Abstract
Google AdWords has a bidding price optimization method for its campaigns, where the user establishes the maximum bidding price, and AdWords adapts the final bidding price according to the performance of a campaign. This chapter proposes a bidding price controller based on a fuzzy inference system. Specifically, two approaches are considered: a type-1 fuzzy inference system, and an interval type-2 fuzzy inference system. The results show that the proposed methods are superior to the AdWords optimization method, and that there is not enough statistical evidence to support the superiority of the interval type-2 fuzzy inference system against the type-1 fuzzy inference system, although type-2 is slightly better.
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Madera, Q., Castillo, O., Garcia, M., Mancilla, A. (2017). Bidding Strategies Based on Type-1 and Interval Type-2 Fuzzy Systems for Google AdWords Advertising Campaigns. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_6
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DOI: https://doi.org/10.1007/978-3-319-47054-2_6
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