Run these after scoring. They pull pain point data per segment so the copy is specific, not generic.
Read scored-leads.csv. Filter for Tier 1 and Tier 2 leads only.
Group leads by: Job Title category, Industry, and Company size band.
For each segment group:
1. Identify the top 3 pain points this persona typically faces
(use web research + LinkedIn data where available)
2. Identify what outcome they are trying to achieve
3. Note any language or phrases this persona commonly uses
when describing their problem
Output a file called segment-research.md with one section per segment.
Format: Segment name > Pain points > Desired outcome > Language patterns
Use this for your highest-value accounts only. It does one-by-one research.
Read scored-leads.csv. Filter for Tier 1 leads only.
For each lead, search their LinkedIn profile and company website.
Find:
1. A recent post, comment, or activity they shared
2. A company milestone, news item, or signal from the last 90 days
(hiring, funding, product launch, leadership change)
3. One thing they likely care about right now based on their role
Output a file called tier1-research.md.
Format per lead: Name | Signal found | Source | Why it matters to them
Use this when your list has multiple job titles and you need copy that speaks to each one differently.
Read scored-leads.csv and segment-research.md.
For each unique job title in the list:
1. What is the #1 metric this role is accountable for?
2. What is the most common obstacle they face in hitting that metric?
3. What does a bad week look like for this person?
4. What would make them take 2 minutes to reply to a cold DM?
Output results in segment-research.md under a new section
called 'Role-Level Pain Points'.