The 10 best Claude prompts for Customer Success — health monitoring, expansion plays, renewal defense. Copy, paste, run with verified data from Lusha.
Most “best AI prompts” posts in B2B target AEs or marketers. CSMs and Account Managers — the function that actually owns the bigger half of revenue at most mature B2B companies — rarely get content written directly for them. The 10 prompts below are the ones a working CSM or AM actually runs in 2026, organized by the rhythm Customer Success teams actually work on: monthly book scans, quarterly business reviews, and the structural events that change the renewal conversation.
Each prompt runs inside Claude with the Lusha connector enabled, which means customer accounts come back with verified buying groups, time-stamped expansion and renewal signals, and named events tied to source URLs — not statistical inference or anonymous activity feeds.
Organized by workflow so you can find what you need fast — watching the book, strategic growth, defensive moves. Copy the green/black block, paste it into Claude, replace the bracketed values with your specifics, and run.
Connect Lusha to Claude in two minutes →
Watching the book (Prompts 1–4)
The monthly and quarterly rhythm. Portfolio digests, expansion signal scans, renewal risk flags, and continuous champion monitoring.
Prompt 1 — Build a weekly signal digest on your customer portfolio
The Monday morning prompt. Run against your saved book every week to surface which accounts moved, which were quiet, and where attention should go.
<context>
This is my weekly signal digest on my customer portfolio.
My customer portfolio (save once, reuse weekly):
[PASTE CUSTOMER LIST — domains or company names]
Run every Monday morning to surface the week's signal activity.
</context>
<task>
For each account in the portfolio, use Lusha's signals layer to retrieve activity in the last 7 days:
- Funding events (rounds, IPO, M&A, strategic investments)
- Leadership events (executive hires, promotions, departures)
- Hiring surges by department
- Product launches and partnerships
Sort accounts into three buckets:
- ACTIVE — one or more signals fired in the window
- QUIET — no signals (carry to next week's digest)
- NO MATCH — Lusha couldn't resolve the entry (re-check)
For each ACTIVE account, return:
Account | Signal type and date | One-line summary | Source URL | Recommended action (call, email, monitor, hold)
At the top, surface a one-line "this week's headline" — the single highest-intensity signal across the portfolio.
At the bottom, list the QUIET accounts as a single line for next-week carryover.
</task>
<constraints>
- Keep each active-account block to 4-5 lines max — the digest is meant to be scannable
- QUIET is not failure — surface the count so I know the digest covered the full portfolio
- Do not invent signals; surface only what Lusha returns
</constraints>See the full workflow with a live demo →
Prompt 2 — Identify expansion signals on existing customers
The monthly expansion-readiness scan. Surfaces which customers are showing the signals that precede an expansion conversation — funding, hiring surges, new leadership, product launches.
<context>
I want to scan my customer book and find which accounts are showing expansion signals — events that mean the customer's buying context just shifted in a direction that creates upsell, cross-sell, or scope-expansion opportunity.
My customer list:
[PASTE — one row per customer, with current spend area and function we sold into]
</context>
<task>
For each customer, use Lusha's signals layer to scan the last 90 days for expansion triggers:
- Hiring surge in the function we sold into (more seats, more usage)
- New leadership in the buying group (mandate window, vendor scope under review)
- Funding round, IPO, M&A as acquirer (budget unlocked)
- Strategic investment in adjacent tech (direction of next spend)
- Major product launch (new platform area we could deepen scope into)
- Geographic expansion (new region rollout opportunity)
For each customer, return:
Customer | Current scope | Expansion trigger fired | Trigger date | Expansion angle (what conversation this opens) | Recommended next step
Rank by expansion-readiness: READY (strong trigger, last 60 days) / WARM (signal fired but requires more discovery) / STABLE (no signal, continue normal cadence).
</task>
<constraints>
- The trigger must map to a real expansion conversation — generic news doesn't count
- New leadership in the buying group function is the strongest single trigger
- A STABLE customer isn't failure — surface for next monthly scan
</constraints>See the full workflow with a live demo →
Prompt 3 — Flag renewal risk on existing customers
The renewal-risk mirror to Prompt 2. Same customer book, opposite question — surface the deterioration signals that precede churn, with enough lead time to act.
<context>
I want to scan my customer book for the events that precede churn — leadership departures, layoffs, M&A as the acquired party, lawsuits, security incidents — so I have 60-90 days of warning instead of 30.
