TLDR: FinTech deals move slowly, approval chains are long, and contact data decays fast. These seven Claude prompts — all built on verified Lusha data — handle the pre-outreach verification, territory audits, and account coverage gaps that regulated sales environments can’t afford to skip.
Selling into FinTech is not like selling into SaaS. Compliance officers review vendor communications. Procurement has strict approval requirements. The person who owns the budget may have changed roles twice since the last annual review. One wrong title in a cold email, one bounce to a departed compliance contact, one QBR walked into without knowing the CFO moved — and the deal stalls.
These seven prompts are for FinTech sales and RevOps teams who need to know their data is current before anything goes out. They cover the full data quality stack: individual contact verification before outreach, territory-wide audits before QBR cycles, buying group coverage maps across named accounts, firmographic enrichment on prospect lists, and early-warning scans for accounts that have gone dark. All seven run in Claude with the Lusha connector.
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Before you send a single email (Prompts 1–2)
In FinTech, regulated industries mean regulated inboxes. A bounce, a wrong title, or an email to someone who left the firm six months ago doesn’t just hurt deliverability — it signals that your data practices don’t match the standards you’re selling to. These two prompts run before any outreach leaves the door.
Prompt 1 — Verify a contact’s title before you reach out
CRM titles decay at roughly 30% per year. In FinTech, where promotions shift regulatory authority and budget ownership, a VP who became SVP isn’t just a title change — it’s a different compliance footprint and a different conversation. A Head of Risk who became Chief Risk Officer now reports to the board, not a department head. This prompt checks the current verified title via Lusha before the first touch, classifies what changed, and flags whether it affects how to open the conversation.
<context>
I have a contact in my CRM and I'm not sure their title is current. I want to verify what Lusha has before I reach out — so I don't reference the wrong role or miss that they've been promoted.
My contact:
- Name: [NAME]
- Company: [COMPANY NAME OR DOMAIN]
- Title I have on file: [TITLE FROM CRM]
- Last updated in CRM: [DATE OR "UNKNOWN"]
</context>
<task>
1. Use Lusha to look up this contact:
- What is their current verified title?
- Are they still at the company?
- Has their title changed from what I have on file?
- How long have they been in the current role?
2. Classify the change (if any):
- SAME: title matches what I have on file
- PROMOTED: same company, higher seniority
- ROLE CHANGED: same company, different function or scope
- DEPARTED: no longer at the company — flag and find replacement if possible
- UNVERIFIED: Lusha can't confirm — needs manual check
3. If PROMOTED or ROLE CHANGED:
- Return the new title and note what changed
- Flag whether the change affects how I should open the conversation
4. Return the verification result with the current verified title, tenure, and one note on what (if anything) changes about the outreach.
</task>
<constraints>
- Only return what Lusha verifies.
- SAME is a useful output — it confirms the CRM is current.
- A promotion is not a reason to delay outreach — it's a reason to acknowledge it in the first line.
</constraints>Prompt 2 — Clean a contact list before a campaign goes out
One bad send on a FinTech list damages deliverability for every send that follows. In regulated environments, bouncing emails to departed compliance or procurement contacts can flag your sending domain — and the firms you’re trying to reach have the tightest email security filters in the market. This prompt validates every contact on a list before the campaign launches, returning a per-contact SEND / UPDATE FIRST / DO NOT SEND decision and a deliverability risk rating before a single email goes out.
<context>
I'm about to launch an outbound campaign. Before the first email goes out, I want to validate every contact on the send list — so we don't burn deliverability on bounces, send wrong personalization to people who've been promoted, or reach out to contacts who left months ago.
My list:
- Contact list: [PASTE NAME, TITLE, COMPANY, EMAIL — one per line]
- Campaign type: [COLD OUTREACH / RE-ENGAGEMENT / PRODUCT UPDATE / EVENT INVITE]
- Personalization tokens used: [e.g. {{title}}, {{company}}, {{first_name}}]
- Last time this list was validated: [DATE OR "NEVER"]
- Estimated send date: [DATE]
</context>
<task>
1. For each contact, use Lusha to validate:
- Still at the company?
- Verified work email — does it match what we have?
- Current title — does it match the personalization token we're using?
