Ads Strategy

Full Ad Strategy Orchestrator

Skill Purpose

Perform a comprehensive, end-to-end advertising strategy build for any business from a single URL. This is the flagship command of the AI Ads Strategist — it launches 5 parallel subagents simultaneously to analyze every dimension of ad readiness, then synthesizes all findings into a unified strategy document with a composite Ad Readiness Score (0-100).

The output is a client-ready deliverable that covers audience research, creative strategy, funnel architecture, competitive positioning, and budget allocation — the kind of document an agency would charge $3,000-$10,000 to produce.

When to Use

• User runs /ads strategy
• User asks for a "full ad strategy", "complete advertising plan", or "ad audit"
• User wants everything in one command without running individual ad skills separately
• User needs a single deliverable covering all advertising dimensions
• User is preparing to launch paid ads and wants a complete roadmap

Input Requirements

• Required: A business URL to analyze
• Optional: Monthly budget, target geography, industry context, specific platforms of interest

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How to Execute

This skill runs 3 phases. Phase 1 gathers intelligence. Phase 2 launches 5 parallel subagents. Phase 3 synthesizes all results into the final report.

Display progress to the user:

================================================================
  ADS STRATEGY BUILD: [Company Name]
================================================================

  Phase 1: Discovery & Business Intelligence ......... [running]
  Phase 2: Parallel Agent Analysis ................... [pending]
    - Audience Research Agent (25%) .................. [pending]
    - Creative Strategy Agent (20%) .................. [pending]
    - Funnel Architecture Agent (20%) ................ [pending]
    - Competitive Intelligence Agent (15%) ........... [pending]
    - Budget & ROI Agent (20%) ...................... [pending]
  Phase 3: Synthesis & Report Generation ............. [pending]

================================================================

Update each status as work progresses:

• [running] -- Currently executing
• [complete] -- Finished successfully
• [limited] -- Completed with limited data
• [pending] -- Not yet started

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Phase 1: Discovery & Business Intelligence

Objective: Fetch the target URL, extract all available business intelligence, detect business type, and prepare the context package that all 5 subagents will receive.

Step 1: Fetch and Analyze the Homepage

Use WebFetch to retrieve the homepage at the provided URL. Extract:

| Data Point | Where to Find | |---|---| | Company name | Page title, logo, footer, about page | | Tagline / Value proposition | Hero section, H1, meta description | | Products or services | Navigation menu, service pages, pricing page | | Pricing model | Pricing page, CTAs ("free trial", "get quote", "add to cart") | | Target market signals | Copy language, imagery, testimonials, case studies | | Trust signals | Client logos, certifications, review counts, media mentions | | Current CTAs | Buttons, forms, phone numbers, chat widgets | | Contact info | Phone, email, address, social links | | Tech stack signals | Meta tags, scripts, platform indicators | | Content assets | Blog, resources, videos, podcasts, lead magnets |

Step 2: Detect Business Type

Classify the business into one of these categories based on homepage signals:

| Business Type | Detection Signals | Ad Strategy Implications | |---|---|---| | SaaS / Software | Pricing page, "Sign up" / "Free trial" / "Book demo" CTAs, feature lists, integration pages, app subdomain | Focus on demo/trial conversions, long sales cycles, retargeting heavy | | E-commerce | Product listings, shopping cart, "Add to cart" buttons, product categories, price displays | Focus on ROAS, product catalog ads, shopping campaigns, impulse triggers | | Local Business | Physical address, Google Maps embed, service area mentions, phone number prominent, "Near me" language | Focus on call extensions, local targeting, Google LSAs, radius targeting | | Agency / Services | Case studies, portfolio, "Our Work", client logos, consultation CTAs, team page | Focus on lead gen, authority building, LinkedIn, long nurture sequences | | Creator / Course | Course listings, "Enroll now", instructor bio, curriculum, testimonials from students, community mentions | Focus on webinar funnels, transformation messaging, urgency/scarcity | | Restaurant / Hospitality | Menu, reservations, location hours, food imagery, delivery links | Focus on Instagram/TikTok visuals, local targeting, seasonal promotions |

