# Hendrik Haandrikman 🐈 (@HHaandr) on x

- id: koinon:creator:x_hhaandr
- url: https://koinonlink.com/kol/x/HHaandr
- schema_version: 1.4

## Identity
- platform: x
- handle: HHaandr
- platform_url: https://twitter.com/HHaandr
- website: http://www.revenuecat.com
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 5127
- following: 1381
- posts_total: 5438
- posts_observed: 3
- posts_per_day: 1.783
- account_age_days: 3050
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00234
- best_post_interactions: 12
- 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: software
- subcategory: martech
- category_confidence: 0.8
- category_source: derived_from_recent_content
- topics: mobile app monetization, subscription analytics, cross-platform revenue tracking, subscription lifecycle management, LTV and retention analysis
- bio: Dad, husband, Gym-rat * Helping apps make more money @RevenueCat * very into mobile * social gaming alumni * he/him * #chaoticgood

## Audience (inferred)
- status: present
- description: Mobile app developers and monetization managers focused on subscription-based revenue, especially in social gaming and connected platforms
- roles: ecom_ops
- seniority: practitioner
- pain_points: Struggling to get unified revenue data across multiple platforms like iOS, Android, web, and Roku, Having difficulty tracking subscription lifecycle events such as trials, renewals, cancellations, and billing issues, Lacking cohort analytics to measure LTV, retention, and revenue trends over time
- posts_analysed: 5
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.8
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 72
- authenticity_basis: engagement_observed
- credibility_score: 72
- 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_hhaandr#bb5fea12] @davidcafor @AndresDefi @elwatto Analytics you usually do not get from the stores alone: (https://twitter.com/HHaandr/status/2042295657218576534)
- [x_hhaandr#fc891dec] ◦Unified subscription and revenue view across iOS, Android, web, Roku, and other connected providers
- [x_hhaandr#d6f4e89e] ◦Cohort analytics for LTV, retention, and revenue over time
- [x_hhaandr#371ffb37] ◦Subscription lifecycle visibility across trials, renewals, cancellations, billing issues, grace periods, expirations, and entitlements
- [x_hhaandr#c3948ac6] ◦Cancellation

## 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=21, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=79, 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=79, 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=79, 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: 79
- audience_updated_days_ago: 21

## AI retrieval
- indexing_requests: 11
- 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_hhaandr
- Request removal: https://koinonlink.com/claim?k=x_hhaandr
- Terms: https://koinonlink.com/for-ai