Fetching Google Trends…Rate limited · retrying /5· s
Your App Intelligence Buddy
Best niches to build your app
iOS users
Sub price
Sub mkt.
Money capacity
Avg MRR/app
Pop.
GDP
GDP/cap
Urban
Internet
Top 3 conc.
Comp. risk
Entrance
Top Chart Trends By Categories
Top Chart Trends By Keywords
By Price
Top Chart Competitors Landscape
Top Chart By Rating
Top Chart By Release Year
Top Chart By Reviews
About Pumf.it
Free market intelligence and ASO toolkit for indie iOS developers. No account, no paywall.
Market intelligence
shows market openness and best niches. lets you sort by Opportunity score to find frustrated users in any category across 170 countries.
ASO production tools
, & tracking, , , , , and — all in one place.
MCP for AI agents
Connect Claude or any MCP-compatible AI to pumf.it's live data. Ask "give me an app idea" in plain English — the agent chains automatically.
The 7-step indie research workflow
From zero to a validated idea in under 30 minutes.
1
Pick a country
Start with markets you understand or where you have a language advantage. Check GDP/cap + iOS share to validate it's worth your time.
2
Read Top Chart Entrance in Pulse
Is it Accessible? Good. Is it Locked? Hard — consider a different country or try Top Grossing to find paying niches.
3
Shortlist 2–3 niches from Best Niches
Cross-check against the category distribution bar. Write down niches where you could plausibly build something in 4–8 weeks.
4
Dive into each niche — sort by Unhappy
Switch to Apps, select the category, sort by Unhappy. Look for apps with reviews % > 40% and rating % < 75%.
5
Read 1–2 star reviews on the App Store
Open the top 3 unhappy apps. Filter by lowest rating. Read 20–30 reviews. Highlight every recurring phrase — those are your product spec.
6
Size the opportunity
Use the review count formula to estimate installs. Check GDP/cap to pick your price tier. Multiply — if 500K installs exist and you get 0.5% at $4.99/mo, that's $1.2K MRR from day one.
7
Build the one thing reviews keep asking for
Pick one specific complaint. Build the minimum version that solves it better than the incumbent. Launch. Use the same Apps view to track your category over time.
Want the full methodology — formulas, signals, and examples?
Add your keywords, sort them in the Inbox by importance, copy-paste into your app settings in the App Store. Finally paste longtail phrases to ASO tools for rank statistics.
Keywords Inbox
Add keywords above to get started
ASO Fields
Title
Subtitle
Keywords
Longtail Phrases
—
ASO Screenshots Generator
Upload 1–5 app screenshots, add slogans — we'll generate App Store-ready frames in all 7 required sizes and pack them into a ZIP.
App Screenshots (/5)
Screenshot Mark [word] to highlight
··
Colors
Background
Text color
Chip color
Preview
Carousel Maker
Upload up to 5 images — each goes on a colour background slide, ready for Threads, Instagram, and similar platforms.
Ratio
Background
App Store Optimization Checklist
Metadata
Icon
Screenshots
App Preview (video)
Description
Localization
Category
Monetization
Technical
Ratings & Reviews
Pre-launch
How to Find App Store Keywords
Keywords don't come from guessing — they come from listening. Here are 9 sources, ranked from fastest to deepest.
1
Keywords Generator — built into Pumf.it
Free · Start here
The fastest way to build a keyword list from scratch. Pick a category (or type any anchor word) and the generator expands it into synonyms, complementary terms, and real App Store autocomplete suggestions — all in one click.
→ Open the tab in this ASO section
→ Select your target country and app category
→ Optionally enter an anchor word to override the category (e.g. "habit tracker")
→ Hit Generate — review the semantic clusters and App Store autocomplete results
→ Use Copy all to export the full list into your metadata worksheet
Tip:Run it for 2–3 different anchor words that describe your app — then use sources 2–9 below to filter and validate which keywords have real search demand.
2
App Store Search Suggest
Free · Fastest
The autocomplete dropdown is a direct window into what real users type. Apple only shows queries with meaningful search volume.
→ Open App Store on device, type your core keyword and pause
→ Screenshot all suggestions — these are gold
→ Try each suggestion as a new seed and repeat
→ Do it for your top 3 competitors' names too
Tip:Suggestions vary by country — switch your App Store region to check target markets.
Order matters:The dropdown is ranked by Apple — the first suggestions are the highest-intent, most-searched terms. And an empty dropdown is a result, not a dead end: it means there's no real search demand for that word in that market. Ranking #1 for a keyword nobody searches is winning an empty room — check this before you assume a top chart position in a locale means the niche is validated there.
3
Competitor Metadata
Free
Top-ranked competitors have already done the keyword research. Their titles and subtitles are a validated starting point.
→ Search your main keyword, open the top 5 results
→ Copy their Title and Subtitle — extract every keyword
→ Look for words that appear across multiple competitors
→ Find gaps: keywords they missed that you could own
Tip:Use this app's Apps tab to browse the top chart by category and spot metadata patterns at scale.
4
Google Trends
Free · Underused
Google Trends doesn't show App Store data, but search intent on Google strongly correlates with App Store behavior. It's the best free tool for comparing keyword variants and finding seasonal peaks.
