Grant: Collaborative Research and Development Grants
University of Western Ontario
$60,000.00
Data analytics for online content management
EF 2017-18
Résumé
Web site traffic analysis and optimization often involves Web click streams, the recordings of user clicks during a Web site visit. There are also mobile application click streams and advertisements (ads) click streams, which record clicks in applications and clicks on ads. Those click streams are valuable resources for any online business because they show how users interact with online content. However, although beneficial, stand-alone analysis of click streams has limited potential because the behaviour of online users is impacted by external factors such as weather and user location. The main objective of this research project is to design a generic and extendable software framework for online content management. The framework will improve online content effectiveness, increase sales, reduce manual processes, and ultimately increase revenue from online sources. Two main components will be developed: the first component, integrated data analytics services, will include analytics of click streams with other data such as weather and user location; the second, a supply-side platform for advertising, will include a highly automated process for pricing online inventory. To achieve these goals, the project will explore and advance integrated data analytics, click-through rate prediction, user segmentation, and the supply-side platform for online advertising. The results from this project will directly benefit the industrial partner Pelmorex by enabling them to extract new insights and increase business value from existing data. A sophisticated supply-side platform to be developed in this project will increase revenue from the online advertising inventory. The project will push the boundaries in the area of data analytics related to click streams, supply-side platforms, and online advertising. As a result, it will contribute to growth in these areas. Furthermore, the HQP involved in this project will gain valuable experience working in data analytics and online advertising with Big Data, which will make them valuable to any related data analytics, online advertising, or Big Data job market.
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
492655-2015
Name nom
Capretz, Miriam
Department département
Electrical and Computer Engineering
Organization id
36
Institution établissement
University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2015
Award amount
60000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
804
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Communication systems and services (planning, organization, services)
Area of application fr
Systèmes et services de communications (planification, organisation et services)
Research subject code
2706
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software engineering
Research subject fr
Génie logiciel
Partie
2
Nb partie
2
Application title
Data analytics for online content management
Keyword
NSERC
Application summary
Web site traffic analysis and optimization often involves Web click streams, the recordings of user clicks during a Web site visit. There are also mobile application click streams and advertisements (ads) click streams, which record clicks in applications and clicks on ads. Those click streams are valuable resources for any online business because they show how users interact with online content. However, although beneficial, stand-alone analysis of click streams has limited potential because the behaviour of online users is impacted by external factors such as weather and user location. The main objective of this research project is to design a generic and extendable software framework for online content management. The framework will improve online content effectiveness, increase sales, reduce manual processes, and ultimately increase revenue from online sources. Two main components will be developed: the first component, integrated data analytics services, will include analytics of click streams with other data such as weather and user location; the second, a supply-side platform for advertising, will include a highly automated process for pricing online inventory. To achieve these goals, the project will explore and advance integrated data analytics, click-through rate prediction, user segmentation, and the supply-side platform for online advertising. The results from this project will directly benefit the industrial partner Pelmorex by enabling them to extract new insights and increase business value from existing data. A sophisticated supply-side platform to be developed in this project will increase revenue from the online advertising inventory. The project will push the boundaries in the area of data analytics related to click streams, supply-side platforms, and online advertising. As a result, it will contribute to growth in these areas. Furthermore, the HQP involved in this project will gain valuable experience working in data analytics and online advertising with Big Data, which will make them valuable to any related data analytics, online advertising, or Big Data job market.