Revenue Booked per Rep per Week ($):
Track Sales Consistency

Sales can look “up” and still hide problems. In this lesson, you’ll learn how to break down booked revenue by rep and by week so you can spot top producers, identify inconsistency, and make forecasting decisions based on real performance trends, not gut feel.

Download the Excel file used in this tutorial:

Revenue Booked per Rep per Week ($)

1. Confirm the required fields in your dataset

  • Deal Status
  • Booked Revenue
  • Closed Week Start Date
  • Rep Name

2. Build the sorted list of week start dates

  • In a blank area, generate the list using a combined formula:
    • SORT(UNIQUE([Closed Week Start Date]))
  • Copy the results and paste values (Ctrl + C, then Ctrl + Shift + V)
  • Delete the zero row that appears due to blanks being treated as zeros
  • Keep the list ordered oldest to newest

3. Build the sorted list of sales reps and transpose it across the top

  • Generate the rep list with:
    • SORT(UNIQUE([Rep Name]))
  • Copy and paste values (Ctrl + C, then Ctrl + Shift + V)
  • Copy that vertical list again
  • Paste Special, then Transpose so rep names run left to right across the header row

4. Calculate weekly booked revenue by rep using SUMIFS

  • In the first data cell of the matrix, use SUMIFS to return booked revenue where:
    • Deal Status equals “Won”
    • Closed Week Start Date equals the week listed on that row
    • Rep Name equals the rep listed in that column
  • Format as currency (Ctrl + Shift + 4) and remove decimals if desired

5. Lock the references so the formula fills correctly

  • Adjust references so when you copy across and down:
    • The week reference stays locked to the week column when copying left to right
    • The rep reference stays locked to the rep row when copying down
  • Use dollar signs to control what moves vs what stays fixed
  • Do not rely on dragging if your table references behave weirdly
    • Copy the formula and paste across instead
    • Then double-click the fill handle to fill down

6. Add a Team Total column

  • Create a Team Total at the end of each week row
  • Use a simple SUM across all rep columns for that week
  • Double-click to fill down

7. Add a 4-week rolling average

  • Create a 4-Week Rolling Average column next to Team Total
  • Start the calculation on week 4
  • Use AVERAGE() across the prior four Team Total values
  • Fill down so it continuously rolls forward week by week

8. Apply conditional formatting to the rep-by-week grid

  • Select only the rep matrix (not the Team Total or Rolling Average)
  • Conditional Formatting → Color Scales
  • Choose a scale where high values are green and low values are red
  • This creates an instant heat map for rep consistency and performance

9. Build the chart: columns for Team Total and a line for the rolling average

  • Select only:
    • Week Start Date
    • Team Total
    • 4-Week Rolling Average
  • Insert → Recommended Charts
  • Choose a combo chart:
    • Team Total as columns
    • Rolling Average as a line
  • Apply a darker style if you want stronger contrast

10. Improve readability of the chart columns

  • Click a column series
  • Format Data Series
  • Add a solid border and increase line width (for example ~2.5 pt)
  • This makes the weekly bars easier to distinguish

11. Read the chart correctly

  • When the weekly column is above the rolling-average line, that week outperformed the last four-week average
  • When the column is below the line, performance dipped versus the recent baseline

Revenue Booked per Rep per Week ($) Reporting

Q1. What does “Revenue Booked per Rep per Week” mean?
It’s the total revenue that gets booked (won deals) each week, broken out by individual sales rep. It helps you see who is driving results and how consistent each rep is over time.

Q2. Why track booked revenue by week instead of just monthly sales?
Weekly tracking reveals patterns that monthly views can hide, like streaky performance, sudden dips, or momentum shifts. It’s one of the fastest ways to improve sales forecasting and coaching.

Q3. How does this help identify top performers vs inconsistent reps?
When you view revenue by rep and week, you can immediately see who produces consistently and who has big spikes followed by long gaps. That visibility makes it easier to support the team with targeted coaching and realistic goals.

Q4. What is a 4-week rolling average and why does it matter?
A 4-week rolling average smooths out weekly volatility and shows the true performance trend. It helps you compare this week’s results against a recent baseline so you can tell if the team is improving or slipping.

Q5. What’s the best way to visualize this KPI for leaders?
A clean weekly chart that shows total team booked revenue with the 4-week rolling average makes trends obvious. Many teams also add a rep-level view (like a heat map) to quickly spot standout reps and underperformance.

Q6. Where can I get the sample file used in the tutorial?
You can download the dataset from the link provided near the video. If you can’t find it, you can request it using the email shown in the lesson.

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Analysis & Development