Incrementality is about identifying the interaction that moves a user from passive to active and finally converting them. All the interactions that influence the actual outcome is identified as incremental.

Let us make it simple for you with a small example. Suppose you are a mother of a 10-year-old kid and you are seeing an ad of a particular health drink on Facebook very frequently. Sometimes you also see ads of the same health drink on YouTube, television, or in your favourite magazine. And one fine day you went to the supermarket, saw a pull-up banner of the same and bought it for you kid. Now as a marketer if you assign the entire credit to the last marketing interaction i.e. interaction with the pull-up banner then that will not be the most accurate measure. To get the accurate measurements you need to analyse all the various interaction points and attribute it to a specific interaction or set of interaction points without which that event wouldn’t have probably occurred and resulted in the desired outcome. This is nothing but Incrementality. For example: Say the Facebook ad which the mother saw very frequently in the above example could be the most important interaction.

Incrementality has great significance from a digital marketer’s perspective. It strives to identify the causal event of a conversion, allowing businesses to properly allocate budget and reduce wasted ad spend. It can identify the impact when a digital marketer chooses to stop spending on a particular channel or increase or decrease budgets for a particular channel very accurately. It also identifies if the ad creative is the key contributor to the desired outcome. Accurately identifying causality is a long-standing problem in data science and isn’t as simple as click or conversion optimization.