Account Overview
Creator Profile
Before InstaGrow
The Problem
The creator's Reels had been growing steadily — recipe content and wellness tips were consistently hitting 10K–30K views. But as reach grew, so did inbound spam. By the time they connected InstaGrow, their comment sections were receiving an average of 163 spam comments per week — roughly 23 per day across all posts.
The spam fell into three main patterns: follow-for-follow bots ("Great content! Follow back @xyz"), DM-bait accounts pushing earn-from-home links, and emoji floods from freshly-created accounts with under 50 followers. Instagram's native Hidden Words filter was active, but the creator estimated it was catching fewer than 40% of what came in.
The real cost wasn't the spam itself — it was what it was doing to the numbers. Real follower comments were getting buried. The visible engagement rate sat at 1.9%, well below the 3–4% typical for food creators in this follower range. And manual cleanup was consuming 2.5 hours per week with no scalable path forward.
Spam breakdown before InstaGrow (weekly average)
The Setup
The creator built their full three-layer filter in 18 minutes after connecting InstaGrow. Here's the exact configuration they used.
Instagram native Hidden Words — enabled
InstaGrow Keywords — 12 niche-specific rules
Added 12 keyword rules targeting the most common patterns for their niche. Unlike Instagram's Hidden Words (exact match only), InstaGrow's keyword matching is case-insensitive and catches partial matches automatically.
follow for follow → Hide
f4f → Hide
check my bio → Hide
check my profile → Hide
collab → Hide
dm for → Hide
earn from home → Delete
make money → Delete
buy followers → Delete
free followers → Delete
promo code → Hide
InstaGrow Rules — 2 multi-condition rules
The two Rules handled what keywords alone couldn't catch: emoji floods and buyer-intent comments.
// Rule 1: Emoji spam from new accounts
Emoji count > 8 AND Follower count < 75
→ Action: Delete
// Rule 2: Capture buyer intent (recipe queries)
Comment contains "recipe" OR "ingredients" AND Length > 8 chars
→ Action: Auto Reply ("Full recipe in our bio link!") + Send DM (with recipe link)
Rule 2 was set up not for spam, but to capture engagement. Anyone asking about a recipe got an automatic public reply and a DM — converting comment section activity into direct outreach.
28-Day Results
Spam Moderation
Engagement & Growth
Before — Week 1
After — Week 4
Key Takeaways
Keyword rules do the heavy lifting
66% of filtered spam (431 of 648) was caught by keyword rules — not the AI. Simple phrases like "follow back" and "check my bio" cover the majority of bot patterns. Add these first.
Rules catch what keywords can't
The emoji flood rule (emoji > 8 AND followers < 75) caught 217 comments that had zero keywords to match on — pure emoji spam from bot accounts. Without multi-condition rules, these all get through.
Engagement rate reflects real interaction
The jump from 1.9% to 3.2% wasn't from more engagement — it was from less fake engagement diluting the real number. Spam removal reveals the actual quality of your audience.
Data note: All figures are based on InstaGrow platform analytics from a creator account in the food & wellness niche (30K–50K follower range), Q2 2026. Creator identity anonymized at their request. Results represent this account's experience over the 28-day measurement period and are not guaranteed for all accounts — spam volume and engagement lift vary based on niche, posting frequency, and audience composition.
Set up your spam filter in under 20 minutes
InstaGrow's comment moderation is free, uses the official Meta API, and takes the same 18-minute setup described in this case study.
Start Free — No Credit CardRelated reading
- Instagram Spam Filter: How to Stop Spam Comments in 2026 — the step-by-step guide behind this case study
- Instagram Comment Bots: Risks & Safe Alternatives — why bots flood your comments in the first place
- How to Automate Instagram Comment Moderation — full automation guide
- All Case Studies →