Fetch one tracked profile by id: follower count, bio, average views/likes/engagement across time windows, and recent tracked posts. The averages are the baseline outlier scores are computed against. Use search_profiles first to resolve a handle to an id.
Fetch one tracked creator's full record by profile id: follower count, bio, average views/likes/engagement across time windows, and their recent tracked posts. Those averages are the exact baseline every outlier score is measured against, so this is the call that tells you what "normal" looks like for an account before you judge any single post. Resolve a handle to an id with search_profiles first. Each call costs 1 credit (1 credit = $0.01).
GET /api/v1/profiles/{profileId}. Authenticate with your API key. Same call in three languages:
cURL
curl -X GET "https://viraloutliers.com/api/v1/profiles/EXAMPLE_ID" \
-H "Authorization: Bearer so_live_YOUR_KEY"Python (requests)
import requests
r = requests.get(
"https://viraloutliers.com/api/v1/profiles/EXAMPLE_ID",
headers={"Authorization": "Bearer so_live_YOUR_KEY"},
)
print(r.json())JavaScript (fetch)
const res = await fetch("https://viraloutliers.com/api/v1/profiles/EXAMPLE_ID", {
method: "GET",
headers: { "Authorization": "Bearer so_live_YOUR_KEY" },
});
const data = await res.json();
console.log(data);| Name | Type | Description |
|---|---|---|
profileId* | string (path) | Profile id from search_profiles or search results. |
A single profile record: platform, handle, display name, bio and follower count, plus the account's average views, likes and engagement across several time windows, the performance baseline, and a list of its recent tracked posts with their own stats and thumbnails. Together that is enough to both benchmark a specific post and get a quick read on the account's overall trajectory.
The averages here are not decoration: they are the denominator in the outlier math. Divide any post's views by the matching-window average and you have reproduced the outlier score the platform computes at scale.
get_profile is a direct, synchronous read against the tracked database (no job to poll). It takes the internal profileId, which you get from search_profiles, compare_profiles, or the profile attached to any post record. If a profile is not in the database yet, crawl_profile adds it and its recent posts within minutes, after which get_profile returns the full record.
The recent-posts list and the averages reflect the latest crawl of the account. For accounts you want kept continuously fresh, track_profile schedules automatic refresh crawls so get_profile always reflects current stats without you re-crawling by hand.
Account audits are the core one: pull the profile, compare its recent posts to the baseline, and flag which formats over- and under-perform. Benchmarking workflows fetch a profile to turn a raw view count into a meaningful multiple ("3x their normal reach"). Reporting agents combine the follower count and averages into a one-line health summary for a creator or competitor.
Because the record bundles identity, baseline and recent posts, a single call answers "who, how big, how engaged, and what have they posted lately". Those are the inputs most creator-strategy tasks start from.
To build this yourself you would scrape a creator's post history, store enough of it to compute rolling averages per time window, and keep re-scraping to stay current, all of it against platform endpoints that rate-limit and change shape. The baseline is the hard part, and it is worthless if it goes stale.
get_profile returns the baseline already computed and continuously refreshed, in one authenticated read at a flat credit price, joined to the account's recent posts. Compared with static influencer-stats exports, this is live-queryable and uses the same baseline the outlier engine runs on, so your benchmarks match the rankings elsewhere in the system.
1 credit ($0.01) per call in prepaid credits (1 credit = $0.01). For example, 100 calls per dollar. Subscriptions include monthly credits; top-up packs start at $15. Failed asynchronous jobs are refunded automatically, and calls stop at a zero balance, never a surprise bill. See the full pricing table.
get_profile returns the account's average views and engagement per time window. Divide any post's views by that baseline and you have exactly the outlier logic this platform runs at scale.
get_profile reflects the latest crawl of the account. To keep it current automatically, call track_profile to schedule refresh crawls on a daily, every-3-days or weekly cadence. Then get_profile always returns fresh follower counts, baselines and recent posts without you re-crawling by hand.
Also available as an MCP tool.
Related topics: influencer statistics API · follower analytics · account performance baseline · creator benchmarking API · engagement rate baseline