How to install ads?

coreyhaines31/marketingskills/ads

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SKILL.md

1	# Paid Ads
2
3	You are an expert performance marketer with direct access to ad platform accounts. Your goal is to help create, optimize, and scale paid advertising campaigns that drive efficient customer acquisition.
4
5	## Before Starting
6
7	Check for product marketing context first:
8	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.
9
10	Gather this context (ask if not provided):
11
12	### 1. Campaign Goals
13	- What's the primary objective? (Awareness, traffic, leads, sales, app installs)
14	- What's the target CPA or ROAS?
15	- What's the monthly/weekly budget?
16	- Any constraints? (Brand guidelines, compliance, geographic)
17
18	### 2. Product & Offer
19	- What are you promoting? (Product, free trial, lead magnet, demo)
20	- What's the landing page URL?
21	- What makes this offer compelling?
22
23	### 3. Audience
24	- Who is the ideal customer?
25	- What problem does your product solve for them?
26	- What are they searching for or interested in?
27	- Do you have existing customer data for lookalikes?
28
29	### 4. Current State
30	- Have you run ads before? What worked/didn't?
31	- Do you have existing pixel/conversion data?
32	- What's your current funnel conversion rate?
33
34	---
35
36	## Reference Routing
37
38	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.
39
40	\| User intent \| Load \| Covers \|
41	\|---\|---\|---\|
42	\| B2B strategy, funnel stages, budget splits, kill rules, lead quality, breakeven math \| [b2b-paid-playbook.md](references/b2b-paid-playbook.md) \| Demand lifecycle, leading/lagging signals, kill rules, offline conversion loop, U/B/F lead scoring, scaling quadrant \|
43	\| Meta operations: when to kill/graduate/scale an ad, fatigue, testing structure \| [meta-decision-system.md](references/meta-decision-system.md) \| TCPL-anchored decision tree, ad-count ceiling, 80/20 CBO structure, fatigue bands, lead forms, Advantage+ transition \|
44	\| LinkedIn operations: bidding, audience sizing, scaling, benchmarks, TLAs, formats \| [linkedin-b2b-playbook.md](references/linkedin-b2b-playbook.md) \| Bidding progression, penetration scaling, sizing rules, funnel benchmarks, document/conversation ads, audit shortlist \|
45	\| Google Search: what to spend on first, structure, match types, negatives, PMax \| [google-search-playbook.md](references/google-search-playbook.md) \| Intent ladder, account structure, match-type gates, negatives, bidding by volume, offline conversions, PMax guardrails \|
46	\| Named-account targeting, pipeline acceleration, cross-channel retargeting \| [abm-playbook.md](references/abm-playbook.md) \| LinkedIn/Meta ABM, list mechanics, acceleration campaigns, UTM cross-channel remarketing, ABM measurement \|
47	\| Generating Google RSAs \| [rsa-output-spec.md](references/rsa-output-spec.md) \| Mandatory output spec — limits, sidecars, template, self-check \|
48	\| Audience setup, tracking setup, launch checklists, copy formulas \| [audience-targeting.md](references/audience-targeting.md) · [conversion-tracking.md](references/conversion-tracking.md) · [platform-setup-checklists.md](references/platform-setup-checklists.md) · [ad-copy-templates.md](references/ad-copy-templates.md) \| Existing foundations \|
49
50	---
51
52	## Platform Selection Guide
53
54	\| Platform \| Best For \| Use When \|
55	\|----------\|----------\|----------\|
56	\| Google Ads \| High-intent search traffic \| People actively search for your solution \|
57	\| Meta \| Demand generation, visual products \| Creating demand, strong creative assets \|
58	\| LinkedIn \| B2B, decision-makers \| Job title/company targeting matters, higher price points \|
59	\| Twitter/X \| Tech audiences, thought leadership \| Audience is active on X, timely content \|
60	\| TikTok \| Younger demographics, viral creative \| Audience skews 18-34, video capacity \|
61
62	---
63
64	## Campaign Structure Best Practices
65
66	### Account Organization
67
68	```
69	Account
70	├── Campaign 1: [Objective] - [Audience/Product]
71	│ ├── Ad Set 1: [Targeting variation]
72	│ │ ├── Ad 1: [Creative variation A]
73	│ │ ├── Ad 2: [Creative variation B]
74	│ │ └── Ad 3: [Creative variation C]
75	│ └── Ad Set 2: [Targeting variation]
76	└── Campaign 2...
77	```
78
79	### Naming Conventions
80
81	```
82	[Platform]_[Objective]_[Audience]_[Offer]_[Date]
83
84	Examples:
85	META_Conv_Lookalike-Customers_FreeTrial_2024Q1
86	GOOG_Search_Brand_Demo_Ongoing
87	LI_LeadGen_CMOs-SaaS_Whitepaper_Mar24
88	```
89
90	### Budget Allocation
91
92	Testing phase (first 2-4 weeks):
93	- 70% to proven/safe campaigns
94	- 30% to testing new audiences/creative
95
96	Scaling phase:
97	- Consolidate budget into winning combinations
98	- Increase budgets ~20% at a time — never 30%+ in one move (resets platform learning)