Compare keyword variants
→ Enter 2–5 variants of your core keyword (e.g. "habit tracker" vs "habit app" vs "daily habits")
→ Pick the variant with the highest and most stable interest over time
→ Avoid terms that peaked years ago and are declining
Find seasonal patterns
→ Set range to "Past 5 years" to see recurring spikes
→ Plan keyword updates and feature pushes around peaks (e.g. fitness apps spike every January)
→ Update metadata 2–3 weeks before the peak — indexing takes time
Discover related queries
→ Scroll to "Related queries" → filter by "Rising" for breakout terms
→ These are fast-growing searches — low competition, real demand
→ "Related topics" reveals the broader context users have in mind
Target markets by region
→ "Interest by subregion" shows which states or cities drive demand
→ Use this to decide which country to optimize for first
Tip:Set category to "Mobile apps" in Google Trends for cleaner, more relevant data.
5
Review Mining
Free · High signal
Users describe their problems in their own words in reviews — exactly the words they'd type into search.
→ Read 1★ and 2★ reviews of your top 3 competitors
→ Extract the nouns and phrases users repeat ("no offline mode", "too slow", "no widget")
→ These are pain points — if you solve them, use that language in your metadata
→ Also mine 5★ reviews: what do users love? That's your value prop
Tip:Copy a batch of reviews into an LLM and ask it to extract the most repeated pain-point phrases.
6
Reddit & Communities
Free · Deep intent
Forums reveal how people think about the problem your app solves — before they even know an app exists for it.
→ Search Reddit for your app's category (e.g. r/productivity, r/financialindependence)
→ Look for "best app for X" and "how do you manage Y" threads
→ Note the exact words users use to describe the problem
→ Check post titles — they often mirror search queries
Tip:Also check Twitter/X, Facebook Groups, and niche Discords for your category.
7
Google Keyword Planner
Free (Google Ads account)
Not built for ASO, but provides search volume ranges that help you prioritize between competing keyword ideas.
→ Use "Discover new keywords" with your core terms
→ Filter by your target country
→ Focus on mid-volume keywords — high-volume terms are dominated by big players
→ Export and cross-reference with your App Store Suggest list
Tip:You don't need to run ads — just create a free Google Ads account to access the planner.
8
App Store Connect — Search Terms
Free · Post-launch only
After launch, App Store Connect shows the exact search terms that led to impressions and downloads. This is ground truth — not a proxy.
→ Analytics → App Store → Sources → App Store Search
→ Sort by Downloads to find what's already converting
→ Sort by Impressions to find terms where you appear but don't convert — fix the page
→ Use high-impression / low-download terms to improve screenshots and description
Tip:Apple anonymizes low-volume terms — you'll see more data once you have consistent traffic.
9
Dedicated ASO Tools
Paid · Most precise
Purpose-built ASO platforms provide App Store-specific search volume, keyword difficulty, and competitor keyword tracking. Worth it once you have revenue to justify the cost.
AppTweakBest keyword intelligence, most accurate volume estimates
MobileActionStrong for Search Ads keyword research crossover
Tip:For indie devs: start with free sources. Invest in tools only after your first 1,000 downloads — you'll know exactly what to look for.
For indie developers
Turn App Store rankings into your next product idea
You have questions every solo developer asks before starting: What should I build? What do users actually hate? Is this market big enough? Pumf.it answers all three using real, live App Store data — no surveys, no guessing.
1
"Which app should I build?"
Most indie developers build what they already know. The smarter move is to find where demand exists but competition is still manageable. That's what the Pulse tab is for.
Top Chart Entrance
Accessible is the best signal for indie launches — no single giant controls the chart. Locked means the top players already own the space.
Best Niches
Categories occupying 4–10% of the top chart. Enough demand to validate, not so dominant that you can't compete. These are your entry points.
Competition Risk
Low risk = leaders are vulnerable. High risk = you'll need very strong differentiation or a different country.
Workflow:Open Pulse → pick a country with good macro signals → scan "Best Niches" → write down 2–3 categories that match your skills. Then go to step 2.
2
"What do users actually need?"
The App Store is already full of honest feedback from people who spent money, got frustrated, and left a review. The Apps tab surfaces those signals before you read a single review.
The Unhappy signal — how it works
Many reviews→real users, proven demand
Low rating→users keep using it despite frustration
Combined→a gap waiting to be filled
Sort by Unhappy. The apps at the top have the most users and the most frustrated ones. Open the top 3 in the App Store and filter reviews by 1–2 stars.
What you're looking for in negative reviews
→Repeated feature requests — 20 people asking for the same thing = real demand
→Workflow complaints — "I have to do X manually every time" = automation opportunity
→Platform gaps — "No iPad support", "no offline mode" = underserved segment
→Pricing frustration — "works great but too expensive" = room for a simpler, cheaper version
Tip:The most valuable review is "I'd pay $X for this if it just had Y." That sentence is your product brief, your pricing anchor, and your target audience — all in one line.
3
"How do I estimate installs and revenue?"
You can't see install numbers directly — but you can triangulate them from signals Pumf.it shows.
Install estimate from review count
Rule of thumb: ~1–3% of users leave a review on iOS
GDP per capita visible in the country signal bar in Pulse
Pricing anchor from Paid apps median
How to read it: Apps → Top Paid → your category
Median < $1Race to bottomavoid paid; freemium or adsMedian $1–3Price-sensitive$0.99–1.99/mo sub; strong free tierMedian $3–7Healthy$2.99–4.99/mo works confidentlyMedian > $7Premium$6.99–9.99/mo; users expect value
Switch chart to Top Paid in Apps tab → look at the price column of the top 25 apps in your category
Why this beats GDP/cap alone:GDP shows economic capacity — Paid apps median shows actual willingness to pay in your specific niche. A country with mid GDP can have a premium-priced Productivity niche if that's what the local market supports. Use both signals together: GDP/cap sets the ceiling, median price confirms what's already working.
