A creator discovery export can mention the same channel many times. Some mentions come from repeated observations of one seed; others come from genuinely different seed channels. A shortlist becomes more useful when those two situations remain distinct and its audience-size evidence stays attached to the candidate.
YouTube Creator Portfolio Planner reads an existing discovery batch and produces a ranked assessment for each usable candidate channel. It consolidates seed references, interprets supported subscriber evidence and applies a configured audience band. The ranking is a transparent way to organize research from an observed batch.
Preserve the discovery relationship
The example retains a channel recommendation from the installed September public snapshot. It is a saved relationship observed in a discovery widget, with its original checkedAt value. Subscriber display text is also historical and should be refreshed before a commercial decision.
{
"items": [
{
"requestedChannelId": "UCBJycsmduvYEL83R_U4JriQ",
"similarChannelId": "UCG7J20LhUeLl6y_Emi7OJrA",
"similarChannelName": "The Studio",
"similarSubscriberCountText": "1.15M subscribers",
"checkedAt": "2026-09-22T05:46:32.738Z"
}
],
"maxInputRows": 100,
"maxResults": 10
}
The candidate's channel ID provides a more stable grouping key than its display name. Preserve seed IDs where available too. A repeated mention from the same seed should increase the duplicate-mention evidence without increasing the number of distinct recommending seeds.
Interpret the subscriber estimate carefully
The transformation distinguishes observed, hidden, invalid and missing subscriber evidence. A display string such as 1.15M supplies an approximate quantity with limited precision. It should not become a claim that an exact number of people will receive a campaign.
Store subscriberCountApproximate and the associated state in the shortlist table. An unknown count needs a review route rather than an automatic rejection based on an invented zero. Conflicting source observations should remain visible, especially if the discovery batch contains several capture dates.
Set an audience band for the actual brief
audienceMin and audienceMax let the team express the size range relevant to its campaign. Candidates outside the band remain inspectable with a different action. This helps a reviewer explain why a plausible creator was deprioritized rather than assuming the transformation failed to find it.
The deterministic rank uses band fit, then seed overlap and then subscriber count. Keep those fields in the receiving worksheet so a person can reconstruct the ordering. A rank alone hides whether a channel rose because of broader discovery evidence or because it happened to have a larger displayed audience.
Make partnership qualification a separate step
Seed overlap counts recommendations from the seeds present in your source batch. It says nothing directly about common viewers, audience geography or purchase behavior. The installed output leaves topics unavailable instead of inventing a topical profile from the recommendation relationship.
Before contacting a creator, a researcher should inspect current content, audience fit and an appropriate public business route. That work needs its own evidence. The Actor neither sends outreach nor predicts campaign return. Its role ends with an explainable shortlist and a set of questions for the next reviewer.
Retain the run summary when exporting. Source-row and result caps can narrow the discovered candidate set, and a rank within that set should not be described as a ranking of all YouTube creators. Reprocessing the same batch is another paid processing decision, so keep accepted output in your own workflow rather than rerunning it merely to reopen a spreadsheet.
Price and verification scope
Listing pricing read on 23 October 2026 is $0.012 per result-found event on the FREE tier. The documented unit is: One useful creator assessment delivered with source evidence and a recommended next step. Source errors, invalid rows and budget diagnostics request no result event. Other platform tiers have their own rates. This pricing record has no separate start event. A usable result from an illustrative input can still be billable; inspect the applicable listing and run spending limit before executing it. maxResults is an output cap, separate from the platform's Max total charge option.
This article uses the installed source contract from build 0.1.6 (RcLCINskM6bcDmTpc). The example is a shortened historical source projection, with local pure-transform validation only. No new Apify cloud build or run was started for this article. Local output does not establish cloud delivery, customer acceptance or commercial results.
Inspect the Actor's current input and pricing.
AI-assisted draft; independent technical and cover review is required before publication.
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