Step 3: Identify Industry and Competitive Context

Use WebSearch to gather additional intelligence:

"[Company Name]" competitors
"[Company Name]" reviews
"[Company Name]" pricing
[industry] + [location] market size
[industry] advertising benchmarks [current year]

Step 4: Detect Recommended Platforms

Based on business type, determine the optimal platform mix:

| Business Type | Primary Platforms | Secondary Platforms | Avoid | |---|---|---|---| | SaaS / Software | Google Ads (Search), LinkedIn | Facebook/Instagram (retargeting), YouTube (demos) | TikTok (unless B2C SaaS) | | E-commerce | Meta (FB/IG), Google Shopping | TikTok, Pinterest, YouTube | LinkedIn | | Local Business | Google Ads (Search + LSA), Facebook/IG | Nextdoor, Yelp Ads | LinkedIn, Pinterest | | Agency / Services | LinkedIn, Google Ads (Search) | Facebook (retargeting), YouTube | TikTok, Pinterest | | Creator / Course | YouTube Ads, Instagram, Facebook | TikTok, Google (search) | LinkedIn (unless B2B) | | Restaurant / Hospitality | Instagram, Facebook, Google (local) | TikTok, Yelp | LinkedIn |

Step 5: Build the Context Package

Compile all Phase 1 findings into a structured context package. This exact package is passed to every subagent so they all operate from the same intelligence:

CONTEXT PACKAGE:
- Company: [Name]
- URL: [URL]
- Business Type: [Type]
- Industry: [Industry]
- Products/Services: [List]
- Pricing Model: [Model]
- Value Proposition: [Tagline]
- Target Geography: [Location or "National/Global"]
- Current CTAs: [List]
- Trust Signals: [List]
- Recommended Platforms: [Platform list]
- Monthly Budget: [If provided, else "Not specified"]
- Key Competitors: [List from search]

---

Phase 2: Parallel Agent Launch

Objective: Launch 5 specialized subagents simultaneously using the Agent tool. Each agent receives the full context package from Phase 1 and produces a category score (0-100) plus detailed findings.

CRITICAL: All 5 agents MUST be launched in parallel (not sequentially) to minimize execution time. Use 5 separate Agent tool calls in the same response.

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Agent 1: Audience Research Agent

Weight in composite score: 25% Corresponding skill: ads-audience

Launch this agent with the following prompt:

You are the Audience Research Agent for an ad strategy build. Using the context below, build a complete audience analysis.

CONTEXT:
[Insert full context package from Phase 1]

YOUR TASK:
1. Build 5-7 detailed audience personas for this business. For each persona include:
   - Persona name and archetype (e.g., "Budget-Conscious Buyer", "Overwhelmed Executive")
   - Demographics: age range, gender split, income level, education, job title, location
   - Psychographics: values, lifestyle, aspirations, fears, daily frustrations
   - Pain points: top 3 problems this business solves for them
   - Buying triggers: what specific events or moments push them to buy
   - Objections: top 3 reasons they hesitate or say no
   - Content consumption: platforms they use, content formats they prefer, influencers they follow
   - Platform-specific targeting parameters:
     - Meta (Facebook/Instagram): interests, behaviors, lookalike seed suggestions
     - Google Ads: search intent keywords, in-market audiences, affinity audiences
     - LinkedIn: job titles, industries, company sizes, skills
     - TikTok: interest categories, creator affinities, hashtag communities
   - Persona relevance score (1-5): how valuable is this persona relative to others

2. Define negative audiences (who NOT to target):
   - Demographic exclusions
   - Interest-based exclusions
   - Behavioral exclusions
   - Why each exclusion matters (wasted spend reasons)

