Results for “productivity-analytics”

Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations. Use PROACTIVELY for business intelligence or strategic analysis.

Cleans datasets, detects anomalies, generates reports, and creates visualizations using pandas, scikit-learn, and plotting libraries to turn raw data into client-ready deliverables.

Define, track, and interpret product metrics across discovery, growth, and mature product stages using frameworks like AARRR, North Star, and HEART.

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.

The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" mentioned.

Product analytics planning for Nick's apps. Use when deciding what to track, setting up events, defining funnels, or making sure a product launch can measure activation, retention, and conversion instead of guessing.

Designs analytics architecture, plans events, defines KPIs, sets attribution boundaries, and reviews instrumentation across product and growth.

Applies quantitative and qualitative analysis techniques, interprets experimental data, validates procedures, and selects appropriate methods with uncertainty quantification.

Analyze sprint data with Python scripts for velocity forecasting, health scoring, and retrospective insights to coach agile teams.

Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.

Choose and audit startup metrics using the Lean Analytics framework: separate actionable metrics from vanity metrics, identify the One Metric That Matters for your business model and stage, set targets, and plan instrumentation.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Use this skill for any data or analytics task — querying databases, analyzing metrics, exploring data warehouses, processing datasets, or creating visualizations.

Design telemetry systems, define KPIs, analyze player behavior data, and set up dashboards for data-driven game design decisions. Use when instrumenting a game for analytics or interpreting player data. Also trigger for "game telemetry", "player analytics", "game metrics", "KPIs", "player retention", "funnel analysis", or "player behavior".

Guide through a structured data analysis workflow: define the question, validate data quality, select the appropriate analytical method, and produce decision-ready findings with caveats.

Implement AI chatbot analytics and conversation monitoring. Use when adding conversation metrics, tracking AI usage, measuring user engagement with chat, or building conversation dashboards. Activates for AI analytics, token tracking, conversation categorization, and chat performance.

Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization.

Inspect, profile, clean, reconcile, analyze, visualize, and verify spreadsheet data while preserving formulas, formatting, types, and source files. Use when working with .xlsx, .xlsm, .xls, .ods, .csv, or .tsv files; answering questions from a workbook; auditing formulas or data quality; comparing sheets or versions; producing pivots, charts, forecasts, or summary workbooks; repairing malformed tables; or validating that spreadsheet edits and calculations are accurate.

Read-only audit of product-analytics instrumentation: event taxonomy, funnel completeness, consent-gated firing, dead/duplicate/phantom events. Use when "audit our analytics", "are we tracking the right events", "funnel instrumentation", or before iterate-post-launch. PostHog/Amplitude/Mixpanel/GA4.

Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.

Analiza datasets con Pandas y NumPy: explora distribuciones, correlaciones y patrones, y aplica tests de hipótesis para extraer conocimiento no obvio.

Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization.

Analyze datasets to answer defined questions through statistical methods, trend identification, hypothesis testing, and correlation analysis. Use when the user needs evidence-backed findings or decisions from data; use exploratory-data-analysis instead for open-ended first-pass profiling before questions are defined.