My customer book:
[PASTE — customer, renewal date or quarter, original champion (name and role)]
</context>
<task>
For each customer, use Lusha's signals layer to scan the last 90 days for risk triggers:
- Executive departures (especially the original champion or their manager)
- Headcount decreases (layoffs, restructuring)
- M&A as the acquired party (acquirers consolidate vendor stacks)
- Lawsuits filed against the company (financial/governance risk)
- Security incidents (operational distraction, vendor scrutiny increases)
- C-suite turnover beyond a single role (broader instability)
For each customer, return:
Customer | Renewal date | Original champion status (in role / departed / manager changed) | Risk triggers fired | Risk angle | Recommended save play
Rank by risk severity: HIGH (champion departed OR 2+ risk triggers) / MEDIUM (1 risk trigger outside the champion) / LOW (minor signal) / STABLE (no risk in window).
Flag any customer where BOTH expansion AND risk triggers have fired. These mixed-state accounts are the highest-priority CSM conversations.
</task>
<constraints>
- The original champion or their manager leaving is the strongest single risk trigger
- A STABLE customer is data, not absence of data
- Mixed-state accounts (expansion AND risk firing) are where the executive sponsor conversation matters most
</constraints>See the full workflow with a live demo →
Prompt 4 — Monitor your champions for role changes
Continuous champion monitoring. The earliest possible warning that a critical relationship is about to break — fires the moment your champion’s individual record shows a role change, often weeks before the company-side data catches up.
<context>
I want to monitor my customer champions for role changes — promotions inside the same company, lateral moves, or departures to a different employer.
My champions (one row per critical contact):
[PASTE — name, current company, current title, LinkedIn URL or email]
</context>
<task>
For each champion, use Lusha's contact signals layer to detect role changes in the last [WINDOW — e.g., 90 days]:
- PROMOTION — same company, new title with later jobStartDate
- COMPANY_CHANGE — different employer than my stored record
- DEPARTED — no current verified employer
For each detected change:
Champion | Change type | Date detected | Old role | New role | New employer (if changed) | Recommended action
Apply action logic:
- PROMOTION at current employer — reach out to congratulate, position the existing engagement under the new scope
- COMPANY_CHANGE to a new employer — reach out at the new company (new prospect opportunity) AND find the replacement at the original customer
- DEPARTED — find the replacement at the original customer urgently; the renewal risk is real
Surface contacts whose individual record shows a change but whose company-side data hasn't refreshed yet — these are the earliest catches.
</task>
<constraints>
- Individual contact records refresh faster than company-side records; trust the individual record when they conflict
- A "no change detected" result is good data — surface the negative result honestly
- The 90-day window catches the change before the renewal cycle reaches the new owner
</constraints>See the full workflow with a live demo →
Strategic growth (Prompts 5–7)
For accounts that are READY. Map the structural expansion opportunities, identify the right cross-sell buyer, time the proposal to the buyer’s actual budget window.
Prompt 5 — Map new buying centers inside an existing customer
Fires when a customer creates a new structural buying opportunity — opens a new region, launches a business unit, acquires another company. Surfaces who’s running the new center with verified contacts.
<context>
My existing customer just created one or more new buying centers since my original deal closed — opened a region, launched a business unit, acquired another company. The original contract covers the original buying center, but the customer is now running more of them.
My customer and current scope:
- Customer: [CUSTOMER NAME / DOMAIN]
- Function we sold into: [FUNCTION]
- Original buying center: [REGION, BU, OR FUNCTION — e.g., "US Sales", "North America Engineering"]
- Trigger event (if known): [new region, new business unit, M&A, function split — leave blank to auto-detect]
</context>
<task>
1. Use Lusha's signals layer to surface recent triggers that would create new buying centers:
- Geographic expansion (new VP of EMEA, Head of APAC, new country office)
- Business unit launch (new VP or GM of a product line)
- M&A as acquirer (newly acquired entity inside the customer's footprint)
- Function split (RevOps separating from Sales Ops, AI Engineering as its own org)
2. For each new buying center, find the verified leadership:
- The owner (VP, Head of, Senior Director)
- 1 adjacent function leader at the same regional/BU level
- 1 technical evaluator if the buying center is product-led
For each contact:
Name | Title | Validated email | Direct dial | Buying center role | Structural trigger | Engagement angle (how the original engagement extends)
Order by buying center, then by role within each.
</task>
<constraints>
- A new buying center is structural (new region, new BU, new acquired entity) — not just a new hire in the existing team
- Cap at 3 buying centers per run for very large customers (5,000+ employees) for actionable output
- The engagement angle must be specific (extending US to EMEA), not generic (deepen the relationship)
</constraints>See the full workflow with a live demo →
Prompt 6 — Identify cross-sell opportunities by adjacent function
For multi-product companies. The cross-sell motion that converts an installed account into a strategic account — different function at the same customer, different product, warm-intro path from the existing champion.
