Managing Apple Ads campaigns has always required hours of manual research, switching between tools, and piecing together competitor insights. With the launch of Iris, SplitMetrics introduces the first AI agent built specifically for Apple Ads & ASO — designed to take on the heavy research, deliver instant market intelligence, and empower you with clear, actionable insights in seconds.
Iris is SplitMetrics’ first AI agent built for Apple Ads & ASO. It represents a major step forward in the way app marketers work with data, replacing time-consuming manual research and fragmented tools with a single intelligent assistant.
Unlike dashboards or static reporting, Iris is a true agentic AI system:
It doesn’t just retrieve data — it analyzes, reasons, and delivers strategic insights.
It can make judgment calls, adapt dynamically, and provide recommendations a human strategist would normally prepare.
Its knowledge is built on real Apple Ads and ASO data, competitor signals, and SplitMetrics’ proprietary Market Intelligence.
With Iris, app marketers can instantly access competitor intelligence, keyword research, and market trends without switching between tools. It functions as a dedicated Apple Ads & ASO strategist within your team, always ready to answer questions and provide actionable guidance for both paid and organic growth.
What powers Iris?
✅ A database of 3 million keywords.
✅ Intelligence on 2+ million apps across 69 app store regions.
✅ Proprietary orchestration layer combining multiple AI models and tools.
✅ Continuous reflection loop for accuracy and refinement.
In short, Iris is your AI-powered Apple Ads & ASO consultant: faster than a human team, trained specifically on app marketing data, and always available
Using Iris is simple and intuitive. You interact with it just like you would with a colleague through chat.
1. Start a conversation
Type in a question or task. Example: “Hi Iris! Please identify high-potential keywords gaps and evaluate brand protection strategy for Amazon”
2. Iris processes your request
Iris understands the intent behind your query, breaks it down into smaller subtasks, and assigns these to specialized tools or models.
It continuously monitors the outputs, evaluates the results, and refines its answer through a “reflection loop,” ensuring accuracy and depth.
3. Get instant, structured insights
Iris responds with clear summaries and recommendations that might include:
Competitor identification & analysis
Keyword strategy insights
Market share and trends
Creative tracking
Geographic presence analysis
Custom Product Pages (CPP) analysis
Strategic recommendations
4. Act on insights
Iris equips you with prioritized, ready-to-implement steps across Apple Ads and App Store Optimization (ASO).
👉 No technical expertise is required. If you can describe your goal in plain language, Iris will deliver insights you can act on immediately.
Iris is not just a one-time assistant — it continuously improves the more you use it.
Iris has an app-level memory shared across your entire organization, allowing it to retain important context and apply it across all future analyses. This means every interaction helps Iris better understand your app, your strategy, and your goals.
What Iris learns from your messages:
Primary KPIs & optimization objectives
Core, growth, and non-focus storefronts
Key competitors and excluded competitors
Post-install funnel dynamics & conversion delays
Known issues, experiments, and seasonality factors
This persistent memory allows Iris to provide more relevant, tailored, and context-aware insights over time — without needing to repeat the same information in every prompt.
Example:
If you tell Iris “My primary KPI in the UK is CPI”, it will automatically prioritize CPI when analyzing performance in the UK in future requests.
👉 As a result, insights become more aligned with your business goals, and decision-making becomes faster and more consistent.
To help you get started with Iris and make your interactions more insightful, we’ve prepared a collection of prompt examples designed to cover key Apple Ads and ASO use cases.
Set the Structure of the answer in the Question - specify the App id, Competitor App id that you are interested in and Storefront name.
Where do we find these elements?
Key Information | Description | Where to Find It |
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Here are Prompt suggestions that you can copy and adapt these directly in chat to get the most out of Iris’s capabilities.
Keyword Strategy & Apple Ads Analysis
Focus Area | High Impact Query |
Full ASA Audit | Do a full audit of <app_id> Apple Ads strategy in France: which keywords are they using, what are the weak spots, missed opportunities, etc.? |
Competitor Targeting | What keywords are competitors of App <app_id> targeting? |
Under Invested opportunities | Which high-value keywords are competitors of App <app_id> under-investing in (low SOV + high search volume)? Form as a table: Competitor App | Keyword | Search Volume | SOV. |
Strategy Comparison | Compare Apple Ads strategy between <app_id> and <app_id> in US. |
Missed Opportunities | Can you identify missed keyword opportunities for the <app_id> in US that competitors are leveraging?
