How do I build a sales forecast with iDBQuery?

A sales forecast projects future revenue from your history. iDBQuery lets you produce a grounded, transparent forecast from your own data instead of a spreadsheet full of manual assumptions.

• You'd ask iDBQuery: 'Using monthly sales for the past 24 months, project the next two quarters by region, accounting for the seasonal pattern.'
• It measures the trend and recurring seasonality in your sales table, extends them forward, and returns a chart showing history plus the projected periods with a range.
• The forecast is grounded in cited source rows for the actuals, so stakeholders can see exactly what history the projection is built on.

iDBQuery is transparent about method: it shows the SQL and logic, so an analyst can adjust the window, exclude outlier months, or blend in a bottom-up pipeline view. You can also combine a trend forecast with your CRM pipeline: 'Compare the statistical forecast to weighted pipeline for next quarter.' Because sales history and pipeline live in different systems, the one live model brings them into a single answer with no ETL. Save the forecast as a live report so it re-runs on fresh data each week, and later compare it to actuals in the same thread. For deeper work, the Analyst agent can test a few forecasting approaches and report which best fits your recent history.