Suede AI Paid Ads

Use this paid-acquisition playbook to create, optimize, and scale campaigns against explicit acquisition economics. Never assume account access.

Before Starting

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Campaign Goals

• Which platform(s) are running now, or which do you want to start with?
• What's the primary objective? (Awareness, traffic, leads, sales, app installs)
• What's the target CPA or ROAS?
• What's the monthly/weekly budget?
• Any constraints? (Brand guidelines, compliance, geographic)

2. Product & Offer

• What are you promoting? (Product, free trial, lead magnet, demo)
• What's the landing page URL?
• What makes this offer compelling?

3. Audience

• Who is the ideal customer?
• What problem does your product solve for them?
• What are they searching for or interested in?
• Do you have existing customer data for lookalikes?

4. Current State

• Have you run ads before? What worked/didn't?
• Do you have existing pixel/conversion data?
• What's your current funnel conversion rate?
• Do you have creative assets already, or do they need to be produced?

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Reference Routing

This skill's depth lives in references: load by intent. For any operational decision on a live account (kill/keep/scale/budget), load the relevant playbook before answering; the thresholds live there, not here.

User intent	Load	Covers
B2B strategy, funnel stages, budget splits, kill rules, lead quality, breakeven math	b2b-paid-playbook.md	Demand lifecycle, leading/lagging signals, kill rules, offline conversion loop, U/B/F lead scoring, scaling quadrant
Meta operations: when to kill/graduate/scale an ad, fatigue, testing structure	meta-decision-system.md	TCPL-anchored decision tree, ad-count ceiling, 80/20 CBO structure, fatigue bands, lead forms, Advantage+ transition
LinkedIn operations: bidding, audience sizing, scaling, benchmarks, TLAs, formats	linkedin-b2b-playbook.md	Bidding progression, penetration scaling, sizing rules, funnel benchmarks, document/conversation ads, audit shortlist
Google Search: what to spend on first, structure, match types, negatives, PMax	google-search-playbook.md	Intent ladder, account structure, match-type gates, negatives, bidding by volume, offline conversions, PMax guardrails
Named-account targeting, pipeline acceleration, cross-channel retargeting	abm-playbook.md	LinkedIn/Meta ABM, list mechanics, acceleration campaigns, UTM cross-channel remarketing, ABM measurement
Generating Google RSAs	rsa-output-spec.md	Mandatory output spec: limits, sidecars, template, self-check
Audience setup, tracking setup, launch checklists, copy formulas	audience-targeting.md · conversion-tracking.md · platform-setup-checklists.md · ad-copy-templates.md	Existing foundations

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Platform Selection Guide

Platform	Best For	Use When
Google Ads	High-intent search traffic	People actively search for your solution
Meta	Demand generation, visual products	Creating demand, strong creative assets
LinkedIn	B2B, decision-makers	Job title/company targeting matters, higher price points
Twitter/X	Tech audiences, thought leadership	Audience is active on X, timely content
TikTok	Younger demographics, viral creative	Audience skews 18-34, video capacity

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Campaign Structure Best Practices

Account Organization

Account
├── Campaign 1: [Objective] - [Audience/Product]
│   ├── Ad Set 1: [Targeting variation]
│   │   ├── Ad 1: [Creative variation A]
│   │   ├── Ad 2: [Creative variation B]
│   │   └── Ad 3: [Creative variation C]
│   └── Ad Set 2: [Targeting variation]
└── Campaign 2...

Naming Conventions

[Platform]_[Objective]_[Audience]_[Offer]_[Date]

Examples:
META_Conv_Lookalike-Customers_FreeTrial_[YYYYQ#]
GOOG_Search_Brand_Demo_Ongoing
LI_LeadGen_CMOs-SaaS_Whitepaper_[MMMYY]

Budget Allocation

Testing phase (first 2-4 weeks):

• 70% to proven/safe campaigns
• 30% to testing new audiences/creative

Scaling phase:

• Consolidate budget into winning combinations
• Increase budgets ~20% at a time: never 30%+ in one move (resets platform learning)
• Wait 3-5 days between increases for algorithm learning

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Ad Copy

Copy formulas, angle libraries, and character limits belong to suede-ad-creative. This skill decides which campaign, audience, and offer the copy serves. Quick structures for a brief live in references/ad-copy-templates.md.

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Audience Understanding & Targeting

Knowing your audience deeply is still the highest-leverage work in paid ads: demographics, job titles, pain points, fears, hopes, the exact language they use, who they follow, what they've tried, why they failed, what they buy. Gather every identifier you can.

What has changed is where you apply that knowledge. As ad-platform algorithms have gotten dramatically better at finding the right person, jamming all your audience identifiers into the platform's targeting filters underperforms feeding those same identifiers into the creative (headlines, copy, visuals, hooks, examples).