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Market Share Takeover | Show me keywords where App <app_id> could take over competitor market share with relatively low effort (high relevance, medium competition). |
New Keyword Research (Localized) | Could you provide the list of new Apple Ads keywords for the <app_id> app in [Storefront Name]? Could you suggest only non-English keywords? Create a keyword list that includes search popularity and <app_id> SOV value for each keyword, without including any other details, and add strategic recommendations at the end. |
New Keyword Research (Competitor) | Could you provide the list of new Apple Ads keywords for the <app_id> app in [Storefront Name], where [Competitor App ID] has SOV? Create a keyword list that includes search popularity, <app_id> SOV value, and [Competitor App ID] SOV value for each keyword, without including any other details, and add strategic recommendations at the end. |
Competitor Analysis (Paid Strategy)
Focus Area | High Impact Query |
Top Spenders & Volume | Who are the top 10 competitors for App <app_id> in [storefront], ranked by paid traffic volume? |
Spend Efficiency & Outliers | Provide estimated paid spend distribution across competitors of App <app_id> in US and highlight outliers (biggest overspenders vs most efficient). |
Keyword Overlap | Which of my competitors from different categories are using the same keywords as our App <app_id> in Poland, and what advantage might that give them? |
Alternative Competitor analysis
| Which of my competitors from different categories are using the same keywords as our app <App ID> in <Storefront>, and what advantage might that give them? |
Keyword Focus | Show me keywords where my app <App ID> could take over competitor market share with relatively low effort in the <storefront>. |
New Storefronts | Show me untapped countries where competitors to <App ID> aren’t advertising but category demand is high. |
Geographic & Market Analysis
Focus Area | High Impact Query |
Geographic Budget Split | Which countries is App <app_id> running Apple Ads in, and what is the estimated budget split? |
Market Comparison & Gap | Compare App <app_id>’s presence across top 5 markets with its key competitor. Where is the biggest growth gap? |
Untapped Markets | Show me untapped countries where competitors of App <app_id> aren’t advertising but category demand is high. |
Expansion Recommendation | Where should App <app_id> expand based on competitor gaps and search volume trends? |
Category Overview | Provide a full overview of the *Example* category in the UK: top apps, ad spend tiers, keyword clusters, and SoV leaders.
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Efficiency Analysis | Analyze top 10 Games apps in Germany: rank them by estimated spend efficiency (spend vs. SoV). |
Structural Differences | Compare <Chosen Category> patterns in US vs UK: highlight structural differences in competition intensity and user behavior. |
Keyword-level Metrics and Analysis
Focus Area | High Impact Query |
Attack Potential | Do a full audit of <app_id> Apple Ads strategy in France: which keywords are they using, what are the weak spots, missed opportunities, etc.? |
Competitor Dominance | Who is running ads on <keyword_list> in US, and how dominant is each competitor? Form result as table: Keyword | Top 10 Apps by $$\text{SOV$ & $$\text{SOV$ values | $ $\text{SOV$ values. |
Hidden Gems | Can you do a SOV report on <keyword_list>? Are there any hidden gems (high SP, low CPT), opportunities? |
ASO - Metadata & Organic Competitor Analysis
Focus Area | High Impact Query |
ASO Improvement Plan | What methods are there for improving ratings in the App Store, and which has the highest CR impact? |
Specific Keyword Changes | What specific keyword changes in the invisible 100-character keyword field could boost App <app_id> ranking for core terms in [Storefront Name]? |
Subtitle Research | Could you please prepare 5 alternative subtitles for the <app_id> app in the [Storefront Name]? Describe potential outcomes and advise whether these messages are already used by the competitors (1st [Competitor App ID], 2nd [Competitor App ID]). |
Organic Competitors & Gaps | Who are organic competitors of App <app_id> and what's their ASO strategy? Are there any gaps? |
Closing the Gap | Suggest metadata changes (title, subtitle, keywords, description) for App <app_id> to close the gap vs. top 3 organic competitors. |
Strategy Comparison | Compare my App <app_id> ASO strategy with top 3 competitors. Where are the weak points? |
General AA & ASO Best Practices
