How LeadHunter works

LeadHunter ranks thousands of prospects so you work the best ones first, then keeps every relationship moving. It is opinionated about how you use it: this page lays out the intended flow end-to-end, from importing a list and ranking it to working the top of it and measuring what each campaign and channel brought in, so you can see what each phase looks like, what to expect at the end of it, and the rhythm you’ll settle into after the first cycle.

The Quick start walks you through the first fifteen minutes mechanically. This page is the bigger picture around it — read it before, after, or in parallel.

The big picture

Phase 1: Set up           ──►  Project · Product · Fit criteria
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Phase 2: Build database   ──►  Accounts (deduplicated, tagged)
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Phase 3: Rank and shortlist ──►  Fit scores · shortlist in a campaign
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                                          │   │ single decisions feed back into scoring
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Phase 4: Outreach         ──►  Conversations, status auto-promoted
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Phase 5: Pipeline         ──►  Today · next steps · funnel
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Phase 6: Costs and CAC    ──►  Spend logged, CAC per outcome
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                          ┌───────────────┘
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                     (loop weekly)

The first three phases are mostly one-time setup work. Phases 4–6 are where you’ll live day-to-day, with periodic returns to phases 2 and 3 as you add new accounts and refine your fit criteria.

Skip cases — when phases compress

Not every starting point is the same. A few common patterns:

• You already have a CSV from your CRM. Phase 2 collapses to a single import. The dedupe stack handles the heavy lifting.
• You’re an agency running a client brief. Phase 1’s fit criteria are half-written for you — paste the brief into the Product description and generate the fit criteria from there. Often a single approve-or-revise pass instead of multiple iterations.
• You’re picking back up a Product you’ve already scored. The fit scores are shared by every campaign of that product and purpose, so a new campaign reuses them (see How scoring works). You drop straight into Phase 2 to add new accounts and Phase 4 to start reaching out.

The phases are a complete framework, not a mandatory sequence — skip and revisit as your situation warrants.

Phase 1 — Set up your workspace

Goal: A project, a Product, and fit criteria good enough to start scoring.

Steps:

1. Create a project. One per line of business; agencies run one per client, grouped under their organization.
2. Add a Product under Settings → Products — name, description, website URL, default communication language.
3. Add 2–3 example good URLs and 2–3 example bad URLs to the Product. This is the single biggest lever on scoring quality — don’t skip it.
4. Generate fit criteria for the purpose you start with (usually sales) in the product’s Fit criteria section. Review the draft, edit anything that’s off, approve. See Fit criteria and fit score.
5. (Optional) Define custom fields for whatever your business tracks beyond the standard fields.
6. (Optional) Invite teammates from Settings → Team.

Expected outcome: An empty Accounts list, but everything downstream is calibrated. Scoring works as soon as accounts arrive.

Common pitfalls:

• Vague Product description. The AI can’t write sharp fit criteria from one-line positioning. Two paragraphs is the minimum.
• Skipping example URLs. Scoring quality plateaus without them.
• Trying to cover two audiences with one Product (e.g. enterprise + SMB). Use two Products, each with its own fit criteria — see Organization, project and product.

Phase 2 — Build your account database

Goal: The accounts you might work. Anywhere from a few hundred to tens of thousands, depending on how broad your market is.

Inputs:

• Existing CSV/XLSX from your CRM, Apollo, ZoomInfo, etc. The columns map themselves from their headers.
• Google Maps text searches (“bike shops in Berlin”) or AI web searches, with Find new accounts on the Accounts page.
• Individual URLs or domains for accounts you already know, via the Account lookup.

Use any of them — or all three. See Import accounts for the flows in detail.

Expected outcome: A populated Accounts list, deduplicated against itself.

Common pitfalls:

• Worrying about duplicates. Don’t. Every import path checks for duplicates before writing, and the import result lets you download every skipped row. Re-importing the same list twice is safe — see Merge duplicates.
• Forgetting to tag existing clients. Give them the Client status (customer in the API) and the client relationship type before running campaigns, so the outreach guardrails can protect them and Today doesn’t offer them as prospects. See Account → Relationship types.

Phase 3 — Rank and shortlist

Goal: A ranked list, and a shortlist of strong-fit accounts ready for outreach.

