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.

User Interaction with Online Advertisements: Temporal Modeling and Optimization of Ads Placement / Vassio, Luca; Garetto, Michele; Chiasserini, Carla Fabiana; Leonardi, Emilio. - In: ACM TRANSACTIONS ON MODELING AND PERFORMANCE EVALUATION OF COMPUTING SYSTEMS. - ISSN 2376-3639. - STAMPA. - 5:2(2020), pp. 1-26. [10.1145/3377144]

User Interaction with Online Advertisements: Temporal Modeling and Optimization of Ads Placement

Luca Vassio;Carla Chiasserini;Emilio Leonardi
2020

Abstract

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.
File in questo prodotto:
File Dimensione Formato  
tompecs_final.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 861.79 kB
Formato Adobe PDF
861.79 kB Adobe PDF Visualizza/Apri
TOMPEC_Final.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 1.06 MB
Formato Adobe PDF
1.06 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2774773