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Summary
Summary
This calculation is designed to measure the percentage change between two date ranges in your dashboards and reports. The logic compares values across the selected periods, allowing you to quickly identify increases, declines, or trends over time.
This logic works only with date ranges that can be selected in the platform and does not support mismatched or custom-length comparisons outside those options. It’s ideal for standard period-over-period analysis such as week-over-week or month-over-month comparisons. This ensures that time-based insights remain consistent, reliable, and actionable.
Please see below for benefits and implementation steps.
Benefits
Benefits
Calculate % change between two date ranges
Compare totals across selected date ranges
Ensure consistent, reliable trend reporting across dashboards
Add values for specific date ranges when needed
Implementation
Below is a simple workflow that allows you to compare two time periods and calculate the difference and percent change between them. This method uses TapClicks’ Compare with Previous Date Range option and an Email Smart Connector.
Implementation
Below is a simple workflow that allows you to compare two time periods and calculate the difference and percent change between them. This method uses TapClicks’ Compare with Previous Date Range option and an Email Smart Connector.
Step 1 - Set Up Your Dashboard
Step 1 - Set Up Your Dashboard
Create a dashboard with a single widget and enable Compare with Previous Date Range in the date filter.
Make sure the fields you want to analyze are included in the Group By section.
These groupings will be used later for mapping and assignment inside the Smart Connector.
Step 2 - Create a Scheduled Report
Step 2 - Create a Scheduled Report
Set up a scheduled report with the following settings:
Attachment: Excel or CSV
Dashboard: Select the dashboard created in Step 1
Date Range: Choose the time period that best fits the user’s needs
Note: The comparison is limited to the date range and its automatically matched “previous” period. TapClicks cannot compare two unrelated custom ranges.
Step 3 - Review the Exported CSV
Step 3 - Review the Exported CSV
The exported CSV will contain two columns for your metric values:
Previous (P) — the earlier period
Current (C) — the selected date range
These two columns form the basis for your calculations.
Step 4 - Create an Email Smart Connector
Step 4 - Create an Email Smart Connector
Use the scheduled report’s CSV as the data source when setting up a new Email Smart Connector.
This imports the previous and current values back into TapClicks as usable fields.
Step 5 - Map Your Assignment Fields
Step 5 - Map Your Assignment Fields
Inside the Smart Connector, select the field(s) you want to use for assignment or mapping, typically the same fields you included in the dashboard Group By.
This ensures your data aligns correctly when displayed.
Step 6 - Verify the Two Date Range Fields
Step 6 - Verify the Two Date Range Fields
You should now see two separate fields in your Smart Connector dataset:
Current (C)
Previous (P)
These represent the two periods you are comparing.
Step 7 - Create Your Advanced Calculations
Step 7 - Create Your Advanced Calculations
Use Advanced Calculations to measure the changes between the two time periods.
A. Difference (absolute change) C - P
B. Percent Change (C - P) * 100 / P
These formulas will allow you to show increases, decreases, and performance trends clearly in any widget or report.
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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