Why your TikTok user run cost three queries

Three charges hiding behind one run

TikTok User Scraper bills four events, and three of them can fire on a single profile:

Event	Price	Included
Profile URL query	$0.005	The account itself
Follower query	$0.005	About 10 users
Following query	$0.005	About 10 users
Each user after	$0.0005

The part that surprises people is that getFollowers and getFollowing both default to true. Submit a profile URL and nothing else, and you have bought all three.

Across a hundred profiles that default is fifty cents in query fees you did not intend, plus every user the unwanted list returns at $0.0005 each. On accounts with large followings, the second half is much the larger number.

Say both out loud, every time

The habit worth building is never relying on the default:

def audience(urls, followers=True, following=False, cap=1000):
    # Always state both. They default to True, and each is its own $0.005.
    return client.actor("apidojo/tiktok-user-scraper").call(run_input={
        "startUrls": urls,
        "getFollowers": followers,
        "getFollowing": following,
        "maxItems": cap,
    })

Two extra lines, and the bill becomes something you chose.

You cannot turn both off

There is a floor. The listing states plainly that you must not disable both toggles in order to fetch a single user, and that every run must return at least ten users. Single-item queries are not permitted.

That tells you what the actor is for. It walks lists. It is not a lookup tool, and if you want one account’s follower count and bio, TikTok Profile Scraper is the right product and a much cheaper one.

The shape that makes the pricing work for you

Because each list query carries roughly ten free users, a shallow pass is almost entirely query fees:

• 20 profiles, followers only, capped at 10 users each: 20 × $0.01 = $0.20, and no item charges at all
• 1 profile, followers, 1,000 users: $0.01 + 990 × $0.0005 = $0.51

Two hundred users across twenty audiences for twenty cents is the cheapest way to decide which audience deserves the deep pull. Sample wide, then go deep once, rather than guessing and paying for depth on the wrong account.

One thing the output will not tell you

Followers and following arrive in the same dataset with the same shape, and nothing on a row says which list it came from. If you need that distinction, run the two directions as separate jobs with one toggle each. The query fees are identical either way, and you get labelled data instead of a merged pile.