Real audience size from iOS share
What the chart actually represents
US (57% iOS)→chart ≈ majority of mobile users
JP (70% iOS)→almost all mobile users represented
IN (5% iOS)→chart = tiny premium slice only
Low iOS share means chart leaders have smaller real user bases than reviews suggest
Quick estimate:If the #1 app in your target niche has 30K reviews in the US → ~1–3M installs → even 0.1% conversion to a $9.99/mo subscription = $1–3K MRR at parity. A better product can take 1–3% easily.
The 7-step indie research workflow
From zero to a validated idea in under 30 minutes.
1
Pick a country
Start with markets you understand or where you have a language advantage. Check GDP/cap + iOS share to validate it's worth your time.
2
Read Top Chart Entrance in Pulse
Is it Accessible? Good. Is it Locked? Hard — consider a different country or try Top Grossing to find paying niches.
3
Shortlist 2–3 niches from Best Niches
Cross-check against the category distribution bar. Write down niches where you could plausibly build something in 4–8 weeks.
4
Dive into each niche — sort by Unhappy
Switch to Apps, select the category, sort by Unhappy. Look for apps with reviews % > 40% and rating % < 75%.
5
Read 1–2 star reviews on the App Store
Open the top 3 unhappy apps. Filter by lowest rating. Read 20–30 reviews. Highlight every recurring phrase — those are your product spec.
6
Size the opportunity
Use the review count formula to estimate installs. Check GDP/cap to pick your price tier. Multiply — if 500K installs exist and you get 0.5% at $4.99/mo, that's $1.2K MRR from day one.
7
Build the one thing reviews keep asking for
Pick one specific complaint. Build the minimum version that solves it better than the incumbent. Launch. Use the same Apps view to track your category over time.
Real App Store data, updated every 3 hours. Free to use, no account needed.
Pumf.it is a free market intelligence and ASO toolkit for indie iOS developers. It pulls live App Store chart data and turns it into structured signals — helping you decide what to build, understand who to compete with, choose which keywords to target, and optimize your App Store listing. No account needed, no paywalls, free forever.
Who it's for
Indie developers
Finding what to build next, validating market size before writing a line of code, and spotting niches where a solo developer can realistically compete.
App publishers
Tracking keyword and chart rankings over time, optimizing metadata, building keyword lists, and monitoring competitor vulnerabilities in their category.
AI agents via MCP
Claude and other MCP-compatible AI assistants can query Pumf.it's live data directly — running niche discovery, competitor analysis, keyword research, and trend validation in natural language.
1
Pulse — market overview
Top-level read of any App Store country. Answers the single most important question: is this market open to a new indie app?
Top Chart Entrance
Based on how much of the top chart the top 3 categories own
top3 < 35%OpenNo dominant niche — most entry points are viabletop3 35–49%AccessibleSome concentration but leaders are still challengeabletop3 35–49% (gap > 8%)CompetitiveTop category dominates — differentiation requiredtop3 ≥ 50%LockedThree categories own the chart — very hard to break in
Competition Risk
gap = #1 category share − median of top-5 shares
gap ≤ 6%LowChart is flat — the leader has no commanding advantagegap 6–12%MediumLeader is ahead but not untouchablegap > 12%HighOne category dominates — you need strong differentiation
Best Niches
Categories with 4–10% chart share (fallback: 3–12% if fewer than 3 found)
The sweet spot: big enough to have real users (≥ 4%) but small enough that no single giant owns the space (≤ 10%). These are the entry points where an indie app can realistically crack the top chart.
Country signal bar
PopulationTotal market size contextGDP (total)Economy size — proxy for spending power in aggregateGDP per capitaIndividual spending ceiling → sets your subscription price tieriOS share% of smartphone users on iOS — how representative the App Store chart is of the full market
Category Distribution
Colour-coded horizontal bar showing each category's % share of the top 200 apps. Click any segment to jump to that category in the Apps tab. Use it to sanity-check "Best Niches" and spot outliers the algorithm might miss.
2
Apps — competitor deep-dive
Browse the top 200 apps in any category across any country. Each app has 5 App Powers — strength scores that tell you instantly who dominates and where the gaps are.
App Powers
Each power is a % relative to the current chart — high = strength, low = vulnerability you can exploit
Chart rank %(1 − (rank−1) / total) × 100. #1 = 100%, last in chart ≈ 0%. High % = strong chart position.Rating %rating / 5 × 100. A 4.8★ app scores 96%. Low % = user frustration signal.Reviews %This app's review count ÷ max review count in chart. High % = dominant review presence = proven demand.Installs %Estimated lifetime installs relative to the chart leader. High % = massive reach.Opportunity %Pumf.it's proprietary gap score: demand × frustration × confidence × age_factor. 100% = the best opening in this chart right now.
Sort modes
Default. Sort by chart rank — #1 first. Shows who's winning right now.Sort by Opportunity score. The key "find a gap" view — brings the most promising targets to the top.Lowest-rated first when descending. Useful to identify who users actively dislike.Most reviews first — shows where the largest user bases are.Highest estimated installs first — market size proxy.Release year — spot aging apps that haven't been updated.Top Paid only. Sort by price — reveals the pricing range users accept in this niche.
Keyword chart
Type any keyword in the search box (top of Apps) to see which apps rank for that term in the App Store — bypassing category filters. Useful for checking real keyword competition before you commit to a positioning.