Steps:

1. Rank the list. On Accounts, filter to what you want ranked (a country, an import, a saved view) and click Rank. Pick the product and purpose, check the estimate, try a sample of 50 first, set a budget cap, start. Each account gets a 0–10 fit score, the band its score falls in — Strong fit (8–10), Good fit (6–8), Weak fit (4–6) or Poor fit (below 4) — and 2–4 typed reasons. See Rank a list without a campaign.
2. Read the sample. If the reasons are off, edit the fit criteria and rank the sample again. When they look right, rank the rest.
3. Pick the best into a campaign. View results opens the ranked accounts best first; narrow with Min fit and click Add matching accounts to campaign. (You can also create a Campaign first and score its accounts there with Score N remaining.)
4. On the campaign’s Review tab, Shortlist strong fits, Defer the maybes, mark the rest Not a fit — one at a time or in bulk by band or top N, with undo. See Review thousands of accounts.

Expected outcome: Every account in your list has a fit score, and a campaign holds the shortlist you’ll reach out to.

Single decisions sharpen scoring

Once you’ve decided on about ten accounts one at a time for a product and purpose (bulk decisions don’t count), your decisions start feeding back into future scoring as concrete “this is what good looks like for us” examples. Below ten the calibration is held back (small samples are noisier than no sample), so the early reviews are exactly when this work pays off most.

The Review tab’s Fit score bands (8–10, 6–8, 4–6, 0–4, not scored yet) show the shape of a campaign at a glance — a healthy campaign is bimodal (strong fits and clear mismatches with a modest middle); a flat or all-middle shape usually means the fit criteria or example URLs need work. See Campaign → Score distribution.

If a run stops partway. Scores already made are kept. A ranking run that hit its budget cap ends Partial; rank the rest when you’re ready. A campaign run that failed or was cancelled resumes with Score N remaining, which only scores accounts without a score. Both kinds are listed under Runs.

Common pitfalls:

• Trusting the number, not the reasons. The score is a starting point; the reasons are the substance. A 9/10 for the wrong reasons is still wrong.
• Ranking 20,000 accounts before reading a sample. A sample of 50 costs little and tells you whether the fit criteria are right.
• Reaching out to unreviewed accounts. At least skim the top of the list first — you’ll spot patterns the AI missed.

Phase 4 — Outreach and conversations

Goal: First messages out, replies pasted in, history kept consistent.

Steps:

1. Open a shortlisted account in the campaign’s Outreach tab (Start outreach on the Review tab takes you to its inbox).
2. AI: first message → pick a draft → edit → send through your normal channel (email, LinkedIn, IG, WhatsApp, phone).
3. Log message in the composer so LeadHunter knows it went out (use Log already sent for a message you wrote elsewhere).
4. When the account replies, paste the reply text in Log inbound reply. The AI translates it into your language if needed.
5. Add the next step right under the conversation, in the same panel.
6. Repeat with AI: continue thread for the messages that follow. The Outreach tab’s Follow-up view lists the accounts you wrote to that haven’t replied.

LeadHunter is a communication log, not a sending platform — you send through your own channels and paste the exchange in so scoring, history, and team visibility all stay in sync. See Messaging for the five message modes in detail.

The conversation thread lives in two places: the campaign account panel (just this campaign’s messages with the account, next to its next steps, review decision and board stage; it opens from Review rows, the Outreach inbox, the Follow-up view and the Board card) and the account page (every conversation across every campaign that account has been in, plus the ones logged without a campaign). When an account moves to a new campaign, its history follows them.

Expected outcome: Each reached-out account has a conversation thread. The account’s status auto-promotes from prospect to contacted on the first outbound; its outreach status in the campaign becomes Replied when a reply lands.

Let LeadHunter pick the language

The fallback chain runs Account.language → Campaign → Product → User → English. Set a language on an individual account if you know one, otherwise leave it blank and let the campaign/product default win. If the account has a language set, that always wins — including across campaigns. See Campaign → Language.

Common pitfalls:

• Forgetting to log the message. If LeadHunter doesn’t know you reached out, outreach status doesn’t move and the funnel doesn’t see the activity.
• Drafting in a language the account doesn’t speak. Let the system pick.
• Cold-pitching a do_not_contact account. Refused with a clear error — there’s no force flag. Resolve the status mismatch instead.

Phase 5 — Pipeline and ongoing operations

Goal: Track relationships as they evolve.