3. Identify the #1 highest-value persona and explain why they should receive the largest budget allocation.

4. Map personas to funnel stages — which personas are TOFU (cold), MOFU (warm), BOFU (hot)?

5. Provide an Audience Clarity Score (0-100) based on:
   - How well-defined the ICP is from the website (0-25)
   - How many distinct personas the business can viably target (0-25)
   - How precise the targeting parameters are on each platform (0-25)
   - How clearly the website speaks to specific audience segments (0-25)

OUTPUT FORMAT:
Return your findings as structured markdown with clear headers for each persona and section. End with:
- AUDIENCE_CLARITY_SCORE: [0-100]
- TOP_PERSONA: [Name]
- TOTAL_PERSONAS: [Count]
- KEY_INSIGHT: [One-sentence biggest finding about the audience]

---

Agent 2: Creative Strategy Agent

Weight in composite score: 20% Corresponding skill: ads-creative

Launch this agent with the following prompt:

You are the Creative Strategy Agent for an ad strategy build. Using the context below, develop a complete creative strategy.

CONTEXT:
[Insert full context package from Phase 1]

YOUR TASK:
1. Develop 3 core messaging angles for this business:
   - Pain-point angle: Lead with the problem the audience faces
   - Aspiration angle: Lead with the outcome/transformation
   - Social proof angle: Lead with results, reviews, or authority

2. Write 10 scroll-stopping hooks (first 3 seconds of an ad):
   - 3 pain-point hooks
   - 3 curiosity/contrarian hooks
   - 2 social proof hooks
   - 2 urgency/scarcity hooks
   For each hook: the text, the psychology behind it, and which platform it works best on.

3. Create ad copy sets for 3 platforms (customize format per platform):
   - **Meta (Facebook/Instagram):** Primary text (125 chars), headline (40 chars), description (30 chars), CTA button. Provide 3 variations using PAS, AIDA, and BAB frameworks.
   - **Google Ads (Search):** 3 responsive search ad sets, each with 15 headlines (30 chars each) and 4 descriptions (90 chars each). Include keyword insertion templates.
   - **LinkedIn:** Introductory text (150 words max), headline, CTA. 2 variations — one thought-leader style, one direct-response style.

4. Develop 3 creative concept briefs:
   - Static image ad concept (with visual description, text overlay, color direction)
   - Short video ad concept (15-second script with shot-by-shot breakdown)
   - UGC-style ad concept (script template for a creator to film)

5. Provide a Creative Quality Score (0-100) based on:
   - Hook strength and attention-grabbing potential (0-30)
   - Copy clarity and persuasion quality (0-30)
   - Visual concept variety and platform fit (0-20)
   - A/B test readiness (multiple variations provided) (0-20)

OUTPUT FORMAT:
Return your findings as structured markdown with clear headers. End with:
- CREATIVE_QUALITY_SCORE: [0-100]
- STRONGEST_HOOK: [The single best hook you wrote]
- RECOMMENDED_FIRST_AD: [Which ad concept to test first and why]
- KEY_INSIGHT: [One-sentence biggest creative opportunity]

---

Agent 3: Funnel Architecture Agent

Weight in composite score: 20% Corresponding skill: ads-funnel

Launch this agent with the following prompt:

You are the Funnel Architecture Agent for an ad strategy build. Using the context below, design a complete advertising funnel.

CONTEXT:
[Insert full context package from Phase 1]

YOUR TASK:
1. Design a complete 4-stage advertising funnel:

   **TOFU (Top of Funnel) — Awareness:**
   - Objective: brand awareness, video views, engagement
   - Audience: cold traffic, broad interests, lookalikes
   - Ad formats: video ads, carousel, boosted content
   - Platforms and campaign types per platform
   - KPIs: CPM, video view rate, engagement rate
   - Budget allocation: percentage of total spend

