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We want to develop a two-stage consumer-level model of paid search advertising response based on Google adwords aggregated data that will be provided to the provider. The proposed model should use behavioral variables available in the data for a utility maximization and should allow recovering parameters of the heterogeneity distribution in consumer preferences (clicks and conversions)
The model for paid search dataset will includes information on the ad copy. The short listed candidates will be provided a theoretical approach to develop a framework to analyze composition and design attributes of paid search ads.
The model results should allow us to correctly evaluate the effects of specific ad properties on ad performance, taking consumer heterogeneity into account. This proposed approach should allow recovery of preference correlation across the click-through and conversion stage. Based on the estimated correlation between ad copy- and position-sensitivity we want to optimiz...
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