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Media channel lift or incrementality can be measured or approximated in a number of ways.
Design of Experiments (DoE) creates an experiment which systematically withholds media channel exposure to a representative subset of customers (the control group) while maintaining normal media channel exposure to the broader customer set (the test group). If the control group is both sizable enough to be statistically significant and selected at random such that they are broadly representative of the customer base, then the media channel lift can be determined by the difference in business outcome (conversion, revenue, profitability, etc.) between the test and control groups.
Media mix modeling (MMM) collects aggregated data across marketing and non-marketing factors over a multi-year historical period. That data is used to develop a demand model which quantifies the historical contribution of each marketing and non-marketing input to business outcome. MMM typically estimates marketing impact on historical business outcomes at the channel level.
Multi-Touch Attribution (MTA) collects cookie-level data for trackable addressable media and conversion events in order to determine the impact of each trackable event on the conversion path at the customer level. By summing the impact of each trackable addressable media on each customers’ likelihood to convert, MTA quantifies the total media channel lift provided by all said trackable addressable media.