# Ecom Mike (@TheecomMike) on x

- id: koinon:creator:x_theecommike
- url: https://koinonlink.com/kol/x/TheecomMike
- schema_version: 1.4

## Identity
- platform: x
- handle: TheecomMike
- platform_url: https://twitter.com/TheecomMike
- website: https://www.youtube.com/@andmi4
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 5995
- following: 27
- posts_total: 6139
- posts_observed: 5
- posts_per_day: 10.266
- account_age_days: 598
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00133
- best_post_interactions: 8
- 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: Ad scaling strategies, Customer retention and loyalty, Brand storytelling in ads, Product selection for long-term growth, Testing and optimization in e-commerce
- bio: $100M+ in sales. Scaling brands to 8 & 9 figures through meta & google ads.👇

## Audience (inferred)
- status: present
- description: E-commerce founders and growth marketers focused on scaling brands with Meta and Google Ads, primarily in the $1M+ revenue range
- roles: ecom_ops
- seniority: practitioner
- pain_points: Struggling to scale ads due to inconsistent testing and premature ad killing, Failing to build repeat customers because of poor brand resonance and customer understanding, Over-relying on chasing new winning products instead of optimizing for retention and loyalty
- posts_analysed: 4
- 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: 68
- authenticity_basis: engagement_observed
- credibility_score: 68
- 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_theecommike#997edf2d] took me 2 years to figure out the store wasn't the problem. i was. kept changing things that were working, kept killing ads that needed more time and kept launching products instead of scaling the winner. this is what leaving it alone looks like. https://t.co/0aI9IaAG4l (https://twitter.com/TheecomMike/status/2062943066177118334)
- [x_theecommike#988b28bd] biggest mistake i see in ecom? everyone's out chasing the next winning product. i'm not looking for that. i'm looking for products people come back and buy again. anyone can copy your product. a guy can screenshot your listing and have it live in a week. what he can't copy is cus
- [x_theecommike#dbb3f53a] Your customers only care about 3 things: 1. Feeling understood. 2. Seeing themselves in your ad. 3. Trusting your brand more than the next tab. Test that. Everything else is noise. https://t.co/fV8HwvOjRf
- [x_theecommike#bd65fe26] Ecom truth: Metrics are

## 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=116, 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=116, 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=116, method=platform_profile

## Freshness
- profile_checked_days_ago: 116
- content_analysed_days_ago: 79
- audience_updated_days_ago: 21

## AI retrieval
- indexing_requests: 14
- 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_theecommike
- Request removal: https://koinonlink.com/claim?k=x_theecommike
- Terms: https://koinonlink.com/for-ai