Marketing attribution models are designed to offer a data-driven way to tie spend to the conversion events – and, ultimately, the revenue dollars – that result from your marketing activities. Many companies develop a holistic attribution model that attempts to capture all of the touchpoints leading up to a conversion by including activity across all marketing channels. A holisitic model requires significant data investment – and typically includes data acquisition, cleaning and storage; statistical modeling; and serving the output into reports, dashboards and sometimes back into ad networks for campaign optimization.
For many years, the trend in marketing attribution has moved towards an ever-increasing effort to identify and track customers and prospective customers. Advertisers and advertising vendors alike tapped into cookies, pixels, mobile device identifiers and location data all in an effort to tie together browsing and shopping behavior across sites, devices, and even across the online / offline divide. This approach to attribution has all begun to unravel, however, with increasing consumer awareness of and discomfort with being tracked, the advent of GDPR and other privacy legislation and, more recently, changes by Apple designed to give individuals the ability to restrict how and when their digital activity is tracked.
However, despite these macro challenges, your teams still need to understand the ROI on your marketing spend. So how can your data team help?