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Journal ArticleDOI

Conversion potential: a metric for evaluating search engine advertising performance

TLDR
This is the first study to formalize and provide a working definition of CvP, which instantiates CvP as a metric for overall SEA account performance while demonstrating that it is a practical tool for future campaign planning.
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.

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Citations
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Journal ArticleDOI

Are personas done? Evaluating their usefulness in the age of digital analytics

TL;DR: It is argued that to survive in the rapidly developing online customer analytics industry, personas must evolve by adopting new practices and benefit from powerful computational techniques and novel data sources.
Journal ArticleDOI

Machine learning approach to auto-tagging online content for content marketing efficiency: A comparative analysis between methods and content type

TL;DR: This work compares three state-of-the-art ML techniques for multilabel classification - Random Forest, K-Nearest Neighbor, and Neural Network - to automatically tag and classify online news articles and suggests that organisations may optimise ML to auto-tag content across various platforms, opening avenues for aggregated analyses of content performance.
Proceedings ArticleDOI

Personas and Analytics: A Comparative User Study of Efficiency and Effectiveness for a User Identification Task

TL;DR: Comparisons of a persona system and an analytics system for efficiency and effectiveness for a user identification task show that personas afford faster task completion than the analytics system, as well as outperforming analytics with significantly higher user identification accuracy.
Journal ArticleDOI

Parallel search engine optimisation and pay-per-click campaigns: A comparison of cost per acquisition

TL;DR: SEO should be the marketing system of preference for e-commerce-based websites, however, there are cases where PPC would yield better results – when instant traffic is required, and when a large initial expenditure is not possible.
Journal ArticleDOI

Digital inbound marketing: Measuring the economic performance of grocery e-commerce in Europe and the USA.

TL;DR: The results confirm that e-commerce is optimizing Digital Inbound Marketing in line with the established model and differences are identified depending on the type of format (pure player versus brick and mortar) and at the country level.
References
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Journal ArticleDOI

An Analysis of Transformations

TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.
Book

Analysis of Variance

TL;DR: The authors have improved on their widely used first edition by adding material on how to do ANOVA using statistical packages for microcomputers, linking the use of ANOVA to regression analysis, and enchancing their discussion on using ANOVA for experimentally gathered data.
Book ChapterDOI

Analysis of variance

TL;DR: In this paper, the authors proposed a method to improve the quality of the data collected by the Japanese government through the use of data from the internet and social media, such as Facebook and Twitter.
Proceedings ArticleDOI

Predicting clicks: estimating the click-through rate for new ads

TL;DR: This work shows that it can be used to use features of ads, terms, and advertisers to learn a model that accurately predicts the click-though rate for new ads, and shows that using this model improves the convergence and performance of an advertising system.
Journal ArticleDOI

A Framework for Conceptual Contributions in Marketing

TL;DR: In this paper, a framework for thinking about conceptualization in marketing is presented, followed by a typology of types of conceptual contributions, their similarities and differences, and their importance to the field.
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