2. Flag each contact with a send decision:
- SEND: confirmed at company, email verified, title current — safe to include
- UPDATE FIRST: still there but title changed enough to break personalization — fix the token before sending
- DO NOT SEND: departed or email undeliverable — remove from this send
- UNVERIFIED: Lusha can't confirm — manual check before including
3. For DO NOT SEND contacts, suggest whether to find a replacement contact at the same company or remove entirely.
4. Return:
- Cleaned list with status and corrected fields where needed
- Summary: X SEND, X UPDATE FIRST, X DO NOT SEND, X UNVERIFIED
- Estimated bounce rate if sent as-is (% of DO NOT SEND)
- Deliverability risk rating: LOW / MEDIUM / HIGH based on list quality
5. Flag any company where multiple contacts on the list are DO NOT SEND — may signal a larger org change worth investigating before outreach.
</task>
<constraints>
- DO NOT SEND is a hard call — don't soften it to "check before sending."
- Title changes matter when they break personalization tokens — a VP who became SVP breaks {{title}} unless updated.
- If 20%+ of the list is DO NOT SEND, flag the whole campaign as HIGH deliverability risk.
</constraints>Territory and account data quality (Prompts 3–5)
FinTech QBRs are high-stakes. Executives from risk, compliance, and legal often sit in alongside the business buyer. Walking into the room with stale data — wrong titles, departed contacts, missing decision-makers — is a credibility problem that compounds when the buyer’s own compliance function has already done their due diligence on your firm. These three prompts run before QBR cycles start.
Prompt 3 — Score a rep’s account list data quality before a QBR
A data quality scorecard before a QBR gives a FinTech sales manager the coaching leverage they need without waiting for the meeting to surface the problem. In financial services, where ACV-weighted deals often sit in long approval queues, finding out mid-cycle that the primary contact has moved is an expensive discovery. This prompt validates every primary contact in a rep’s territory, maps contact health to active pipeline, and returns a GREEN/AMBER/RED scorecard with ACV at risk and a talking point built from the actual data patterns.
<context>
I want to score the data quality of a rep's entire account list before a QBR or 1:1 — so I walk into the conversation with a clear picture of where their CRM data is clean, where it's at risk, and what it means for their pipeline.
Rep and territory:
- Rep name: [REP NAME]
- Account list with primary contacts: [PASTE COMPANY, CONTACT NAME, TITLE, LAST TOUCH DATE — one per line]
- Active pipeline: [PASTE DEAL NAME, COMPANY, STAGE, ACV — one per line]
</context>
<task>
1. For each account's primary contact, use Lusha to validate:
- Still at the company in the same role?
- Title current?
- Reachable (verified email or phone)?
2. Score each account's contact health:
- GREEN: contact confirmed, verified, reachable
- AMBER: contact still there but title changed, or last touch 30+ days ago
- RED: contact departed, unverified, or unreachable
3. Map contact health to pipeline:
- For any RED or AMBER account with an active deal: flag as pipeline risk
- Return: deal name, stage, ACV, contact status, risk reason
4. Return a rep data quality scorecard:
- Overall score: % GREEN / AMBER / RED across all accounts
- Pipeline at risk: RED and AMBER deals sorted by ACV
- Total ACV exposure from RED accounts
- Accounts with longest gap since last verified touch
- 3 coaching observations based on the data patterns
5. A one-paragraph QBR talking point: what does this data tell us about how the rep is managing their territory?
</task>
<constraints>
- The QBR talking point must be based on actual data patterns — not generic commentary.
- 3 coaching observations must be specific: "6 of your top 10 accounts by ACV have a contact last touched 45+ days ago" not "some accounts need attention."
- Total ACV at risk is the headline number — surface it first.
</constraints>Prompt 4 — Validate every contact in a territory before a QBR
In FinTech, a contact who moved from Head of Compliance to Chief Risk Officer isn’t a minor update — it changes what they own, who they report to, and what they need from a vendor conversation. This prompt validates every CRM contact in a territory before a QBR cycle, flags departures, significant title shifts, and structural gaps, and finds replacements for every account where the main contact has moved. The output is a contact health report the manager can use to direct reps to specific accounts before they walk into the meeting.
<context>
I want to validate the contacts in my CRM before a QBR cycle starts. I need to know which contacts are still current, which have changed roles, and which have left — so my reps aren't walking into QBRs with stale data.
My territory:
- Account list: [PASTE COMPANY NAMES — one per line]
- Contact list (optional): [PASTE NAME, TITLE, COMPANY — one per line, OR "find key contacts from Lusha"]
- Focus: [ALL CONTACTS / DECISION MAKERS ONLY / ECONOMIC BUYERS ONLY]
- What matters most: [TITLE CHANGES / DEPARTURES / EMAIL ACCURACY / ALL]
</context>
<task>
1. For each contact in the list, use Lusha to validate:
- Are they still at the company?
- Is their title current — or has it changed since it was logged?
- Is their work email still valid?
- How long have they been in the current role?
