# Mouss | Unlimited Scaling (@mouss_us) on x

- id: koinon:creator:x_mouss_us
- url: https://koinonlink.com/kol/x/mouss_us
- schema_version: 1.4

## Identity
- platform: x
- handle: mouss_us
- platform_url: https://twitter.com/mouss_us
- website: https://wa.me/33648819810
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1648
- following: 295
- posts_total: 3512
- posts_observed: 10
- posts_per_day: 2.248
- account_age_days: 1562
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00061
- best_post_interactions: 1
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: ecommerce
- subcategory: ecom_ads
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: Meta反馈分数机制, 广告delivery实时监控, 电商无封禁规模化, post-purchase survey信号
- bio: CEO Unlimited Scaling  | We help ecoms scale unlimited without blocks  | Feedback Score Expert and more 📊

## Audience (inferred)
- status: present
- description: E-commerce operators and small-to-mid-sized advertisers running Meta ads, focused on scalable, non-banned campaigns
- roles: ads
- seniority: practitioner
- pain_points: Can't view real-time metrics directly after Meta hid feedback scores, Feedback scores are delayed by a month, based on order fulfillment data from the previous month, Ad delivery is influenced by delivery signals but can't be proactively adjusted, Post-purchase survey signals are hard to control, increasing account risk
- posts_analysed: 2
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.9
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 66
- authenticity_basis: engagement_observed
- credibility_score: 66
- flagged_for_review: false
- koinon_bd_grade: A — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_mouss_us#11d57d65] there's no number to check anymore. meta removed the visible feedback score. the only live readout left is what delivery is doing. the input was never in the ad account. it's generated after the customer gets the order. shipping, product accuracy, support response. from a cycle t (https://twitter.com/mouss_us)
- [x_mouss_us#4fe26649] the facebook feedback score you're feeling this week was written by orders you shipped last month. the signal is built from post-purchase surveys. deliveries that already happened. the gap between what the ad promised and what the customer opened. so you

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=80, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=80, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=108, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.5, freshness_days=80, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=108, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=108, method=platform_profile

## Freshness
- profile_checked_days_ago: 108
- content_analysed_days_ago: 80
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 9
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_mouss_us
- Request removal: https://koinonlink.com/claim?k=x_mouss_us
- Terms: https://koinonlink.com/for-ai