Clean up inactive social follows with automated unfollow tools

Executive Summary

Many active social users struggle with “feed relevance fatigue”: long follow lists filled with inactive, low-quality, or bot accounts make discovery and attention management harder, and manually pruning 200–2,000 follows is tedious. This affects an estimated 250 million power social users worldwide, a segment that supports a $3.0B annual market at roughly $12 ARPU/year for tools that meaningfully improve the feed experience. You could build a privacy-first browser/mobile extension plus web dashboard that combines lightweight ML classification (last post date, engagement decay, bot signals) with deterministic rules so users can bulk unfollow, mute, or schedule maintenance runs and recover actions with an audit log. Monetization is straightforward—annual subscriptions around $12 or tiered monthly plans—while key engineering work will be connector reliability (APIs, rate limits, UI automation), robust undo/backup, and explicit opt-in data processing to avoid privacy and platform-policy issues. This is an attractive moment: users are tired of noisy feeds, browser extension platforms are more capable again, and small ML models can beat naive heuristics, which is why the opportunity scores 92/100 with a revenue potential of 72/100 despite medium competition. To stand out you’ll need superior classification accuracy, transparent privacy and consent, easy recovery to reduce user fear, and partnerships for credibility; the main risks are platform policy changes, automation limits, and building trust at scale. If you can solve those operational and trust challenges, this is a reasonable product to pursue—moderate technical complexity, clear value for a sizable addressable audience, and predictable subscription economics make it worth validating with a focused MVP.