Apify Store Analytics Scraper
Pricing
from $2.70 / 1,000 listing analyses
Scrape any niche of the Apify Store and see who already built what you are about to build. Get 30-day user counts, run totals, failure rates, review ratings, review counts, pricing model and maintenance notices for every matching Actor. Unreviewed Actors show as unrated, never as badly rated.
name
Optional
The Actor's technical identifier, as username/actor-name.
title
Optional
The display title shown on the Store listing.
url
Optional
The public Store page for this Actor.
users30d
Optional
Distinct users who ran this Actor in the last 30 days. The best available proxy for real adoption.
runs30d
Optional
Total runs in the last 30 days. Null when the platform reports no run statistics, never zero for absent.
failureRate
Optional
Failed runs divided by total runs. Null when there were no runs, because a ratio with no denominator is not zero.
rating
Optional
Average review score, reported only when backed by enough reviews. Null otherwise, and ratingState says which case you are in.
reviewCount
Optional
How many reviews the rating is based on.
ratingState
Optional
Why the rating reads as it does. UNRATED means nobody has reviewed it, which is NOT a bad score: the platform returns 0 for both cases and this field is what separates them.
pricingModel
Optional
How the Actor charges, for example PAY_PER_EVENT.
notice
Optional
Platform notice on the listing, such as UNDER_MAINTENANCE or RESIDENTIAL_PROXY_REQUIRED. NONE when there is none.
weak
Optional
Whether any weakness signal fired. False means nothing tripped a threshold on the data available. It does not mean the Actor is good.
weakReasons
Optional
Which signals fired, written so you can read them.
[ "rating 3.85 over 99 reviews"]result
Optional
Present only on a status row: NO_RELEVANT_LISTINGS when nothing matched, STOPPED_EARLY when the run was cut short by the charge limit. Its absence means this is a listing row.
searchTerm
Optional
The search this row came from. Every row echoes its own input, so rows from several runs can be pooled without losing track of which query produced which.
examined
Optional
How many listings were fetched before relevance filtering. The denominator: a row count without it cannot be told apart from an empty market.
relevant
Optional
How many of those matched every token of the search and were analysed.
discarded
Optional
How many were dropped as irrelevant. The Store search parameter narrows but does not rank by relevance, so this is usually most of them.
capped
Optional
True when the fetch stopped at your limit, meaning there may be more listings than this run saw. False means the market was exhausted. Hitting a cap and running out are different answers.
retrievedAt
Optional
When these numbers were read. Store statistics change daily, so a saved row that cannot say when it was true is not evidence of anything.
pushed
Optional
On a STOPPED_EARLY row: how many listings were analysed before the run was cut short.
charged
Optional
On a status row: whether it was billed. Status rows never are.
why
Optional
On a status row: why this run produced no listings, or why it stopped. Names the search, the counts behind the verdict and what would change it. Absent on a listing row.
interpretation
Optional
On a NO_RELEVANT_LISTINGS row only: how to READ that emptiness. A zero result here is evidence that nobody serves the target, which may be an opening or may be absence of demand — this field says which question you are now holding, and refuses to answer it for you.