TikTok Influencer Discovery — Rank Creators by Engagement

Find TikTok influencers by niche. Enter keywords or hashtags, get a ranked creator list scored on REAL engagement rate, virality (views/followers) and posting cadence — plus followers, bio, public email and link. Pay per creator. RESIDENTIAL proxy built-in.

What it does

TikTok Influencer Discovery — Rank Creators by Engagement is a data-collection tool for the social media and lead generation category. The inputs let you set the scope and preferences for a run, while the results provide organized records that are easier to review and use.

Input

Provide the values that define the scope and preferences for the run. Review each option before starting so the resulting dataset matches the information you want to analyze or reuse.

Name	Type	Description	Default
hashtags	array	Niche hashtags (without #) to discover creators from, e.g. ["fitness", "gymtok"]. This is the most reliable discovery path — recommended.	—
keywords	array	Free-text niche terms, e.g. ["home workout", "fitness coach"]. Each is tried as a TikTok search; if search returns nothing it falls back to the collapsed hashtag ("home workout" → #homeworkout). For best results prefer hashtags.	—
maxCreators	integer	Maximum number of ranked creators to return (you are charged per returned creator).	50
maxFollowers	integer	Exclude creators above this many followers. 0 = no upper limit. Use to target micro/nano creators.	0
minFollowers	integer	Exclude creators with fewer than this many followers. Set low to surface micro-influencers.	1000
proxyConfiguration	object	TikTok rate-limits datacenter IPs, so a RESIDENTIAL proxy is required for reliable access. Leave default.	{"useApifyProxy":true,"apifyProxyGroups":["RESIDENTIAL"]}
requireEmail	boolean	If true, return only creators whose public bio exposes an email address. Useful for building an outreach list.	false
sortBy	string	Ranking signal. engagement_rate = interactions per view; view_to_follower_ratio = virality; followers = audience size; avg_views = reach.	"engagement_rate"
videosPerQuery	integer	How many videos to sample per keyword/hashtag to discover creators and measure engagement. Higher = wider discovery.	30

Output

A successful run produces a dataset of structured items collected according to your inputs. You can review the records, use them in analysis, or pass them to another part of your workflow. The exact fields depend on the source data and the options selected for the run.

Usage

1. Open the actor page.
2. Fill in the input values and review the configuration.
3. Run the actor and wait for the collection to finish.
4. Download the results from the dataset and use the records in your preferred workflow.

Pricing

Pricing is pay-per-event, so you pay only for results.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.