sachacoldiq

personalization-6-buckets

Complete 6 Buckets of Personalization framework from Flip The Script - Self-Authored Content, Engaged Content, Self-Identified Traits, Junk Drawer, Background Centric, and Company Level. Use when researching prospects, choosing personalization angles, or building personalized outreach.

sachacoldiq 158 56 Updated 4mo ago
GitHub

Install

npx skillscat add sachacoldiq/coldiq-s-gtm-skills/personalization-6-buckets

Install via the SkillsCat registry.

SKILL.md

6 Buckets of Personalization

Bucket 1: Self-Authored Content (Highest Value)

Content the prospect has created themselves:

  1. Speaking Engagements - Conferences, podcasts
  2. Webinars - Hosted or participated
  3. Articles - Blog posts, publications
  4. Posts - LinkedIn, Twitter content

Usage: Highest value personalization. Reference their thought leadership directly.


Bucket 2: Engaged Content

Content the prospect has interacted with:

  1. Commented On - Their comments on posts
  2. Shared - Content they've shared
  3. Liked Comments - Comments they've liked
  4. Liked Posts - Posts they've liked

Usage: Shows what topics interest them. Reference shared interests.


Bucket 3: Self-Identified Traits

How the prospect describes themselves:

  1. Profile Line ("About me" Section) - Bio content
  2. Company Line (Role, Specialization & Achievements) - Role description
  3. Headline (Below Profile Picture) - LinkedIn headline

Usage: Use their own words to frame relevance.


Bucket 4: Junk Drawer

Personal details from their profile:

  1. Personal Interests - Hobbies, activities
  2. Volunteer Experience: Personal (Charity) - Causes they support
  3. Languages Spoken - Multilingual abilities
  4. Schools Attended - Education background
  5. Interested In/Following - Topics they follow

Usage: Build rapport but don't overdo it. Use sparingly.


Bucket 5: Background Centric

Professional history and credentials:

  1. Tenure at Company - How long they've been there
  2. Professional Trajectory - Career movement
  3. Recommendations Given - Who they recommend
  4. Recommendations Received - Social proof
  5. Boards They're On - Board positions
  6. Volunteer Experience: Professional (Mentorship) - Industry involvement
  7. Awards Received - Recognition
  8. Certifications - Professional credentials
  9. Mutual Connections - Shared network
  10. Skill Endorsements - Endorsed abilities

Usage: Reference career achievements and professional credibility.


Bucket 6: Company Level

Company-wide information:

  1. Company Website Language - Messaging and positioning
  2. Company Post - Recent social content
  3. Company Blog Entry - Blog content
  4. Company News Mentions - Press coverage
  5. Company IPO - Public offering
  6. Company Funding - Investment rounds
  7. Company Financial Reports - Public financials
  8. M&A: Acquired/Were Acquired/Merged - M&A activity
  9. Company Growth - Growth trajectory
  10. Hiring / Made a "Key Hire" - Team changes
  11. Moved Headquarters / Opened New Locations - Expansion
  12. New Product/Feature/Integration Release - Product updates
  13. Impactful Marketing Moves - Marketing activities
  14. Company Competitors / Competitor Moves - Competitive landscape
  15. Negative/Positive Outputs/Midputs/Inputs - Business problems

Usage: Trigger-based personalization at scale.


5 Types of Core-Static Relevance (Fallback)

When personalization isn't possible:

  1. Demographic: Buyer Persona
  2. Firmographic: Company Segment
  3. Firmographic: Company Industry Vertical
  4. Firmographic: Company Market Geos
  5. Technographic: Tech Stack

Combines with

Skill Why
personalization-hooks Turn bucket data into hooks
ai-personalization-prompts Automate bucket research
personalization-playbooks Choose personalization level
cold-email-4-sequence Apply buckets to sequence

Example prompts

Research Bucket 1 (Self-Authored Content) for this prospect: [LinkedIn URL]
Which bucket should I prioritize for a quick 50-prospect campaign?
Create a strong hook using Bucket 6 (Company Level) data about their funding.