G
Glimpse
Use Case

Spot Fake Engagement

Tell a real backlash apart from a coordinated bot campaign before you react to either one.

The Problem

Why this is hard without Glimpse

A sudden wave of negative — or suspiciously positive — posts can be genuine customer sentiment, or it can be a coordinated campaign designed to look like it. Reacting to the wrong one wastes time and can make a manufactured story look credible.

Why It Matters

What's actually at stake

Responding publicly to fake engagement can accidentally validate it. Ignoring genuine feedback because it looked like noise is just as costly. Telling the two apart quickly and reliably is the actual hard part, not just noticing volume moved.

The Glimpse Workflow

How it works

The Outcome

What you get

See how bot detection works

See it on your own brand

Compare plans and get started.

View Pricing
Spot Fake Engagement FAQs

A single bot mention is one data point; fake engagement is often coordinated — many accounts posting in a similar pattern or timeframe. Glimpse's filtering looks at posting timing patterns across accounts specifically to catch that coordination.

Filtering weighs multiple signals together (sentence structure, timing, account profile) rather than a single trigger like posting volume, which is specifically meant to reduce false positives against genuine organic spikes.

No — mentions identified as bot or troll activity are separated out before scoring, so they don't inflate or deflate your reported reputation.

Filtered activity is kept distinct from your primary sentiment feed rather than silently discarded, so it remains available to review separately from your core metrics.