Which action helps ensure pivot table results reflect non-campaign purchases by treating them as a separate campaign code?

• A. Filter out non-campaign purchases.
• B. Aggregate non-campaign data at the end of analysis.
• C. Assign a distinct 'None' campaign code to non-campaign purchases.
• D. Exclude non-campaign data from the dataset.

Answer: (C)

Categorizing purchases by campaign label in a pivot table to keep non-campaign purchases visible.

When you want pivot table results to show non-campaign purchases separately, you need a dedicated category for them in the campaign field. Assigning a distinct 'None' campaign code to non-campaign purchases creates a separate bin, so those transactions are counted and analyzed alongside actual campaigns. This preserves data visibility and enables direct comparisons, accurate totals, and meaningful metrics for both campaign-driven and non-campaign purchases.

Filtering out non-campaign purchases or excluding them from the dataset would hide those data points, while simply aggregating them at the end doesn’t place them in their own campaign category within the pivot structure. Excluding them from the dataset altogether also omits valuable information. The distinct 'None' code keeps everything in one analysis framework and supports proper attribution and reporting.