Research workflow:Pulse → pick a niche → Apps → Unhappy sort → open top 3 in App Store → read 1-star reviews. Those reviews are your product spec.
2
ASO production tools
Once you have your niche and keywords, these tools help you build and optimize your App Store listing.
ASO Maker
Keyword workspace — add, prioritize, and export your title, subtitle, and keyword field. Tracks character limits.
Search Rank
Check where any app ranks for a specific App Store keyword search.
Chart Rank
Track where your apps rank in Top Free / Paid / Grossing across multiple countries.
Google Trends
Compare search interest for up to 5 keywords over time. Confirm a niche is growing before you commit.
Keywords Generator
Expand any seed keyword into App Store autocomplete suggestions and semantic relatives.
Screenshots Generator
Create App Store screenshots with device frames, gradients, and text overlays. Export ready-to-upload PNGs.
Carousel
Generate social media carousel sequences from your screenshots — ready to post on Instagram, TikTok, or Twitter.
Pumf.it exposes all its data through a Model Context Protocol (MCP) server at https://pumf.it/mcp. Connect Claude or any MCP-compatible AI and ask market research questions in plain English — the agent chains the tools automatically.
Quickest way
Tell Claude Code in any session:
"Connect pumf.it MCP server: https://pumf.it/mcp"
10 tools available via MCP
get_pulseMarket overview + niche signals for any country
get_chartsRaw Top Free / Paid / Grossing chart with opportunity scores
search_appsApp Store search — returns ranked results with metadata
get_app_infoFull details for any app — ratings, reviews, price, keywords
get_keywordsApp Store autocomplete suggestions for any seed keyword
get_google_trendsSearch interest over time for up to 5 keywords
get_metaList of supported countries and categories
check_search_rankPosition of an app for a specific keyword search
check_chart_rankPosition of an app in Top Free / Paid / Grossing chart
generate_screenshotTurn a raw app screenshot into an App Store-ready promo image, all sizes
Data & pricing
Live data, refreshed every 3 hours
Charts are fetched from the App Store on a schedule. If data is older than 3 hours, the UI shows a stale warning and a fresh fetch is triggered in the background.
170 countries, all chart types
Every App Store country — from the US to Ukraine. Top Free, Top Paid, and Top Grossing charts. All 26 App Store categories.
Free forever, no account needed
No subscription, no paywall, no login. All tools — including the MCP server — are free to use. If Pumf.it saves you a bad build decision, consider .
Ready to start? Pick a country and explore the market.
Pick a category (or enter an anchor word) — we'll expand it into synonyms, complementary words, and real App Store autocomplete suggestions.
Country
Category
Anchor word (optional — overrides category)
keywords + App Store +
appstoreno demand
Apple has no App Store autocomplete suggestions for "" in — nobody is really searching this. Ranking #1 for it in this market wins nothing; look for a market or seed with real demand instead.
Synonyms & complementary
App Search Rank
Find where your app appears in App Store search results for specific keywords — across multiple countries. Tracks changes between checks.
Your App
Keywords (comma-separated, up to 10)
keywords
Countries (up to 5)
/5 selected
Checked: vs. previous:
Keyword
—
#1–3 Top 3#4–10 Top 10#11–30 Mid30+ out of check limit▲ improved · ▼ dropped vs. previous
App Chart Rank
Track where your apps rank in their category charts — across multiple countries. Compares Top Free, Paid, and Grossing. Each app is checked in its own primary category.
Apps
Countries
selected
Chart
Checked:
· vs.
Country
—
·
–
#1–3 Top 3#4–10 Top 10#11–50 Mid100+ not in chart▲ improved · ▼ dropped vs. previous
Google Trends
See how search interest for a keyword changes over time. Identify seasonal patterns and rising demand before building.
📡
Google Trends unavailable
Search interest · last 5 years · 0–100
Top queries
Rising queries
No related queries available for this keyword
Data via Google Trends. Values 0–100 are relative to peak interest in the period.
Enter a keyword above to see search trends
For indie developers
Use pumf.it with AI agents via MCP
Connect Claude (or any MCP-compatible AI) to pumf.it's live App Store data. Ask natural-language questions and get structured market research — keyword gaps, opportunity scores, trend signals — without switching tabs.
1
Connect to pumf.it MCP
Two transports are supported. Use Streamable HTTP — it's the new 2025 standard. SSE remains available for clients that haven't updated yet.
Quickest way
Just ask Claude Code directly in any session — it will run the command itself:
"Connect pumf.it MCP server: https://pumf.it/mcp"
Streamable HTTP
Recommended
claude mcp add pumfit --transport http https://pumf.it/mcp
Add this to ~/Library/Application Support/Claude/claude_desktop_config.json on Mac, or the equivalent on your OS.
SSE (legacy)
claude mcp add pumfit --transport sse https://pumf.it/mcp/sse
For clients that don't support Streamable HTTP yet.
2
Available tools
The agent has access to 10 tools covering market data, keyword research, rank tracking, and promo asset generation. All data is live from the App Store — no manual searching required.
get_pulse / get_charts
Fetch live Top Free / Paid / Grossing charts with opportunity scores (0–100%) for any country and category.
search_apps / get_app_info
Search the App Store and get full metadata (ratings, reviews, price, release date, keywords) for any app.
get_keywords
Pull App Store search suggestions for any keyword — the same autocomplete users see. Great for building keyword lists.
get_google_trends
Compare search interest over time for up to 5 keywords. Use to validate whether a niche is growing or shrinking.
check_search_rank / check_chart_rank
Check where your app (or a competitor) ranks for a specific keyword search or in a specific chart category.
generate_screenshot
Turn a raw app screenshot into a branded App Store promo image — slogan, phone frame, and all 7 required sizes in one call.
get_meta
List of supported countries (with GDP/iOS share) and App Store categories — used to resolve valid country codes and genre IDs for the other tools.