<context>
I have an existing customer using Product A. I want to identify the right buyer at the same customer for Product B, which lives in an adjacent function.
The existing engagement:
- Customer: [CUSTOMER NAME / DOMAIN]
- Product A (deployed): [PRODUCT NAME]
- Function we sold Product A into: [FUNCTION]
- My champion: [NAME, TITLE]
The cross-sell:
- Product B: [PRODUCT NAME]
- Function that owns Product B: [FUNCTION]
- Buyer profile for Product B: [SENIORITY + ROLE FAMILY]
</context>
<task>
1. Use Lusha to find the verified leadership in the cross-sell function at the customer:
- C-suite owner of the function (CMO, CTO, CFO — the right one for Product B)
- 1-2 VP-level leaders running operational areas matching the product's use case
- 1 Director-level operator likely to be the day-to-day evaluator
2. For each contact:
Name | Title | Validated email | Direct dial | Buyer role for the cross-sell (economic, operational, technical evaluator) | Warm-intro path from my existing champion
3. Surface the cross-sell rationale per buyer — one sentence on why this specific person, in this specific function, is the right buyer for Product B given the customer's current state and recent signals.
4. If recent buying signals on the customer (funding, hiring surge in the new function, product launches) make the cross-sell timing especially strong, flag those signals.
</task>
<constraints>
- The cross-sell is to an adjacent function. If Product B sells to the same buyer as Product A, that's upsell — use the multi-thread prompt instead
- The warm-intro path matters — a cross-sell intro routed through the existing champion converts at multiples of cold outreach
- Cap at 4 target buyers per cross-sell for a single discovery brief
</constraints>See the full workflow with a live demo →
Prompt 7 — Surface the post-event budget window
The “when to propose” prompt. Find the structural moments when the customer’s budget reopens — fiscal year crossings, new leader mandate windows, post-funding allocation periods, M&A vendor rationalization cycles.
<context>
I want to know when my customer's budget reopens for new vendor commitments — the structural moments inside the next 6-12 months when expansion proposals will land inside an active budget window.
My customer:
- Customer: [CUSTOMER NAME / DOMAIN]
- Current contract scope and renewal date: [SCOPE + DATE]
- Expansion I want to propose: [ADDITIONAL SEATS / NEW REGION / CROSS-SELL PRODUCT]
</context>
<task>
1. Use Lusha's signals layer to scan the customer's last 12 months for structural budget events:
- Funding rounds (budget allocation lands 60-90 days post-close)
- IPO events (6-12 months of investor-mandated growth spending)
- M&A as the acquirer (acquired entities get vendor-rationalized within 12 months)
- Executive hires in the buying group (CRO, CFO, CMO, CTO — 60-90 day mandate windows)
- Executive departures (HOLD window — avoid expansion during transition)
2. For each event, calculate:
- Open date (when budget conversation becomes possible)
- Peak window (when budget allocation decisions are being made)
- Close date (when window narrows back to normal procurement)
3. Cross-reference with the customer's likely fiscal year structure.
4. Output a budget calendar:
Event | Window opens | Peak window | Window closes | Status (OPEN NOW / OPENING SOON / CLOSED / HOLD) | Recommended action
5. At the bottom, list the 2-3 highest-value windows to act on this quarter.
</task>
<constraints>
- A budget window is structural — created by a specific event, not a calendar quarter
- New CRO mandate windows are 60-90 days; funding allocation is 90-180 days; IPO is 6-12 months
- Don't propose expansion inside a HOLD window (transition or risk events make authority unclear)
- Do not invent events — surface only what Lusha returns
</constraints>See the full workflow with a live demo →
Defensive moves (Prompts 8–10)
Renewal protection. Multi-thread mapping, pre-QBR briefs, champion recovery — the workflows that keep the book intact.
Prompt 8 — Build a multi-thread map for an existing customer
The relationship insurance prompt. Single-threaded customer relationships are renewal risk in slow motion. Map 6-8 verified contacts across the buying group with roles tagged.
<context>
I have an existing customer where I'm under-threaded — I know one main contact but should know 6-8 across the buying group.
My known contact:
- Name: [NAME]
- Title: [TITLE]
- Customer: [CUSTOMER NAME]
- Function we sold into: [FUNCTION]
</context>
<task>
Use Lusha to find 6-8 additional verified contacts at the customer, organized into five relationship roles:
- PEER OF CHAMPION — same function, same level (1-2)
- MANAGER / SKIP-LEVEL — the boss above, and the boss above that (1-2)
- ADJACENT FUNCTION — leaders in adjacent functions the engagement should touch (2-3)
- EXECUTIVE SPONSOR — C-suite owner of the broader business unit (1)
- SUCCESSOR CANDIDATE — Director/VP-level who could step into my champion's role if they move (1)
For each:
Name | Title | Validated email | Direct dial | Relationship role | Why this person matters (one sentence)
Group output by relationship role, not seniority. Flag any role where Lusha returns zero — that's a structural gap.