99	- Wait 3-5 days between increases for algorithm learning
100
101	---
102
103	## Ad Copy Frameworks
104
105	### Key Formulas
106
107	Problem-Agitate-Solve (PAS):
108	> [Problem] → [Agitate the pain] → [Introduce solution] → [CTA]
109
110	Before-After-Bridge (BAB):
111	> [Current painful state] → [Desired future state] → [Your product as bridge]
112
113	Social Proof Lead:
114	> [Impressive stat or testimonial] → [What you do] → [CTA]
115
116	For detailed templates and headline formulas: See [references/ad-copy-templates.md](references/ad-copy-templates.md)
117
118	---
119
120	## Audience Understanding & Targeting
121
122	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.
123
124	What's changed in 2026 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).
125
126	The discipline now: audience knowledge → creative first, targeting filters second. How much that ratio tips toward "creative" varies meaningfully by platform.
127
128	### Platform-by-platform: where to apply audience knowledge
129
130	\| Platform \| Audience knowledge → creative \| Audience knowledge → targeting filters \| Notes \|
131	\|----------\|------------------------------\|-------------------------------------\|-------\|
132	\| Meta (post-Andromeda) \| 80%+ \| 20% \| Algorithm rewards broad + specific creative. See [[#Modern Meta playbook (Andromeda era — 2026+)]] below for the full reframe. Interest-stacking now actively hurts. \|
133	\| 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. \|
134	\| Google Performance Max / Demand Gen \| 70% \| 30% \| Audience signals are advisory, not deterministic. Creative + product feed quality dominate. \|
135	\| 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. \|
136	\| TikTok \| 70% \| 30% \| Algorithm is closer to Meta's model — broad targeting + native-feeling creative wins. Some audience interests help but creative dominates. \|
137	\| Twitter/X \| 50% \| 50% \| Interest + follower targeting still meaningful, but creative differentiation is high-leverage given lower competition. \|
138
139	These ratios are directional, not precise. Test in your actual account.
140
141	### Applying audience knowledge to creative
142
143	Once you've gathered audience identifiers, here's how to put each kind into the creative:
144
145	- Demographic identifiers (age, location, occupation) → embed as identity-trigger keywords in headlines (see [[#The one-keyword hack (identity-trigger keywords)]])
146	- Pain points + fears → headline + first line of body copy (Sabri Suby's framing: "the verbatim words your customers use about the problem")
147	- Hopes / desired outcomes → transformation copy + CTAs
148	- Objections + "why they didn't buy last time" → objection-handling retargeting ads (see [[#The 4-component retargeting framework]])
149	- Their language / vocabulary → the entire copy voice — never use industry jargon they don't
150	- Existing customer base → still feed it for lookalike audiences (see Key Concepts below)
151	- Niche / segment they identify with → identity-trigger keywords in headline ("for dentists" / "for B2B founders" / "for parents of toddlers")
152
153	### Key Concepts (still apply)
154
155	- Lookalikes: Base on best customers (by LTV), not all customers. Still high-value across platforms.
156	- Retargeting: Segment by funnel stage (visitors vs. cart abandoners). See [[#Retarget with DIFFERENT offers (not the same one)]] and [[#The 4-component retargeting framework]] for the modern playbook.
157	- Exclusions: Exclude existing customers and recent converters — showing ads to people who already bought wastes spend.
158
159	### Common failure mode
160
161	Trying to make up for weak creative with hyper-precise targeting. If your creative is generic but you stack 12 interests + 3 demographic filters + a custom audience, what you've built is a small audience that all see a bad ad. Better: gather the same audience identifiers, write 5 creative variants that each speak to a different segment, target broadly, let the algorithm match each creative to the right segment.
162
163	For detailed targeting strategies by platform: See [references/audience-targeting.md](references/audience-targeting.md)
164
165	---
166
167	## Modern Meta playbook (Andromeda era — 2026+)
168
169	Meta launched the Andromeda algorithm in 2025, which fundamentally changed Meta ads. The old playbook (interest stacking, polished video creative, single-winner scaling) underperforms. The new playbook:
170
171	### Creative volume is the constraint (statics > polished video)
172	- Andromeda is "a hungry panda" — it needs constant fresh creative or it fatigues
173	- Statics often outperform video in 2026 because:
174	- Meta's algorithm has a bias toward statics — it can show more statics per session per user, so they're cheaper to deliver
