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When building a cold outreach sequence and you need to personalize the first touch with a specific individual — not when running list scraping, not...
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| name | prospect-research |
| description | When building a cold outreach sequence and you need to personalize the first touch with a specific individual — not when running list scraping, not... |
When building a cold outreach sequence and you need to personalize the first touch with a specific individual — not when running list scraping, not for generic email templates. Trigger: you have a LinkedIn URL (or name + company) and 2–3 hours before the outreach deadline, and you want hooks that will clear the 3-C test (Credible, Complimentary, Connected).
Every strong prospect dossier rests on four research buckets. Rank sources by recency and signal strength (recent actions = higher intent).
1. LinkedIn Profile
What to extract: Current pain points inferred from their stated focus. Language patterns (if they use "transformation" or "modernization," they care about change). Gaps between headline claim and actual content (if they say "innovative" but never post, there's a mismatch).
2. Content Authored Search for: articles (Medium, company blog, LinkedIn articles), podcast appearances, conference talk recordings, YouTube videos, guest posts, comments on industry forums.
What to extract: Explicit problem statements they've articulated. Frameworks they champion. Audiences they address (if they speak at startup events, they may be venture-minded; if at enterprise conferences, they're aligned with scale). Tone and expertise level.
3. Career Trajectory Assemble: all past employers (in reverse chronological order), tenure at each role, title progression, promotion velocity.
What to extract: What priorities do they reveal through role choices? Scaling operations → process and efficiency matter. Joined a Series B startup → they bet on execution and founder vision. Stayed at one company 7+ years → loyalty, or risk-averse. Moved functions (engineering → product → founder) → broad thinking, or restlessness.
4. Digital Footprint Search: Twitter/X account, personal blog, company website (for founder/executive), conference talk videos, GitHub (for technical roles), Reddit participation.
What to extract: Authentic interests outside the corporate biography. Positions they hold strongly (watch for contrarian takes — these often reveal what they value). Audience size (10k followers vs. 10 followers changes the story).
A strong cold-outreach opening follows this three-part structure:
[Hook from highest-value bucket] + [Bridge sentence connecting to your value prop] + [One specific open question]
Hook selection logic:
Example structure:
"I noticed you published [specific insight from recent talk/post] on [topic] — the [specific claim they made] resonates with how [parallel problem exists in your domain]. Quick question: when you think about [open question that reveals their priority], how do you currently [decision they need to make]?"
The 3-C Test for a Good Hook
Every hook must pass all three criteria:
When you have 15–30 minutes and need a ranked list of hooks fast, use this Claude prompt:
You are a B2B outreach researcher. Analyze the prospect and generate 3 personalisation hooks ranked by strength.
PROSPECT DATA:
LinkedIn URL: [URL or full profile summary]
Company: [Company name]
Role: [Title]
Industry: [Industry]
YOUR VALUE PROP:
[One sentence: what you do, who you help, what problem you solve]
TASK:
1. Research the prospect using the 4 sources: LinkedIn profile (headline, summary, recent activity, endorsements), content authored (articles, podcasts, conference talks), career trajectory (role progression, company history), digital footprint (Twitter, blog, public talks).
2. For each hook, state which bucket it comes from and explain the 3-C score (Credible, Complimentary, Connected).
3. Rank by strength: Hook 1 (strongest) to Hook 3 (useful if you can't use the top two).
4. For the strongest hook, draft a one-sentence opening.
OUTPUT FORMAT:
Hook 1: [Hook text] (Source: [Bucket])
- Credible: [Why it's factual]
- Complimentary: [How it positions them well]
- Connected: [How it bridges to your value prop]
- Opening line: "[Actual outreach sentence]"
Hook 2: ...
Hook 3: ...
After research, distill findings into a brief that your outreach team uses. Format:
PROSPECT BRIEF
Name: [Full name]
Title: [Current role + company]
Tenure: [How long in current role]
Research date: [Date]
BACKGROUND (2–3 sentences) [Role, company, industry. Why did we identify them? What's their context?]
