Lifecycle Pillar
Listen where complaints surface first
Track public social and review platforms for reputation drift and complaint intensity linked to merchant portfolios. Consumer complaints often appear on social media weeks before they escalate to formal disputes.
How it works
Discover merchant presence
AURA identifies the merchant's profiles across monitored platforms: Facebook, Instagram, Google Reviews, Xiaohongshu, Lemon8, and TikTok.
Monitor for risk signals
Public posts, reviews, and comments are scanned for complaint patterns, scam accusations, and sentiment shifts using configurable keyword rules.
Feed into risk triage
Reputation signals are surfaced as contextual evidence within the merchant's risk profile, supporting (not replacing) formal investigation workflows.
Social Signals
5| Type | Author | Review | Risk | Date | |
|---|---|---|---|---|---|
| Scam Report | @syafiqah_hr | Ordered 3 weeks ago, no tracking, seller ghosted me. This is a scam! Bunga Emas... | 82 | 2h ago | |
| Bram Violation | google_reviews | They're selling vape juice on their Instagram stories under the same brand. | 94 | 5h ago | |
| Consumer Complaint | @azlin.my | Package arrived damaged, refund request ignored for 10 days now. | 48 | 1d ago | |
| Category Pivot | New post promoting 'casino demo accounts'. This is a retail page?? | 76 | 2d ago | ||
| Social Link Added | tiktok | Merchant linked a new TikTok Shop account to their profile bio. | 28 | 3d ago |
Public-platform monitoring
Monitor consumer signals from Facebook pages and groups, Instagram business profiles, Google Business reviews, Xiaohongshu (Little Red Book), Lemon8, and TikTok. These platforms are where Malaysian and ASEAN consumers first voice complaints about non-delivery, scams, counterfeit products, and service failures, often weeks before formal chargebacks appear.
Configurable keyword context
Risk teams can define portfolio-specific terms and complaint patterns to improve triage precision. Keywords can target specific risk categories (gambling terminology, pharmaceutical product names, counterfeit brand indicators) in English, Bahasa Malaysia, and Chinese. Keyword sets can be different per merchant segment.
One signal layer in risk operations
Sentiment data is a supporting layer, not a decision-maker. It sits alongside verification, web monitoring, and investigation outputs in the merchant's risk profile. A spike in consumer complaints doesn't automatically trigger enforcement. It adds urgency to an analyst's investigation queue and provides context when reviewing drift alerts.
Trend detection across portfolios
Beyond individual merchant signals, AURA can surface portfolio-level patterns: emerging complaint trends across a merchant category, seasonal fraud spikes, or new scam typologies appearing across multiple merchants. This gives risk leads early visibility into systemic issues before they scale.
Frequently asked questions
- Does sentiment alone trigger enforcement action?
- No. It is a contextual signal that supports analyst investigation and evidence review. Enforcement decisions are always made through the formal investigation workflow.
- Can teams tune what they monitor?
- Yes. Sources, keywords, and monitoring terms can be aligned to merchant portfolio risk policy. Different merchant segments can have different keyword sensitivity.
- Which platforms are monitored?
- Facebook, Instagram, Google Reviews, Xiaohongshu, Lemon8, and TikTok. Additional platforms can be added based on portfolio and regional requirements.
- How is this different from web change detection?
- Web change detection monitors the merchant's own website. Reputation monitoring tracks what consumers and the public say about the merchant on third-party platforms.