What research you can run
These tools aren't meant to be called one-by-one — the agent chains them automatically based on your question. Here's what each research type looks like in practice.
Niche opportunity scan
Uses get_pulse to score every category in a country's chart. Surfaces niches where demand is real but competition is soft — ranked by opportunity score.
Competitor analysis
Uses get_charts + get_app_info to map the top players in a niche — their ratings, review counts, age, pricing, and how vulnerable they are to a new entrant.
Keyword gap analysis
Uses get_keywords to expand a seed keyword into App Store suggestions, then check_search_rank to see which of those terms competitors rank for — revealing gaps you can target.
Trend validation
Uses get_google_trends to compare search interest for your candidate keywords over time. Confirms whether a niche is growing, peaking, or already in decline before you commit to it.
Rank monitoring
Uses check_search_rank and check_chart_rank to track how your app's position moves after an ASO update or new review burst — across keywords and chart categories.
Idea generation
Chains get_pulse → get_charts → get_google_trends into a structured output: niche, problem, proposed solution, demand evidence, and competition level. One prompt, a full brief.
Audience portrait
Cross-reads chart signals to build a behavioural profile of who buys in a niche — before you write a line of code.
Price sensitivitymedian_price (top-paid) + GDP tier → what they'll pay
Pain severity% low-rated apps in niche → how desperate the audience is
Engagement depthreviews ÷ installs → vocal power users vs. silent casual users
Search intentkeyword clusters → problem / tool / identity driven
Adjacent interestsGoogle Trends related.top → lifestyle and motivation signals
Output: a named persona — "Anna, 31, freelance designer. Searches 'focus timer pomodoro'. Pays €3.99/mo. Adjacent interest: burnout recovery." Directly informs screenshots, onboarding, and paywall copy.
Promo screenshot generation
Send the agent a raw app screenshot and generate_screenshot composites it onto a branded background with a slogan and phone frame, returning all 7 App Store-required sizes ready to upload. Colors auto-derive from the screenshot; the agent can suggest a slogan from the audience portrait it just built.
3
Prompts that actually work
Copy any of these as a starting point. The agent knows how to chain tools together — you don't need to specify which APIs to call.
Short prompts — works as-is
"Give me an app idea""What niche should I build in?""Find a gap in the US App Store""Which categories are least competitive?""What are users complaining about in productivity apps?""Is [keyword] trending?"
The agent will ask for clarification if it needs more context, or pick sensible defaults (US, Top Free) and proceed.
Niche discovery
"Find niches in the US Top Free chart with the highest opportunity score where a solo developer could realistically compete. Rank them and explain why each is promising."
Idea generation
"Give me 5 iOS app ideas based on real App Store data. I want low competition, meaningful opportunity score, and a growing search trend. I can code but have no marketing budget."
Competitor deep-dive
"Analyze the top 10 apps in the Productivity category in Germany. Which ones have the most unhappy users (high reviews, low rating)? What pain points could I solve?"
Keyword strategy
"I'm building a habit tracker app. Get App Store keyword suggestions for 'habit tracker', 'daily routine', and 'self discipline'. Then check Google Trends to see which terms are growing. Give me a priority keyword list."
Market validation
"I want to launch a meditation app in Japan. Pull the Top Free chart for Japan in the Health & Fitness category and tell me if this market is accessible for a new indie app or already dominated by big players."
Audience portrait
"Build an audience portrait for the meditation app niche in the US. I want to understand who these users are, what pain they're solving, how much they'll pay, and what they search for — give me a named persona I can use for onboarding and paywall copy."
Promo screenshot generation
"Here's a screenshot of my app's home screen [attach image]. Turn it into an App Store promo screenshot with the slogan 'Every Habit, [Tracked]'. Show the full screen, don't crop the bottom."
Full research pipeline
"Run a full niche research for the UK market: 1) Find best niches in Top Free chart, 2) Pick the top opportunity, 3) Get keywords from App Store suggestions, 4) Check Google Trends for those keywords, 5) Give me a go/no-go decision with reasoning."
Tips
Always specify a country. App Store charts are country-specific. If you don't say "in the US", the agent defaults to US but results will vary.
Data is cached for 3 hours. If the agent warns about stale data, the chart may be from an earlier fetch. Use the Charts tab with force-refresh if you need fresh data right now.
Opportunity score is 0–100%. 100% = the best opportunity in that chart set. Compare scores within the same chart, not across different countries or chart types.
An empty get_keywords result is a signal, not an error. Zero App Store autocomplete suggestions for a seed means nobody searches that term in that country — not that the data failed. Ranking #1 in a chart for a keyword with no search demand is "winning an empty room," not a validated niche. Always cross-check with check_search_rank / check_chart_rank before treating a top position as proof of demand — this shows up most in smaller locales (e.g. pl, cs, sk, hu, da, sv).
How we pick these categories
Short answer: we look for categories that are big enough to have real users, but not so big that the top apps have already locked everything down.
Step 1 — we look at the whole chart
We take the current top chart for your selected country and calculate what share of apps belongs to each category. For example, "Games: 18%, Health: 9%, Finance: 6%…"
Step 2 — we find the sweet spot
We're looking for categories with 4–10% share. That range is the sweet spot for indie developers:
• Under 4% — too small. Very few users, hard to get traction or reviews.