Focus Area | High Impact Query |
Ratings Improvement | Do a full audit of <app_id> Apple Ads strategy in [Storefront]: which keywords are they using, what are the weak spots, missed opportunities, etc.? |
Seasonal Optimization | How to optimize app for seasonal trends (e.g., Holidays, specific events) in both ASO and ASA? |
New Launch Campaign | What are best practices for structuring an Apple Ads campaign for a new app launch? |
Efficiency KPIs | How do I measure efficiency in Apple Ads - which KPIs matter most (SP, SoV, conversion rate, ROAS)? |
Wasted Spend | How can I reduce wasted spend in Apple Ads campaigns? |
Ranking Factors | What are the most important ranking factors in App Store Optimization right now? |
Paid vs. Organic Balance | How should I balance paid UA (Apple Ads) and organic ASO for maximum growth? |
Localization Impact | How does localization affect ASO, and which markets benefit the most from localized keywords/metadata? |
These prompts provide a structured starting point for your research, helping you ask more effective questions and uncover actionable insights faster 🚀
Iris is designed to replace hours of manual research and fragmented tools with a single, intelligent, agent-driven solution. But beyond efficiency, it also empowers teams to make smarter, revenue-focused decisions that drive incremental growth.
Save time
Iris delivers market insights in seconds, freeing you from manual competitor and keyword research.
Act faster than competitors
Catch emerging trends and competitive moves early and respond before your rivals.
Gain a 360° view of Apple Ads & ASO
Understand competitor activity, market shares, keyword strategies, Custom Product Pages, and regional presence across all storefronts — covering both paid campaigns and organic visibility.
Smarter, revenue-focused decisions
With data-backed insights, Iris allows you to act with speed and confidence. Decisions aren’t just faster — they’re aligned with growth goals like improved efficiency, increased share of voice, and stronger revenue outcomes.
High-impact actions for UA managers
Identify new keywords
Adjust bids and budgets (CPT)
Optimize Custom Product Pages
Explore new regions for expansion
Performance outcomes
Improved CPA (Cost Per Acquisition), ROAS (Return on Ad Spend), and SOV (Share of Voice)
Higher install volume, better efficiency, and stronger market share
Incremental growth fueled by smarter ASO and Apple Ads alignment
Flexibility and creativity
Iris handles the heavy research while you focus on strategy. You can ask broad strategic questions (“What is the best way to improve my app’s share of voice on branded terms?”) or very specific queries (“Check if I am missing any important keywords compared to this competitor.”).
How do I use Iris?
Just type your question or request in the chat interface. Iris will analyze the query, run the necessary research, and return a structured answer with insights and recommendations.
Do I need technical expertise?
No. Iris is designed for everyone — from seasoned UA managers to newcomers. Plain-language prompts are enough for Iris to deliver actionable insights.
What’s behind Iris?
Iris is powered by SplitMetrics’ proprietary agentic AI architecture. It combines multiple AI models, internal tools, and real-time market data. Unlike a simple chatbot, Iris understands intent, decomposes tasks, monitors outputs, and refines results continuously.
Is my data safe?
Yes. Iris does not use your Apple Ads account or app-specific performance data for training. All insights are generated from anonymized, proprietary market intelligence (keywords, competitor activity, storefront signals). Your account data stays private and secure.
What makes Iris unique?
💎 It’s the first AI agent built specifically for Apple Ads & ASO.
💎 Combines paid and organic intelligence in one place.
💎 Built on a decade of SplitMetrics expertise in app marketing and AI.
Does Iris execute actions for me?
Not yet. Today, Iris is a strategic assistant: it analyzes data, uncovers opportunities, and provides prioritized next steps. Execution features (like automatically changing bids or adding keywords) are on the roadmap.
How does Iris identify competitors?
It tracks real market behavior — apps actively bidding on the same keywords or targeting the same audience. This shows your true competitors for user attention and spend, not just apps in your category.
Can Iris help with ASO?
Yes. Iris connects insights across paid and organic performance to show how Apple Ads strategy and App Store presence can reinforce each other.
