Best for
- Marketers who need ad hoc answers from exported data
- Teams without analyst capacity for every small question
- Operators who want reproducible analysis rather than chatbot guesses about spreadsheets
Give Claude Code a documented marketing dataset and a set of business definitions, then let marketers ask plain-language questions while the system shows its calculations, filters, source columns, and uncertainty.
A governed natural-language analysis workflow with a field dictionary, tested question set, reproducible calculations, source traceability, and human review for consequential interpretations.
Quick view
Check the audience, core tools, and access before you start the detailed steps.
Best for
Core tools
2 tools used across the workflow.
Access
Preview the open steps, then unlock the remaining implementation details and prompts.
Why this works
Natural-language analysis is useful when the model is required to inspect a documented dataset and expose the transformations behind the answer. This workflow makes metric definitions, filters, calculations, and validation visible so ease of asking a question does not come at the cost of analytical traceability.
Expected results
Traceability
Every answer has a saved analysis artifact
Plain-language summaries remain reproducible and inspectable.
Ambiguity handling
Undefined metrics and filters trigger clarification
The system does not quietly choose a definition simply to produce an answer.
Reusable knowledge
Validated question patterns become templates
Common analyses get faster without losing the checks that made them trustworthy.
Step-by-step workflow
The first 2 steps are open. Pro unlocks the remaining steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and implementation details.
60 min
60 min
Create a field dictionary with column name, definition, data type, grain, source, allowed values, null meaning, timezone, currency, and owner. Write the approved formulas for business metrics such as qualified conversion, pipeline, CAC, or opportunity stage rather than letting Claude infer them from column names. Review five random rows and several edge cases to confirm the dictionary matches the data. The gate is a dataset another analyst could interpret without tribal knowledge.
A field dictionary and approved metric-definition sheet.
A column named “revenue” is not self-explanatory. Define whether it means booked, invoiced, attributed, forecast, or something else.
45 min
45 min
Give Claude Code access only to the approved dataset files and documentation in a dedicated workspace. Require generated analysis files or scripts to be written separately from the source dataset. Add a run folder containing question, timestamp, input version, code or formulas used, and output. Test that the workflow refuses or clearly fails when a required column is missing rather than silently substituting another field.
A read-only analysis workspace with reproducible run folders.
Never let convenience turn the analysis workspace into a place that edits the source-of-truth spreadsheet.
Pro workflow preview
Previewing 2 of 6 steps
Get the remaining 4 steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and ongoing workflow and prompt releases.
$9/month
Related workflows
Continue with workflows that share a similar GTM motion, category, or tool stack.
A daily account-manager briefing with client performance flags, relevant emails, CRM context, public news, open commitments, confidence, and a prioritized action list.
A low-noise paid-media monitoring system with normalized metrics, baseline ranges, data-quality checks, anomaly severity, diagnostic context, and human-reviewed Slack alerts.
A multi-surface competitor signal system with source baselines, change detection, materiality rules, cross-signal synthesis, Slack routing, and human-verified intelligence.