</task>
<constraints>
- Only include contacts with validated email
- Cap at 2 contacts per relationship role
- For ADJACENT FUNCTION, pick functions that genuinely connect to the engagement
- The successor candidate is renewal insurance — flagging structural risk, not paranoia
</constraints>See the full workflow with a live demo →
Prompt 9 — Get a single-account signal brief before a QBR
Pre-QBR prep in 60 seconds. Every signal event in the last six months at one customer, organized into five categories, with talk tracks tied to each signal.
<context>
I have a QBR or strategic review on [ACCOUNT NAME] in [TIMEFRAME — e.g., 24 hours]. I need a complete pre-meeting brief.
</context>
<task>
Use Lusha's signals layer to pull every signal at the account from the last 6 months, organized into five categories:
1. LEADERSHIP — executive hires, promotions, departures
2. STRATEGIC MOVES — M&A, IPO, funding, strategic investments
3. PRODUCT ACTIVITY — launches, integrations, new features
4. HIRING INTENSITY — surges by department, headcount growth, geographic spikes
5. MARKET SIGNALS — web traffic shifts, partnerships, new customers
For each signal:
- Event type and date
- One-line summary
- Source article URL where available
At the top, surface a 3-line headline summary:
- Most important leadership move
- Biggest strategic shift
- Strongest active hiring signal
After the categorized brief, suggest 3-5 talk tracks for the QBR, each tied to a specific surfaced signal.
</task>
<constraints>
- Pull every signal type, not just funding and hiring
- Surface source URLs on every news event that has one
- If the account is quiet, surface that honestly
</constraints>See the full workflow with a live demo →
Prompt 10 — Find the new champion when yours moves on
The recovery prompt. Your champion left — find the verified replacement before the renewal cycle reaches them first. Cross-validates each candidate against their individual record to filter out anyone who also moved.
<context>
My champion at an existing customer just left. I need to find the verified replacement and re-engage before the renewal cycle reaches them first.
My departed champion:
- Name: [NAME]
- Former title at the customer: [TITLE]
- Customer account: [CUSTOMER]
- Function they owned: [FUNCTION]
</context>
<task>
1. Use Lusha to find current contacts at the customer matching the departed champion's function and seniority (4-6 candidates including one level up).
2. CROSS-VALIDATE each candidate against their individual record:
- Confirm current employer is still the customer
- Confirm current title and job start date
- Flag anyone who ALSO moved to a different company (company-side data may still list them at the customer)
3. For each verified candidate:
Name | Current title | Validated email | Direct dial | Tenure in role | Previous job | Inheritance likelihood (HIGH / MEDIUM / LOW based on scope, seniority, tenure)
4. If no clean candidate emerges in the function, surface the C-suite owner one level up as the re-engagement starting point.
</task>
<constraints>
- Cross-validation is the critical step. Company search may return contacts whose individual records show they moved on.
- Inheritance likelihood is a judgment based on scope, tenure, seniority — surface the reasoning
- Empty results are data, not failure
</constraints>See the full workflow with a live demo →
The pattern across all 10 prompts
The 10 prompts above cover three different CS workflows — watching the book, strategic growth, defensive moves — but share one structural pattern: the verified data layer is what makes them usable across a real customer portfolio. Generic AI prompts can summarize a customer’s news. These prompts return verified contacts at the customer, time-stamped signals tied to specific dates and source URLs, and cross-validated identity that catches the contact moves the company-side data hasn’t refreshed yet.
For CS teams specifically, the difference shows up in four measurable ways:
Verified data isn’t a nicety for CS. It’s the difference between a portfolio that holds and a portfolio that quietly bleeds.
- Renewal-risk catch rate rises when champion role changes surface in week 1 of the move, not at the renewal call
- Expansion conversion improves when the proposal lands inside the buyer’s actual budget window
- Multi-thread relationships become structural insurance rather than ad-hoc effort
- QBR quality rises when every meeting starts with a verified signal brief
Running all 10 in one chat
The 10 prompts above each solve one workflow well. For CSMs and AMs who want to run the full health workflow as one chat — book scan → expansion classification → renewal-risk classification → role-specific Gmail drafts for every action item — the Customer Health to Action Skill packages it into a single Claude Project install. The same scan that surfaces a customer’s expansion-ready triggers also surfaces the renewal risks, and drafts the role-specific outreach for both. (See the Skill →)
More in this series:
The 12 best Claude prompts for sales in 2026
