Embedded Files
Summary
Summary
This logic calculates how much a campaign has spent so far in the current calendar month and compares it to the expected spend for the same period. It helps monitor whether a campaign is pacing correctly within a single month, regardless of its total flight duration.
This approach is especially useful for monthly reporting cycles and identifying short-term over- or under-delivery.
Please see below for benefits and implementation steps.
Benefits
Benefits
Tracks in-month performance against budget expectations.
Enables timely adjustments for campaigns with monthly goals.
Useful for monthly reporting and billing alignment.
Easy to interpret and present in client-facing dashboards.
Implementation
Implementation
Step 1
Step 1
Navigate to Data in the left navigation then choose Calculation and press the + button to create a new calculated field.
You will need to create the following fields:
Current Month Spend
Current Month Expected Spend
Current Month Pacing (%)
Step 2
Step 2
Use the following logic in calculated fields:
Current Month Pacing (%)
(Current_Month_Spend / Current_Month_Expected_Spend) * 100
*Ensure that “Per_Day_Budget” is already calculated as:
Budget / (Stop_Date - Start_Date + 1)
Current Month Spend
IF Date >= FIRST_DAY(CURRENT_DATE()) THEN Spend ELSE 0
Current Month Expected Spend
IF Stop_Date >= CURRENT_DATE()
THEN (CURRENT_DATE() - FIRST_DAY(CURRENT_DATE())) * Per_Day_Budget
ELSE (Stop_Date - FIRST_DAY(CURRENT_DATE()) + 1) * Per_Day_Budget
Step 3
Step 3
Test the calculations and save each one by pressing the button at the bottom of the page.
Step 4
Step 4
Add the new calculation dimension to your dashboard widgets and reports.
There is often more than one way to solve a problem in the Tapclicks platform, so it's important to consider how each one could impact the performance of your instance. Here are some key points to keep in mind:
Advanced calculations: While powerful, advanced calculations can slow performance with large datasets. Use simpler calculations when possible and reserve advanced ones for when necessary to maintain efficiency.
Limit CASE statements: Keep CASE statements to 10 branches or fewer. Larger ones can slow processing, so simplify or break them into smaller segments for better performance.
Data lookups for large conditions: For complex conditions, consider using data lookups from external sources like Google Sheets to simplify logic and improve performance.
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