The best Claude prompts for RevOps and sales managers

A pipeline review built from CRM data tells you what your reps logged. It doesn’t tell you the CFO at one of your deals left three weeks ago, or that a prospect was acquired last month, or that a rep has gone 26 days without a meeting on the calendar. By the time those things surface in a standup, the deal has usually already slipped.

These four Claude prompts are built for the visibility and data quality problems RevOps and sales managers deal with every week: flagging deal risk before the standup, validating CRM contacts before a QBR cycle, building a quarterly record of who left your accounts, and scoring a new target list before handing it to the team.

All four run on Lusha’s verified contact and company data. Connect the Lusha connector once and it runs in the background. The pipeline review prompt also uses Google Calendar to check meeting cadence per deal.

PROMPT 1 — Run the weekly pipeline review and flag every deal at risk

Before the Monday standup, this prompt scans every active deal for structural account risk via Lusha — a departed CFO, an acquisition, a headcount cut in the buying team — and checks meeting cadence per deal via Google Calendar. It returns a one-screen health report: RED deals with a specific standup question per rep, AMBER deals flagged with the signal, GREEN deals listed and done. A deal that’s RED on both account risk and engagement risk gets a double-RED flag — those are the ones to act on before you walk into the room.

Tools: Lusha + Google Calendar

→ Full play page and example output

<context>
I want to run a weekly pipeline review before my team standup. I need to know which deals have a risk signal worth flagging — not from CRM health scores, but from what's actually happening at the prospect accounts right now.

My pipeline:
- Deal list: [PASTE DEAL NAME, COMPANY, STAGE, ACV, OWNER — one per line OR "pull from my calendar"]
- Team size: [NUMBER OF REPS]
- Focus: [ALL DEALS / CLOSE THIS QUARTER / SPECIFIC STAGE]
- What I want to flag: [ALL RISKS / STUCK DEALS / MISSING MEETINGS / STRUCTURAL CHANGES]
</context>

<task>
1. For each deal, use Lusha to scan the prospect account for structural changes in the last 30 days:
   - Executive departure or new hire in the buying function
   - M&A activity where the prospect is the acquired party
   - Significant headcount contraction in the team being sold into
   - Any signal that typically re-routes or freezes vendor decisions

2. For each deal, check Google Calendar for meeting activity:
   - When was the last meeting with this account?
   - Is there a next meeting scheduled?
   - Flag any deal where the last meeting was more than 21 days ago with nothing on the calendar

3. Rate each deal on two axes:
   ACCOUNT RISK (Lusha): RED / AMBER / GREEN
   ENGAGEMENT RISK (Calendar): RED / AMBER / GREEN

4. Return a pipeline health report:
   - Summary: X deals reviewed, X RED, X AMBER, X GREEN
   - RED deals first — account risk, engagement risk, one recommended action, one standup question for the rep
   - AMBER deals — flagged with the specific signal or gap
   - GREEN deals — listed only
   - Flag any deal where both axes are RED

5. One question to ask each RED deal owner in the standup — specific to the risk, not generic.
</task>

<constraints>
- Flag only signals Lusha actually returns. Don't infer risk from deal age or rep tenure.
- Standup question must be specific to the risk — not "how's this deal going?"
- One screen only.
- GREEN means no signal and active cadence — don't manufacture risk.
</constraints>

PROMPT 2 — Validate every contact in a territory before a QBR

CRM contact data decays at roughly 30% per year. A QBR cycle built on six-month-old contact data means reps walking into rooms with wrong titles, bounced emails, or contacts who left months ago. This prompt validates every key contact in a territory before the cycle starts — confirms who’s still current, flags title changes that affect seniority or decision-making authority, finds replacements for anyone who’s left, and surfaces the accounts where a departure makes QBR prep a risk.

Tools: Lusha

→ Full play page and example output

<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, use Lusha to validate:
   - Still at the company?
   - Title current or changed?
   - Work email still valid?
   - How long in the current role?

2. For any contact who left or changed roles significantly, find their replacement via Lusha:
   - Verified title, email, direct phone
   - Flag if no clear replacement found

3. Flag contacts by status:
   - CURRENT: confirmed, still at the company
   - TITLE CHANGED: still there but role shifted — CRM update needed
   - DEPARTED: no longer at the company — replacement found or gap flagged
   - UNVERIFIED: Lusha can't confirm — needs manual check

4. Return a contact health report:
   - Summary: X checked, X CURRENT, X TITLE CHANGED, X DEPARTED, X UNVERIFIED
   - DEPARTED and TITLE CHANGED with what changed and replacement or new title
   - UNVERIFIED flagged for manual follow-up
   - CURRENT listed only

5. Flag any account where a key contact departure makes QBR prep a risk.
</task>

<constraints>
- Only return what Lusha verifies. UNVERIFIED means can't confirm — don't assume still current.
- Title changes matter when they affect seniority or function, not every internal promotion.
- Report is for the manager — reps get only their relevant rows.
- Flag structural gaps where no replacement is found.
</constraints>

PROMPT 3 — Build the quarterly account contact change log

At the end of each quarter, this prompt builds a structured record of every contact who left your accounts, whether a replacement has been found and verified, and which accounts have a coverage gap that’s been open the longest. Three categories: COVERED (replacement verified in Lusha), GAP (no replacement confirmed), ROLE CHANGED (still at the company but function or seniority shifted). Accounts with multiple changes in one quarter get flagged separately — that pattern usually signals a restructure or acquisition, not normal attrition.

