Asa Roas Analysis logo

Asa Roas Analysis

Organization
appeeky
asa-roas-analysis

When the user wants Apple Search Ads profitability, ROAS, or spend vs RevenueCat revenue analysis. Use when the user mentions "ASA ROAS", "Apple Search Ads profit", "ASA revenue", "keyword profitability", "which ASA keywords make money", or joining ASA with RevenueCat. For campaign structure and bidding strategy, see aso-skills apple-search-ads. For automated scale recommendations, see asa-admaxxing.

Overview

Publisherappeeky
Repositoryua-skills
Skill nameasa-roas-analysis
Stars
73
Forks
5
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by appeeky on GitHub. Read the source before you install it.

Installation

Install the Asa Roas Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/appeeky/ua-skills/tree/main/skills/asa-roas-analysis
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/appeeky/ua-skills.git /tmp/ua-skills
mkdir -p .claude/skills
cp -r /tmp/ua-skills/skills/asa-roas-analysis .claude/skills/asa-roas-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Asa Roas Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Asa Roas Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Asa Roas Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Apple Search Ads ROAS Analysis

You are an Apple Search Ads analyst. Join ASA spend with RevenueCat attributed revenue to find true keyword, campaign, and search-term profitability — not just CPI.

Why ASA ROAS Is Different

ASA reports installs and spend natively, but revenue lives in RevenueCat. Without the join:

  • Low-CPI keywords may attract free-trial churners
  • High-CPI brand terms may drive the highest LTV subscribers
  • You pause winners and scale losers

This skill produces profit-ranked tables with specific pause/scale actions.

Prerequisites

Before pulling data, verify integrations:

CheckMCP Tool
ASA connectedasa_credentials_status
RevenueCat connectedrc_overview with rc_key + rc_project
Playbook readinessasa_playbook_status

Read app-ads-context.md for target CPA, LTV, and geo focus.

Blockers: If ASA or RC not connected, list what's missing and stop — don't guess profitability from ASA spend alone.

Data Pull

Primary profitability join

asa_profitability
  rc_key: "<sk_xxx>"
  level: keyword          # or campaign | adgroup | search_term | country
  days: 14
  currency: USD
  min_spend: 10
  insights: true
ParameterWhen to change
level: keywordWeekly optimization, bid decisions
level: campaignBudget reallocation across campaign types
level: adgroupCPP/CPS performance comparison
level: search_termNegative keyword candidates
level: countryGeo ROAS before expansion
days: 7Recent changes, fresh creative tests
days: 30Stable LTV apps, sufficient volume
min_spend: 20Filter noise on low-spend terms

Supporting context

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

rc_attribution_summary
  rc_key: "<sk_xxx>"
  rc_project: "<proj_xxx>"

Use rc_overview for MRR and subscription health baseline. Use rc_attribution_summary to compare ASA share vs. other media sources.

Metrics to Report

MetricFormulaGood benchmark (subscription)
SpendASA report—
Attributed revenueRC join—
ROASrevenue / spend> 1.0 break-even; > 1.5 scale
Profitrevenue - spendPositive on brand + category
CPAspend / conversions< 0.5× LTV to scale
CPTspend / tapsVaries by category
CVRinstalls / taps> 30% investigate if below
TTRtaps / impressions> 5% strong

Important: Compare ROAS to targets in app-ads-context.md, not generic benchmarks. A 0.9× ROAS app with 60% margins may still be profitable.

Analysis Workflow

Step 1 — Summary

Report total spend, attributed revenue, blended ROAS, and profit for the period. State whether ASA is net profitable.

Step 2 — Rank by profit

Sort keywords/campaigns by profit (not ROAS alone). A keyword with $200 profit at 1.2× ROAS beats one with $20 profit at 3.0× ROAS.

Step 3 — Segment by campaign type

Campaign typeExpected ROASAction if below
BrandHighest (1.5–3.0×)Investigate product page CVR
CategoryMedium (0.8–1.5×)Test CPP routing
CompetitorLower (0.5–1.0×)Tighten bids, add negatives
DiscoveryVariableMine search terms, promote winners

Step 4 — Flag bleeders

Keywords/search terms meeting all:

  • ROAS < 1.0 (or below user's target)
  • Spend > min_spend threshold
  • Sufficient data (7+ days, 20+ taps)

→ Recommend pause or bid reduction. Route negatives to asa-negative-keywords.