The discipline now: audience knowledge → creative first, targeting filters second. How much that ratio tips toward "creative" varies meaningfully by platform.

Platform-by-platform: where to apply audience knowledge

Platform	Audience knowledge → creative	Audience knowledge → targeting filters	Notes
Meta	80%+	20%	Broad audiences plus distinct creative usually beat interest stacking. See "Meta in the Andromeda era" below.
Google Search	40%	60%	Keywords are still the dominant signal: match-types, search-intent layering, and negative keywords still drive performance. Creative (RSA headlines) matters but is downstream of the keyword.
Google Performance Max / Demand Gen	70%	30%	Audience signals are advisory, not deterministic. Creative + product feed quality dominate.
LinkedIn	40%	60%	Job-title / company / industry filters still produce real precision because LinkedIn's identity data is high-quality. Creative makes the click; firmographics make the right person see it.
TikTok	70%	30%	Algorithm is closer to Meta's model: broad targeting + native-feeling creative wins. Some audience interests help but creative dominates.
Twitter/X	50%	50%	Interest + follower targeting still meaningful, but creative differentiation is high-leverage given lower competition.

These ratios are directional, not precise. Test in your actual account.

For how each identifier becomes a headline, hook, or angle, use suede-ad-creative: it owns the angle-to-copy mapping.

Key Concepts (still apply)

• Lookalikes: Base on best customers (by LTV), not all customers. Still high-value across platforms.
• Retargeting: Segment by funnel stage (visitors vs. cart abandoners). See "Retarget with a different offer" and "The four-ad retargeting layer" below.
• Exclusions: Exclude existing customers and recent converters: showing ads to people who already bought wastes spend.

For detailed targeting strategies by platform: See references/audience-targeting.md

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Meta in the Andromeda era

What is verified. Andromeda is Meta's ad retrieval system. Meta Engineering described it on December 2, 2024: for each impression it narrows tens of millions of eligible ads to a few thousand candidates before the ranking models and the auction run. Meta's advertiser guidance in December 2025 called creative diversification a foundational practice: vary format, message, and persona instead of iterating on one concept. Everything else below is operating practice to test, not platform fact.

Operating practice that follows:

• Creative does most of the targeting. Start broad (country plus customer exclusions) and let distinct creative find distinct buyers. Test it: duplicate a winning interest-stacked ad set, remove the interests, run both for 7 days on equal budget, and compare CPA on the optimization event.
• Distinct concepts beat near-duplicates. Ten color swaps of one ad teach the system one thing. Ten different angles, formats, and personas teach it ten. Track concept count, not ad count.
• Make statics part of the mix. Statics are cheap and fast, so they make concept volume affordable. Test them against video on cost per qualified result; do not assume either format wins.
• Identity-keyword variants. Duplicate a winner and insert the buyer's identity into the headline or first line ("leads per week" becomes "dental leads per week", "law firm leads per week"). The word works on the reader and gives the system a clearer signal. Use only identities the offer truly serves.
• AI-assisted segment rewrites. Give a model the winning ad and ask it to rewrite for one named segment while keeping voice, structure, and claims identical. Review every variant for invented claims, then route the batch through suede-ad-creative for the pre-delivery self-check.
• Rescue test for unspent variants. Budget optimization often gives most variants little or no spend. Move the few you have strong evidence for into a separate ad set and give them a fair read before discarding them.
• Look native. Study what performs organically in the niche on Instagram, TikTok, and YouTube and match that look. A proven organic post run as a partnership or boosted ad is often the cheapest test available.
• Attribution windows changed. Since January 12, 2026 the Ads Insights API no longer returns 7-day view and 28-day view windows. Available windows are 1-day click, 7-day click, 28-day click, 1-day engaged-view, and 1-day view. Update dashboards and any report that compared view-through windows.

The full kill, graduate, and scale rules live in meta-decision-system.md.

Creative Best Practices

Image Ads

• Clear product screenshots showing UI
• Before/after comparisons
• Stats and numbers as focal point
• Human faces (real, not stock)
• Short, legible text overlay. Meta retired its 20% text rule in 2020, but text-heavy images can still deliver worse; test a lighter version

Video Ads Structure (15-30 sec)

1. Hook (0-3 sec): Pattern interrupt, question, or bold statement
2. Problem (3-8 sec): Relatable pain point
3. Solution (8-20 sec): Show product/benefit
4. CTA (20-30 sec): Clear next step

Production tips:

• Captions by default: much feed video plays muted, and captions help comprehension either way
• Vertical for Stories/Reels, square for feed
• Native feel outperforms polished
• First 3 seconds determine if they watch

Creative Testing Hierarchy

1. Concept/angle (biggest impact)
2. Hook/headline
3. Visual style
4. Body copy
5. CTA

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Campaign Optimization

For hard kill/keep/scale thresholds, use the platform playbooks (see Reference Routing): the kill rules and breakeven CPL/CPC math live in b2b-paid-playbook.md, and Meta's full decision tree lives in meta-decision-system.md.