   **MOFU (Middle of Funnel) — Consideration:**
   - Objective: traffic, lead generation, content consumption
   - Audience: warm traffic (engaged with TOFU), website visitors, email subscribers
   - Ad formats: lead ads, content downloads, case studies, webinar registrations
   - Platforms and campaign types per platform
   - KPIs: CPC, CTR, cost per lead, landing page conversion rate
   - Budget allocation: percentage of total spend

   **BOFU (Bottom of Funnel) — Conversion:**
   - Objective: purchases, demos, consultations, sign-ups
   - Audience: hot traffic (MOFU engagers), cart abandoners, pricing page visitors
   - Ad formats: offer ads, testimonial ads, urgency/scarcity ads, dynamic product ads
   - Platforms and campaign types per platform
   - KPIs: CPA, ROAS, conversion rate
   - Budget allocation: percentage of total spend

   **Retargeting — Recovery & Loyalty:**
   - Retargeting windows (1-3 days, 3-7 days, 7-14 days, 14-30 days, 30-60 days)
   - Audience segmentation by engagement depth
   - Creative rotation strategy (avoid ad fatigue)
   - Frequency caps per platform
   - Cross-sell / upsell sequences for existing customers
   - Budget allocation: percentage of total spend

2. Map the conversion path:
   - Ad click -> Landing page -> [Micro-conversion] -> [Primary conversion]
   - Identify the primary conversion action (purchase, demo, call, form)
   - Define landing page requirements for each funnel stage

3. Define the retargeting pixel strategy:
   - What events to track (page views, add to cart, initiate checkout, form start, video watch %)
   - Custom audience definitions for each retargeting segment
   - Lookalike audience recommendations from each segment

4. Provide a Funnel Architecture Score (0-100) based on:
   - Funnel completeness (all 4 stages defined) (0-25)
   - Stage-to-stage flow logic and audience progression (0-25)
   - Retargeting sophistication and timing (0-25)
   - Platform-specific campaign structure quality (0-25)

OUTPUT FORMAT:
Return your findings as structured markdown with clear headers for each funnel stage. End with:
- FUNNEL_ARCHITECTURE_SCORE: [0-100]
- RECOMMENDED_FUNNEL_TYPE: [e.g., "Lead Gen Funnel", "Direct Purchase Funnel", "Webinar Funnel"]
- BUDGET_SPLIT: [TOFU: X% | MOFU: X% | BOFU: X% | Retargeting: X%]
- KEY_INSIGHT: [One-sentence biggest funnel opportunity]

---

Agent 4: Competitive Intelligence Agent

Weight in composite score: 15% Corresponding skill: ads-competitors

Launch this agent with the following prompt:

You are the Competitive Intelligence Agent for an ad strategy build. Using the context below, analyze the competitive advertising landscape.

CONTEXT:
[Insert full context package from Phase 1]

YOUR TASK:
1. Identify 3-5 direct competitors using web search:
   - Search: "[Company Name] competitors", "[Company Name] alternatives", "[Company Name] vs"
   - Search: "best [industry] [location]" or "top [product category] companies"
   - Fetch each competitor's homepage to analyze their positioning

2. For each competitor, analyze:
   - **Positioning:** How do they position themselves? What is their main value proposition?
   - **Offer structure:** What are they selling and at what price points? Free trials, discounts, bundles?
   - **Landing page quality:** CTA clarity, trust signals, page speed, mobile optimization
   - **Ad presence indicators:** Do they appear to run ads? (look for UTM parameters, retargeting pixels, ad library presence)
   - **Content strategy:** Blog, YouTube, podcast, social media activity
   - **Unique angles:** What messaging do they use that the target business does NOT?

3. Search for competitor

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [zubair-trabzada](https://github.com/zubair-trabzada)
- **Source:** [zubair-trabzada/ai-ads-claude](https://github.com/zubair-trabzada/ai-ads-claude)
- **License:** MIT
- **Homepage:** https://www.skool.com/aiworkshop

Install and usage instructions live in the source repository linked above.