Scrape TikTok profiles at scale — followers and following lists, username enrichment, and the accounts that commented on a video. Every profile returns emails, bio links, follower and like counts, and video stats. No login needed. Export to CSV, JSON or Excel, or run via API.
All notable changes to the TikTok Profile Scraper actor are documented here.
The format follows Keep a Changelog .
[0.0.167] - 2026-07-29
Changed
The Store listing now says what this actor returns — emails, bio links, follower and like
counts and video stats on every profile, across follower and following lists, username
enrichment, and the accounts that commented on a video — and the price line shows the
per-profile price instead of a generic label.
[0.0.166] - 2026-07-28
Fixed
The record that lets an interrupted run resume is now declared in the actor's storage schema.
It was always written, but the schema did not list it, so anything reading the schema had no way
to know it existed.
Changed
Local helper files that were never needed at run time no longer travel with the actor, so the
build is smaller.
[0.0.165] - 2026-07-28
Maintenance build — no user-facing changes.
[0.0.164] - 2026-07-27
Added
New Source column on every row. It says how each profile entered your results — Follower of <target> or Following of <target> in Mode 1, Direct Input in Mode 2, Commenter on <target> in Mode 3. Previously, a run covering several target accounts produced one undifferentiated list and there was no way to tell which account any given profile came from. This column was already being worked out internally on every run; it simply was never written to the output.
Mode 3 rows now carry Comments Left and Posts Engaged.Comments Left counts every comment the account left across the target posts that were read, and Posts Engaged counts how many different posts they commented on — which separates someone engaging steadily from someone leaving a burst of replies under a single post. Both describe what the run actually read: scanning stops once your profile limit is reached, so treat them as a floor rather than a lifetime total.
Changed
Mode 3 results are now ordered by engagement instead of follower count — most comments first, then most posts engaged, with follower count as the tie-breaker. Follower count is the wrong headline for a mode whose purpose is finding the people who actually engage. Rows are written in batches and ordered within each batch, so sort the exported dataset by Comments Left if you need a strict ranking across the entire run.
In Mode 3, an account that comments on several of your target accounts is now counted across all of them, and its Source lists each one. Previously it was credited only to whichever target happened to be scanned first, and repeat comments from the same person were discarded rather than counted.
No pricing change: the same single Profile Analyzed event fires once per analyzed profile, exactly as before, and no run performs extra retrievals because of this release.
[0.0.163] - 2026-07-06
Changed
Every "Upgrade" link in run messages now says what's behind it: paid plans start at $29/mo with $29 in platform credits, and the link opens your plan page in Apify Console.
[0.0.162] - 2026-07-06
Fixed
The "Upgrade" link in run summaries now opens your Apify plan page directly (the old link form could land on the wrong billing tab).
[0.0.161] - 2026-07-02
Fixed
Profiles that fail to retrieve are no longer billed. Not-found, deleted, and private accounts never counted as deliverable rows, but each retrieval attempt was still charged as a Profile Analyzed event. Billing now fires only after a profile actually comes back readable — matching what the pricing table and FAQ always promised.
Trying the actor with the default demo input is now always cheap. The pre-filled example input (e.g. willsmith in Mode 1 with no profile cap) previously started a full-size run — on a paid account that meant an unbounded follower crawl. Runs using the untouched demo input are now detected and capped at 10 profiles (~$0.02), with a storage notice explaining the cap and how to switch to your own accounts.
Added
Every empty run now explains itself. A run that ends with 0 rows writes a USER_MESSAGE storage record naming the cause and the fix: no candidates found (per-mode guidance with known-good starter accounts), every profile rejected by your filters (with the top rejection reasons and which filter to loosen), or no account reachable (not-found / private / temporary-error breakdown). Previously these runs reported only "Completed successfully".
Free-plan caps now say what was held back — with real numbers. When the free plan trims your run (a list longer than 100 profiles, more than 3 target accounts, or the 100-profiles-per-run ceiling), the run writes a notice with the exact counts (e.g. "Your list has 110 profiles — the free plan analyzed the first 100") plus a FREE_LIMITS_APPLIED storage record. Caps you set yourself (like maxCountList) are never presented as plan limits.
Input form: honest guidance where it was missing — Mode 1 states it works on public accounts with visible lists only, the filter section explains that filters run after profiles are fetched, and username fields point to verified starter accounts.