Key Metrics by Objective

Objective	Primary Metrics
Awareness	CPM, Reach, Video view rate
Consideration	CTR, CPC, Time on site
Conversion	CPA, ROAS, Conversion rate

Optimization Levers

"Too high" and "low" below are not opinions. Too high means above the break-even CPA / ROAS ceiling computed in Scaling discipline, and low means below the funnel benchmark in the platform playbook for that channel. Compute the ceiling before you pull any lever, and for hard kill/scale thresholds, use the playbooks routed at the top of Campaign Optimization.

If CPA is too high:

1. Check landing page (is the problem post-click?)
2. Tighten audience targeting
3. Test new creative angles
4. Improve ad relevance/quality score
5. Adjust bid strategy

If CTR is low:

• Creative isn't resonating → test new hooks/angles
• Audience mismatch → refine targeting
• Ad fatigue → refresh creative

If CPM is high:

• Audience too narrow → expand targeting
• High competition → try different placements
• Low relevance score → improve creative fit

Bid Strategy Progression

1. Start with maximize-conversions (no target) or cost caps while data is thin
2. Gather conversion data: roughly 30 per month per campaign on Google, about 50 per week per ad set to leave Meta's learning phase
3. Set targets (tCPA, tROAS, cost cap) at or slightly above trailing actuals
4. Move targets in 10 to 15% steps and wait one to two weeks between moves

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Retargeting Strategies

Funnel-Based Approach

Funnel Stage	Audience	Message	Goal
Top	Blog readers, video viewers	Educational, social proof	Move to consideration
Middle	Pricing/feature page visitors	Case studies, demos	Move to decision
Bottom	Cart abandoners, trial users	Urgency, objection handling	Convert

Retargeting Windows

Stage	Window	Frequency Cap
Hot (cart/trial)	1-7 days	Higher OK
Warm (key pages)	7-30 days	3-5x/week
Cold (any visit)	30-90 days	1-2x/week

Exclusions to Set Up

• Existing customers (unless upsell)
• Recent converters (7-14 day window)
• Bounced visitors (<10 sec)
• Irrelevant pages (careers, support)

Retarget with a different offer

The conventional retargeting playbook re-shows the same product/offer to people who didn't buy. Working premise: the most common reason someone didn't buy is that the offer wasn't right for them. Re-showing the same thing harder doesn't help.

Instead, retarget with different products, services, or offers from your catalog:

• Visitor clicked on protein powder, didn't buy → retarget with creatine (totally different category)
• Visitor downloaded a lead magnet, didn't book a call → retarget with a different lead magnet on a related topic
• Visitor viewed pricing, didn't sign up → retarget with a free audit or assessment instead

Measure it as its own ad set against same-offer retargeting; the lift varies by catalog depth and margin.

The four-ad retargeting layer

Build out your retargeting layer with these 4 ad types running simultaneously:

1. Objection-handling ad: directly addresses the most common reasons people didn't buy. To find these, outbound call every lead who didn't convert and ask why. The verbatim objections become the headline of this ad.
2. Proof testimonial carousel: multi-image/multi-slide carousel of testimonials and proof that supports the claims of your original ad
3. Other-offers CBO: your other best-performing ads for other products/services in one CBO, retargeted to the same audience
4. Value-first audit/assessment ad: wraps your call in a free piece of value. Whether they buy or not, they leave with something useful. Lowers the friction to engage.

Run the four together against the audience that did not convert, and judge the layer on blended CPA, not each ad alone.

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Landing Page Alignment (the headline-mirror trick)

The ad platform tests headlines against far more people than ever reach the landing page, so it resolves a winning headline much faster than on-page testing does. Use it that way:

1. Run 20-40 different headlines as ad variations
2. Pick the winner by CTR and downstream conversion, not CTR alone
3. Mirror the winning headline verbatim in the landing page H1, sub-headline, and lead-in copy
4. Measure the landing-page conversion rate before and after with suede-ab-testing; message match usually helps, but the size of the lift is the account's to prove

Keep at least 3 split tests running somewhere in the funnel (creative, page, offer, or post-conversion flow) at any given time.

Post-click page work itself belongs to suede-site-alchemy.

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Reporting & Analysis

Weekly Review

• Spend vs. budget pacing
• CPA/ROAS vs. targets
• Top and bottom performing ads
• Audience performance breakdown
• Frequency check (fatigue risk)
• Landing page conversion rate

Attribution Considerations

• Every platform counts the same sale; never sum platform-reported conversions
• Use UTM parameters consistently and reconcile against the CRM or backend
• Record each platform's attribution window with the number (Meta's API now offers only 1-day view and click windows up to 28 days)
• Judge on blended CAC and pipeline, not platform CPA alone; route model and reconciliation work to suede-attribution

Scaling discipline (net cash > ROAS percentage)

The most common scaling failure: a business at a 40 ROAS spending $5k/month, refusing to scale because "if I spend more, my ROAS will drop." This is the wrong frame.