Step 5 — Flag scalers

Keywords with:

  • ROAS > 1.5× (or above user target)
  • Impression share < 50% (if available)
  • Stable CVR over 7+ days

→ Recommend bid increase 10–15%. Route to asa-admaxxing for playbook validation.

Scale Gate

Before recommending budget increases:

asa_review_country_gate
  app_id: "<apple_app_id>"
  min_rating: 4.5

Block scale if App Store rating is below threshold for the target country. Low ratings crush CVR — scaling spend wastes budget.

Interpretation Guide

PatternDiagnosisAction
High TTR, low CVRProduct page mismatchTest CPP (aso-skills custom-product-pages)
Low TTR, decent CVRKeyword irrelevant or weak creativePause or add negative
High spend, 0 RC revenueAttribution gap or bad trafficCheck RC ASA attributes; add negative
Brand ROAS < 1.0Serious onboarding/paywall issueaso-skills paywall-optimization, not more bids
Discovery terms profitablePromote to exact match campaignasa-weekly-optimization

Output Template

markdown
# ASA ROAS Report — [App Name] — [Period]

## Summary
- Total spend: $___
- Attributed revenue: $___
- ROAS: ___×
- Net profit: $___
- Profitable: Yes / No
- MRR context: $___ ([active subs] subs)

## Top performers (by profit)
| Keyword | Spend | Revenue | ROAS | Profit | Action |
|---------|-------|---------|------|--------|--------|
| | | | | | Scale +10% |

## Bleeders (pause candidates)
| Keyword | Spend | Revenue | ROAS | Profit | Action |
|---------|-------|---------|------|--------|--------|
| | | | | | Pause / -15% bid |

## Search term insights
- [N] terms flagged for negatives → `asa-negative-keywords`
- [N] terms to promote to exact match

## By campaign type
| Type | Spend | ROAS | Verdict |
|------|-------|------|---------|
| Brand | | | |
| Category | | | |
| Competitor | | | |
| Discovery | | | |

## Recommendations
1. [Specific action with keyword ID and bid change]
2. [Specific action]

## Do NOT scale until
- [blocker from country gate or data volume]

Data Volume Warnings

Tell the user when data is insufficient:

SignalMinimum for keyword decisions
Keyword bid change$20+ spend, 7+ days
Campaign budget change$100+ spend, 14+ days
Geo expansion50+ conversions in home geo
ROAS trend call30+ days or 100+ installs

Cross-Skill Handoffs

FindingRoute to
Automated scale/pause recsasa-admaxxing
Weekly bid/keyword opsasa-weekly-optimization
Wasted search termsasa-negative-keywords
Low CVR on high-intent termsaso-skills custom-product-pages, ab-test-store-listing
All-channel profitabilitycampaign-profitability

Related Skills

  • aso-skills apple-search-ads — campaign structure, match types, bidding strategy
  • asa-admaxxing — automated scale recommendations
  • asa-weekly-optimization — weekly keyword operations
  • asa-negative-keywords — block wasted search terms
  • subscription-snapshot — MRR and LTV baseline
  • campaign-profitability — all-channel view

See revenuecat.md for RC metrics reference.

Frequently asked questions

What does the Asa Roas Analysis AI skill do?

When the user wants Apple Search Ads profitability, ROAS, or spend vs RevenueCat revenue analysis. Use when the user mentions "ASA ROAS", "Apple Search Ads profit", "ASA revenue", "keyword profitability", "which ASA keywords make money", or joining ASA with RevenueCat. For campaign structure and bidding strategy, see aso-skills apple-search-ads. For automated scale recommendations, see asa-admaxxing.

Why use Asa Roas Analysis on TypingMind?

Because you install it once and use it with any model. Asa Roas Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Asa Roas Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/appeeky/ua-skills/tree/main/skills/asa-roas-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Asa Roas Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Asa Roas Analysis?

As many as you like. As long as a model supports skills, you can use Asa Roas Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Asa Roas Analysis AI skill free?

It is published on GitHub by appeeky. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