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Every quarter, your CSMs and AEs face the same problem: pulling together a QBR brief for each customer takes hours per account. ARR comes from CRM. Engagement trends come from calls. Risk signals are scattered across email and Slack. By the time prep is done, half the team is walking into QBRs underprepared and important signals get missed. QBR Preparation auto-generates a complete brief for every customer QBR on the calendar — pulled from every source, delivered where your team works.

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Data Sources

CategoryRequiredRecommended
CRM✓
Calls✓
Email + Calendar✓
Messaging✓
Starter (required only): a useful brief covering ARR, account record, deal history, and engagement themes from recent calls. Full (required + recommended): the same brief, plus important context such as email patterns, calendar engagement, and any Slack activity from your team or shared customer channels. Same workflow — significantly more depth. See the Customer Context Graph for how each source feeds the brief.

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Choose your path

PathBest forOutput is delivered
Build in ClearskiesTeams whose daily surface is SlackTo Slack DMs or channels (today)
Build in Claude or ChatGPTTeams whose daily surface is Claude or ChatGPT, or RevOps testing before deployIn the Claude or ChatGPT conversation

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Build in Clearskies

For teams whose daily surface is Slack. Build the workflow once in the Clearskies app and every customer QBR comes with a complete brief — delivered to Slack, no manual assembly.

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The Workflow

In the Clearskies app, open the workflow builder and describe what you want in plain language: 
Every Sunday, generate a QBR brief for each customer with a QBR
coming up in the next week, using the Clearskies Context Graph.
Cover customer overview, ARR and usage trends, engagement themes
from calls and emails, risk signals, expansion opportunities, and
a recommended agenda. Post the brief to the account owner's Slack
DM seven days before the QBR.
The app configures the trigger (weekly scheduled scan), the data pulled (your connected sources), and the destination (per-rep Slack DM, a team channel, or both with the CSM cc’d). Review and refine before deploying.

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Deploy to Slack

Once deployed, the account owner sees this in their Slack DM seven days before each customer QBR: 
QBR Prep — Acme Corp
Scheduled QBR: May 25 (7 days)
Account owner: @daniel · CSM: @jenna

Customer overview
B2B logistics platform, 800 employees, San Mateo. Customer since
Q3 2024. Current ARR $180K on the core platform.

ARR and usage
ARR flat YoY. Active users grew 14% this quarter. Reporting feature
adoption still below benchmark (28% MAU vs. 60% average for cohort).

Engagement trends
6 calls in the quarter, healthy attendance throughout. Sentiment
trended more cautious in May after legal raised data retention
concerns on the May 6 call. Champion Sarah Kim remains highly
engaged.

Risk signals
Economic buyer (Mark Chen, VP Sales) quiet for 9 days. New stakeholder
David Park joined Acme 3 weeks ago — not in CRM. Legal questions on
data residency unresolved.

Expansion opportunities
Active conversation on the analytics module ($90K). Sarah has
internally championed but procurement may want a security review. A
30-day pilot path discussed but not committed.

Recommended agenda
1. Acknowledge usage growth; dig into the reporting adoption gap.
2. Get David Park's view on the analytics module expansion.
3. Address legal and security questions to clear the path.
4. Confirm Mark Chen's alignment on the Q3 roadmap.

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Customize the rollout

  • Match the brief sections to your team’s QBR template (account health, business review, success criteria, account plan)
  • Choose recipients (account owner DM, manager cc, CSM team channel)
  • Adjust the cadence (weekly scan for upcoming QBRs, monthly preview, on-demand only)
  • Tailor the depth and tone (internal QBR vs. external QBR)

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Build in Claude or ChatGPT

For teams whose daily surface is Claude or ChatGPT — sales leaders working in either, or RevOps testing the workflow before deploying it to the team. Output appears in your conversation.

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The Prompt

Open Claude or ChatGPT with the Clearskies MCP connected and paste this (or modify to your needs). Replace the account name with your own. 
Using the Clearskies Context Graph, prep me for the QBR with Acme.

Cover:
- Customer overview — what they do, since when, current ARR
- ARR and usage trends this quarter
- Engagement themes from calls and emails
- Risk signals — stakeholder changes, unresolved threads, sentiment shifts
- Expansion opportunities — what's in motion, what's possible

End with a recommended agenda for the meeting.

Be direct. Flag anything that needs leadership attention before the QBR.
Claude or ChatGPT returns a brief structured like the Slack example above, generated from your data and formatted as a chat response. Refine the prompt to fit how your team works QBRs.

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Make it yours

  • Add Focus on internal QBR — prep me to present this account to leadership to shift the audience from customer to executive.
  • Add Compare to last quarter's QBR — what changed? to surface trends across reviews.
  • Add Draft talking points I can use in the QBR opening to chain prep with delivery.

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The Skill (Claude)

The clearskies:qbr-prep skill in the Clearskies plugin for Claude runs the same workflow on demand: customer overview, ARR and usage trends, engagement themes, risk signals, expansion opportunities, and a recommended agenda — all from your Context Graph.

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Trigger phrases

  • “Prep me for the [account] QBR”
  • “QBR prep for [account]”
  • “Generate a QBR brief on [account]“

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Customize it for your team

  • Match the brief sections to your team’s standard QBR template
  • Adjust depth based on internal vs. external QBR
  • Layer in success metrics specific to your account scoring framework
Want this packaged for your team? Reach out and we’ll help you customize the skill to your workflow.

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The Plugin

Ready to make this part of your team’s workflow? We’ll set up the Clearskies plugin with you — Clearskies workflows, Claude skills, all tailored to how your team works. Book 15 minutes →

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Next steps

  1. Sign in to Clearskies
  2. Connect your data sources
  3. Get your Clearskies MCP server and try with Claude or ChatGPT