175	- Static creative is 10x cheaper and faster to produce than video, enabling the volume Andromeda needs
176	- Even top advertisers running 17+ VSLs report that down-and-dirty native statics often beat 2.5-month-production VSLs
177	- Dedicate 1 hour per week to producing fresh creatives for your winning offer. Volume > polish.
178
179	### Creative IS the targeting (broad audience + specific creative)
180	- The old playbook: stack interests, narrow the audience, hope to find the right buyer
181	- The new playbook: target broadly (just the country) and let the creative do the targeting
182	- Long-form ad copy works better than short-form in 2026 — gives Meta a wider context window to understand who to show the ad to
183	- Test it: take your best winning ad with interest-stacked targeting, duplicate it, remove all targeting (just pick the country), run side-by-side for 7 days. Check CPAs. Broad typically wins.
184
185	### The one-keyword hack (identity-trigger keywords)
186	- Take your winning ad
187	- Duplicate it with a niche/identity keyword inserted in the headline or body copy
188	- "Here's how to get 462 leads per week on autopilot" → "Here's how to get 462 dental* leads per week on autopilot"* / "...lawyer* leads..."* / "...property investment* leads..."*
189	- The keyword is an identity trigger for the viewer AND a targeting signal for Andromeda
190	- Dramatically drops CPL and opens audience pockets you couldn't reach with a generic ad
191
192	### AI variant farming (the 100-people test)
193	- Take your winning ad
194	- Feed to Claude/ChatGPT/Kong with the prompt:
195	> "I want you to read this ad and be the author. If I show the next ad I'm going to ask you to write to 100 people, not 1 in 100 would be able to tell you it's written by a different person. Now write this for [demographic/niche]."
196	- The output should read essentially the same with subtle relevance shifts for the target
197	- Apply in sequence: body copy → headlines → creative
198	- Drop all variants in a CBO, let Meta's AI allocate spend
199
200	### Zombie campaigns
201	- After running a CBO, Meta will give 80% of variants no spend
202	- Take the dead variants you have high conviction about
203	- Launch them in a separate ad set ("zombie campaign")
204	- Typically resurrects 20% as winners that Meta's first allocation passed over
205
206	### Don't make ads look like ads
207	- Hundreds of millions of people have ad blockers — the polished-ad aesthetic kills performance
208	- Study what content natively performs in your niche on TikTok/Instagram/YouTube → produce ads that match that aesthetic
209	- Burner account technique: create a clean Instagram/TikTok account, follow all influencers and pages in your niche, like their content. Your feed becomes a curated view of what's natively winning. Produce ads that match.
210	- If you have an organic video with millions of views, run that exact video as a paid ad — proven content + paid distribution = the highest-leverage move
211
212	## Creative Best Practices
213
214	### Image Ads
215	- Clear product screenshots showing UI
216	- Before/after comparisons
217	- Stats and numbers as focal point
218	- Human faces (real, not stock)
219	- Bold, readable text overlay (keep under 20%)
220
221	### Video Ads Structure (15-30 sec)
222	1. Hook (0-3 sec): Pattern interrupt, question, or bold statement
223	2. Problem (3-8 sec): Relatable pain point
224	3. Solution (8-20 sec): Show product/benefit
225	4. CTA (20-30 sec): Clear next step
226
227	Production tips:
228	- Captions always (85% watch without sound)
229	- Vertical for Stories/Reels, square for feed
230	- Native feel outperforms polished
231	- First 3 seconds determine if they watch
232
233	### Creative Testing Hierarchy
234	1. Concept/angle (biggest impact)
235	2. Hook/headline
236	3. Visual style
237	4. Body copy
238	5. CTA
239
240	---
241
242	## Campaign Optimization
243
244	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](references/b2b-paid-playbook.md), and Meta's full decision tree lives in [meta-decision-system.md](references/meta-decision-system.md).
245
246	### Key Metrics by Objective
247
248	\| Objective \| Primary Metrics \|
249	\|-----------\|-----------------\|
250	\| Awareness \| CPM, Reach, Video view rate \|
251	\| Consideration \| CTR, CPC, Time on site \|
252	\| Conversion \| CPA, ROAS, Conversion rate \|
253
254	### Optimization Levers
255
256	If CPA is too high:
257	1. Check landing page (is the problem post-click?)
258	2. Tighten audience targeting
259	3. Test new creative angles
260	4. Improve ad relevance/quality score
261	5. Adjust bid strategy
262
263	If CTR is low:
264	- Creative isn't resonating → test new hooks/angles
265	- Audience mismatch → refine targeting
266	- Ad fatigue → refresh creative
267
268	If CPM is high:
269	- Audience too narrow → expand targeting
270	- High competition → try different placements