Net cash flow > ROAS percentage at the business level:

• ROAS dropping from 10 → 5 sounds bad
• But if spend goes from $10k → $100k, you net dramatically more total profit
• The number to optimize is blended ROAS at the business level, not per-ad-set ROAS
• Even better: optimize net free cash flow, not ROAS at all

Find your break-even ROAS:

1. Calculate the absolute maximum you can pay to acquire a customer and still be profitable (factoring LTV)
2. That's your break-even ROAS / CPA ceiling
3. Scale until you approach that ceiling, not until your ad-account ROAS drops below an arbitrary preference

The monthly owner review:

• Block about 3 hours a month for the budget owner to read the raw numbers directly, not a summary from the analyst or media buyer
• First-hand familiarity with the data is what makes fast scale decisions safe

Outbound-call your leads who didn't convert:

• Every lead that downloaded a lead magnet or hit your funnel but didn't buy gets a call
• Ask why they didn't book, what was confusing, what the actual blocker was
• These verbatim answers become objection-handling ads (see Retargeting section)
• Massive insight-to-creative loop that most advertisers skip

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Platform Setup

Before launching campaigns, ensure proper tracking and account setup.

For complete setup checklists by platform: See references/platform-setup-checklists.md

For conversion pixel installation and event setup: See references/conversion-tracking.md

Universal Pre-Launch Checklist

Each box names the artifact that proves it. A box is checked when the artifact exists, not when it sounds true.

• Conversion tracking fired: the test conversion is visible in the platform's event manager with a timestamp
• Landing page loads in <3 sec: cite the PageSpeed / Lighthouse number and the test date
• Landing page mobile-friendly: a mobile render of the page, not a desktop assumption
• UTM parameters working: paste the resolved destination URL with parameters intact
• Budget set correctly: the daily/lifetime figure, against the cap the user stated
• Targeting matches intended audience: the saved audience definition, read back

Any unchecked box means do not recommend launch. Name the box and what is missing.

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Google RSA Output Spec (mandatory when generating RSAs)

When the user requests Google Ads RSAs, load references/rsa-output-spec.md and follow it exactly: hard character limits, required sidecar artifacts (ad groups, negatives, sitelinks, callouts), output order, template shape, CFM medical compliance, and the pre-send self-check. Do not output any RSA that violates it.

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Common Mistakes to Avoid

• Too many campaigns: fragmenting budget across campaigns none of which exit learning
• Optimizing for the wrong metric: clicks or CTR when the objective is conversions
• Only one ad per ad set: the algorithm has nothing to allocate between
• Overlapping audiences competing: the same account bidding against itself

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Tool Integrations

This pack does not include ad-network integrations. Work through an authorized platform UI, current export, API, or installed connector; verify current official documentation and the selected account before any mutation.

Platform family	Typical use	Verify before execution
Search ads	Capture declared intent	Query scope, match behavior, negatives, location, conversion action
Social feed ads	Create or harvest demand	Audience controls, placement, creative specs, attribution window
Professional-network ads	Reach role or account segments	Targeting availability, minimum audience, lead form and CRM mapping
Short-video ads	Visual discovery and creator-style demand	Placement specs, audio rights, age and regional policy

For the measurement contract, use references/conversion-tracking.md and route implementation and firing checks to suede-analytics.

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Boundaries

• Do not create, launch, pause, delete, or change campaigns, bids, audiences, or budgets without explicit authorization.
• Do not claim ROAS, attribution, or incrementality when conversion tracking and revenue inputs have not been verified.
• Do not recommend spend above the stated cap; if no cap exists, provide a bounded test budget and wait for approval.
• Do not target sensitive traits, evade platform policy, or present inferred audience attributes as verified facts.

When authorization is missing. If an authorized account or connector is present and the user asks for a mutation you have no approval for, stop before the call. Name the exact mutation and the account, campaign, or ad set it would hit. Offer: a draft-only change list they can apply themselves, a request for written approval on that specific change, or continuing read-only with an audit instead. Then wait, do not execute on assumed consent. (For the spend-cap case, the standing rule in the third boundary above already applies; don't restate it.)

Routing

• Need ad copy or visual variants -> use suede-ad-creative.
• Need conversion tracking implementation -> use suede-analytics; attribution models and cross-platform reconciliation -> use suede-attribution.
• Need post-click conversion work -> use suede-site-alchemy.
• Need CRM handoff or offline conversion design -> use suede-revops.
• From those skills, route paid channel, budget, bid, and campaign decisions back to suede-ads.