• 4–10% — just right. Real demand, but no single player dominates.
• Over 10% — too crowded. Big studios with big budgets are already there.
Why does this help you?
In a 4–10% category, your app can actually rank. Users are searching for apps there, competitors aren't perfect, and there's room to get noticed without a marketing budget. Think of it as: enough people in the room, but not so many that you get lost.
What to do next
Tap any category icon to dive deeper — you'll see the actual apps, their ratings, and how old they are. A category full of 4-star apps from 2019 is a strong signal: users are stuck with outdated tools and would switch if something better showed up.
iOS users
How many people in this country actually use an iPhone or iPad.
Formula: Population × iOS market share %
This is your real addressable audience — not total population. A country with 1B people but 5% iOS share gives 50M potential users. Same as a 130M country with 38% share.
💡 Combine with GDP per capita to judge quality vs quantity. A smaller iOS audience in a rich country can be worth more than a huge one in a price-sensitive market.
Sub price (estimate)
Suggested monthly subscription price range based on the country's GDP per capita.
$1–2/mo → GDP/cap < $10K (India, Indonesia, Philippines)
💡 Sets the economic ceiling — what people can generally afford. If Sub mkt. is also shown, use both together: this sets the ceiling, Sub mkt. confirms what already works.
Sub price (market)
Median price of paid apps in the current chart. What the market is actually charging right now.
Formula: Median paid app price from the top chart
More reliable than the GDP estimate — it shows confirmed willingness to pay in this specific niche. If the median is $4.99 in a mid-income country, that's real purchase behavior, not a theoretical ceiling.
💡 If market median is lower than the GDP estimate suggests, price-sensitivity is higher than average. If it's higher — users in this category are willing to pay premium. Follow the market, not the model.
Money capacity
Estimated annual iOS App Store spending in this country.
Formula: iOS users × GDP per capita × 0.4%
The 0.4% coefficient is calibrated against known data: US App Store spending ~$33B/year with ~184M iOS users at GDP/cap $65K gives ~0.27%. We use 0.4% as a conservative upper estimate that accounts for higher engagement in developed markets.
💡 Use it to compare countries and size the prize. A $50B market and a $200M market take the same effort to enter but have very different upside. Don't treat this as an exact figure — treat it as an order of magnitude.
Avg MRR/app
Rough estimate of average monthly revenue per app if the market were split evenly across all apps in the current chart.
Formula: Money capacity ÷ apps in chart ÷ 12
Reality check: App revenue follows a power law — the top 10 apps earn most of the money, the bottom 150 earn very little. This number is a market-size reference, not a personal revenue forecast.
💡 Best used for cross-country comparison. If Avg MRR/app in Germany is 5× Ukraine, that's a signal about the prize pool size. Whether you capture it depends on your product and positioning.
GDP (total)
Gross Domestic Product — total economic output of the country per year.
Source: Wikipedia / IMF. Shown in trillions USD.
GDP is a proxy for total spending power. Larger GDP = more money flowing through the economy = bigger absolute App Store opportunity.
💡 Don't use GDP alone — a huge but poor country (high GDP, low GDP/cap) has less app-buying power per person than a small rich one. Always pair with GDP/cap to get the full picture.
GDP per capita
Average economic output per person. The best single signal for individual spending power.
Source: Wikipedia / IMF. Shown in thousands USD (e.g. 12,34 = $12,340/year).
GDP/cap directly drives subscription pricing — what people can realistically pay per month. It's the foundation for the Sub price estimate shown earlier in this row.
💡 Higher GDP/cap = users more likely to convert on IAP or subscriptions. A market with 20M iOS users at $50K GDP/cap is usually more valuable than 80M users at $8K.
Population
Total number of people in this country.
Source: Wikipedia / IMF
Context for iOS users. A country with high population but low iOS share is still a large market — it's Android-first, but iPhones exist. Compare with iOS users to understand iOS penetration.
💡 Small countries can still be premium markets. Switzerland (8M people) and Germany (83M) have very different populations but both have high iOS share and GDP/cap — making them both excellent targets.
Urban %
Share of population living in cities.
Source: World Bank
Urban users have faster internet, higher smartphone usage, and more app spending habits. Rural populations in lower-income countries often have limited data plans or shared devices.
💡 70%+ urban is a good signal. Below 50% — even with large total population — the actual addressable smartphone audience is smaller than the numbers suggest.
Internet %
Share of population with internet access.
Source: World Bank / ITU
No internet = no downloads. Directly limits your real addressable market. In most developed markets it's 90%+, but in some emerging markets it can be 40–60%, which cuts your audience significantly.
💡 Look for markets with 80%+ internet penetration unless you're building offline-first apps. Below 60% — only target if you have a specific reason (language niche, diaspora audience, etc.).
Top 3 concentration
What percentage of the top chart is taken by the 3 biggest categories combined.
Formula: Sum of the % share of the 3 largest categories
50%+ → chart dominated by 3 categories, hard to break in outside them
35–49% → healthy balance, most categories have room
<35% → fragmented chart, many niches have real traction
💡 Low concentration = more places to land. High concentration doesn't mean avoid — it means either compete inside the big 3 with a sharp angle, or find a niche in the long tail.
Competition risk
How dominant the top category is compared to the rest of the chart.
