# Cody Schneider (@codyschneider) on x

- id: koinon:creator:x_codyschneider
- url: https://koinonlink.com/kol/x/codyschneider
- schema_version: 1.4

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

## Reach
- followers: 61914
- following: 4420
- posts_total: 17766
- posts_observed: 22
- posts_per_day: 4.328
- account_age_days: 4105
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00108
- best_post_interactions: 67
- 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: ai_tools
- category_confidence: 0.92
- category_source: derived_from_recent_content
- topics: AI-powered ad creation, customer persona mapping, emotional triggers in marketing, data scraping for targeting, B2B ad performance optimization, automated marketing workflows
- bio: follow to learn how to build AI agents that do marketing to grow your business 

building @graphed with @maxchehab

## Audience (inferred)
- status: present
- description: B2B marketers and growth hackers building AI-driven ad campaigns, primarily agency operators and in-house growth teams
- roles: ads
- seniority: practitioner
- pain_points: Struggling to identify which ad creatives or messaging actually convert, Having difficulty mapping customer personas to real emotional triggers and purchase contexts, Lacking scalable systems to scrape and organize customer behavioral data for targeting
- posts_analysed: 6
- confidence: 0.4

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

## Quality signals
- authenticity_score: 96
- authenticity_basis: engagement_observed
- credibility_score: 96
- 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_codyschneider#06748541] we make over 500 facebook ads per day for the b2b companies we work with (https://twitter.com/codyschneider)
- [x_codyschneider#91bdc340] here's how we actually identify what's working
- [x_codyschneider#d9fa87bc] >first, persona mapping
- [x_codyschneider#c3782497] a persona is an emotional trigger and a situation the customer is in
- [x_codyschneider#0452ba00] EG
- [x_codyschneider#774cef3c] emotional trigger is "my business is doing great but I can't make payroll" and an event is "i just deposited checks at my bank"
- [x_codyschneider#fba1b890] you need to build a matrix of this by scraping so

## 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_codyschneider
- Request removal: https://koinonlink.com/claim?k=x_codyschneider
- Terms: https://koinonlink.com/for-ai