Expert insights on business intelligence, data analytics, and AI-powered decision making for modern businesses.
The four questions that determine which BI tool fits a 10-person company, and what to skip until yo…
A minute-by-minute walkthrough of the first five minutes of a clariBI trial — connect one source, a…
A plain-English introduction to the Model Context Protocol — what it is, why it changes how AI tool…
A practical guide to running weekly business reviews that drive action. Covers agenda design, metric selection, pre-read preparation, and follow-up accountability so your reviews stop being status updates.
A practical comparison of self-service BI tools and traditional analyst-driven reporting. Covers when each approach works, how to evaluate the trade-offs, and how to run both models together.
A detailed playbook for creating a single source of truth for your business data. Covers metric governance, data modeling, tool selection, organizational buy-in, and maintaining trust over time.
A practical evaluation framework for choosing BI tools at the 50-person company stage. Covers the criteria that matter, common traps, total cost of ownership, and how to run a meaningful trial.
How to present data findings to executives, clients, and colleagues who do not speak analytics. Covers chart selection, narrative structure, common mistakes, and techniques for making numbers memorable.
A hands-on guide to cohort analysis for subscription and e-commerce businesses. Covers cohort construction, retention curves, revenue cohorts, behavioral cohorts, and interpreting the results.
CAC is more nuanced than total spend divided by total customers. Learn how to calculate blended and channel-specific CAC, account for time lag, handle organic attribution, and use CAC to make real budget decisions.
A step-by-step guide to building and analyzing e-commerce conversion funnels. Covers funnel construction, drop-off diagnosis, segmented analysis, and practical optimization strategies for each stage.
A practical guide to identifying and preventing data quality problems. Covers the most common data quality issues, automated checks you should implement, and how to build a data quality monitoring habit.
A practical guide to building revenue forecasts for SaaS and subscription companies. Covers MRR-based forecasting, churn assumptions, expansion modeling, scenario planning, and common forecasting mistakes.