# Christian (@coldemailchris) on x

- id: koinon:creator:x_coldemailchris
- url: https://koinonlink.com/kol/x/coldemailchris
- schema_version: 1.4

## Identity
- platform: x
- handle: coldemailchris
- platform_url: https://twitter.com/coldemailchris
- website: https://pipeline.tech/pilot
- entity_type: creator
- person_id: koinon:person:linkedin_coldemailchris

## Reach
- followers: 19292
- following: 344
- posts_total: 7819
- posts_observed: 4
- posts_per_day: 4.291
- account_age_days: 1822
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00062
- 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: 0.9
- category_source: derived_from_recent_content
- topics: GTM engineering and automated outbound, Cold email deliverability tactics, Follow-up email strategies, AI-native B2B outreach
- bio: AI-Native Outbound for B2B Companies | 10M+ Emails Sent, 30,000+ Leads, $70M+ Pipeline Generated | My Links 👉 https://t.co/ujF3ZNVERd

## Audience (inferred)
- status: present
- description: B2B sales teams, SDRs, GTM engineers and outbound operators running cold email campaigns
- roles: sales
- seniority: practitioner
- pain_points: Scaling outbound volume without hiring more SDRs, Avoiding spam filters and deliverability issues with unsubscribe links, Crafting effective follow-ups that don’t feel spammy, Getting high reply rates from automated sequences
- 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_coldemailchris#5d3e89c6] 1 GTM engineer + 1 SDR outperforms 5 SDRs 10/10 times. The GTM engineer runs high-volume automated outbound to entire TAM for TOF traffic SDR works on setting warm traffic generated from GTM engineer’s campaigns. Whereas when SDRs handle both manual prospecting for TOF traffic an (https://twitter.com/coldemailchris/status/2070210131065971124)
- [x_coldemailchris#8006dcba] Never add Unsubscribe links to your emails Use written opt-outs with a random keyword instead Ex: “If you don’t want anymore emails from me, just reply ‘banana’ & I’ll stop.” Tricks the spam filter into seeing more positive intent from your email replies vs seeing a bunch of ‘no’
- [x_coldemailchris#1dec9aaa] When following up with prospects, you don’t want to spam non-stop “value” emails Ex. sending Looms, Gamma docs, etc You need to implement a “bump” type email after each value email you send Here’s the cadence: Loom video -> “did yo

## 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=117, 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=117, 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=117, method=platform_profile

## Freshness
- profile_checked_days_ago: 117
- content_analysed_days_ago: 79
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 9
- 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_coldemailchris
- Request removal: https://koinonlink.com/claim?k=x_coldemailchris
- Terms: https://koinonlink.com/for-ai