Tools: Lusha

→ Full play page and example output

<context>
I want to build a contact change log for this quarter — a structured record of every key contact who left our accounts, whether we've found their replacement, and which accounts now have a coverage gap.

My account base:
- Account list: [PASTE COMPANY NAMES — one per line]
- Contact tier to check: [ALL CONTACTS / DECISION MAKERS ONLY / ECONOMIC BUYERS ONLY]
- Quarter: [Q1 / Q2 / Q3 / Q4 YEAR — or "last 90 days"]
- What I want to track: [DEPARTURES ONLY / DEPARTURES + ROLE CHANGES / ALL CHANGES]
</context>

<task>
1. For each account, use Lusha to identify contacts who left or significantly changed roles in the last 90 days.

2. For each departed contact, find their replacement via Lusha:
   - Verified title, email, direct phone
   - How long in the role?
   - If no replacement found: flag as structural gap

3. Build a change log with three categories:
   COVERED: contact left, replacement found and verified
   GAP: contact left, no replacement found — one recommended next action
   ROLE CHANGED: still at company but significantly different role — flag if it affects buying function

4. Return a summary:
   - Total accounts checked, total departures, COVERED vs GAP count
   - Accounts with longest-running gap — highest priority for outreach
   - One recommended action per GAP account

5. Flag any account with multiple changes this quarter — sign of broader org instability.
</task>

<constraints>
- Only flag changes Lusha verifies.
- COVERED means replacement is verified in Lusha — not assumed.
- Role changes only matter when they affect buying function or decision-making authority.
- One row per change, structured for export.
</constraints>

PROMPT 4 — ICP score a new target list before the team works it

A new list from a conference, a data import, or a marketing campaign lands with no prioritization. This prompt scores every account against your ICP criteria using Lusha’s verified firmographic data — headcount, industry, geography, function size, active signals — before anyone makes a call. It returns four tiers: STRONG FIT (meets ICP and has a live signal), FIT (meets ICP, no signal), PARTIAL FIT (missing one or two criteria), and DISQUALIFIED (fails a hard rule). DISQUALIFIED is as useful as STRONG FIT — it’s the output that stops two accounts from consuming rep time that should go to the four accounts with live signals.

Tools: Lusha

→ Full play page and example output

<context>
I have a new list of target accounts I want to score against our ICP before handing it to the team. I want to know which accounts are worth working, in what order, and why — based on verified firmographic data, not assumptions.

My list:
- Account list: [PASTE COMPANY NAMES OR DOMAINS — one per line]
- Our ICP criteria:
  - Industry: [LIST TARGET INDUSTRIES]
  - Company size: [HEADCOUNT RANGE]
  - Geography: [REGION OR COUNTRY]
  - Function we sell into: [SALES / MARKETING / FINANCE / IT / OPS / OTHER]
  - Signals that indicate fit: [RECENT FUNDING / HEADCOUNT GROWTH / NEW EXEC / OTHER]
- Disqualifiers: [CRITERIA THAT RULE AN ACCOUNT OUT]
</context>

<task>
1. For each account, use Lusha to pull verified firmographic data:
   - Current headcount and trend
   - Industry and sub-industry
   - Geography and HQ location
   - Headcount in the function we sell into
   - Any active signals: funding, exec hire, M&A

2. Score each account:
   - STRONG FIT: meets all ICP criteria and has at least one active signal
   - FIT: meets ICP criteria, no active signal
   - PARTIAL FIT: meets some criteria, missing one or two — flag which
   - DISQUALIFIED: fails a disqualifier — flag why

3. For STRONG FIT and FIT accounts, identify the right first contact:
   - Verified title, work email, direct phone
   - Flag if no verified contact found

4. Return:
   - STRONG FIT first (ranked by signal recency), then FIT, then PARTIAL FIT, then DISQUALIFIED
   - One-line reason for each DISQUALIFIED account

5. Summary: counts by tier, top 5 to work first with reasons, any pattern in disqualified accounts.
</task>

<constraints>
- Score only against the ICP criteria provided.
- DISQUALIFIED is a clean output — don't soften to PARTIAL FIT.
- Flag UNVERIFIED if Lusha can't find firmographic data — don't score it.
- Top 5 must explain why, not just repeat the score.
</constraints>

Where these prompts live

Each prompt above has a full play page with a detailed example output — worth reading before running one for the first time.

• Run the weekly pipeline review and flag every deal at risk →
• Validate every contact in a territory before a QBR →
• Build the quarterly account contact change log →
• ICP score a new target list before the team works it →

All four are part of the Lusha Pipeline Acceleration Gallery — a library of Claude prompts built for every role in a revenue team.