LinkedIn Data Export Index

Generated: 2026-03-26 Author: Dmitri Sunshine Pipeline: linkedin-data-maximizer

Purpose

Complete index of all data exports and analysis documents produced from Dmitri’s LinkedIn export (exported 2026-03-13). Designed for consumption by: Dmitri, coach, Nexus AI assistant, and eventual database import.

Base paths:

Exports: C:\_my\_solanasis\solanasis-scripts\linkedin-pipeline\data\export\
Analysis docs: C:\_my\_solanasis\solanasis-docs\linkedin-analysis\

Database-Ready Exports (JSON/CSV)

Core Contact and Messaging Tables

File	Format	Rows	Purpose	Schema Reference
contacts_for_database.json	JSON	2,478	All connections with full scoring and ICP tags	contacts_schema.md
contacts_for_database.csv	CSV	2,478	Same as JSON, spreadsheet/import-compatible	contacts_schema.md
conversations_full_export.json	JSON	562	Consolidated conversation threads, one entry per contact	—
messaging_summary_for_database.csv	CSV	562	Per-contact messaging stats (counts, dates, response times)	—
interaction_timeline.json	JSON	5,730	Chronological log of all interactions (messages, invitations, follows)	—
interaction_timeline_for_database.csv	CSV	5,730	Same as JSON, flattened for relational import	—
meeting_notes_export.json	JSON	100	Meeting notes exported from Baserow, one entry per note	—
meeting_notes_for_database.csv	CSV	100	Same as JSON, flattened for DB import	—
non_connections_for_database.csv	CSV	805	People who interacted with Dmitri but are not connections	—

Dimension Exports (Behavioral and Engagement Data)

File	Format	Rows/Entries	Purpose	Schema Reference
ads_clicked_for_database.csv	CSV	21	Monthly LinkedIn ad click history (5,852 total clicks tracked)	—
ads_clicked_analysis.json	JSON	21 monthly entries	Ad engagement patterns, monthly timeline, top months	—
company_follows_for_database.csv	CSV	299	Companies Dmitri follows on LinkedIn	—
company_follows_icp_analysis.json	JSON	299 companies	ICP segment mapping of followed companies	—
member_follows_for_database.csv	CSV	2,030	Members Dmitri follows (includes non-connections)	—
member_follows_analysis.json	JSON	2,030 follows	Follow analysis; 50-contact outreach sample identified	—
connection_velocity_analysis.json	JSON	67 monthly entries	Connection growth timeline; 2,498 total connections tracked	—
inferences_analysis.json	JSON	7 entries	LinkedIn’s inferred interest/demographic categories	—
invitation_effectiveness_analysis.json	JSON	232 template entries	Invitation acceptance rates; 1,549 total invitations analyzed	—
security_audit_analysis.json	JSON	8 monthly entries	Login security events; 117 challenges, IP analysis, fCISO framing	—
remaining_dimensions_analysis.json	JSON	19 top-level keys	Composite analysis: endorsements (11), events (6), learning (7 courses), reactions (601), reposts (6), saved items (5), saved jobs (15), account history (18.6 yr account), rich media (5), logins (22)	—

Outreach Lists (Ready-to-Use Prospect Lists)

All files in data/export/outreach-lists/:

File	Format	Rows	Filter Criteria	Purpose
colorado-local-network.csv	CSV	70	segment_tags contains ‘boulder-local’, sorted by warmth_score DESC	Priority local outreach — Colorado Front Range contacts
dormant-gold-high-value-never-engaged.csv	CSV	57	strategic_value_score >= 30 AND warmth_score < 15, sorted by strategic_value_score DESC	High-value dormant connections worth reactivating
foundation-nonprofit-targets.csv	CSV	136	segment_tags contains ‘foundation’ OR ‘nonprofit’, sorted by strategic_value_score DESC	Foundation and nonprofit ICP prospects
fractional-exec-referral-partners.csv	CSV	363	segment_tags contains ‘fractional-exec’ OR ‘connector’, sorted by warmth_score DESC	Referral partner network — fractional execs and connectors
reactivation-gone-silent.csv	CSV	80	message_count_total >= 5 AND days_since_last_contact > 90, sorted by warmth_score DESC	Previously engaged contacts who have gone quiet
warm-introduction-map.csv	CSV	20	Top 5 warmest contacts per vertical (foundation, nonprofit, wealth-mgmt, tech)	Warm intro leverage points — one table per vertical
wealth-management-targets.csv	CSV	21	segment_tags contains ‘wealth-mgmt’, sorted by strategic_value_score DESC	Wealth management and RIA ICP prospects

Total outreach list contacts: 747 rows across 7 lists (some contacts appear in multiple lists)

Schema and Documentation (in export/)

File	Format	Purpose
contacts_schema.md	Markdown	Full field reference, scoring methodology, tier thresholds, ICP segments, import instructions
messaging_insights.md	Markdown	Messaging pattern analysis — generated during pipeline run, lives in export/

Analysis Documents (Markdown)

All files in solanasis-docs/linkedin-analysis/:

Primary Analysis Files

File	Purpose	Key Findings
linkedin-complete-data-audit.md	Master audit of all 37 LinkedIn export source files; field-by-field documentation	37 source files catalogued; identifies empty/PII files; maps each to pipeline output
linkedin-outreach-strategy.md	Full GTM playbook with 7 service lines and sequenced outreach tactics	2,478 connections; ~35 Tier A contacts; 2,024 member follows not yet connected; 7 service-line ICP maps
non-connection-targets.md	Analysis of 805 people who engaged with Dmitri but are not connections	805 non-connection interactors scored; identifies high-value follow-up targets outside connection list
voice-enrichment-llm-analysis.md	LLM analysis of Dmitri’s LinkedIn communication style and voice	670 corpus samples (138 comments, 41 shares, 50 conversations, 263 invitation templates); voice profile sections A-F

Outreach List Companion Docs

All files in solanasis-docs/linkedin-analysis/outreach-lists/:

File	Companion CSV	Key Findings
colorado-local-network.md	colorado-local-network.csv	70 Boulder/Denver/Colorado contacts; filter: boulder-local segment
dormant-gold-high-value-never-engaged.md	dormant-gold-high-value-never-engaged.csv	57 high-strategic-value contacts with zero messaging history
foundation-nonprofit-targets.md	foundation-nonprofit-targets.csv	136 foundation and nonprofit ICP contacts
fractional-exec-referral-partners.md	fractional-exec-referral-partners.csv	363 fractional execs and connectors — largest outreach segment
reactivation-gone-silent.md	reactivation-gone-silent.csv	80 contacts with 5+ prior messages who have not engaged in 90+ days
warm-introduction-map.md	warm-introduction-map.csv	20 contacts across 4 verticals; warmest possible intro path per vertical
wealth-management-targets.md	wealth-management-targets.csv	21 wealth management / RIA targets

Supplementary Documents

File	Purpose
blog-post-linkedin-data-ai-insights.md	Draft blog post: “What I Learned From Running AI on My Own LinkedIn Data”
social-media-linkedin-data-ai-campaign.md	Social media campaign content derived from the LinkedIn data analysis
baserow-migration-continuation-prompt.md	Structured prompt for resuming Baserow import work in a new session
linkedin-pipeline-continuation-prompt.md	Structured prompt for resuming pipeline development in a new session
linkedin-pipeline-plan.md	Original plan document for the linkedin-data-maximizer pipeline

Previously Generated (Still Valid)

These files were produced before the linkedin-data-maximizer pipeline and remain valid:

File	Generated	Purpose
network-intelligence-report.md	2026-03-23 by analyze_network.py	Network composition breakdown, top contacts by tier, geographic distribution
gtm-alignment-report.md	2026-03-23 by analyze_network.py	GTM gap analysis — alignment between network composition and Solanasis service lines
voice-analysis-report.md	2026-03-23 by analyze_voice.py	Statistical voice analysis (pure Python, no LLM) — baseline before LLM enrichment

Import Instructions

For Baserow

The contacts table is the recommended starting point.

Create a new table named linkedin_contacts
Import contacts_for_database.csv via Import > CSV
Set linkedin_url as the unique identifier field
Set these fields to Number type: warmth_score, strategic_value_score, message_count_total, message_count_from_dmitri, message_count_to_dmitri, connection_age_days, days_since_last_contact
Set relationship_tier to Single Select (values: A, B, C, D)
Set date fields to Date: connected_on, invitation_date, first_message_date, last_message_date
Set boolean fields to Checkbox: relationship_decay_flag, invitation_accepted, dmitri_follows_them, they_follow_dmitri, is_endorser

For additional tables, import the corresponding CSVs and join on linkedin_url (contacts, messaging, timeline) or name/profile_url (non-connections).

For outreach lists: import each CSV in outreach-lists/ as a separate Baserow view or table. These are pre-filtered subsets of the master contacts table.

For PostgreSQL

-- Primary contacts table
create table linkedin_contacts (
    linkedin_url                  varchar(500) primary key,
    first_name                    varchar(200),
    last_name                     varchar(200),
    full_name                     varchar(400),
    email                         varchar(300),
    company                       varchar(500),
    position                      varchar(500),
    connected_on                  date,
    connection_age_days           int,
    invitation_direction          varchar(20),
    invitation_message            text,
    invitation_date               timestamp,
    invitation_accepted           boolean,
    message_count_total           int,
    message_count_from_dmitri     int,
    message_count_to_dmitri       int,
    first_message_date            timestamp,
    last_message_date             timestamp,
    last_message_direction        varchar(20),
    avg_response_time_hours       float,
    longest_conversation_length   int,
    conversation_count            int,
    last_message_content_preview  text,
    dmitri_follows_them           boolean,
    they_follow_dmitri            boolean,
    warmth_score                  int,
    strategic_value_score         int,
    relationship_tier             char(1),
    relationship_decay_flag       boolean,
    days_since_last_contact       int,
    segment_tags                  text,
    icp_match_details             text,
    notes                         text,
    endorsed_skills               text,
    is_endorser                   boolean
);
 