Steps:

• Move status as deals progress, from the Status chip on the account page: Contacted → In negotiation → Client (or Lost).
• Add relationship types as they become true — a prospect that converts becomes a client; the same account might also be a partner or press contact later.
• Mark opt-outs as do_not_contact. This is sticky and survives merges so opt-outs stay opt-outs.
• Give every live account a next step with a due date: the bell, the morning email and (if you subscribe) your calendar remind you when it’s due. Once an account is a client, Client Pulse flags it when nobody has been in touch for too long.
• Start each day on Today: steps due, replies waiting for an answer, what is waiting in each campaign, clients to contact, then the best-scored accounts nobody is working yet.
• Watch the outreach funnel on Insights → Funnel — accounts initiated, clicked, replied, closed — daily, weekly, monthly. Treat it as your activity gauge. (Clicked comes from tracked links: contacts who clicked something you sent but haven’t replied yet — your warmest silent prospects.)

Expected outcome: Your account database stays current with reality. The funnel tells you whether outreach effort and conversion are trending right.

Two corrections you’ll want to know about

The funnel’s Closed (won) count is stricter than “count every customer transition”: it requires the account’s current status to still be customer or lost, so an “oops, wrong account” revert drops back out. And when you load existing customers (a CRM import, a long-standing renewal), tick Mark as pre-existing client when changing the status — that flags the transition so it doesn’t fake-inflate this month’s wins. See Account → Recording a pre-existing customer.

Common pitfalls:

• Letting status drift. If your accounts say prospect when half of them are customers, every guardrail and every report drifts with them.
• Skipping the monthly dedupe pass. New imports introduce new duplicate candidates; resolve them before they accumulate.
• Importing an existing customer book without the pre-existing flag. The funnel’s win count balloons, then you have no clean baseline to measure new campaign wins against.

Phase 6 — Costs and CAC

Goal: Pair every outreach outcome with what it cost so the numbers you read are honest.

Steps:

• Log spend as it accrues — Adwords invoices, agency fees, internal hours, software subscriptions, content production, event costs. Each entry goes against a specific campaign with an amount + currency + date + vendor.
• The Costs & expenses panel on the campaign’s Settings & costs tab surfaces total spend (per currency), cost per outreached account, and cost per replied account in real time.
• Insights → Breakdown rolls up cost per closed-won customer across the last 30 days, per campaign, per product and per channel.

Auto-tracked API costs (LLM tokens, Google Maps calls, Tavily searches) are surfaced alongside user-entered expenses on every campaign — same panel, same totals — so a campaign’s full cost is one number, not two surfaces you have to add together. The API also returns a per-account cost block with each account, so you can answer “how much did processing this single account actually cost?”.

Expected outcome: Every campaign carries a real cost-of-acquisition number you can compare against other campaigns and against the value of a customer.

Common pitfalls:

• Forgetting the costs side. A response rate without a cost is half a story. Logging spend weekly is the minimum cadence to keep the numbers honest.
• Mixing currencies in a single campaign. LeadHunter shows per-currency totals but doesn’t compute CAC across currencies (no FX layer). Either normalise to one currency or run cost analysis externally.

See Track campaign costs and CAC for the full mechanics.

The recurring rhythm

After the first cycle, you’ll settle into something like this:

• Daily — work down Today: due steps, replies waiting, clients to contact; send today’s outreach; paste yesterday’s replies; update status on anything that moved.
• Weekly — rank this week’s new imports; shortlist the top of your campaigns, deciding five to fifteen accounts one at a time to keep feeding the model; refresh saved views as your segmentation evolves; log this week’s ad spend / agency invoices / hours against the right campaign.
• Monthly — run Find duplicates; revisit the fit criteria and example URLs based on what closed-won (rescore the scores marked old criteria); archive completed campaigns; check the 30-day trend lines on Insights → Funnel; read the per-campaign CAC on Insights → Breakdown and pick the most efficient campaigns to do more of.

The product is built to reward this rhythm. The funnel reads better with consistent activity; the scoring model calibrates better with continuous review; the database stays clean if duplicates are caught monthly rather than yearly.

Where to go next

• First-time setup — Quick start.
• Data model — Account, Campaign, Organization, project and product, Fit criteria and fit score, How scoring works.
• Ranking — Rank a list without a campaign, Review thousands of accounts.
• Operations — Use Today, Run your first campaign, Log a conversation, Track campaign costs and CAC.
• Hitting a snag? — FAQ covers the most common first-week questions.
• Recent changes — What’s new.