2. For any contact who has left or changed roles significantly, use Lusha to find their replacement:
- Who now holds the equivalent role at the account?
- Return their verified title, email, and direct phone
- Flag if no clear replacement is found — structural gap at the account
3. Flag contacts by status:
- CURRENT: title and email confirmed, still at the company
- TITLE CHANGED: still at the company but role has shifted — update needed in CRM
- DEPARTED: no longer at the company — replacement found or flagged as gap
- UNVERIFIED: Lusha can't confirm — needs manual check before the QBR
4. Return a territory contact health report:
- Summary: X contacts checked, X CURRENT, X TITLE CHANGED, X DEPARTED, X UNVERIFIED
- DEPARTED and TITLE CHANGED contacts listed with what changed and the replacement or new title
- UNVERIFIED contacts flagged for manual follow-up
- CURRENT contacts listed only — no detail needed
5. For each account where a key contact has departed or changed roles significantly, flag it as a QBR prep risk — the rep needs to re-establish the relationship before walking into the meeting.
</task>
<constraints>
- Only return what Lusha verifies. If a contact can't be confirmed, flag as UNVERIFIED — don't assume they're still current.
- Title changes matter when they affect seniority or function. "Senior Manager" to "Director" at the same account is worth flagging. "Manager" to "Senior Manager" in the same function is not.
- The report is for the manager, not the rep — keep it structured and scannable. Reps get the relevant rows for their accounts, not the full report.
- If Lusha returns no replacement for a departed contact, flag the account as having a structural gap — don't leave it blank.
</constraints>Prompt 5 — Audit contact coverage gaps across named accounts
Three contacts at a FinTech account with no economic buyer is a coverage gap, not coverage. In complex financial services deals — where compliance, legal, procurement, and the business buyer are all involved in the sign-off — missing one required role can stall a deal at any stage. A STALE CONTACT creates false confidence that’s harder to fix than a known gap. This prompt maps every required buying group role across named accounts, flags CRITICAL GAPs and STALE CONTACTs, and returns a verified replacement for every gap found.
<context>
I manage a set of named accounts and I want to audit whether we have the right contacts mapped for each one — not just whether we have any contact, but whether we're covering the right roles in the buying group. Gaps in contact coverage mean gaps in deal control.
My named accounts:
- Account list: [PASTE COMPANY NAMES — one per line]
- What I sell: [PRODUCT / SOLUTION]
- Buying group roles I need covered: [e.g. Economic buyer / Technical evaluator / Champion / Procurement]
- Contacts I currently have: [PASTE NAME, TITLE, COMPANY — one per line]
</context>
<task>
1. For each account, use Lusha to map the current verified contacts in the relevant buying group roles:
- Who currently holds each role I need covered?
- Are my existing contacts still in the right roles?
- Are there roles I need covered but have no contact for?
2. For each account, return a coverage map:
- Role: COVERED (existing verified contact) / GAP (no contact for this role) / STALE (contact no longer in this role)
3. Prioritize the gaps:
- CRITICAL GAP: a must-have role with no verified contact — blocks deal progression
- IMPORTANT GAP: a should-have role missing — increases risk at current deal stage
- STALE CONTACT: someone I think I have but who's no longer in that role
4. For each GAP and STALE CONTACT: use Lusha to find the current verified contact for that role, with email and direct phone.
5. Return a contact coverage report:
- Per-account coverage map with GREEN / AMBER / RED status
- Critical gaps ranked by deal stage and ACV
- Replacement contacts found via Lusha for every gap
- Total accounts with at least one critical gap
</task>
<constraints>
- Coverage is role-specific, not headcount-specific. Having 3 contacts at an account but missing the economic buyer is a CRITICAL GAP.
- A STALE CONTACT is more dangerous than a GAP — it creates false confidence. Flag it prominently.
- If Lusha can't find a contact for a required role, flag it as a research task — don't leave it unmarked.
</constraints>Enrichment and dark account recovery (Prompts 6–7)
These two prompts handle the bookends of the data quality problem: building a clean firmographic picture of FinTech targets before scoring them, and catching accounts where the relationship has gone quietly dark before it surfaces as a churn risk or dead pipeline at renewal time.
Prompt 6 — Enrich a list of company domains
FinTech target lists are often built from domain lists — inbound form fills, conference attendee exports, partner referrals, event scans. A domain list doesn’t tell you whether the company is publicly traded or Series B, whether it has 200 employees or 5,000, or whether its last priced round was this quarter or three years ago. In financial services, those details change the entire conversation: a company three years past its last round behaves differently from a firm that just closed a $300M raise. This prompt turns a list of company domains into a full firmographic table with funding history, headcount, revenue range, and office footprint.
