Using a variety of data sources, FD can accurately measure the effectiveness and impact of marketing campaigns.
Attribution models determine which marketing channel gets credit for a given conversation. Attribution models can be rule-based (i.e. last click) or based on statistical models. By default, FD uses statistical models to determine the impact of campaigns on sales. In the absence of a deterministic identifier, probabilistic attribution models are used as a fallback option to understand campaign efficiency and impact. We do not use statistical modelling to attribute conversions to individual customers or users.
To increase accuracy, these models rely on a variety of data sources. In addition to traditional tracking data from pixels (Google Analytics or Metas Pixel or other), our probabilistic attribution models incorporate campaign insights (e.g. how many clicks per hour), but crucially also sales data from ticketing systems. This last part is the key differentiator that most other attribution solutions lack due to lack of integration.
While in the past the de facto standard in the advertising industry was deterministic attribution (counting how many times a page was visited), this is no longer technically possible/allowed by major platforms and operating systems such as Apple's iOS/iPadOS, and more and more browsers have adopted these changes. Companies like Meta and Google have updated their methods accordingly to be probabilistic. This means that they also rely on statistical models to measure how many people bought something.
Our attribution model takes other external factors into account. These include general market trends, changes in national buying sentiment of ticket buyers, changes in demand for other events in similar sales cycles of each promoter, but also known patterns of other marketing events and external 'shocks' (e.g. email marketing campaigns, press publications).
It also includes insights from fans' price sensitivity and changes in average price points to account for available discounts.
Combining all those factors gives a reliable insights into campaign efficiency and effect on sales.