Estimates Run per Month Dashboard
(With Close Rate by Rep)

Learn how to turn your sales process into a measurable monthly system. In this lesson, you’ll build a month-by-month view of estimate volume, track how many estimates turn into wins, and spot performance patterns by sales rep and lead source so you can coach smarter and reallocate leads with confidence.

Download the Excel file used in this tutorial:

Estimates Run per Month and Rep Step by Step

1. Build the month list for the summary table

  • In a new sheet or section, type Month as a header.
  • Type January underneath it.
  • Drag the fill handle down until you reach December.
  • Center the month labels for readability.

2. Convert the dataset into an Excel Table

  • Click anywhere inside the raw dataset.
  • Press Ctrl + T and confirm the range has headers.
  • Rename the table to something easy to reference (example: TBL).
  • This lets you reference columns cleanly in formulas and keeps ranges dynamic as data grows.

3. Count estimates run by month

  • Create a column header called Estimates Run.
  • Use COUNTIFS to count rows where:
    • The Estimate Run Flag is TRUE
    • The Month equals the month label in your summary table (January, February, etc.)
  • Use table column references in the formula so the dataset expands automatically.
  • Copy the formula down for all months.

4. Count closed deals from those estimates by month

  • Create a column header called Closed.
  • Use COUNTIFS again, but this time count rows where:
    • Estimate Run Flag is TRUE
    • Sold Flag is TRUE
    • Month equals the month label in your summary table
  • Copy the formula down for all months.

5. Calculate close rate by month

  • Create a column header called Close Rate.
  • Divide Closed by Estimates Run for each month.
  • Format as percentage using Ctrl + Shift + 5.

6. Add a dynamic target close rate line

  • Create a single input cell for Target Close Rate (example: 45%).
  • Create a Target column next to Close Rate where each month references that single target cell (example: equals the target cell).
  • This makes the target line dynamic when you change the benchmark.

7. Build the combo chart with a target band line

  • Highlight Month and Estimates Run.
  • Hold Ctrl and also select:
    • Close Rate
    • Target
  • Insert a chart using Insert → Recommended Charts, then switch to Combo.
  • Set:
    • Estimates Run as clustered columns on the primary axis.
    • Close Rate as a line on the secondary axis.
    • Target as a line on the secondary axis.
  • If Close Rate shows as a column, change its chart type to Line.
  • Adjust chart title and sizing.
  • Add data labels only to the series you want to emphasize to avoid clutter.

8. Create unique lists for Lead Source and Sales Rep

  • In a new area, create a header for Lead Source.
  • Use a sorted unique list:
    • SORT(UNIQUE(TBL[Lead Source]))
  • Copy and paste values (Ctrl + Shift + V) to freeze the list if needed.
  • Repeat for Sales Rep Name:
    • SORT(UNIQUE(TBL[Sales Rep Name]))
  • Copy and paste values if needed.
  • Transpose the Sales Rep list so reps run across columns:
    • Copy the list, then Paste Special → Transpose.

9. Build the Estimates Run matrix by Rep and Lead Source

  • Set up a grid where:
    • Lead Sources are listed down the left side.
    • Sales Reps are across the top.
  • In the first cell of the grid, use COUNTIFS to count Estimate Run Flag = TRUE with criteria:
    • Sales Rep Name equals the rep header cell.
    • Lead Source equals the lead source row cell.
  • Fix references correctly so dragging works:
    • Lock the rep row when copying down.
    • Lock the lead source column when copying across.
  • Fill the formula across all reps and down all lead sources.

10. Build the Close Rate matrix with a minimum volume threshold

  • Create a second matrix for Close Rate.
  • Start with the same COUNTIFS logic, but now:
    • Numerator counts rows where Estimate Run Flag = TRUE and Sold Flag = TRUE.
    • Denominator counts rows where Estimate Run Flag = TRUE.
  • Divide numerator by denominator.
  • Wrap it in an IF statement so low-volume combinations show a dash:
    • If denominator is less than your threshold (example: 10), return “-”
    • Otherwise return the close rate calculation
  • Copy across and down to complete the matrix.
  • Format as percentage where values exist.

11. Add Overall Close Rate by Lead Source and by Rep

  • Create an Overall by Lead Source column:
    • Use the close rate formula but remove the Sales Rep criteria.
    • Keep Lead Source as the only grouping criteria.
  • Create an Overall by Rep row:
    • Use the close rate formula but remove the Lead Source criteria.
    • Keep Sales Rep as the only grouping criteria.
  • Format as percentage.

12. Add benchmark-based conditional formatting

  • Create a benchmark input cell (example: 45%).
  • Select the close rate matrix range.
  • Apply conditional formatting:
    • Highlight cells less than the benchmark value.
  • Add another conditional format rule:
    • If the cell contains “-” then fill it gray.
  • This makes underperforming areas stand out and removes noise from low-volume combinations.

Estimates Run per Month KPI Tracking

Q1. What does “Estimates Run per Month” mean?
It’s the total number of estimates your team delivers each month. This KPI helps you understand whether your reps are generating enough sales opportunities and moving leads forward in the pipeline.

Q2. Why is this KPI important for sales growth?
You can work a ton of leads and still stall if estimates are not being produced consistently or if they are not converting. Tracking estimate volume alongside close performance helps separate lead volume from execution.

Q3. What will I be able to see after building this dashboard?
You’ll be able to track monthly estimate runs, see how many were closed, monitor your close rate by month, and identify patterns by rep and lead source so you can pinpoint what is working and what needs attention.

Q4. How does this help with coaching sales reps?
It gives you objective data to coach from. For example, if one rep’s close rate is strong but estimate volume is low, they may need more leads. If estimate volume is high but close rate is weak, that is a coaching opportunity.

Q5. Why does the video include a “minimum count” idea (not enough data yet)?
When a rep or lead source has only a few estimates, the results can be misleading. Adding a minimum threshold helps you avoid overreacting and keeps the dashboard focused on trends backed by enough activity.

Q6. Can I use this approach to evaluate lead sources too?
Yes. By comparing results by lead source, you can see which channels produce enough estimate opportunities and which ones convert into closed deals, making it easier to adjust budget and lead allocation.

Q7. Will I need a complicated dataset to follow along?
No. Even though the sample file is detailed, the dashboard can be built from a small set of fields like month, lead source, rep name, estimate status, and sold status (plus dates).

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