Attribution Modeling Task

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An Attribution Modeling Task is a modeling task that identifies a set of user actions which contribute to a given outcome, and then assigns of a value to each of them.



References

2022

  • (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Attribution_(marketing) Retrieved:2022-8-22.
    • In marketing, attribution, also known as multi-touch attribution, is the identification of a set of user actions ("events" or "touchpoints") that contribute to a desired outcome, and then the assignment of a value to each of these events.[1] [2] Marketing attribution provides a level of understanding of what combination of events in what particular order influence individuals to engage in a desired behavior, typically referred to as a conversion.[1][2]
  1. 1.0 1.1 Benjamin Dick (August 1, 2016). "Digital Attribution Primer 2.0" (PDF). IAB.com. Retrieved April 30, 2019.
  2. 2.0 2.1 Stephanie Miller (February 6, 2013). "Digital Marketing Attribution.Digital Marketing Attribution". DMNews.com. Retrieved March 25, 2013.

2016

  • (Kannan et al., 2016) ⇒ P. K . Kannan, Werner Reinartz, and Peter C. Verhoef. (2016). “The Path to Purchase and Attribution Modeling: Introduction to Special Section.” International Journal of Research in Marketing, 33(3).
    • ABSTRACT: Firms make significant marketing investments in online, mobile and offline media and channels such as search engines, social media, e-mail, display advertising, print, TV, etc., to draw in customers to their websites, mobile apps, and stores to effect conversions and spur sales. As customers go through a series of touch points across media, channels and devices on their paths to purchase, attributing the appropriate credit for each touch point has emerged as an important problem. By focusing on estimating the incremental value of a touch point and spillover effects across channels, attribution models can provide insights for allocating marketing investments across channels and targeting customers across channels and devices. In this paper, we provide a survey of the state-of-the-art in attribution modeling and analytics. As part of the survey, we also introduce the articles in this special section and position them in our classification framework. Finally, we propose a research agenda to guide future work in the area.

2011