While Iris focused on research and strategy, teams still faced another challenge: understanding performance changes fast enough to act.
Performance can shift quickly due to bids, spend, competition, or market dynamics. Iris AI Agent was built to address this need.
Iris AI Agent expands Iris into a Market & Ad Performance Analyst, combining market intelligence with historical performance analysis and actionable recommendations.
Iris AI Agent is designed to answer questions like:
What changed in my performance?
Why did it change?
What should I do next?
It does this by analyzing performance over time and connecting the dots between metrics, competition, and market behavior.
Detecting trends and anomalies
Iris AI Agent compares current performance to previous periods to help you spot meaningful changes early.
It can:
Show trends across campaigns, keywords, geos, and competitors
Identify changes in key metrics such as SOV, SP, ROAS, CPI, and revenue
Highlight early signals of risks or growth opportunities
This makes it easier to react before small issues become bigger problems.
Identifying best and worst performers
Instead of reviewing performance line by line, Iris AI Agent helps you focus on what matters most.
It can:
Identify top- and bottom- performing campaigns and keywords
Detect under- and overspending
Highlight inefficient spend and potential budget waste
Benchmark performance across storefronts
This is especially useful when managing large or complex accounts.
Explaining why performance changed
One of the biggest differences in Iris AI Agent is its focus on explanation.
Rather than just showing that a metric moved, Iris helps you understand why.
It can:
Explain performance changes over time
Link results to bids, spend levels, competition, and market dynamics
Identify drivers behind ROAS drops or CPA / CPI increases
This turns reporting into insight, and insight into clarity.
Iris AI Agent also helps you decide what to do next.
Based on its analysis, it can:
Suggest campaigns and keywords to scale, optimize, or pause
Recommend budget reallocation across campaigns and geos
Provide bid recommendations based on performance and competition
Prioritize actions by expected impact on key KPIs
Recommendations are tailored to your request and performance context.
Iris is available from any Acquire tab, to start:
1. Click the Iris chat to open it as a side panel 👇
Your current app context is passed automatically where applicable.
2. You can expand Iris to full-screen mode 👇
You can switch apps at any time using the app selector 👇
After sending a request, you can close Iris — you’ll be notified when the response is ready 🙌
Iris also includes a library of recommended question templates to help you get started or explore common use cases 👇
❗Data limitations in AI Agent
At this stage, Iris AI Agent supports:
Data levels: Campaign and Keyword
Metrics: All key metrics, excluding Custom Metrics and Cohort Metrics
To help you stay organized and work more efficiently, Iris supports multiple chats.
You can:
Create separate chats for different topics (e.g., keyword research, performance analysis, competitor insights) 👇
Easily switch between conversations 👇
Rename chats for better clarity
This makes it easy to structure your workflows, revisit previous analyses, and manage multiple research threads without losing context.
🔍 Is Iris still available?
Yes. Iris AI Agent builds on Iris — it doesn’t replace it. You can still ask market research and strategy questions as before.
🔍 What’s the main difference between Iris and Iris AI Agent?
Iris focuses on market intelligence and strategic research.
Iris AI Agent adds performance analysis, historical comparison, explanations, and recommendations.
🔍 Does Iris AI Agent use my Apple Ads data?
Yes. Iris AI Agent analyzes supported Apple Ads performance data to explain changes and generate recommendations.
🔍 Is Iris AI Agent a reporting or automation tool?
No. Iris does not execute changes automatically. It analyzes, explains, and recommends — decisions and actions remain fully in your control.
Iris started as a research assistant and has grown into a performance-aware analyst.
Whether you’re exploring a new market, reviewing performance shifts, or deciding what to optimize next, Iris is designed to help you move from data to decisions faster — all in one place.
Want to see Iris in action? You can book a personalized demo with our team and explore how the AI agent can enhance your Apple Ads & ASO strategy. Simply follow this link to schedule your session: Book an Iris demo.
Iris is more than an AI assistant — it’s your AI-powered Apple Ads & ASO strategist. With real-time competitor intelligence, comprehensive market research, and actionable recommendations, Iris not only saves you time but also empowers you to make smarter, revenue-focused decisions that drive incremental growth.
The agentic revolution in app marketing starts now, and Iris is your first step into it 🌟