Data

Designs marketplace fee structures with commission models, premium tiers, and competitive analysis. Use when setting or restructuring pricing for a platform business.

Defines and tracks marketplace health metrics including liquidity, take rate, GMV, and supply/demand balance. Use when measuring and optimizing marketplace performance.

Creates board meeting packets with agenda, financial summaries, program updates, and vote items for nonprofit governance.

Organizes and documents reusable prompt libraries with categories, variables, and quality scoring. Use when building a structured collection of AI prompts for your business.

Sets up SaaS metrics dashboards tracking MRR, churn, LTV, CAC, expansion revenue, and cohort retention. Use when building or improving subscription business analytics.

Use when building or debugging a complex Excel/Google Sheets formula — XLOOKUP, INDEX/MATCH, array formulas, conditional logic. Knows when to write a formula and when to admit it's time for a script.

Use when handed a CSV and asked "what's in this?" — the diagnostic pass before any analysis. Schema discovery, distribution checks, anomaly hunting. The 15-minute investigation that prevents days of wrong conclusions.

Writes grant progress and final reports with metric tracking, narrative updates, and financial accounting.

Creates annual impact reports with metric visualization, beneficiary stories, and donor recognition sections.

Designs social impact measurement frameworks with indicators, data collection methods, and reporting templates.

Analyzes customer feedback data to identify themes, sentiment patterns, and actionable improvement priorities for product and service decisions.

Use when turning a query result, chart, or dashboard into a written narrative for a human audience. Applies the "so what" test, leads with the headline, and explains surprises without hand-waving.

Use when analyzing an A/B test result — power, p-values, Bayesian alternatives, segment analysis, when to call it. Tells you what the data actually supports, not what the PM wants to hear.

Use when running cohort analysis for retention, revenue, or behavior. Defines cohorts precisely, reads the triangle correctly, and calls out the common misreads that make execs draw wrong conclusions.

Sets up KPI tracking dashboards in Notion with metrics, targets, status indicators, and trend tracking for any business type. Use when a user wants to track business performance, needs a visual dashboard for key metrics, or wants to replace scattered spreadsheets with a centralized KPI view.

Use when a company can't agree what a metric means — DAU, conversion, revenue, churn. Writes the definition, names the edge cases, and sets up governance so the argument doesn't restart in three months.

Designs A/B test plans with hypothesis, variants, sample size calculations, success metrics, and statistical significance criteria. Use when optimizing conversions or UX.

Plans web analytics implementation with event tracking, goals, conversion setup, and dashboard configuration. Use when setting up Google Analytics or similar tools from scratch.

Designs marketing attribution models with channel mapping, weighting logic, reporting recommendations, and implementation steps. Use when understanding which channels drive conversions.

Creates industry benchmarking reports comparing business metrics against standards and best-in-class performers. Use when evaluating where your business stands versus peers.

Creates cohort analysis frameworks for understanding retention, revenue, and behavior patterns over time. Use when measuring how user groups perform across their lifecycle.

Maps and analyzes conversion funnels with drop-off identification, optimization priorities, and benchmarking. Use when diagnosing where prospects are lost in your sales process.

Calculates customer lifetime value with segmentation, prediction models, and retention investment recommendations. Use when determining how much a customer is worth over time.

Plans data collection strategies with tracking requirements, privacy compliance, storage recommendations, and implementation steps. Use when building your business data infrastructure.

Plans data dashboard layouts with metric selection, visualization types, refresh frequency, and user-focused design. Use when building dashboards that drive decisions.

Creates metric glossaries defining how each business KPI is calculated, tracked, and interpreted with formulas, data sources, and ownership. Use for team alignment on numbers.

Analyzes customer sentiment from reviews, social media, and support tickets with trend tracking, theme categorization, and alert recommendations. Use for brand health monitoring.

Analyzes survey results with statistical summaries, cross-tabulations, trend identification, and actionable insight recommendations. Use when interpreting survey data for decisions.

Use when a CSV, Excel sheet, or database table is messy — junk rows, mixed types, duplicates, dates as strings, the works. Diagnoses first, fixes second, and never silently throws away data.

Use when writing or debugging SQL — joins, CTEs, window functions, query plans, denormalization decisions. Answers like someone who has owned a warehouse, not someone reciting a textbook.

Use when a SQL query is too slow and you need to make it fast. Reads EXPLAIN, designs indexes, and follows the first-principles debugging order — not the "throw indexes at it" approach.

Use when picking the right chart for a finding. Bar vs line vs scatter vs heatmap — when each works, when each lies. Calls out charts that mislead and offers the honest alternative.

Use when designing or fixing an ETL/ELT pipeline. Idempotency, backfills, schema drift, monitoring. The pragmatic patterns that keep pipelines alive — and the gotchas that page you at 3 AM.

Use when designing a dashboard for execs or operators. Picks the 5 metrics that matter, lays them out so the answer is obvious in 10 seconds, and refuses to build the "every chart at once" dashboard.