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Fake engagement check for @Kajal_Aggarwal_Official

Kajal Aggarwal 💃 — public reach metrics and manipulation-risk assessment dated 2026-09-02.

Kajal Aggarwal is an Indian actress who works predominantly in Telugu and Tamil language films. https://adsly.me/@kajal_aggarwal_official Buy ads: https://telega.io/c/Kajal_Aggarwal_Official

Grade D some signals require caution cleanliness index
checked 2026-09-02
Subscribers
10,151
Median views
13,908
ERR
137.0%
Posts sampled
40
Niche Movie

Assessment summary

Views exceeding subscriber count combined with disabled comments and roughly 89% of posts deleted point to the risk of artificial reach inflation or purging of ad posts. With an infrequent posting schedule (about 0.2 posts per day), this combination of metrics makes forecasting ROI difficult and advertising questionable.

Compared with similar channels

Compared with 14 checked Movie channels with no visible signs of manipulation. There are too few channels of a similar size, so the whole niche is used: 849 to 1,887,650 subscribers.

ERR (reach) higher than 14 of 14
137% for @Kajal_Aggarwal_Official similar channels median: 27%
Reactions per 100 views lower than 8 of 13
0.78 for @Kajal_Aggarwal_Official similar channels median: 1.23

This is not a niche norm: only channels checked by the service are included. An unusually high ERR can also be a sign of inflated views.

How the assessment was produced

Data source
Public Telegram data: posts, views, reactions, and channel metadata.
Date or snapshot
2026-09-02
Sample
The latest 40 public posts available at check time.
Calculation method
TG Inspector calculates metrics from the saved snapshot and combines independent signals into a deterministic 0–100 cleanliness index.
Factual result
The @Kajal_Aggarwal_Official assessment dated 2026-09-02 uses 40 recent public posts. At that snapshot the channel had 10,151 subscribers, median post views were 13,908, ERR was 137.0%, and the cleanliness index was 50/100.
Limitations
This is a probabilistic assessment based on public data, not proof of intentional manipulation or a real-time channel measurement.

Full methodology and interpretation rules

Advertising outlook

Advertising placement: questionable.

Some of the views may be fake.

About 6,955–13,908 people will see your post in the first 48 hours.

Reach of advertising posts

No advertising posts among the latest 40.

What grade D means

Clear signs of manipulation: several strong signals at once. Ads here are risky.

What to pay attention to

High reach driven by external forwards: ERR ≈ 137%

Views exceed the subscriber base, but this looks organic rather than inflated: view counts vary significantly from post to post, and reactions are genuine. This is typical for content actively forwarded to external chats (work groups, aggregators) or going viral outside the channel.

Dynamics and anomalies

Views by post

The latest 40 posts with views, from Mar 3 to Sep 2. The dashed line is the median (13,908).

014K29KMar 3: 28,697 viewsApr 24: 14,196 viewsApr 30: 12,058 viewsApr 30: 12,688 viewsApr 30: 12,070 viewsApr 30: 14,036 viewsApr 30: 13,020 viewsApr 30: 13,312 viewsMay 4: 13,375 viewsMay 10: 13,114 viewsMay 17: 13,064 viewsMay 27: 12,154 viewsMay 27: 14,994 viewsMay 27: 12,291 viewsMay 27: 14,671 viewsJun 4: 11,395 viewsJun 4: 11,225 viewsJun 4: 12,503 viewsJun 4: 11,525 viewsJun 4: 11,938 viewsJun 4: 12,386 viewsJun 4: 13,869 viewsJun 4: 13,612 viewsJun 4: 13,867 viewsJun 10: 13,948 viewsJun 10: 15,092 viewsJun 10: 18,299 viewsJun 10: 17,490 viewsJun 10: 17,116 viewsJun 16: 17,045 viewsJun 16: 19,607 viewsJun 16: 17,116 viewsJun 16: 20,377 viewsJun 16: 19,756 viewsJun 22: 19,548 viewsJun 22: 19,505 viewsJun 22: 19,547 viewsJun 22: 21,224 viewsJun 22: 21,294 viewsSep 2: 508 views Mar 3Sep 2

Maximum: 28,697 views. Data as of Sep 2.

What scoring found in the view pattern

High reach driven by external forwards: ERR ≈ 137%

Views exceed the subscriber base, but this looks organic rather than inflated: view counts vary significantly from post to post, and reactions are genuine. This is typical for content actively forwarded to external chats (work groups, aggregators) or going viral outside the channel.

Cleanliness-index history

The channel has been checked once — the chart will appear after the next check.

Check today: @Kajal_Aggarwal_Official

Data from 2026-09-02 — 18 days old. Check the channel today before buying ads.

Buy advertising

No signs of manipulation. You can buy ads on these marketplaces — they have channel catalogs, prices, and checkout.

We don't sell ads. This channel may not be listed there.

Where to buy advertising

Affiliate links: we get a commission. It never affects the channel's score.

Monitor this channel

The bot will recheck @Kajal_Aggarwal_Official and message you if reach drops, subscribers jump, or the cleanliness index changes.

Monitor @Kajal_Aggarwal_Official

Questions about @Kajal_Aggarwal_Official

What fraud risk level was identified for the channel?

The channel received a risk score of 50 out of 100 (medium risk zone) with low confidence. Concerns are raised by the combination of reach exceeding 100% of the subscriber base, disabled comments, and 89% deleted posts.

Why is ad placement considered questionable?

There is a possibility that views are generated artificially or content is driven by unstable external traffic. Additionally, the mass deletion of past posts makes it impossible to track the performance of previous placements.

What is the posting frequency in the feed?

Posts are published on average once every 5 days (0.2 posts per day). An advertisement won't get lost in the content stream, but accurate reach forecasting is difficult due to the lack of advertising history in the sample.

Similar channels in Movie

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