One Full-Time Moderator Eliminated — 100+ Ad Accounts Managed Automatically in Real Time
A mass tort marketing agency was employing a full-time person to moderate comments across 100+ Meta ad accounts. The ads were sensitive (medical injury cases) and attracted high volumes of negative and spam comments. We automated the entire moderation system — instant response to interested leads, immediate hiding of damaging comments.
Quick Overview
The Challenge
Sensitive Ads, Angry Comments, and Missed Leads
Left visible, these comments damage ad performance, deter other genuine claimants from engaging, and create compliance and reputational problems for the law firm clients.
The agency was running 100+ Meta ad accounts across dozens of clients. One full-time employee was employed entirely to moderate comments — replying to interested leads, hiding negative comments, filtering spam. At scale, they couldn't keep up. Interested leads were waiting hours for engagement. Damaging comments were staying visible for too long. And there was no way to add more ad accounts without adding more moderators.
Key Pain Points:
- One full-time employee ($40K–$60K/year) dedicated entirely to comment moderation
- Hours delay in responding to interested commenters — leads going cold
- Negative and profane comments staying visible — damaging ad perception
- Couldn't scale ad account volume without proportional headcount increase
- Inconsistent moderation — human moderator couldn't maintain coverage across 100+ accounts simultaneously
The Solution
Real-Time AI Moderation Across Every Account Simultaneously
Every comment that appears on any ad triggers the system immediately. AI sentiment analysis classifies the comment: interested/positive (engage), negative (hide), spam (hide), neutral (monitor). Positive comments receive an immediate automated reply with the appropriate engagement message and conversion link. Profane, negative, or spam comments are hidden within seconds.
The agency team retains the ability to review hidden comments if needed, but the system handles over 95% of cases automatically without any human input.
How It Works:
- Meta Graph API webhooks monitor all comments across 100+ accounts in real time
- Every comment triggers AI sentiment classification
- Positive/interested comments receive automated reply within seconds
- Profane, negative, and spam comments auto-hidden immediately
- Team retains oversight — can review hidden comments via dashboard
- System scales to any number of accounts with no additional configuration
Implementation: Standard build
Technical Challenge: Mass tort ads generate highly specific language around medical and legal topics. The AI sentiment model needed to distinguish between genuine injury claimants expressing distress (who should receive empathetic engagement) and hostile comments that should be hidden. This required careful classification logic beyond standard positive/negative sentiment.
The Results
One Full-Time Role Eliminated. Instant Response at Scale.
| Metric | Before | After | Impact |
|---|---|---|---|
| Moderation headcount | 1 FT employee | Zero manual work | $40K–$60K/year saved |
| Response to positive comments | Hours | Seconds | Leads engaged while warm |
| Negative comment visibility | Hours visible | Hidden immediately | Brand protection |
| Scalability | Capped by headcount | Unlimited ad accounts | No incremental cost |
Interested leads are now engaged within seconds of commenting. At the moment a genuine claimant expresses interest, the system responds and provides the conversion path immediately — before they've closed the tab.
Hear From the Client
Frequently Asked Questions
Can the automated replies be customised per client or campaign?
Yes. Reply templates are configured per campaign and can reference the specific case type, law firm, and conversion link. The system sends the right message for the right ad, not a generic reply.
What happens to comments that don't clearly fit positive or negative?
Ambiguous comments are classified as neutral and flagged for human review. The system only auto-hides comments it's confident about — anything uncertain is held for the team.
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