User Interaction with Online Advertisements
| Autor: | Carla Chiasserini, Emilio Leonardi, Luca Vassio, Michele Garetto |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer Networks and Communications
Computer science 0102 computer and information sciences 02 engineering and technology Recommender system 01 natural sciences ads placement CTR Online advertisements recommendation systems user behaviour Advertising campaign 020204 information systems 0202 electrical engineering electronic engineering information engineering Media Technology Computer Science (miscellaneous) Targeted advertising Revenue Safety Risk Reliability and Quality Focus (computing) theoretical models Unit of time Advertising filtering performance evaluation System dynamics 010201 computation theory & mathematics Hardware and Architecture Metric (mathematics) Recommendation systems performance evaluation filtering theoretical models Software Information Systems |
| Zdroj: | ACM Transactions on Modeling and Performance Evaluation of Computing Systems. 5:1-26 |
| ISSN: | 2376-3647 2376-3639 |
| DOI: | 10.1145/3377144 |
| Popis: | We consider an online advertisement system and focus on the impact of user interaction and response to targeted advertising campaigns. We analytically model the system dynamics accounting for the user behavior and devise strategies to maximize a relevant metric called click-through-intensity (CTI), defined as the number of clicks per time unit. With respect to the traditional click-through-rate (CTR) metric, CTI better captures the success of advertisements for services that the users may access several times, making multiple purchases or subscriptions. Examples include advertising of on-line games or airplane tickets. The model we develop is validated through traces of real advertising systems and allows us to optimize CTI under different scenarios depending on the nature of ad delivery and of the information available at the system. Experimental results show that our approach can increase the revenue of an ad campaign, even when user’s behavior can only be estimated. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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