<context>
I have a list of company domains. I want to enrich each one with firmographics, funding history, and location footprint before scoring or planning outreach.
</context>
<task>
1. Take this domain list (one per line):
[PASTE DOMAINS]
2. For each domain, use Lusha to return:
- Company name and alternative names
- Headcount band and LinkedIn follower count
- Revenue range (annual USD)
- Founded year and company type (public, private)
- Full funding history (rounds, amounts, IPO status)
- HQ city and country, plus a count of regional offices
- Main industry and sub-industry
- Key specialties or product areas
3. Output an enrichment table:
Company | HQ | Headcount | Revenue range | Total raised | Last round | Offices worldwide | Industry
4. Flag any domain Lusha cannot resolve.
5. Summarize at the top: total enriched, total no-match, total combined headcount, total combined capital raised.
</task>
<constraints>
- Do not invent fields. If Lusha returns no record for a domain, surface it as no-match.
- Funding history should include the last round date and amount where available.
- Office count helps RevOps understand regional reach without listing every address.
- Use Lusha's canonical company name, not the literal domain string.
</constraints>Prompt 7 — Find every account where the main contact has gone dark or left
FinTech firms restructure constantly — mergers, regulatory changes, compliance team overhauls. An account that looked active three months ago may now have a departed primary contact and 60 days of silence. By the time a rep discovers this on a renewal call, the new contact has already inherited the vendor list with no relationship context. This prompt runs a monthly scan across the full book, classifies each account as DARK / COOLING / ACTIVE, and for every DARK account returns a replacement contact via Lusha and a specific re-engagement action — not “reach out” but who, how, and what angle.
<context>
I want to find every account in my book where the primary contact relationship has gone dark — either the contact left, or engagement dropped off — before it turns into a churn risk or a dead deal I don't know about.
My book:
- Account list with primary contacts: [PASTE COMPANY, CONTACT NAME, TITLE — one per line]
- What counts as dark: [45+ DAYS NO REPLY / CONTACT DEPARTED / BOTH]
- Account type: [CUSTOMER / PROSPECT / BOTH]
</context>
<task>
1. For each account, check two things in parallel:
CONTACT STATUS (Lusha):
- Is the primary contact still at the company in the same role?
- If departed: find the most likely replacement via Lusha
ENGAGEMENT STATUS (Gmail):
- When was the last inbound email from this account?
- When was the last outbound email to this account?
- Is there an unanswered outbound email sitting unacknowledged?
2. Classify each account:
- DARK — CONTACT GONE: primary contact has left, no active thread
- DARK — GONE QUIET: contact still there but no inbound for 45+ days
- COOLING: last inbound was 21–44 days ago — not dark yet but trending that way
- ACTIVE: recent inbound, contact verified — no action needed
3. For DARK accounts:
- Return the specific reason (departed / gone quiet)
- Return replacement contact details if contact has departed (via Lusha)
- Suggest one specific re-engagement action
4. Return a dark accounts report:
- Summary: X DARK (contact gone), X DARK (gone quiet), X COOLING, X ACTIVE
- DARK accounts sorted by account value or deal stage
- For each DARK account: contact status, last touch date, replacement if found, recommended action
- Total ACV or ARR at risk from DARK accounts (if provided)
5. Flag any account that is DARK on both dimensions simultaneously — contact gone AND no engagement. These are the highest-priority accounts to act on this week.
</task>
<constraints>
- An account can be DARK for two different reasons — contact gone vs gone quiet. Both are risks but they require different responses.
- Don't surface COOLING accounts as urgent — they're a watch list, not an action list.
- The recommended action must be specific: not "reach out" but who to contact, how, and what angle.
</constraints>The pattern across all prompts
Every prompt on this list treats data accuracy as a pre-condition, not a nice-to-have. In FinTech, the cost of working from stale data isn’t just a wasted touch — it’s a credibility signal to buyers who scrutinize data practices as part of their own vendor evaluation. The prompts are structured to surface what’s wrong before anything goes out: wrong titles before outreach, stale contacts before QBRs, missing roles before deals progress, dark accounts before they churn. Lusha does the verification. Claude does the prioritization. The output is always a specific action, not a data dump.
Where these prompts live
All seven run in Claude with the Lusha connector.
- Verify a contact’s title before you reach out
- Clean a contact list before a campaign goes out
- Score a rep’s account list data quality before a QBR
- Validate every contact in a territory before a QBR
- Audit contact coverage gaps across named accounts
- Enrich a list of company domains
- Find every account where the main contact has gone dark or left
