# Phil Kiel (@PhilKiel) on x

- id: koinon:creator:x_philkiel
- url: https://koinonlink.com/kol/x/PhilKiel
- schema_version: 1.4

## Identity
- platform: x
- handle: PhilKiel
- platform_url: https://twitter.com/PhilKiel
- website: https://taikundigital.com/linkbios/phil
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 16927
- following: 1098
- posts_total: 25063
- posts_observed: 4
- posts_per_day: 3.876
- account_age_days: 6467
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00089
- best_post_interactions: 15
- 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: 0.9
- category_source: derived_from_recent_content
- topics: Meta ads audience segmentation and exclusions, CBO optimization, High-performance creative and media buying
- bio: Scaling Meta accounts to 7+ figures/mo 🚀 High performance creative + hands on media buying. 200+ accounts audited https://t.co/CdlMYLcCrt

## Audience (inferred)
- status: present
- description: Meta ads media buyers and performance marketers running high-budget accounts
- roles: ads
- seniority: practitioner
- pain_points: Audience segments set up correctly but still missing performance due to poor exclusions, Deciding when to switch to or optimize CBO, Scaling accounts without flying blind on targeting
- posts_analysed: 3
- 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: 71
- authenticity_basis: engagement_observed
- credibility_score: 86
- 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_philkiel#40a7a6b7] Got into bean coffee at home because we got a Delonghi two hopper machine, this is what I’m on currently, cool brand and experience. https://t.co/ffArqzW4bF (https://twitter.com/PhilKiel/status/2067972588391854480)
- [x_philkiel#6bab9a0e] Scrap that, going ham on CBO now.
- [x_philkiel#0444fd88] You can have Audience Segments set up correctly and still be flying blind. Here's what most people miss. → Match your Exclusions to your Segments Setting up your Existing Customers segment without matching exclusions misses the point. The audiences inside your Existing Customers 

## 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=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=115, 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=115, 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=115, method=platform_profile

## Freshness
- profile_checked_days_ago: 115
- content_analysed_days_ago: 79
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 12
- 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_philkiel
- Request removal: https://koinonlink.com/claim?k=x_philkiel
- Terms: https://koinonlink.com/for-ai