Changed
README: mode-selection guidance in four places (each mode reads its own username field), an expectation line for Mode 1, three new FAQ entries (no-login/no-cookies, scheduled runs, "how do I get more results"), one-click example tasks, and a store description without pricing boilerplate.
[0.0.160] - 2026-05-07
Changed
README — aligned to Apify quality template. Hero rewritten with value-first prose and a "beyond what TikTok's official Research API offers" comparison; numbered 3-step Quick start; new 💡 Tips & Best Practices section (4 sub-sections × 3 bullets); new 🛟 Support & feedback section pointing to Apify Store reviews / bookmark / Issues tab; promoted disclaimer to dedicated ⚖️ Is it legal to scrape TikTok? H2 with link to Apify's web-scraping legality blog; FAQ expanded to 12 Q&As (including legality, ban risk, data freshness, cost cap); 3-mode descriptions condensed to a table. No functional changes — same input, output, dataset shape, and pricing.
[0.0.159] - 2026-05-05
Fixed
Run-level analytics no longer fail with "Insufficient permissions for the key-value store" on every paid run — the per-user session and first-run timestamp stores were using actor-agnostic names that, under Apify's LIMITED_PERMISSIONS scoping, were owned by another actor in the same account. Renamed to actor-scoped names so this actor's runs can read/write its own analytics state.
Changed
Improved diagnostics when every account in the input was already analyzed by an earlier run. Previously, the actor silently skipped every cached account, completed with 0 saved profiles, and reported "Completed successfully" — paying users saw a successful run that produced nothing. Runs in this state now show Stop Reason: All accounts already processed and write a USER_MESSAGE storage record telling you to set "Clear saved data before run" to true if you want to re-analyze them.
Per-account "skipped because already analyzed in a prior run" is now counted and surfaced in the run-complete summary block.
[0.0.4] - 2026-05-04
Changed
README expanded with a full output sample, pricing math examples, three filter recipes (nano-influencer outreach / English-speaking creators / B2B partnership shortlist via engaged commenters), an FAQ section, and a comparison table to other actors in this portfolio for multi-platform users.
Every output column now has a per-field description, type, and example available in the Apify Console's dataset view and to clients that read the actor schema programmatically — covers all 16 base columns plus the conditional Email, Website, and Post N columns.
Input field help text rewritten throughout — each field now leads with what it does and any prerequisites (e.g. "Required when keywordLocation is 'posts' or 'anywhere'"), so it's clearer what to set before running.
SEO title / description tightened on the Apify Store page (no functional change).
[0.0.3] - 2026-04-30
Fixed
Followup to 0.0.2: extended the bounded timeout to the remaining mid-run storage calls — the totals-counter write, the per-batch checkpoint save, and the per-account checkpoint and detailed-cache writes. Under reduced-permission contexts these were each stalling silently and preventing the run from progressing past the main analysis loop, even with the start-of-run paths already bounded. Storage operations now degrade to no-ops when unavailable rather than blocking the run.
[0.0.2] - 2026-04-30
Fixed
Followup to 0.0.1: extended the 3-second-timeout bounding to the run-startup paths too. Under reduced-permission contexts, the saved-data clear (setValue / dataset.drop / openDataset) and checkpoint resume (dataset.getData / getValue) were also stalling silently, preventing the run from ever reaching the main loop. With these calls bounded, runs proceed even when the underlying storage operations are unavailable.
[0.0.1] - 2026-04-30
Fixed
Bound every async finalization step (run-summary write, run-metadata fetch, first-run timestamp lookup, analytics POST) with a 3-second timeout each, plus a 60-second cleanup safety net. Under reduced-permission run contexts these calls were stalling silently and the run could reach the platform timeout instead of exiting cleanly. Completed runs now terminate within ~15 seconds of the "Run complete" log.
![TikTok User Search Scraper - Find Creators [NO LOGIN] ✅ avatar](https://images.apifyusercontent.com/xQN1VJN2CrdTx_ww-l8Mdp0h4WEd5eETlcN_nftk4Wc/rs:fill:76:76/cb:1/aHR0cHM6Ly9hcGlmeS1pbWFnZS11cGxvYWRzLXByb2QuczMudXMtZWFzdC0xLmFtYXpvbmF3cy5jb20vc0NDU2R3bm1LTUoxUTJzVG4tYWN0b3ItR3BOSzFGUEtBakpmYjFFVGctam5mZjh4UUMzNC1jYW52YS10aWstdG9rLWxvZ28tTUFHek5nb0lIancucG5n.webp){kind=avatar}
