Opportunity ledger / Dossier O-0023

Candidate▲ Warming ×2.0OPPORTUNITY DOSSIER · O-0023

Diagnosing unexplained TikTok reach loss

Help creators investigate sudden reach suppression, test likely causes, and choose a recovery path.

First seen 2026-07-03 · Last updated 2026-07-15 · Recalculated daily

13.2
Evidence confidence, not a return forecast
2
Independent source items, deduplicated by post
1
Public source families
0
Payment evidence: current spend or explicit intent
ProblemSome TikTok accounts receive almost no For You traffic without a clear warning, while support responses offer little diagnostic detail.
People affectedTikTok creators, creator agencies, and commerce teams operating content accounts
Named alternativesTikTok
TopicsTikTok operationsReach diagnosisAccount recovery
Weekly mentions · 12 weeks▲ Warming ×2.0
04-2705-2506-2207-13

Trend factor ×2.0, capped at 2.0.

Representative evidence

2 public excerpts · 2 items in the full chain
Pain★★★☆☆First-hand pain

从平均100万+浏览量跌到5小时内勉强6000,我连1万浏览量都很难达到,我的内容没有被推送给新受众了 Chinese research excerpt

Use the source link for the original-language context.

Reddit2026-07-11View source ↗
Pain★★★☆☆First-hand pain

I don’t get more than 80 views and 2 likes😭😭 help. Source excerpt

Reddit2026-07-03View source ↗

Follow the full evidence chain

Traceable items · inspectable scoring · warming and payment alerts

Scoring summary

Evidence confidence = strength × evidence volume × source diversity × payment × competition × trend × 10. Counts use independent content items; only first-hand pain, current spend, explicit willingness to pay and concrete feature requests affect the score. Repeated posts by one author are discounted. Scoring and status changes follow deterministic rules.

“Evidence-backed” means the problem appears real, recurring and connected to spending. It does not mean the business is worth building. Read the full methodology.