Marco Russo and Alberto Ferrari take us through a scenario:
Marketing campaigns drive sales, but not all sales can be directly attributed to a specific campaign. A customer might see a promotion and later purchase the product without using any discount code or campaign link. How do you measure this broader influence? This article presents data modeling and DAX measures to analyze campaign effectiveness by separating attributed sales (transactions for which we can clearly identify the one campaign that generated the sale) from influenced sales (all sales of products participating in one or more campaigns, regardless of whether the sale can be attributed to one exact campaign). The solution includes several measures using a many-to-many relationship between products and campaigns, combined with dynamic CROSSFILTER manipulation, to provide a complete view of the campaign’s impact.
Read on to see how you can use DAX capabilities to build attribution measures.