The Normalised Date Comparison feature allows users to compare data across time periods on an equal, like-for-like basis. This is especially important when the comparison period differs in length from your selected reporting period.
Bright Analytics offers two ways to compare performance across varied date comparison periods:
Summation Performance – This shows the total performance over the full extent of each period.
Useful when you want to understand the actual total spend or delivery that occurred in each time frame, even if the periods differ in length.
Normalised Performance – This adjusts the comparison period so that it matches the length of your selected period.
Useful when you want a fair, like-for-like comparison that removes differences caused purely by calendar length.
How it works:
Imagine you want to report on spend for the previous week and compare it to spend over the last 8 weeks.
The system first calculates the average daily spend for the comparison period:
Last 8 weeks = 56 days (8 × 7)
Total spend over 56 days is divided by 56 to produce a daily spend rate.
That daily rate is then multiplied by the number of days in your primary date range (in this case, 7 days).
The result is a normalised spend figure that represents what the comparison period would look like over a matching length of time.
This ensures the comparison is based on equal time periods, independent of how long each date range originally was.
This feature also works with multiple comparison periods, applying the same normalisation method to each one.
Summation performance over the last 8 weeks:
Normalised performance over the last 8 weeks:
How to enable Normalised Comparison:
Open the report builder and navigate to "Date Comparison' tab.
Tick the Normalisation comparison time-basis box