Formula: Gap between the #1 category share and the median of the top 5
Low (gap ≤ 6%) → balanced chart, no single category crushes everything
Medium (gap 7–12%) → one category pulls ahead, but others are still viable
High (gap > 12%) → one category dominates, very hard to compete outside it
💡 High risk doesn't mean "avoid" — it means be deliberate. Outside the dominant category you face less pressure. Inside it, you need a sharper product, not just a newer one.
Chart entrance
Overall read on how easy it is to get into the top chart in this market.
Formula: Based on Top 3 concentration + gap between #1 and median category
Open → <35% top 3 share. Many categories competing, lots of room for a new entrant.
Accessible → 35–49% share, small gap. Some concentration but leaders are still challengeable.
Locked → 50%+ share. Top categories own the chart. Hard to break in without a very specific angle.
💡 Accessible or Open is the sweet spot for indie developers. Locked isn't impossible — it means you need a niche play or a product that's clearly better than what's already there.
How to use this block
Quickly shows if this market is worth entering and where your app has the best chance to grow.
Top Chart Entrance
Shows how easy it is to enter the top charts.
Locked → big players dominate, hard to break in
Competitive → there's room, but you'll have to fight for it
Accessible → best signal for indie launches
Open → chart is fragmented, many niches to target
💡 Accessible or Open = better odds for small teams.
Top 3 Concentration
How much of the market belongs to the top 3 categories.
50%+ → hard outside top niches
35–49% → healthy balance
<35% → breakout potential everywhere
💡 Lower is usually better for new apps.
Competition Risk
How hard it is to compete with category leaders.
Low → best for indie apps
Medium → niche differentiation needed
High → avoid broad launches
💡 Low risk + strong niche = great launch setup.
Best Niches
Categories in the 4–10% sweet spot. Best for:
• ASO growth
• fast MVP validation
• early subscription tests
• UX-led differentiation
💡 If your idea fits here, launch odds improve.
Population
Total number of people in the country.
100M+ → large addressable market
10–100M → mid-size, often underserved
<10M → niche, high-LTV potential
💡 Small countries can still be premium markets — combine with GDP/cap.
GDP
Total economic output of the country (USD billions). Reflects overall market size and spending power.
>$1T → top-tier economy
$100B–$1T → strong regional market
<$100B → emerging market
💡 High GDP = larger App Store spend in absolute terms.
GDP per Capita
Average economic output per person. Best predictor of willingness to pay for apps.
>$30K → premium pricing works
$10K–$30K → mid-tier, price-sensitive
<$10K → freemium-first approach
💡 Higher GDP/cap = users more likely to convert on IAP or subscription.
Urbanization
Share of population living in cities. Urban users typically have faster internet, more screen time, and higher app spend.
80%+ → highly urban, strong digital habits
50–80% → mixed, urban centers drive growth
<50% → rural-heavy, harder to reach
Internet Penetration
Percentage of population with internet access. Defines your real reachable audience.
90%+ → nearly full coverage
60–90% → majority connected
<60% → significant offline segment
💡 Low internet + high urbanization = fast-growing market, act early.
iOS Share
Percentage of mobile users on iOS. Higher share = larger App Store audience in this country.
50%+ → iOS-dominant market (US, JP, AU)
25–50% → healthy iOS presence
<25% → Android-first country
💡 Low iOS share means chart rankings reflect a smaller slice of total users.
iOS Population
Estimated number of iOS users: Population × iOS share. This is your real addressable App Store audience.
💡 A country with 1B people but 5% iOS share gives you only 50M potential users — smaller than the Netherlands on iOS.
Sub./mo 1 — GDP ceiling
Suggested monthly subscription range based on GDP per capita. Sets the economic ceiling — what users in this country can afford to pay.
Suggested monthly subscription range based on the median price of top paid apps in this market. Shows what users already pay — actual willingness to spend, not just economic capacity. Only visible when Top Paid chart is selected.
$0–1 → median <$1 · race to bottom — prefer freemium or ads
$3–5 → median $3–7 · healthy — subscription works confidently
$7–10 → median >$7 · premium — users expect real value
💡 Use both together: Sub./mo 1 sets the ceiling, Sub./mo 2 confirms what already works.
Based on the current top chart for this country.
Top Chart Trends By Categories
Shows which app categories dominate the top chart right now.
How to read it
Each color segment is a category. Wider = more apps in the top chart. The legend below shows exact percentages.
What to do with this
• 5–15% share — sweet spot. Proven demand, but no single player owns it. Good place to enter.
• Over 20% — saturated. Hard to stand out unless you have a clear differentiator.
• Under 4% — niche. Smaller audience, but almost no competition. Works for very specific tools.
💡 Tap any segment or legend item to filter the app list to that category.
Top Chart Trends By Keywords
The most common words found in app names across the top chart.
How to read it
Bigger bubble = word appears in more app names. Percentage shows how many top-chart apps include this word.
What to do with this
• These words signal what users actually search for. If your app solves something in this space, include the relevant keyword in your app name or subtitle.
• If a word matches your idea — good. There's real demand for it.
• If none of the words match your idea — either you're very niche, or your target users call it something different. Worth checking.
💡 Use the copy button to grab all keywords at once for ASO research.
Top Chart Competitors Landscape
A scatter plot of every app in the top chart — shows where the gaps are.
How to read it
X axis — App rating (1–5)
Y axis — Opportunity Score (rank + reviews + age combined)
Each dot — one app in the top chart
What to do with this
• Top-left — high opportunity, low rating. Users find these apps but aren't happy. That's your gap to fill.
• Top-right — high opportunity, high rating. Strong apps. Hard to beat.
