ ] Events configured (ViewContent, Purchase, etc.)
- [ ] Events API set up (recommended)

### Audience Setup

- [ ] Custom audiences created
- [ ] Lookalike audiences created
- [ ] Interest categories identified

### Creative

- [ ] Vertical video (9:16) ready
- [ ] Native-feeling content (not too polished)
- [ ] First 3 seconds are compelling hooks
- [ ] Captions added (most watch without sound)
- [ ] Music/sounds selected (licensed if needed)

---

## Universal Pre-Launch Checklist

Before launching any campaign:

- [ ] Conversion tracking tested with real conversion
- [ ] Landing page loads fast (<3 sec)
- [ ] Landing page mobile-friendly
- [ ] UTM parameters working
- [ ] Budget set correctly (daily vs. lifetime)
- [ ] Start/end dates correct
- [ ] Targeting matches intended audience
- [ ] Ad creative approved
- [ ] Team notified of launch
- [ ] Reporting dashboard ready

# Google RSA Output Spec

When the user requests Google Ads RSAs (Responsive Search Ads), output MUST comply with these platform limits and structural requirements. Do not output any RSA that violates them.

## Hard limits per RSA (enforce before responding)

Per-field **character** limits are owned by `suede-ad-creative` — use the numbers it states,
so the two skills cannot drift. This spec adds the stricter **quantity** mandate on top:
Google permits "up to" 15 headlines and 4 descriptions; a Suede RSA ships all of them.

- **Headlines:** exactly **15** per RSA, each within the headline character limit `suede-ad-creative` states (count characters, including spaces). Render as `1. ... (NN chars)` so the reader can verify.
- **Descriptions:** exactly **4** per RSA, each within the stated description character limit.
- **Paths:** up to 2 path fields, each within the stated path character limit.
- **Final URL:** present, https.
- **Pinning:** state any pinned positions explicitly. Default = unpinned unless user asks.
- **Per-account guardrail:** Google enforces **3 RSAs max per ad group**. When the user asks for >3, group them by ad group.

## Required sidecar artifacts (always include with RSA request)

1. **Ad group structure**, labeled `Ad group structure:` — list each ad group with its theme, target keywords (match types), and which RSAs map to it.
2. **Negative keyword list**, labeled `Negative keywords:` — minimum **8** entries, group-level vs campaign-level called out.
3. **Sitelinks** (≥ 4), **Callouts** (≥ 4 ≤25 chars), **Structured snippets** if relevant.

## Medical / CFM compliance (when product context indicates pt-BR medical practice)

If `.agents/product-marketing.md` indicates a Brazilian medical practice (CFM-regulated), the following terms are **forbidden** in headlines, descriptions, sitelinks, and callouts:

- Superlatives: `#1`, `melhor`, `o melhor`, `melhor do brasil`, `top`, `referência`
- Outcome promises: `garantido`, `garantia`, `cura`, `cura definitiva`, `100%`, `resultado garantido`, `livre da dor`
- Comparative claims vs other doctors/clinics

Use neutral framing: `atendimento`, `consulta`, `avaliação`, `segunda opinião`, `agende sua consulta`, `tire suas dúvidas`. Geo modifier (`Porto Alegre`, `POA`, `Zona Sul POA`) required where the prompt specifies a region.

## Output ORDER (mandatory — emit in this order to avoid truncation)

1. **Ad group structure** (short)
2. **Negative keywords** (≥8, MANDATORY — emit BEFORE RSAs so it isn't dropped if output runs long)
3. **Sitelinks** (≥4)
4. **Callouts** (≥4)
5. **RSA1, RSA2, RSA3** (largest section, last — safe to truncate gracefully)

## Output template (mandatory shape)

```
Ad group structure:
- AG1 [theme]: keywords (match types) → RSA1, RSA2
- AG2 [theme]: ...

Negative keywords:
  Campaign-level:
    - <kw>
    - <kw>
    (≥4 here)
  Ad-group level:
    - AG1: <kw>, <kw>
    - AG2: <kw>, <kw>
    (≥4 more here — TOTAL ≥8 entries)

Sitelinks (≥4):
  - <title (≤25)> | <desc1 (≤35)> | <desc2 (≤35)> | URL

Callouts (≥4, each ≤25 chars):
  - <callout>

RSA1 — [ad group name]
  Final URL: https://...
  Path1: ...   Path2: ...
  Headlines (15, each ≤30 chars):
    1. <headline> (NN chars)
    ...
    15. <headline> (NN chars)
  Descriptions (4, each ≤90 chars):
    1. <description> (NN chars)
    ...
    4. <description> (NN chars)
  Pinning: H1=none; H2=none; ...   (or explicit pins)

RSA2 — ...
RSA3 — ...
```

## Self-check before responding

Before sending the output, run this checklist mentally:

- [ ] Each RSA has exactly 15 headlines, exactly 4 descriptions.
- [ ] Every headline is ≤30 chars; every description is ≤90 chars. Character counts printed.
- [ ] Negative keyword list labeled and ≥8 entries.
- [ ] Ad group structure labeled.
- [ ] If medical (CFM): no forbidden superlative/outcome words; geo modifier present where required; language is pt-BR.

If any check fails, rewrite before responding. Do not ship partial RSAs.