See the truth behind the numbers before you sign.
Bigfluencer cross-checks an Instagram profile's views, likes and comments against 7 statistical signals and flags purchased-engagement patterns in seconds.
What Bigfluencer reveals in seconds
Why Bigfluencer
Don't pay for ghost followers. Spot bought engagement before money changes hands.
7 statistical signals
Engagement rate, comment/like balance, variance, view→like conversion, spikes and more — cross-checked at once.
Bot pattern detection
Median/MAD robust statistics catch flat, machine-like engagement and isolated paid boosts a simple average would miss.
Answer in seconds
Enter a public username and get an influence score, signal breakdown, red flags and a per-post fingerprint.
Compare candidates
Every profile you analyze is added to a comparison table so you can rank influencers side by side.
The 7 signals behind every score
Each analysis runs a profile's real post data through seven independent statistical checks. Every signal is scored 0–100 and weighted into the final verdict.
Engagement rate fit
Catches bought followers & engagement podsLikes and comments per follower are compared against the healthy range for the account's size — a 50K account and a 5M account behave very differently. Engagement far below the band points to ghost followers who never interact; far above it points to engagement pods or bot boosts pumping the numbers.
Comment / like balance
Catches cheap like packagesReal audiences comment in a predictable proportion to how much they like. Purchased likes are cheap; purchased comments are expensive — so fraudsters usually buy only likes. When a profile shows thousands of likes but almost no conversation underneath, this signal flags it.
Engagement variance
Catches automated, machine-like activityOrganic engagement is naturally messy — some posts land, some don't. Bot services deliver suspiciously consistent numbers on every post. We measure the spread of engagement across recent posts: too flat means automation, too wild means artificial boosting on selected posts.
View → like conversion
Catches purchased video viewsA predictable share of real viewers tap like. When videos show huge view counts but conversion collapses far below the organic norm, the views were most likely bought — inflated reach that will never translate into sales for your brand.
Follower / following balance
Catches follow-for-follow growthAccounts that grew by mass-following thousands of profiles and waiting for follow-backs carry audiences that never chose them. The follower-to-following ratio exposes this growth history at a glance — a warning sign the "reach" is hollow.
Isolated spike detection
Catches one-off paid boostsUsing robust median statistics, we detect single posts that explode far above the account's typical performance. One isolated spike is the classic fingerprint of a paid boost bought to impress sponsors — often on exactly the post shown in a media kit.
Comment quality
Catches bot comment farmsBot comments look alike: single emojis, "nice pic!", generic praise with no connection to the content. We analyze the actual comment texts for repetition, length and diversity to separate a real conversation from a comment farm filling the void.
Simple pricing
Start with 2 free analyses. Need more? Pick a pack — 1 credit per analysis, credits never expire.
- ✓ 10 full 7-signal reports
- ✓ 1 credit per analysis
- ✓ Credits never expire
- ✓ 30 full 7-signal reports
- ✓ 1 credit per analysis
- ✓ Credits never expire
- ✓ 60 full 7-signal reports
- ✓ 1 credit per analysis
- ✓ Credits never expire