| name | codexkit-cx-qbr-preparer |
| description | Prepare customer or executive business reviews with outcome tracking, adoption health, ROI narrative, risks, commitments, and next-quarter plan using customer success and CX frameworks. Use when teams need QBRs, success plans, churn-risk conversations, or executive account reviews. Do not use for generic slide beautification or cold outreach prospecting. |
| version | 1.0.0 |
| category | data |
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
- Start from the customer's goals, not your product features.
- Summarize what was committed last period and what actually happened.
- Quantify adoption health and value where evidence exists.
- Surface risks, open issues, and trust-sensitive misses honestly.
- Build the next-quarter success plan with mutual commitments.
- 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
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