-- Load contacts
\copy linkedin_contacts from 'contacts_for_database.csv' csv header;
 
-- Messaging summary (join key: linkedin_url)
create table linkedin_messaging (
    linkedin_url       varchar(500) references linkedin_contacts(linkedin_url),
    -- see messaging_summary_for_database.csv for full column list
    primary key (linkedin_url)
);
\copy linkedin_messaging from 'messaging_summary_for_database.csv' csv header;
 
-- Interaction timeline (join key: linkedin_url)
create table linkedin_timeline (
    id                 serial primary key,
    linkedin_url       varchar(500),
    event_date         timestamp,
    event_type         varchar(100),
    direction          varchar(20),
    content_preview    text
);
\copy linkedin_timeline from 'interaction_timeline_for_database.csv' csv header;
 
-- Non-connections (separate dataset, no FK to contacts)
create table linkedin_non_connections (
    id                 serial primary key,
    name               varchar(400),
    profile_url        varchar(500),
    -- see non_connections_for_database.csv for full column list
);
\copy linkedin_non_connections from 'non_connections_for_database.csv' csv header;

For Any Generic Database

Import order (respects dependencies):

contacts_for_database.csv — master table, 2,478 rows, 37 columns
messaging_summary_for_database.csv — 562 rows, joins on linkedin_url
interaction_timeline_for_database.csv — 5,730 rows, joins on linkedin_url
non_connections_for_database.csv — 805 rows, standalone table
meeting_notes_for_database.csv — 100 rows, joins on contact name or URL
member_follows_for_database.csv — 2,030 rows, standalone or joined
company_follows_for_database.csv — 299 rows, standalone
ads_clicked_for_database.csv — 21 rows (monthly aggregates), standalone
Outreach lists (7 CSVs) — subsets of contacts, import as views or separate tables

All CSV files use UTF-8 encoding with headers in row 1.

Data Dictionary

Key fields used across multiple export files:

Field	Type	Found In	Description
`linkedin_url`	string	contacts, messaging, timeline	LinkedIn profile URL; primary join key across all contact tables
`warmth_score`	integer	contacts, outreach lists	Relationship warmth (0-60+); 11 signals including bidirectional messaging, recency, follow status. A >= 50 combined
`strategic_value_score`	integer	contacts, outreach lists	Strategic fit score (0-40+); 6 signals including title/role, ICP vertical match, geography, connector status
`relationship_tier`	char (A/B/C/D)	contacts, outreach lists	Combined tier: A = 50+ points, B = 30-49, C = 15-29, D = <15
`relationship_decay_flag`	boolean	contacts	True if connected 1+ year with zero recent contact
`days_since_last_contact`	integer	contacts	Days since last message, invitation, or engagement
`icp_segments`	string	contacts (as segment_tags)	Comma-separated ICP tags; values: foundation, nonprofit, wealth-mgmt, fractional-exec, tech, startup, coliving-community, boulder-local, connector, spiritual-wellness
`icp_match_details`	string	contacts	Semicolon-separated scoring signals that fired for this contact
`message_count_total`	integer	contacts, messaging	Total messages exchanged across all threads
`message_count_from_dmitri`	integer	contacts, messaging	Messages sent by Dmitri
`message_count_to_dmitri`	integer	contacts, messaging	Messages received by Dmitri
`avg_response_time_hours`	float	contacts, messaging	Average hours between message exchanges
`last_message_direction`	string	contacts, messaging	from_dmitri or to_dmitri — who sent the last message
`invitation_direction`	string	contacts, timeline	INCOMING = they invited Dmitri; OUTGOING = Dmitri invited them
`invitation_message`	string	contacts, timeline	Personalized note in connection request, if any
`invitation_accepted`	boolean	contacts, timeline	Whether invitation was accepted
`dmitri_follows_them`	boolean	contacts	True if Dmitri follows this member
`they_follow_dmitri`	boolean	contacts	True if this member follows Dmitri
`endorsed_skills`	string	contacts	Comma-separated skills this contact endorsed for Dmitri
`is_endorser`	boolean	contacts	True if this contact has endorsed any of Dmitri’s skills
`segment_tags`	string	contacts, outreach lists	Comma-separated ICP segment tags assigned by pipeline
`connected_on`	date	contacts	Date of LinkedIn connection
`connection_age_days`	integer	contacts	Days since connection was established
`event_type`	string	timeline	Type of interaction event (message_sent, message_received, invitation_sent, etc.)
`warmth_score_bucket`	string	non-connections	Warmth bracket for non-connection interactors
`strategic_value_score`	integer	non-connections	Same scoring logic applied to non-connection interactors

Coverage Summary

Category	Count
Total connections in export	2,478
Contacts with message history	562
Total interaction events tracked	5,730
Meeting notes imported	100
Non-connection interactors	805
Member follows	2,030
Company follows	299
Outreach list contacts (7 lists)	747
Total JSON/CSV export files	20
Total analysis documents (MD)	19
Total files produced by pipeline	39

Solanasis Docs

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