data.ai — the company most people still call App Annie — is the heavyweight of mobile-market intelligence. Its modeled download and revenue estimates, usage panels and market-share charts power investor decks, M&A diligence and the strategy slides at big publishers. When you genuinely need those numbers, there is no real substitute. This page isn't pretending otherwise. It's an honest map of what data.ai gates behind its contract, what's actually observable in the public stores for free, and a self-serve tool for the very common case where you don't need modeled estimates at all.
The real friction with data.ai isn't the data — it's the front door
data.ai's intelligence suite is enterprise-only and sales-led. There are no public self-serve plans for the estimate products; you book a call, scope markets and feeds, negotiate seats, and sign an annual contract that commonly lands in the high four to five figures and up. There's a limited free Store Stats-style tier, but the famous modeled downloads and revenue live behind the paywall. For an indie dev, a small ASO team, or anyone who just needs to look at the stores, that's a heavy gate to clear for data that, in many cases, you didn't need the modeled version of.
Public vs. modeled: what each side actually holds
App title, subtitle, description, category, icon, screenshots, current rating and rating count, chart rankings, price, version history, and the full text of user reviews across countries.
Private download counts, revenue estimates, DAU/MAU and engagement panels, retention curves, demographic splits and cross-app market-share — none of which the store pages expose.
This is the cleanest way to decide. If everything you need is in the top row, you don't need data.ai — you need a way to pull the public stores reliably and at scale. If you need anything in the bottom row, no scraper will conjure it, and that's a legitimate reason to pay.
The self-serve option: a pay-per-run App Store scraper
For the public row, our App Store scraper on Apify pulls Apple App Store and Google Play metadata, chart positions and the full review stream on demand, and returns it as JSON or CSV. No sales call, no annual commitment — you run it when you need it and pay for the run, with free-tier platform credits to start. It's especially handy for ASO research (keywords, ratings, competitor descriptions) and voice-of-customer mining (reading thousands of reviews to find what users beg for).
curl -X POST "https://api.apify.com/v2/acts/renzomacar~app-store-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"appIds": ["com.spotify.music","com.duolingo"],
"store": "both",
"scrapeReviews": true,
"reviewsCount": 500
}'Out comes a dataset of app metadata, rankings and reviews you can drop into a sheet, a sentiment model, or an ASO tracker — the public picture, on your schedule.
Honest comparison
| Aspect | data.ai (App Annie) | App Store scraper |
|---|---|---|
| Access model | Enterprise, sales-led annual contract | Self-serve, pay per run on Apify |
| Entry price | High four to five figures+ for estimates | Free-tier credits, then per-run cost |
| Download & revenue estimates | Yes — its core strength | No — not derivable from public pages |
| Usage / engagement panels | Yes, modeled from panels | No |
| Public metadata & rankings | Yes, plus history | Yes, on demand |
| Full review text | Available in product | Yes — bulk review scraping |
| Time to first data | After a sales cycle | Minutes |
| Best for | Estimates for investment & strategy | ASO, review mining, competitor metadata |
Where data.ai is worth every dollar
To be square about it: if your decision hinges on how many downloads or how much revenue a competitor app is pulling, on cross-market share trends, or on engagement and retention you can't observe from outside, data.ai's modeled datasets are the right and arguably only credible tool. Investors sizing a category, publishers planning a portfolio, and teams building a market-entry case are paying for the model, not the metadata — and a scraper that returns public pages genuinely can't replace that. Don't try to fake estimates from public data; that's how bad decisions get made.
Pick by the row you're in
If you live in the public row — ASO, review sentiment, competitor descriptions, rankings — a pay-per-run App Store scraper gets you there in minutes without a contract. If you need the modeled row — downloads, revenue, usage — budget for data.ai and use it for what only it can do. Many teams sensibly do both: scrape the public picture continuously, and buy the modeled numbers only when a specific decision demands them.
Get the public app picture without a sales call
App Store and Google Play metadata, rankings and full review streams as JSON or CSV. Self-serve on Apify's free-tier credits, pay only for the runs you fire.
Open the App Store scraper → Or get done-for-you leadsDisclosure: links to Apify on this page are affiliate links. If you create a paid account through them we may earn a commission, at no extra cost to you. We recommend the actor because we build and ship it on Apify ourselves. We are not affiliated with data.ai / App Annie; product details reflect its publicly described enterprise, sales-led model and may change. Scrape only public data and follow each store's terms.