Publisher · 11 actors

insights_data on the Apify Store

insights_data publishes 11 actors on the Apify Store, used by 23 people in the last 30 days. Oldest actor is 16d old. Prices, reliability and maintenance below come from our daily census of the public store catalog.

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Last 7 dayson this catalogue

…and 59 more changes this week. Follow insights_data — every change by email each morning

By monthly users#1,080↓ 88of 4,120 publishers · 23 users in 30 days
By catalogue size#985↓ 357of 4,120 publishers · 11 actors listed
By users all time#1,186↑ 57of 4,120 publishers · 77 users since they began
Graded1 of 111 C · 10 not yet judged
Needs a build0 of 1111 fresh · 0 aging · stale = no build in 180 days
Carries half the users1 of 8top 3 hold 78.3% · 60.9% on the largest

Places are over the 4,120 publishers listed today; the week’s move is measured against the 3,645 also listed on 17 Oct, so nobody falls because the store grew around them.

What they build11 actors in the catalogue
Platforms targeted
TikTok2
Booking.com1
Douyin1
Facebook1
Instagram1
LinkedIn1
Google News1
Taobao1

+3 more platforms

Biggest actors, monthly users
tiktok-profile-scraper61%
google-news-scraper9%
wechat-official-account-scraper9%
linkedin-profile-extractor-enricher4%

share of this publisher’s 23 monthly users

11platforms targeted
11 a monthnew actors, last 30 days
Oct 2026first actor still listed
6dsince their newest actor

insights_data spreads 11 actors across 11 platforms, most of all TikTok (2). They have created 11 a month over the last 30 days.

How this is counted

Platforms come from our own classification of each actor’s listing, and an actor can target several — so these counts overlap and add up to more than the catalogue. Dates are the store’s own creation timestamp for each actor, which means the chart shows the actors still listed today, grouped by when they were made: a publisher who built forty last year and has since removed thirty shows ten. Shares are of this publisher’s own monthly users, from the same daily census as the table below.

Monthly userssummed across this catalogue
23↑ 16over 18 readings
Runs / daymatched per actor
36↑ 25over 17 readings
Runs / 30drolling window, summed
323↑ 134over 18 readings
Actorsin the census that day
11↑ 5over 18 readings

Runs per day is each actor's own step in its lifetime run counter, added up over the actors present on both days — an actor joining this catalogue moves the actor count, never the runs line. Last 30 days; the full history is in the app.

Build activitylast 60 days
94builds published
8/60days with a build
100%of the catalogue touched in 30 days
Last touched
2–7d8
8–30d3

insights_data published 94 builds on 8 of the last 60 days. Busiest was 18 Oct (35).

How this is counted

A build is counted from the store's own build counter, read once a day, so a cell is an exact count and an empty cell is a day nobody shipped. Shading runs against this catalogue's busiest day, so it compares days here — not catalogues. “Touched” is broader than a build: it is the last change the store saw of any kind, on a rolling re-fetch, so it can lag a build by days. Per-actor history is in the app.

Sort
#ActorGradePrice / 1kUsers /30dSuccessRatingAgeFresh
1CEVT$1.50 /1k main_resultgood price1455 total94.1%—16dfresh
2—EVT$4.00 /1k main_resulthigh price23 total——7dfresh
3—EVT$4.99 /1k main_resulthigh price23 total——12dfresh
4—EVT$5.00 /1k main_resulthigh price12 total——7dfresh
5—EVT$2.99 /1k main_resultfair price12 total——12dfresh
6—EVT$1.00 /1k main_resultgood price12 total——7dfresh
7—EVT$2.00 /1k main_resultgood price12 total——7dfresh
8—EVT$5.00 /1k main_resulthigh price12 total——12dfresh
9—EVT$6.99 /1k main_resultsteep price02 total——12dfresh
10—EVT$3.00 /1k main_resultfair price03 total——12dfresh
11—EVT$2.00 /1k main_resultgood price01 total——6dfresh
11 actors, sorted by monthly users · * prices normalized per 1,000 units Open in search with filters →