Abstract: Attribution in digital marketing is the task of assigning the credit due to each marketing interaction toward a marketing outcome. Such information helps the brand decide on marketing strategies for the future. In web analytics, attribution goes beyond marketing channels, and can be performed across a broad range of dimensions (e.g. images displayed on a website). This requires attribution algorithms to operate on dimensions with a large number of dimensional elements (hundreds of thousands in the extreme). Additionally, given the many possible metrics a marketer may be interested in, it is infeasible to perform ahead of time computation for all combinations. In this work, we propose a game theoretic attribution model that can be computed at query-time. Our demo of Attribution IQ runs in the Adobe Analytics production system. Our system is highly scalable (it operates on millions of customer journeys), interactive (the user can change the parameters and get updated results instantaneously) and requires no pre-computation (all computation being performed at query time). We demonstrate the effectiveness of Attribution IQ on real-world e-commerce web analytics datasets.