lead-research-assistant

name	lead-research-assistant
description	Build evidence-backed B2B account and prospect research for sales, partnerships, pilots, or customer discovery. Use whenever the user wants an ICP, target-account list, qualified leads, account scoring, buying signals, decision-maker roles, outreach angles, CRM-ready research, or deeper analysis of named companies.
category	business
license	MIT
compatibility	Live web access is required for current company facts, public contacts, consent rules, and source verification.

Lead Research Assistant

Find organizations with a credible, timely reason to care. Optimize for fit, evidence, and a respectful next step—not for the largest possible list.

Safety and Data Rules

• Use public, lawful, business-relevant sources and respect site terms, robots controls, access restrictions, and rate limits.
• Do not obtain or infer sensitive personal traits, private contact details, passwords, hidden data, or personal email addresses. Do not enrich people through data breaches or deceptive pretexts.
• Do not invent employee counts, funding, technology, budgets, contacts, or buying intent.
• Record a source URL and verification date for every material lead claim.
• Prefer role-level targeting until a named person is verified from a current public source.
• Follow applicable marketing, privacy, telemarketing, and platform rules. Provide research and compliant strategy; do not promise that outreach is lawful in every jurisdiction.
• Exclude obvious non-fit accounts and explain why.

Inputs and Defaults

Inspect the repository, homepage, docs, pricing, and existing customers first. Establish:

• product and measurable outcome;
• target user, buyer, champion, and blocker;
• company type, size, geography, maturity, and technology constraints;
• triggering events or pain signals;
• disqualifiers;
• desired motion: discovery, pilot, self-serve sale, enterprise sale, or partnership;
• list size and required output format.

When the ICP is vague, produce an initial hypothesis and a small calibration set before scaling the search.

Workflow

1. Define the ICP and Negative ICP

Create a one-page hypothesis:

• firmographic fit;
• workflow/problem fit;
• technical and compliance fit;
• urgency/trigger fit;
• ability to buy and implement;
• reachable channel;
• explicit exclusions.

Separate must-have, strong signal, and nice-to-have criteria. A narrow segment with repeatable evidence is more useful than a broad category label.

2. Create a Source Plan

Use sources appropriate to the signal:

• company website, documentation, pricing, trust/security pages;
• official job posts and careers pages;
• filings, procurement notices, public budgets, and registries;
• product changelogs, engineering blogs, repositories, and status pages;
• current news and official announcements;
• conference talks, podcasts, public interviews, and permissioned directories;
• professional profiles for current roles, subject to platform terms.

Search results and aggregators are leads to verify, not final evidence. Prefer primary sources for company facts.

3. Build Account Evidence Cards

For each account capture:

Field	Requirement
Company	Legal/common name and official website
Fit evidence	Specific match to ICP with source
Trigger	Current event or observable need with date
Current approach	Known tool/workaround, or unknown
Likely user/buyer	Role, not an invented person
Value hypothesis	Outcome tied to observed context
Risk/disqualifier	Reason it may not fit
Confidence	High, medium, or low with explanation
Next research	Missing fact that changes priority

Do not claim a company “needs” the product merely because it belongs to an industry.

4. Score Transparently

Score 0 to 5 and cite the basis:

Criterion	Weight
Problem/workflow fit	3
Trigger strength and recency	3
Product/technical fit	2
Economic value	2
Buying/implementation plausibility	2
Reachability	1
Competitive lock-in	-2
Legal, reputation, or data risk	-2

Show raw scores, confidence, and missing data. Do not use a precise score to disguise weak research.

5. Identify the Buying Group

Map likely roles:

• end user;
• operational champion;
• budget owner;
• technical/security reviewer;
• procurement/legal approver;
• executive sponsor where relevant.

Only name individuals when their current role is verified publicly. Include the source and date, and avoid unnecessary personal details.

6. Design the Contact Strategy

For top accounts, create a concise, evidence-grounded approach:

• why this account now;
• the observed context;
• a cautious value hypothesis;
• one low-friction question or offer;
• the most appropriate channel;
• follow-up cap and opt-out handling.

Personalization should use relevant business facts, not surveillance. Never fabricate familiarity, referrals, customer logos, or results. Avoid automated high-volume sequences until the segment and message are validated.

7. Calibrate Before Scaling

Review a small batch for:

• false positives and missing disqualifiers;
• source freshness;
• response quality, not only response rate;
• conversion to qualified conversation;
• objections and segment differences;
• complaints, opt-outs, blocks, or reputation damage.

Update the ICP and scoring model before researching a larger list.

Output Contract

Return:

1. product and ICP summary;
2. positive and negative ICP criteria;
3. source methodology and research timestamp;
4. ranked account table;
5. evidence card for each high-priority account;
6. buying-group role map;
7. account-specific outreach hypothesis;
8. CRM-ready CSV columns when requested;
9. uncertainties, exclusions, and next research steps.

Sources

• Market Research and Competitive Analysis | U.S. Small Business Administration
• CAN-SPAM Act Compliance Guide | U.S. Federal Trade Commission
• Direct Marketing Guidance | UK Information Commissioner's Office
• LinkedIn Professional Community Policies
• Data Minimisation | UK Information Commissioner's Office