# Conor Sunderland (@conortrains) on x

- id: koinon:creator:x_conortrains
- url: https://koinonlink.com/kol/x/conortrains
- schema_version: 1.4

## Identity
- platform: x
- handle: conortrains
- platform_url: https://twitter.com/conortrains
- website: https://www.instagram.com/conorfromkmh/
- country: Spain
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 15164
- following: 873
- posts_total: 18743
- posts_observed: 1
- posts_per_day: 8.641
- account_age_days: 2169
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00448
- best_post_interactions: 68
- 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: 0.95
- category_source: derived_from_recent_content
- topics: eCom ad account structure, UGC/creator content scaling, ROAS and budget allocation, Klaviyo/email for eCom brands
- bio: eCom Brands + Email Marketing Agency | International Flâneur | Klaviyo Audit 👉 https://t.co/44qJcmTwMl

## Audience (inferred)
- status: present
- description: eCommerce ad managers and brand operators running paid campaigns with focus on UGC, native ads and email/Klaviyo
- roles: ads
- seniority: practitioner
- pain_points: Struggling to produce effective static ads, Optimizing CBO structures so good ads actually get budget, Finding and repurposing winning creator scripts across genders, Balancing agency sales calls with day-to-day campaign management
- posts_analysed: 4
- 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: 88
- authenticity_basis: engagement_observed
- credibility_score: 88
- 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_conortrains#ac60888a] Big unlock for me has been finding male creators and giving them scripts that have already won for some of our female creators I think this opens up a new audience pocket or something and gives you loads of fresh purchasers Has anyone expounded on this and given the same script t (https://twitter.com/conortrains/status/2066279049786171502)
- [x_conortrains#2f9d8567] I am dog shit at static ads Have maybe hit 3-4 decent ones in the entirety of the last 9 months in eCom What resources have been genuinely good for people to learn these? I wonder what nuances I am missing and what skill issues I have tbh
- [x_conortrains#bc3cba88] Changed our CBO structure to be: - Video CBO (mainly UGC) - LFS CBO (native ads) - Image CBO ROAS is up and good ads are actually getting spend now without me having to do a tonne of media buying work
- [x_conortrains#780a37e6] Sales call with a funded brand back to back with a Chad from Twitter - First call I had to

## 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=111, 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=111, 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=111, method=platform_profile

## Freshness
- profile_checked_days_ago: 111
- content_analysed_days_ago: 79
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 13
- 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_conortrains
- Request removal: https://koinonlink.com/claim?k=x_conortrains
- Terms: https://koinonlink.com/for-ai