Cross-Channel Real-Time Response Analysis
Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Transfer
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Programmatic Advertising: The Successful Transformation to Automated, Data-Driven Marketing in Real-Time. ed. / Oliver Busch. Springer Verlag, 2016. p. 141-151.
Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Transfer
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TY - CHAP
T1 - Cross-Channel Real-Time Response Analysis
AU - Funk, Burkhardt
AU - Abou Nabout, Nadia
PY - 2016
Y1 - 2016
N2 - Programmatic Advertising allows advertisers to bid for single advertising impressions, i.e., each time a user visits a website advertisers can decide whether they would like to bid for the opportunity to being displayed to that specific user and at what price. Programmatic Advertising, which emerged around 2009, thereby comes with a huge amount of data that can be used for decision making purposes (e.g., bidding). This article will provide an overview of the two fundamental decision making fields in Programmatic Advertising: budget allocation across the media mix and micro decision making in Programmatic Advertising ad auctions at the individual user-level. In this article, we outline state of the art modeling techniques used in both decision making areas as well as the specific challenges faced by analysts when developing models. In addition, we present common heuristics used by practitioners and potential drawbacks related to the use of heuristics vs. statistical models.
AB - Programmatic Advertising allows advertisers to bid for single advertising impressions, i.e., each time a user visits a website advertisers can decide whether they would like to bid for the opportunity to being displayed to that specific user and at what price. Programmatic Advertising, which emerged around 2009, thereby comes with a huge amount of data that can be used for decision making purposes (e.g., bidding). This article will provide an overview of the two fundamental decision making fields in Programmatic Advertising: budget allocation across the media mix and micro decision making in Programmatic Advertising ad auctions at the individual user-level. In this article, we outline state of the art modeling techniques used in both decision making areas as well as the specific challenges faced by analysts when developing models. In addition, we present common heuristics used by practitioners and potential drawbacks related to the use of heuristics vs. statistical models.
KW - Business informatics
KW - Marketing
KW - Data Mining and Knowledge Discovery
KW - IT in Business
KW - Media Management
KW - Budget Allocation
KW - Bidding Strategy
KW - Media Channel
KW - Online Advertising
KW - Advertising Effectiveness
UR - http://link.springer.com/chapter/10.1007/978-3-319-25023-6_12
U2 - 10.1007/978-3-319-25023-6_12
DO - 10.1007/978-3-319-25023-6_12
M3 - Contributions to collected editions/anthologies
SN - 978-3-319-25021-2
SP - 141
EP - 151
BT - Programmatic Advertising
A2 - Busch, Oliver
PB - Springer Verlag
ER -