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Veriscore/Audience Intelligence Report
V
Tiktok · Subject

@viral.dance.co

Viral Dance Co

#
920K
Followers
0.60%
Engagement
41%
Authentic
68Risk / 100
Sketchy — Likely inflated views
84% confidence · 16.1s analysis
Recommendation

View counts are far out of line with engagement and saves are near zero. Strong indicators of purchased views. Do not proceed without an independent audience audit.

01
Overview

Account Snapshot

Followers
920K
Authentic
41.0%
Suspicious
59.0%
Engagement
0.60%
Avg Views
1.9M
Plays per video
Avg Likes
4.2K
Per video
Avg Comments
38
Per video
Avg Shares
60
Per video
Influencer Risk Evaluation Model

IREM Evaluation

IREM v1
01
Authenticity Integrity
Weak30/100
02
Engagement Stability
Weak38/100
03
Audience Quality
Weak36/100
04
Behavioral Consistency
Moderate60/100
05
Reputational Risk Signals
Moderate52/100

Evaluated under the Influencer Risk Evaluation Model (IREM) — a Regnor applied intelligence framework.

02
Authenticity

View Authenticity

High Risk · 72/100
Views / Followers
2.01x
Healthy: >0.05x
Likes / Views
0.2%
Healthy: 2–15%
Saves / Views
0.00%
Healthy: >0.5%
Comments / Likes
0.9%
Healthy: 1–5%
Shares / Likes
1.4%
Organic share signal
Avg Plays
1.9M
Views per video
Why saves matter
Saves (bookmarks) signal a viewer found the content valuable enough to return to — a far stronger intent signal than a passive like or view. Low saves on high view counts is a red flag for purchased views. Zero saves on 1.9M average views is highly suspicious.
03
Forensics

Comment Intelligence

Generic Comments
54.0%
Bot-typical phrases
Spam Comments
12.0%
Promo / F4F
Emoji-Only
38.0%
Low-effort interaction
Duplicate Comments
9.0%
Comment-pod signal
04
Content

Content Quality

Avg Hashtags
17.0
Optimal: 3–10
Caption Similarity
46.0%
Low = varied content
Original Sound
28.0%
% using own audio
Hashtag Spam
64.0%
>15 tags/video
05
Trend

Engagement Trend

Risk

Critical Findings

1 flagged
Zero saves on high view counts
Videos average 1.85M views but record effectively zero saves. Genuine high-reach content almost always accrues saves; this pattern is consistent with purchased views.
06
Assessment

Analyst Assessment

High risk
The account exhibits a textbook purchased-view pattern: very high view counts paired with negligible likes, comments, and zero saves. The audience that does engage skews low-quality. This profile carries high partnership risk.
Supporting Evidence
  • ·0.23% likes-to-views ratio versus a 2–15% healthy band.
  • ·Zero saves across analyzed videos at ~1.85M average views.
  • ·54% generic comment rate among the comments that exist.
Brand Risk Assessment

High brand risk. The reach is unlikely to convert to genuine attention. Not recommended for performance-driven campaigns.

07
Methodology

Detailed Signal Analysis

View AuthenticityWeight 35%72/100
  • ·Likes-to-views ratio of 0.23% is far below the healthy 2–15% range.
  • ·Zero saves recorded across analyzed videos despite high view counts.
  • ·Views-to-followers ratio is high while engagement is very low — classic purchased-view signature.
Comment QualityWeight 25%58/100
  • ·High generic and emoji-only comment rates.
Content QualityWeight 20%36/100
  • ·Heavy hashtag usage; moderate caption repetition.
Follower QualityWeight 20%60/100
  • ·Estimated authentic follower share of 41%.
08
Next Steps

Action Plan

  1. 01
    Request an audience demographics breakdown and follower audithigh

    About 59% of sampled followers show suspicious characteristics — confirm reachable audience size before pricing the deal on follower count.

  2. 02
    Manually review comments on 3–5 recent posts before committinghigh

    54% of comments are generic or low-effort — spot-check that real conversation is happening, not pods or bots.

  3. 03
    Require native TikTok analytics before any spendhigh

    Only 0.23% of views convert to likes (healthy is 2–15%), a common signature of purchased views.

  4. 04
    Treat headline view counts as unverifiedhigh

    Effectively zero saves against ~1,850,000 average views — genuine high-reach content almost always accrues saves.

  5. 05
    Do not commit budget without independent verificationhigh

    Several high-risk indicators are present.

This report is generated by algorithmic analysis of publicly available data and AI evaluation. Verdicts and scores are signals and estimates, not accusations or statements of fact about any individual. They reflect a single point in time and can change as an account evolves. This is not a professional fraud investigation or legal determination — use it as one input alongside your own due diligence. To re-run with fresh data, use Force Refresh above. If you believe a result is inaccurate, request a recheck or correction at romil@regnor.systems.