June 17, 2026 · 3 min read

Build a pivot table from any data with Crade

Pivot tables are powerful but unintuitive. Crade reads your raw data on screen and tells you exactly which fields to drag where, in plain language, for Excel or Sheets.

NumbersFileEditViewWindow
9:24
sales-2026-q2.numbers. Numbers
Σ$%
BI
Pivot
G3fx=SUMIFS(Revenue, Date, ">="&E3, Date, "<"&EDATE(E3,1), Region, F3)
Raw data
DateRegionRev
Apr 12EMEA14,200
Apr 18APAC8,700
Apr 24AMER21,300
May 03EMEA16,800
May 11AMER19,500
May 22APAC11,400
Jun 02EMEA17,900
Jun 09AMER24,600
Jun 14APAC9,800
Pivot. Revenue by month by region
MonthEMEAAPACAMERTotal
April14,2008,70021,30044,200
May16,80011,40019,50047,700
June17,9009,80024,60052,300
Total48,90029,90065,400144,200
New chat

Build me a pivot table that shows revenue by month by region, with totals.

Pivot setup for Numbers: Rows: Date (group by month) Columns: Region Values: Revenue (sum) In Numbers: 1. Click any cell in your data 2. Organize . Pivot Table . New Pivot Table 3. Drag Date to Rows, Region to Columns, Revenue to Values 4. Right-click the date column . Group by . Month Totals appear automatically in the rightmost column and bottom row.

Ask anything about your screen...
Crade

Pivot tables are the highest-leverage spreadsheet feature most people never learn. The reason is the UI: rows, columns, values, filters, and somehow you are supposed to know which goes where. Crade reads your data on screen and tells you exactly what to do for the report you want.

What you put on your screen

  • A spreadsheet with your raw data visible
  • Headers in the first row (Crade needs to see the column names)
  • At least one numeric column to aggregate, and at least one categorical column to break down by

What you say to Crade

Build me a pivot table that shows revenue by month by region, with totals.

Crade reads the columns on your screen and tells you which field goes in Rows, which in Columns, which in Values. For Excel and Sheets, the menu paths are similar but with different button labels.

Step-by-step

  1. Select your data range

    Click any cell in your data. For Sheets, the whole connected range is picked up automatically. For Excel, you can select the range explicitly.

  2. Ask Crade what the pivot should look like

    Describe in plain English: "Show me revenue grouped by month and region". Crade tells you the exact field assignments.

  3. Open the pivot insert dialog

    Sheets: Insert → Pivot Table. Excel: Insert → PivotTable. Crade tells you the exact menu path for your version.

  4. Drag fields per Crade's instructions

    "Drag Date to Rows, Region to Columns, Revenue to Values". Follow exactly. The pivot updates as you drag.

  5. Verify totals

    Check that the row totals and column totals match your expectation. If the numbers look wrong, paste back to Crade: "Total is too low, what is missing?". Often it is a sum filter or a date format issue.

  6. Adjust grouping

    For Date columns, ask Crade: "Group by month instead of day". Spreadsheet UI for this is buried; Crade gives you the exact menu path.

What you get back from Crade

Exact field assignments: which column goes in Rows, which in Columns, which in Values, and which aggregation (sum, average, count). Plus the menu path to open the pivot dialog for your specific tool and version.

Tips

  • Clean dates before pivoting. If your Date column has mixed formats, the pivot groups them weirdly. Ask Crade: "Are my dates consistent?" before pivoting.
  • For percentages, ask Crade to walk you through "Show Values As → Percent of Total". The Sheets/Excel UI for this is non-obvious.
  • Pivot charts: "Make me a pivot chart from this pivot table". Crade tells you how.
  • Filtering: "Add a slicer for Region" lets you toggle subsets without rebuilding.
  • If a pivot looks wrong, take a screenshot and ask Crade: "Why does this pivot have $0 in some cells?". Usually a sum filter, blank rows, or formula error.

Common pivots

  • Revenue by month by region (time-series breakdown)
  • Headcount by department by role (org reporting)
  • Customer count by acquisition channel (marketing)
  • Defect count by severity by sprint (engineering quality)
  • Conversion rate by campaign by week (growth)

The whole loop in one sentence

Raw data on screen, one plain question, exact field assignments back. Pivot tables go from "I do not know how to do this" to "three clicks and done".