Conversion potential: a metric for evaluating search engine advertising performance

Abstract

Purpose This research is based on the premise that current metrics for search engine advertising (SEA) are misleading and do not sufficiently allow managers to evaluate traffic and conversions simultaneously. This study aimed to conceptually develop and assess conversion potential (CvP) as a unifying construct for both measuring and evaluating the performance of SEA campaigns. Design/methodology/approach A data set of nearly seven million records covering almost three years of a multi-million-dollar keyword marketing campaign from a major US retailer was used to validate the construct of CvP. Findings Results empirically validate how CvP measures both campaign traffic and sales in SEA, using the optimization factor of ad rank, which is one of many possible factors. Research limitations/implications Although the data set is large and covers a lengthy period of time, it is limited to one company in the retail sector. Practical implications The research instantiates CvP as a metric for overall SEA account performance while demonstrating that it is a practical tool for future campaign planning. The metric simultaneously incorporates a sales ratio and a traffic ratio. Originality/value This is the first study to formalize and provide a working definition of CvP in the academic literature. The contribution is a theoretical and practical managerial framework to mutually evaluate, measure and make decisions about SEA efforts.

How Does Personification Impact Ad Performance and Empathy? An Experiment with Online Advertising

“…To test H01, we choose two metrics that are widely deployed as success metrics for online advertising (see Table 1): clicks and initiated checkouts. Both are important in the industryclick response rates are typically used for assessing advertising appeal (Järvinen & Karjaluoto, 2015), and purchase intent is especially critical for e-commerce companies that want to increase their sales (Clarke & Jansen, 2017;Salminen et al, 2017). We also analyze the actual number of purchases from both PUG and NUG ads.…”

Informing, implying or directing? Testing the effects of message sidedness, conclusiveness and their interaction in national and local Google Ads campaigns

“…Search engine advertising campaigns can measure the effectiveness at multiple levels: impressions, clicks and therefrom CTRs. Some researchers also suggest adding conversion potential as a metric of performance (Jansen and Clarke, 2017) Researchers have tested the effectiveness of sidedness and conclusiveness, separately, at the levels of the attitude toward the advertisement (Crowley and Hoyer, 1994;Eisend, 2006;Kardes, 1988;O'Keefe, 2016;Pechmann, 1992) or the knowledge (Ketelaar et al, 2012;Martin et al, 2003), attitude (Ahearne et al, 2000;Crowley and Hoyer, 1994;Pechmann, 1992;Skard and Thorbjornsen, 2017) or behavioral intention regarding the brand (Martin and Strong, 2016;Yao et al, 2018). Measurements in traditional studies, however, are mostly consumer self-reports with well-known drawbacks (errors from subjects' social bias, inability to remember, etc.…”

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Revisiting product classification to examine content marketing practices

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