Reference Library

The underlying knowledge base the chatbot draws from. 10 documents, always up-to-date with what\'s shipped.

Active Match Lead Engine — lead.o1dmatch.com (Account Manager Guide)

Priority training for Active Match account managers. This is the tool that turns one Active Match candidate into a batch of verified, ready-to-contact hiring-side decision-makers. Watch the walkthrough first, then use this page as the reference.

1. What it does (one paragraph)

Give it a talent (the person we are placing), tell it who to target, and how many leads you want. It searches hiring-side decision-makers on LinkedIn, verifies each email, researches the company, writes a personalized icebreaker, and returns exactly that many Ready (campaign-ready) leads. US-only, de-duplicated across the whole team, and budget-capped. It builds the leads — it does not send anything.

2. Key features

  • Talents — save each person we are placing once (field, skills, achievements), then reuse them on every run. No re-typing their details.
  • New Run — pick a talent, set targeting (job titles, seniority, departments, industries, keywords, seed companies, states, company size), choose how many Ready leads you want, set a max spend in USD, and run.
  • AI targeting ("Suggest") — one click fills the targeting fields from the talent's profile. Use it, then add or remove what you know.
  • Perplexity sourcing (on by default) — automatically finds US companies with live openings that match the candidate and pulls decision-makers there, on top of the normal LinkedIn search.
  • Live activity feed — the run page shows every step in real time (finding LinkedIn profiles, enriching, verifying email, scoring) and the running spend.
  • Leads views — filter by Ready / Review / Rejected, see which run each lead came from, open a lead for the full record, and Export CSV.
  • Run history — every run with its candidate, results, and spend.
  • Light / dark mode toggle in the header.
  • In-app Guide — a short built-in explainer of every screen.

3. How to use it (step by step)

  1. Go to lead.o1dmatch.com and sign in (email + password). First time: sign up.
  2. Talents → Add talent. Enter the candidate you are placing: field, skills, achievements. Do this once per candidate.
  3. New Run. Pick the talent from the dropdown. Click ✨ Suggest targeting and let the AI fill titles, seniority, departments, industries and keywords. Adjust if needed.
  4. Set the batch size and the spend cap (see the rules below). Leave Perplexity sourcing on.
  5. Click Run. You are taken to the run page with the live activity feed. Leave it open in a tab and keep working — it is working even when the feed looks idle.
  6. When the run finishes, open View Ready leads, read the "why relevant" notes and the icebreaker, then Export CSV and drop it into your Google Sheet or outreach tool.
  7. Check the Review tab as well (see section 5). Those are usually good leads.

4. Yusuf's operating rules (from the walkthrough)

  • Batch size: 25 maximum, ideally 10. The slider goes to 250 — do not use it. Every lead is scraped, researched, email-verified and scored, so big batches are slow and expensive.
  • Max spend: about 3–5 USD per run, never above 5 USD. A 5-lead run should cost well under 1 USD.
  • Expect about 1–2 minutes per lead. A 5-lead run is a few minutes; a 25-lead run can be a good while. Start it, open it in a new tab, and go do other work.
  • Seed companies: leave empty unless you have specific companies you want targeted. Filling it narrows the search to those companies only.
  • States: leave all open for a broad US search, or pick one state (e.g. Alabama) to work the country state by state. The engine is US-only either way.
  • Seniority: select all unless the talent needs a narrow band.
  • Departments: match the talent's field (e.g. Engineering, Operations, Aerospace, Manufacturing for an aerospace/propulsion engineer).
  • Company size: leave open, or 11–50 if you want smaller firms first.
  • Exclude interns and students. They are never decision-makers.
  • Narrowing the targeting makes runs faster and cheaper.

5. Ready vs Review vs Rejected (read this — it is the most misunderstood part)

  • Ready — verified end to end. Email valid, decision-maker confirmed, relevance score computed, icebreaker written. Just read the personalization and go.
  • Review — these are NOT bad leads. The gate is deliberately strict. A lead lands in Review when one check needs a human look, almost always "Email needs review." Open the lead, read the reason, and verify the email yourself in Hunter.io the way you were trained. Everything else about the lead (decision-maker status, function, seniority, LinkedIn URL, relevance, score) is usually fine — Yusuf's example in the video was a Director of Engineering with a 95% relevance score sitting in Review only because of the email check.
  • Rejected — failed a hard gate (not US, not a decision-maker, role inbox, duplicate already contacted by the team, invalid email). Do not work these.

6. What a lead record contains

  • Name, title, company, LinkedIn URL
  • Decision-maker: yes/no, function (e.g. Engineering), seniority (e.g. Director)
  • Email + email status (valid / needs review) — verified through Hunter.io and QuickEmailVerification to keep bounce rates down
  • Phone field — best effort. The field exists but phone coverage is still being shipped; do not promise a phone number on every lead.
  • Relevance score (0–100; 95–100 means a very strong fit for that talent) and a plain-English "why relevant" explanation
  • A personalized icebreaker you can use to open the email on the talent's behalf
  • Which run and which talent it came from

7. What is happening in the background (why it is slow)

The engine uses LinkedIn search to find matching hiring-side profiles, Perplexity to find companies with live openings and to research each company, Hunter.io plus QuickEmailVerification to confirm the email is safe to send to, and an AI model to write the relevance note and icebreaker. Several layers have to pass before a lead is marked Ready. That is why one lead takes a minute or two.