KEY INSIGHT (1–2 sentences) [The single strongest finding from the 4-source stack. What did you learn that others might miss?]
PERSONALISATION HOOK [The hook. Which bucket did it come from? How does it pass the 3-C test?]
RECOMMENDED OPENING LINE [Full first sentence of the email.]
RESEARCH SOURCES
Before committing time to personalized outreach, use this gate:
Can you articulate their pain point in their own words? (From their recent content, career moves, or public statements.)
Does your value prop solve a problem they publicly stated or implied?
Can you craft a hook that passes the 3-C test without guessing?
Is this prospect's buyer type aligned with your ICP? (Check: company size, growth stage, industry, role seniority.)
Research time allocation:
Hook quality thresholds:
Response rate correlation (B2B SaaS benchmark):
Recency heuristic:
Company: Apollo (sales intelligence platform)
ICP: VP of Sales at mid-market B2B SaaS (20–500M ARR)
Target prospect: Alex Chen, VP of Sales at Notion (hypothetical)
INPUT: LinkedIn URL + Value Prop
LinkedIn profile summary:
Value prop: "Apollo gives sales leaders real-time visibility into prospect intent and engagement, reducing prospecting time by 40%."
RESEARCH OUTPUT
Hook 1: LinkedIn Post (Source: LinkedIn profile + recent activity)
"Your recent post on 'outbound not scaling without data truth' nails the core problem we see with teams winging it on prospect research. Given your scale at Notion, I'd imagine that visibility gap compounds — you're likely managing multiple GTM motions with limited signal on which paths are actually working."
Hook 2: Career Trajectory (Source: Career trajectory + speaking)
"You scaled sales motions at 6sense (early-stage intent data company) and now you're applying that at Notion across a massive user base. That's a rare position — you know what intent-driven selling looks like, and you're managing the challenges of scaling it. I'd bet the biggest friction point now is picking which prospects matter most across your 10M+ user base."
Hook 3: Speaking Activity (Source: SaaStr talk)
"Your SaaStr talk on building $10M ARR without 'outbound hell' implies you've systematized prospecting. The phrasing suggests you've had to cut through chaos to find what works. With that level of rigor, you probably demand better data inputs than most teams — and you likely wish your stack gave you that reliably."
PROSPECT BRIEF
Name: Alex Chen
Title: VP of Sales, Notion
Tenure: 1 year (in current role)
Research date: 2026-06-02
BACKGROUND Alex is scaling Notion's go-to-market function after 4 years at 6sense (an intent-data startup), where he built sales processes from the ground up. He's now managing multiple GTM motions across a 10M+ user base—an unusually large and complex sales challenge.
KEY INSIGHT He has lived the intent-driven sales motion and publicly stated that "outbound doesn't scale without data truth." This indicates he's personally experienced the gap between aspirational and actual sales data. His recent post had high engagement (2.3k likes), meaning the broader market resonates with this frustration. His move from a data-startup to a 10M-user product suggests he's moving toward scale and execution—likely feeling the limits of intent data at volume.
PERSONALISATION HOOK "Your recent post on outbound scaling and data truth hits a nerve—most sales leaders realize they're flying blind, but you've articulated why. At Notion's scale, I imagine that visibility gap compounds across motions. Apollo gives you the insight layer you're probably building manually right now."
(Source: LinkedIn post. Passes 3-C: Credible [real post, 6 days old], Complimentary [positions him as a thoughtful leader], Connected [Apollo = visibility tool].)
RECOMMENDED OPENING LINE "I saw your recent post on why outbound doesn't scale without data truth—and it's clear you're thinking deeply about this at Notion's scale. Quick question: when you're managing multiple GTM motions with limited signal on which are actually working, what's your current system for separating signal from noise?"
RESEARCH SOURCES
Before you research, confirm these:
After research, before outreach: