Product Updates
clariBI Forecasting: backtested projections, prediction ranges and drivers
clariBI Forecasting projects a metric forward with a method chosen by backtest on your own history, shows 50, 80 and 95…
Blog
The clariBI blog
Articles on business metrics, reporting, forecasting and getting answers from the data in the tools you already use.
Featured
Product Updates
The clariBI MCP server: use clariBI from Claude, Cursor or ChatGPT
clariBI runs its own MCP server at claribi.com/mcp/v1/. Connect Claude Desktop, Cursor, ChatGPT or your own agent and i…
Comparisons & Evaluations
Picking your first BI tool as a 10-person startup
At ten people the spreadsheet that runs the company starts to crack. Four questions decide which BI tool fits: engineer…
Latest posts
Data Analytics
Spot data quality issues before they cost you
Most bad numbers come from five predictable problems: missing values, duplicates, stale data, wrong values and changed columns. Here is how to catch each one with simple checks before it reaches a dashboard or a decision.
Data Analytics
Revenue forecasting for subscription businesses
Subscription revenue should be easy to forecast because most of next month's revenue is already on the books. Most forecasts still miss because of optimistic assumptions. Here is a component model with a worked example, three scenarios and a monthly routine that keeps it honest.
Data Analytics
Data warehouses: what they are and when you need one
A data warehouse is a database built for analysis rather than for running an app. Here is what that means in practice, how ETL and ELT work, the signs a growing business needs one, and the cheaper options that are often enough first.
Data Analytics
Customer segmentation: RFM, behavioral and practical methods
A practical guide to customer segmentation for small and mid-size businesses: RFM scoring step by step, behavioral and value-based segments, the formulas behind them, and how to put the segments to work.
Business Intelligence
Self-service business intelligence: a practical guide for 2026
Self-service BI lets the people who ask the questions get the answers themselves, without a queue of report requests. This guide covers what it is, how to roll it out in four phases, which features matter in 2026 and how to keep the numbers trustworthy.
Data Analytics
Time series patterns in business data: trends, seasons and anomalies
Revenue, orders and signups all mix a long-term trend, repeating seasonal cycles and the occasional anomaly. Here is how to tell them apart with simple methods, worked examples in round numbers, and what each pattern means for your decisions.
AI & Machine Learning
How natural language analytics works, and where it fails
Asking your data a question in plain English works well for some questions and badly for others. Here is what happens between the question and the chart, the failure modes to watch for, and how to phrase questions that get reliable answers.
How-To Guides
How to build executive dashboards that actually get used
Most executive dashboards are opened twice and forgotten. Here is how to build one around the decisions your leadership makes, with the right number of metrics, honest comparisons and a clear owner.
AI & Machine Learning
AI reports: what to trust and what a person should review
AI can draft a business report from your data in the time it takes to get a coffee. Some parts of that draft are reliable, some need a quick check, and some should be rewritten by someone who knows the business. Here is how to tell them apart.
Data Analytics
Why real-time analytics is often overkill, and what you need instead
Streaming data pipelines are expensive to build and run, and most business decisions do not need them. A plain framework for deciding how fresh each metric has to be, what real-time really involves, and what to do instead for the few things that cannot wait.