data-export

Installation
SKILL.md

/dm:data-export

Purpose

Export marketing data — metrics, contacts, campaign results, and performance snapshots — to an external data store for analysis, reporting, or integration with other tools. Supports BigQuery for data warehousing and advanced analytics, Google Sheets for sharing and collaboration with stakeholders, and Supabase for custom database use and application integration. Transforms raw marketing data into clean, structured, tabular formats ready for downstream consumption with full schema documentation. Handles PII redaction when exporting contact data to shared destinations, ensuring compliance with privacy regulations.

Use this command to move data out of the marketing system for external analysis, client reporting, or data warehouse integration. For exporting audience segments specifically, use /dm:segment-audience to create the segment first, then this command to export the member data.

Input Required

The user must provide (or will be prompted for):

  • Data type: What to export — metrics (KPIs, channel performance, funnel metrics), contacts (CRM records, segments, lead lists), campaigns (structure, settings, targeting, creative), performance (daily/weekly snapshots, trend data, year-over-year comparisons), or custom query (specific fields and filters defined by the user)
  • Destination: Where to export — BigQuery (project, dataset, and table name), Google Sheets (existing spreadsheet ID or create new with specified name), or Supabase (project reference, schema, and table name)
  • Date range: Time period for the export — specific start and end dates, relative window (last 7/30/90/365 days), quarter-to-date, year-to-date, or all available historical data
  • Filters (optional): Criteria to narrow the export — specific channels, campaigns, audience segments, geographic markets, device types, performance thresholds (e.g., only campaigns with ROAS above 2.0), or custom field values
  • Format preferences: Column ordering priority (dimensions first or metrics first), naming conventions (snake_case, camelCase, Title Case), date format (ISO 8601, MM/DD/YYYY, YYYY-MM-DD), currency formatting (symbol, code, decimal places), timezone for timestamps, and whether to include calculated fields (percentages, ratios, period-over-period deltas)
  • Append or replace: Whether to append new data to existing destination table/sheet or replace the entire contents — critical for recurring exports where append prevents data duplication while replace ensures a clean snapshot
  • Schema preferences (optional): Custom column definitions, data types, or transformations — e.g., "split full name into first_name and last_name", "convert all currencies to USD", "aggregate daily data to weekly", or "pivot channels into columns"
Related skills
Installs
31
GitHub Stars
100
First Seen
Feb 27, 2026