CX QBR Preparer

Purpose

Build a review pack that turns account data into a value and renewal conversation.

When to use

• A customer QBR or executive account review is coming up.
• A team needs a structured success-plan update.
• An account shows renewal or adoption risk and needs a focused conversation.

When not to use

• The task is only to polish slide visuals.
• The request is for prospecting or pre-sales outreach.

Inputs

• customer goals, stakeholders, and prior commitments
• adoption, usage, support, and ROI signals
• open risks, blockers, roadmap relevance, and renewal context
• audience and meeting objective

Procedure

1. Start from the customer's goals, not your product features.
2. Summarize what was committed last period and what actually happened.
3. Quantify adoption health and value where evidence exists.
4. Surface risks, open issues, and trust-sensitive misses honestly.
5. Build the next-quarter success plan with mutual commitments.
6. End with the decisions or asks needed from both sides.

Output

• QBR agenda and story arc
• results against commitments
• adoption and ROI narrative
• risk and open-issue summary
• next-quarter plan with owners and dates

Definition of done

• The review is anchored in customer outcomes.
• Risks and misses are visible, not buried.
• The next-quarter plan has mutual commitments and follow-up actions.

Examples

• "Prepare a QBR for this enterprise customer using usage, support, and renewal notes."
• "Turn our account health data into an executive review pack with risks and next-quarter commitments."

Quality Criteria

• Data sources and assumptions are explicitly stated
• Calculations are reproducible from provided inputs
• Visualizations or tables have clear labels, units, and time ranges
• Caveats and confidence levels are documented for estimates

Verification (4C)

Check	Question
Correctness	Are formulas, aggregations, and statistical methods applied correctly?
Completeness	Does the analysis cover all requested metrics and time ranges?
Context-fit	Are the chosen metrics relevant to the business question being answered?
Consequence	If this data were used for a decision today, what blind spots remain?

Edge Cases

• Missing or incomplete data — Document gaps and their potential impact on conclusions. Provide ranges instead of point estimates.
• Outliers skewing results — Report with and without outliers. Document the decision to include or exclude.
• Changing data definitions mid-period — Split analysis at the change boundary and note the schema difference.

Changelog

• v1.0.0 — Initial release