← All templates
Influencer vetting

Influencer audit template

Audit X creators for fake followers, bot-like engagement, paid-post networks, and collaboration risk before you spend campaign budget.

Use this template →

X has too many accounts that look useful at a glance: inflated followers, paid verification, generic replies, copied engagement, and networks that amplify each other without real audience trust.

Kollab turns influencer vetting into an evidence-based workflow. Paste X profiles, let the agent collect public signals, calculate health metrics, score risk dimensions, and leave a report your brand team can review before outreach or payment.

How it works

  1. 01

    Collect the public X signals

    Kollab reads profile and recent timeline signals from each handle, then normalizes account age, follower data, bio links, verification, and visible engagement.

  2. 02

    Score fake-account risk

    The workflow checks engagement rate, follow-back ratio, generic replies, repeated promotional language, suspicious URLs, and network overlap.

  3. 03

    Compare creators side by side

    Every creator receives evidence, risk score, and a contact decision so brand teams can compare real audience quality instead of raw follower counts.

  4. 04

    Keep a reviewable audit record

    Kollab leaves the report, shortlist, rejected accounts, manual-review questions, and payment guardrails in the campaign workspace.

Starter prompt

I want to evaluate X influencers before a brand collaboration.

Brand context:
- Product or offer: [what we want to promote]
- Target audience: [who should care]
- Region and language: [markets we care about]
- Collaboration type: sponsored post / thread / long-term ambassador / affiliate
- Budget range: [optional]
- Must-avoid risks: fake followers, bot engagement, paid-post networks, irrelevant audience, reputation risk

X accounts to audit:
1. https://x.com/[username]
2. https://x.com/[username]
3. https://x.com/[username]

Please build an influencer health check report:
1. Normalize every URL or @handle into a clean account list.
2. For each account, collect public profile and recent timeline signals: account age, followers, following, bio, links, verification type, recent posts, replies, likes, and visible engagement.
3. Calculate useful metrics: account age, following-to-follower ratio, average engagement rate, reply percentage, generic reply rate, and daily likes given.
4. Flag suspicious patterns with evidence: extremely low engagement for follower count, high follow-back ratio, repetitive replies, pure emoji replies, generic praise, copied promotional wording, suspicious bio links, and clusters of accounts sharing the same brand or URL.
5. Produce a risk table with evidence for each account, a score, and one decision: reject, manual review, or safe to contact.
6. If several accounts appear connected, add a network section explaining the shared bios, links, handles, or engagement patterns.
7. Finish with a brand-safe shortlist: who to contact first, who needs manual review, who to avoid, and what extra proof to request before payment.
Use this template →