• Bottom — low opportunity. Smaller apps, less pressure.
💡 Tap the chart to open the full app list sorted by Opportunity Score.
Top Chart By Rating
Distribution of app ratings across the top chart.
How to read it
Each bar is a rating range. Taller bar = more top-chart apps with that rating.
What to do with this
• If most apps cluster around 4.0–4.4 — there's room for a polished 4.7+ app to stand out on quality alone.
• If most are already 4.7+ — the bar is high. You'll need a real differentiator beyond just being well-made.
• Low ratings across the board = users are frustrated. Study the 1-star reviews — that's your product brief.
💡 Tap the chart to sort the app list by rating.
Top Chart By Release Year
When were the top-chart apps originally released?
How to read it
Each bar is a year. Taller bar = more top-chart apps released that year.
What to do with this
• Most apps are 5+ years old — the chart hasn't been refreshed. A modern UX or AI-first approach could win fast.
• Most apps are recent (last 2 years) — active competition. You'll need a sharper angle, not just a newer app.
• Old apps dominating = users are loyal to legacy products. Hard to displace, but one bad update from them is your opening.
💡 Tap the chart to sort the app list by release year.
Top Chart By Reviews
How many reviews do top-chart apps have?
How to read it
Each bar is a review count range. Shows how established the competition is.
What to do with this
• Most apps have under 1K reviews — low barrier. You can compete from launch with a focused push.
• Most apps have 10K–100K reviews — mature market. Social proof matters. Budget for early review generation.
• 50K+ reviews everywhere — entrenched players. Hard to crack without a serious differentiator or a niche angle.
💡 Tap the chart to sort the app list by review count.
How to read these signals
Five quick percentages that help you spot patterns across apps in the list.
Chart Rank %
Position in chart relative to #1. 100% = leader, lower = further down.
100% → chart leader (#1)
~50% → middle of the pack
Low → further down the chart
💡 High opportunity + low chart rank = fast riser before mainstream notice.
Rating %
User satisfaction score relative to a perfect 5★.
80%+ → well-loved app
50–79% → average reception
<50% → users have complaints
💡 Low rating in a popular category = clear gap to fill.
Reviews %
Audience size relative to the most-reviewed app in the list.
90%+ → market leader
30–70% → established player
<10% → early, niche, or fast-rising
💡 10–30% range = proven demand without extreme lock-in.
Installs %
Estimated annual installs relative to the highest-volume app in the list. Derived from review count and app age (reviews ÷ age × 100).
90%+ → dominant install volume
20–60% → solid traction, real user base
<10% → niche, new, or growing quietly
💡 High installs + low rating = lots of users, lots of pain — prime opportunity window.
Opportunity %
Composite gap score: demand × user frustration × confidence × freshness.
High → strong signal, unhappy users, real market
Medium → some signal but weaker conviction
Low → satisfied users or thin data
💡 Best workflow: sort by Unhappy → open top 3 → read 1–2★ reviews → find pain points → build faster.
Scores update instantly when you switch country or chart.
How to use macro signals
Key macro signals that tell you how big and accessible this market really is.
Population
Total number of people in the country.
100M+ → large addressable market
10–100M → mid-size, often underserved
<10M → niche, high-LTV potential
💡 Small countries can still be premium markets — combine with GDP/cap.
GDP
Total economic output of the country (USD billions). Reflects overall market size and spending power.
>$1T → top-tier economy
$100B–$1T → strong regional market
<$100B → emerging market
💡 High GDP = larger App Store spend in absolute terms.
GDP per Capita
Average economic output per person. Best predictor of willingness to pay for apps.
>$30K → premium pricing works
$10K–$30K → mid-tier, price-sensitive
<$10K → freemium-first approach
💡 Higher GDP/cap = users more likely to convert on IAP or subscription.
Urbanization
Share of population living in cities. Urban users typically have faster internet, more screen time, and higher app spend.
80%+ → highly urban, strong digital habits
50–80% → mixed, urban centers drive growth
<50% → rural-heavy, harder to reach
Internet Penetration
Percentage of population with internet access. Defines your real reachable audience.
90%+ → nearly full coverage
60–90% → majority connected
<60% → significant offline segment
💡 Low internet + high urbanization = fast-growing market, act early.
iOS Share
Percentage of mobile users on iOS. Higher share = larger App Store audience in this country.
50%+ → iOS-dominant market (US, JP, AU)
25–50% → healthy iOS presence
<25% → Android-first country
💡 Low iOS share means chart rankings reflect a smaller slice of total users.
iOS Population
Estimated number of iOS users: Population × iOS share. This is your real addressable App Store audience.
💡 A country with 1B people but 5% iOS share gives you only 50M potential users — smaller than the Netherlands on iOS.
Sub./mo 1 — GDP ceiling
Suggested monthly subscription range based on GDP per capita. Sets the economic ceiling — what users in this country can afford to pay.
Suggested monthly subscription range based on the median price of top paid apps in this market. Shows what users already pay — actual willingness to spend, not just economic capacity. Only visible when Top Paid chart is selected.
$0–1 → median <$1 · race to bottom — prefer freemium or ads
$3–5 → median $3–7 · healthy — subscription works confidently
$7–10 → median >$7 · premium — users expect real value
💡 Use both together: Sub./mo 1 sets the ceiling, Sub./mo 2 confirms what already works. If they agree — charge confidently. If Sub./mo 2 is lower — the market is more price-sensitive than GDP suggests.
Data sourced from World Bank and StatCounter. Updated periodically.
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