8. Team rules

  • Do not send from the tool. It produces leads only. Send from your normal outreach channel and follow the standing outbound rules (BCC leads@o1dmatch.com on every pitch, ~40 LinkedIn touches per day per account maximum).
  • Dedup is org-wide. If another account manager already pulled a person, you will not get them again. That is intentional.
  • Watch the spend. The run page shows the running USD; the max-spend cap stops the run if it is hit.
  • Feature requests and questions go to Yusuf. He built the tool for the account managers and asked for requests: anything that would make the work easier or faster, tell him and he will add it.

9. Quick FAQ for the chat coach

  • Where do I log in? — lead.o1dmatch.com, email + password.
  • How many leads should I request? — 10 is ideal, 25 is the maximum. Never 250.
  • How much should a run cost? — under 5 USD; a 5-lead run under 1 USD.
  • Why is my run taking so long? — 1–2 minutes per lead is normal. Open it in a tab and keep working.
  • Are Review leads bad? — No. Usually only the email needs a manual check in Hunter.
  • Does it send emails? — No. Export CSV and send from your outreach channel.
  • Can I get phone numbers? — Best effort only; the phone feature is still being shipped.
  • Who do I ask for a new feature? — Yusuf.

Appendix — cleaned transcript of the walkthrough (Yusuf Awodire, 2 Sep 2026, 12:25)

Lightly cleaned for readability: product names corrected ("New Run", "Perplexity", "QuickEmailVerification", "lead.o1dmatch.com"), filler removed. The raw AI transcript and SRT captions are in the Drive folder.

This is the lead engine I made to help outreach for the account managers. The link is lead.o1dmatch.com. Open it and it brings you to the home page. Open the dashboard, or sign up if you have not, with your email and password.

The dashboard is where you run and find leads. "New Run" starts a run. "Run history" shows every run you have done for a particular candidate. "Leads" shows every lead the system has searched and reviewed for the candidates you have tried. Leads have three categories. Ready leads are already verified; no review needed, everything is satisfied, just read about them. Click a lead to see all the details: the phone number field (the phone feature is there and I will still ship it), why they are relevant to the candidate you want to reach out on behalf of, the match, and the score. The score is the relevance score. One at 95–100 means this person is a very good fit. If you do not like dark mode you can switch to light mode in the header.

Talents is where you save the people we are placing. One of our talents is Mithun, in aerospace and propulsion engineering. Click "Add talent" and enter their details once, so you never need to input them again. There is also a Guide that briefly explains how everything works.

To run: go to New Run, pick the candidate from the dropdown. There is an AI Suggest button that fills all the fields from the candidate's details so you do not fill them one by one. While it thinks, the other part: the number of leads you want. I recommend keeping it at 25 maximum, even though the control goes to 250. 25 maximum, or even 10, because it does a lot of work to give you those leads. Then the cost cap in USD: you do not want to go above 3–5 USD, never above 5 USD per run. For a 5-lead run you should not even finish 1 USD.

The AI has suggested the fields. Add the suggested keywords; you can add all of them to search across. Seed companies: leave it open, do not use it, unless you have specific companies in mind you want to target. States: this is all 50 US states; we want a broad search so leave them open. Another approach is to start with one state, say Alabama, get all the employers in Alabama, then move on. The engine uses LinkedIn and Perplexity: it searches LinkedIn for employer profiles that match your candidate, and it also checks for job openings, which is why runs take a while. Seniority: pick everything. Departments for this person: Engineering, Operations, Aerospace, Manufacturing. Company size: keep it open, or ideally 11–50. Exclude interns and students. Then click Run.

It takes you to the run page and starts working. The activity feed shows "finding LinkedIn profiles", the targets, and how much it is spending. While it runs, open Leads in a new tab. Ready are the ones ready to go. Review — I need to say this — they are not bad leads. They are under review for you to look at one thing or two before you use them. The email status may be valid and the score high; the gate is the threshold I set, and it is strict about separating Ready from Review. Click the person and review it yourself as a human to see why there is a doubt. Most of the time they are good leads; the system just separates them.

Back on the run: it is slow, so open it and go about whatever you are doing. It can be faster if you narrow the targeting. It is doing a lot of work to make sure the lead is valid: it uses Hunter.io to check the email to avoid bounces, QuickEmailVerification to make sure the email is good, Perplexity to enrich the lead, and LinkedIn to find the lead in the first place. There are many layers before it can tell you a lead is Ready.

Now there is one lead under review. Click the person and you see everything: decision maker, function Engineering, seniority Director, confirmed, the LinkedIn URL, and why they are relevant. The reason for review is "Email needs review" — check the email yourself; take it to Hunter.io like I taught you and verify it. Apart from that the lead is good, with a 95% score. Back on the run, two are now under review and it is still going. By the end you have your five leads.

This tool does the job for you: everything you would be doing — searching, checking LinkedIn — it already does, which is why it takes long. The Review ones are good leads. When you are done, open the Ready leads and click Export CSV; download the leads and put them in your Google Sheet or wherever, and you are ready to go with all the details.

If you have any questions or anything you think I need to add — this is made for you — to make your work easier or faster, tell me and I will include it. The run is still going and the number is increasing; I will not wait for it to finish. Thank you.