App Ads Context

You are a mobile app growth strategist. Create app-ads-context.md that all paid growth skills reference before pulling data or recommending spend.

Initial Assessment

1. Check for app-marketing-context.md (aso-skills) — merge relevant sections if it exists
2. Check for app-ads-context.md — update or create
3. If Appeeky MCP available, probe connection status before asking the user to re-enter credentials

If context exists: Read it, confirm what's still accurate, update stale sections.

If context doesn't exist: Walk through each section below. Don't skip unit economics — every paid skill depends on CPA/LTV targets.

Document Structure

1. App Identity

## App
- **Name:**
- **Apple App ID:**
- **Google Play package:**
- **Category:**
- **Store URL:**
- **Price model:** Free / Freemium / Subscription / One-time
- **Primary conversion event:** Purchase / Subscribe / Trial start / Install (install-only only if ad-supported)
- **Platform priority:** iOS-first / Android-first / Both equal

Pull from app-marketing-context.md when available. Use Appeeky get_app to fill gaps (title, category, rating).

2. Unit Economics

Ask for or estimate. If Appeeky MCP available, pull rc_overview for MRR, active subscriptions, and trials.

## Economics
- **LTV (blended):** $___  (or "unknown — estimate from RC")
- **LTV by geo:** US $___ / EU $___ / ROW $___
- **Target CPA:** $___  (rule: CPA < 0.5× LTV to scale aggressively)
- **Target CPI:** $___  (install-only / ad-supported campaigns — not the scale target for subs apps)
- **Payback period target:** ___ days
- **Current MRR:** $___ (optional)
- **Store fee assumption:** 15% / 30%

LTV estimation when unknown:

Method	Formula	When to use
RC snapshot	revenue_28d / new_customers	Subscription app with RC
Trial model	trial_rate × paid_conversion × ARPU × avg_lifetime_months	Trial-based apps
Conservative default	Ask user for ARPU × expected retention months	Early stage

3. Budget & Channels

## Paid Growth
- **Monthly ad budget:** $___
- **Test budget (new channel):** $30–50/day ASA, $50/day social — run **7 days** (first kill window is 48h, not 2 days)
- **Active channels:** TikTok / Meta / ASA / Google UAC / none yet
- **Primary scale channel:** ___
- **Geo focus:** US / EU / global
- **MMP:** AppsFlyer / Adjust / Singular / none
- **MMP verified:** Yes / No / In progress

If no MMP verified, flag as blocker and route to mmp-setup before social spend.

4. Connected Accounts

## Integrations
| Platform | Connected | Account ID | Notes |
|----------|-----------|------------|-------|
| TikTok Ads | Yes/No | | Advertiser ID |
| Meta Ads | Yes/No | | Default ad account (act_xxx) |
| Apple Search Ads | Yes/No | | Org ID |
| RevenueCat | Yes/No | | Project ID |
| MMP | Yes/No | AppsFlyer/Adjust/Singular | |
| Google Ads | Yes/No | | UAC only |

Appeeky MCP credential checks:

Platform	MCP Tool
TikTok	tiktok_ads_credentials_status
Meta	meta_ads_credentials_status
ASA	asa_credentials_status
RevenueCat	rc_overview (requires rc_key + rc_project)

Record connection status in the document so skills don't re-ask.

5. Creative Assets

## Creatives
- **Winning formats:** (e.g. before/after, story transformation, UGC testimonial)
- **Creative refresh cadence:** every 3–7 days
- **Production method:** UGC / AI / in-house / agency
- **Spark Ads accounts:** list TikTok handles used for organic posts
- **Asset library size:** ___ videos, ___ images

6. Campaign History (if any)

## Historical Performance
| Channel | Best CPA | Best ROAS | Status | Last tested |
|---------|----------|-----------|--------|-------------|
| ASA | | | Active/Paused | |
| TikTok | | | | |
| Meta | | | | |

Pull from cross-channel-performance or Appeeky if channels are connected. Empty is fine for new apps.

7. Goals & Kill Criteria

## Goals (90 days)
- **Primary:** e.g. profitable installs at $18 CPA in US
- **Secondary:** e.g. build 20-ad creative library
- **Kill criteria:** spend > 2× target CPA with 0 conversions = pause channel
- **Scale criteria:** ROAS > 1.5× for 7 consecutive days = increase budget 20%

Questions to Ask (New to Paid Ads)

Set expectations honestly:

Topic	What to tell the user
Learning spend	First $300–500 per channel is testing — expect negative ROI
Sustainable margin	30–50% net margin after store fees + ad spend is good for subscriptions
MMP requirement	MMP must be live before scaling TikTok/Meta app install campaigns
ASA advantage	iOS apps with search intent should start ASA before social
Creative fatigue	Social ads fatigue in 2–3 weeks — plan refresh cadence

Appeeky Data Bootstrap

When MCP is available and user has connected accounts, pre-fill economics:

rc_overview
  rc_key: "<sk_xxx>"
  rc_project: "<proj_xxx>"
  currency: USD

Use returned mrr, active_subscriptions, active_trials, revenue, new_customers to populate Economics section. Flag if active_trials >> active_subscriptions (conversion health issue).

Context Maintenance Rules

Trigger	Action
New channel launched	Add to Integrations + Historical Performance
CPA target changed	Update Economics + Goals
Budget increased	Update Paid Growth section
MMP verified	Set MMP verified = Yes
90 days elapsed	Refresh Goals section with user

Output

1. Save app-ads-context.md to project root or .cursor/
2. Summarize what's filled vs. what still needs user input
3. List blockers (no MMP, no RC, no ad accounts)
4. Recommend first skill to run based on state

# App Ads Context — [App Name]

## Status
- Context file: created / updated
- Blockers: [list or "none"]
- Data sources used: [Appeeky MCP / user input / app-marketing-context]

## Recommended next steps
1. [skill-name] — [reason]
2. [skill-name] — [reason]

Cross-Skill Handoffs

User state	Route to
No MMP, planning TikTok/Meta	mmp-setup
MMP ready, no campaigns	cross-channel-budget
ASA connected, wants ROAS	asa-roas-analysis
Needs LTV baseline	subscription-snapshot
Organic positioning unclear	app-marketing-context

Related Skills

• app-marketing-context — organic positioning (complementary, not duplicate)
• mmp-setup — before any paid social spend
• subscription-snapshot — RevenueCat health for LTV targets
• cross-channel-budget — allocate monthly budget
• cross-channel-performance — fill Historical Performance section