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Optimal Budget Allocation over Time for Keyword Ads in Web Portals
- Source :
- Journal of Optimization Theory and Applications. 124:157-174
- Publication Year :
- 2005
- Publisher :
- Springer Science and Business Media LLC, 2005.
-
Abstract
- This study investigates how to dynamically allocate resources with a given budget for advertising through Web portals using keyword-activated banner ads on the Internet. Identifying the factors that affect the potential number of banner ad clickthroughs in each portal, we show that the process of budget allocation between the two types of portals (generic vs specialized) that leads to the largest banner clicksthrough in the long run is an optimal control problem. Using techniques of dynamic programming, we find analytical solutions for the optimal budgeting decisions. Our analysis shows that an advertiser’s optimal portal budgeting depends nonlinearly on the number of visitors who type the same trigger keyword and the average clicksthrough rates, as well as on the advertiser and ad effectiveness. Further, we find that the maximal number of banner clickthroughs from both portals, at time t, depends on the remaining budget until the end of the planning period. The analytical results have useful managerial insight. One of the interesting features of our solution shows that, while a large visitor base may favor the generic portal, other parameters may affect it unfavorably: e.g., lower clickthrough rates of keyword banners from a more heterogeneous audience. Using a specificaction that is consistent with empirical observations, we show that, in the long run, an advertiser must always spend more ad money at the specialized portal.
- Subjects :
- Control and Optimization
Operations research
business.industry
Applied Mathematics
Visitor pattern
InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL
Management Science and Operations Research
Online advertising
Web banner
Dynamic programming
Resource allocation (computer)
The Internet
Banner
business
Empirical evidence
Mathematics
Subjects
Details
- ISSN :
- 15732878 and 00223239
- Volume :
- 124
- Database :
- OpenAIRE
- Journal :
- Journal of Optimization Theory and Applications
- Accession number :
- edsair.doi...........7ec1eacaef7203a4f6b44e39a428da63
- Full Text :
- https://doi.org/10.1007/s10957-004-6470-0