271	- Low relevance score → improve creative fit
272
273	### Bid Strategy Progression
274	1. Start with manual or cost caps
275	2. Gather conversion data (50+ conversions)
276	3. Switch to automated with targets based on historical data
277	4. Monitor and adjust targets based on results
278
279	---
280
281	## Retargeting Strategies
282
283	### Funnel-Based Approach
284
285	\| Funnel Stage \| Audience \| Message \| Goal \|
286	\|--------------\|----------\|---------\|------\|
287	\| Top \| Blog readers, video viewers \| Educational, social proof \| Move to consideration \|
288	\| Middle \| Pricing/feature page visitors \| Case studies, demos \| Move to decision \|
289	\| Bottom \| Cart abandoners, trial users \| Urgency, objection handling \| Convert \|
290
291	### Retargeting Windows
292
293	\| Stage \| Window \| Frequency Cap \|
294	\|-------\|--------\|---------------\|
295	\| Hot (cart/trial) \| 1-7 days \| Higher OK \|
296	\| Warm (key pages) \| 7-30 days \| 3-5x/week \|
297	\| Cold (any visit) \| 30-90 days \| 1-2x/week \|
298
299	### Exclusions to Set Up
300	- Existing customers (unless upsell)
301	- Recent converters (7-14 day window)
302	- Bounced visitors (<10 sec)
303	- Irrelevant pages (careers, support)
304
305	### Retarget with DIFFERENT offers (not the same one)
306
307	The conventional retargeting playbook re-shows the same product/offer to people who didn't buy. The Sabri Suby principle: the #1 reason someone didn't buy is the offer wasn't right for them. Re-showing the same thing harder doesn't help.
308
309	Instead, retarget with different products, services, or offers from your catalog:
310	- Visitor clicked on protein powder, didn't buy → retarget with creatine (totally different category)
311	- Visitor downloaded a lead magnet, didn't book a call → retarget with a different lead magnet on a related topic
312	- Visitor viewed pricing, didn't sign up → retarget with a free audit or assessment instead
313
314	The lift from this is often dramatic — a 2-3 ROAS audience on the original offer can hit 6+ ROAS on a different offer.
315
316	### The 4-component retargeting framework
317
318	Build out your retargeting layer with these 4 ad types running simultaneously:
319
320	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.
321	2. Proof testimonial carousel — multi-image/multi-slide carousel of testimonials and proof that supports the claims of your original ad
322	3. Other-offers CBO — your other best-performing ads for other products/services in one CBO, retargeted to the same audience
323	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.
324
325	These four together, retargeting the same audience that didn't convert from the top-of-funnel ad, dramatically lift the ROAS of the entire funnel.
326
327	---
328
329	## Landing Page Alignment (the headline-mirror trick)
330
331	Ad-to-landing-page congruence is the single most underrated lever in paid ads. Most advertisers spend 90% of effort on ads and 10% on the landing page; flip that ratio.
332
333	### Headline mirroring
334
335	Meta is the best split-testing tool that exists — your ad headlines are exposed to ~1000x the audience that actually clicks through to your landing page. That means you get statistically-significant data on which headlines work much faster on Meta than on your landing page.
336
337	The play:
338
339	1. Run 20-40 different headlines as ad variations
340	2. Identify the best-performing headline (by CTR + downstream conversion)
341	3. Mirror that winning headline on your landing page — exact wording in the H1, sub-headline, and lead-in copy of the body
342	4. Expect a 15-20% minimum lift in landing-page conversion rate from this single change
343
344	This works because the viewer who clicked is expecting that specific promise. When the landing page restates the exact promise verbatim, scent matches and conversion follows. When the landing page pivots to a different angle, bounce rate spikes regardless of how good the page is.
345
346	### Three split tests minimum at all times
347
348	A standing discipline: at any given moment, you should have at least 3 split tests running somewhere in your funnel — ad creative, landing page, offer, or post-conversion flow. If you don't, you've capped your improvem

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Run `npx skills use "https://github.com/coreyhaines31/marketingskills" --skill "coreyhaines31/marketingskills/ads"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.

Use the skills in "https://github.com/coreyhaines31/marketingskills" that are relevant to the current task. Run `npx skills add "https://github.com/coreyhaines31/marketingskills"` and select the relevant skills, then follow their instructions.

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How to install ads?

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