To Score or Not to Score? Estimates of a Sponsored Search Auction Model

We estimate a structural model of a sponsored search auction model. To accomodate the "position paradox", we relax the assumption of decreasing click volumes with position ranks, which is often assumed in the literature. Using data from "Website X", one of the largest online market places in China, we find that merchants of different qualities adopt different bidding strategies: high quality merchants bid more aggressively for informative keywords, while low quality merchants are more likely to be sorted to the top positions for value keywords. Counterfactual evaluations show that the price trend becomes steeper after moving to a score-weighted generalized second price auction, with much higher prices obtained for the top position but lower prices for the other positions. Overall, there is only a very modest change in total revenue from introducing popularity scoring, despite the intent in bid scoring to reward popular merchants with price discounts

Pay-per-click advertising: A literature review

Digital marketing is being widely employed to efficiently and effectively market products/services to achieve increased sales and generate higher revenues. It allows businesses to effectively communicate desired content to their consumers. Pay-per-click (PPC) is one such form of digital marketing. PPC is often acknowledged for the different advantages it offers, and at the same time, it is notably criticised for fraud and other issues associated with its use. The literature on this subject, although limited, has invested considerable efforts in unveiling the pros and cons of employing PPC as a marketing/advertising strategy. This paper reviews 50 publications on PPC advertising to synthesise their findings and arrive at a common ground for understanding the digital presence and impact of this form of marketing. Alongside discussing the findings, observed limitations and opportunities for future research have been identified and reported

Paying for prominence

We investigate three ways in which firms can become "prominent" and thereby influence the order in which consumers consider options. First, firms can affect an intermediary's sales efforts by means of commission payments. When firms pay commission to a salesman, the salesman promotes the product with the highest commission, and steers ignorant consumers towards the more expensive product. Second, sellers can advertise prices on a price comparison website, so that consumers investigate the suitability of products in order of increasing price. In such a market, equilibrium prices are lower when search costs are higher since a firm's benefit from being investigated first increases with search costs. Finally, consumers might first consider their existing supplier when they purchase a new product, which suggests a relatively benign rationale for the prevalence of cross-selling in markets such as retail banking.Consumer search, e-commerce, price comparison websites, cross-selling, mis-selling, commission sales.

A Novel Approach for Bidding on Newly Set-Up Search Engine Advertising Campaigns

Advertisers setting up search engine advertising campaigns for the first time need to place bids on keywords, but typically lack experience and data to determine ranks that maximize a keyword's profit (generally referred to as a cold-start problem). This article aims at solving the problem of bidding on keywords in newly set-up search engine advertising campaigns. We suggest that advertisers collect data from the Google Keyword Planner to obtain precise estimates of the percentage increases in prices per click and clickthrough rates, which are needed to calculate optimal bids (exact approach). Together with the profit contribution per conversion and the conversion rate, the advertiser might then set bids that maximize profit. In case advertisers cannot afford to collect the required data, we suggest two proxy approaches and evaluate their performance using the exact approach as a benchmark. The empirical study shows that both proxy approaches perform reasonably well-the easier approach to implement (proxy 2) sometimes performs even better than the more sophisticated one (proxy 1). As a consequence, advertisers might just use this very simple proxy when bidding on keywords in newly set-up SEA campaigns. This research extends the stream of literature on how to determine optimal bids, which so far focuses on campaigns that are already running and where the required data to calculate bids is already available. This research offers a novel approach of determining bids when advertisers lack the aforementioned information

Essays in Modeling the Consumer Choice Process

In this dissertation, I utilize and develop empirical tools to help academics and practitioners model the consumer\u27s choice process. This collection of three essays strives to answer three main research questions in this theme. In the first paper, I ask: how is the consumer\u27s purchase decision impacted by the search for general product-category information prior to search for their match with a retailer or manufacturer ( sellers )? This paper studies the impact of informational organic keyword search results on the performance of sponsored search advertising. We show that, even though advertisers can target consumers who have specific needs and preferences, for many consumers this is not a sufficient condition for search advertising to work. By allowing consumers to access content that satisfies their information requirements, informational organic results can allow consumers to learn about the product category prior to making their purchase decision. We develop a model characterize the situation in which consumers can search for general information about the product category as well as for information about the individual sellers\u27 offerings. We estimate this model using a unique dataset of search advertising in which commercial websites are restricted in the organic listing, allowing us to identify consumer clicks as informational (from organic links) or purchase oriented (from sponsored links). With the estimation results, we show that consumer welfare is improved by 29%, while advertisers generate 19% more sales, and search engines obtain 18% more paid clicks, as compared to the scenario without informational links. We conduct counterfactuals and find that consumers, advertisers, and the search engine are significantly better off when the search engine provides free general information about the product. When the search engine provides information about the advertisers\u27 specific offerings, however, there are fewer paid clicks and advertisers at high ad positions will obtain lower sales. We further investigate the implications on the equilibrium advertiser bidding strategy. Results show that advertiser bids will remain constant in the former scenario. When the search engine provides advertiser information, advertisers will increase their bids because of the increased conversion rate; however, the search engine still loses revenue due to the decreased paid clicks. The findings shed important managerial insights on how to improve the effectiveness of search advertising. In the second paper, I ask: how is the consumer\u27s search for information, during their choice process and in an advertising context, influenced by the signaling theory of advertising? Using a dataset of travel-related keywords obtained from a search engine, we test to what extent consumers are searching and advertisers are bidding in accordance with the signaling theory of advertising in literature. We find significant evidence that consumers are more likely to click on advertisers at higher positions because they infer that such advertisers are more likely to match with their needs. Further, consumers are more likely to find a match with advertisers who have paid more for higher positions. We also find strong evidence that advertisers increase their bids when there is an improvement in the likelihood that their offerings match with consumers\u27 needs, and the improvement cannot be readily observed by consumers prior to searching advertisers\u27 websites. These results are consistent with the predictions from the signaling theory. We test several alternative explanations and show that they cannot fully explain the results. Furthermore, through an extension we find that advertisers can generate more clicks when competing against advertisers with higher match value. We offer an explanation for this finding based on the signaling theory. In the third paper, I ask: can we model the consumer\u27s choice of brand as a sequential elimination of alternatives based on shared or unique aspects while incorporating continuous variables, such as price? With aggregate scanner data, marketing researchers typically estimate the mixed logit model, which accounts for non-IIA substitution patterns among brands, which arise due to similarity and dominance effects in demand. Using numerical examples and analytical illustrations, this research shows that the mixed logit model, which is widely believed to be a highly flexible characterization of brand switching behavior, is not well designed to handle non-IIA substitution patterns. The probit allows only for pair-wise inter-brand similarities, and ignores third-order or higher dependencies. In the presence of similarity and dominance effects, the mixed logit model and the probit model yield systematically distorted marketing mix elasticities. This limits the usefulness of mixed logit and probit for marketing decision-making. We propose a more flexible demand model that is an extension of the elimination-by-aspects (EBA) model (Tversky 1972a, 1972b) to handle marketing variables. The model vastly expands the domain of applicability of the EBA model to aggregate scanner data. Using an analytical closed-form that nests the traditional logit model as a special case, the EBA demand model is estimated with marketing variables from aggregate scanner data in 9 different product categories. It is compared to the mixed logit and probit models on the same datasets. In terms of multiple fit and predictive metrics (LL, BIC, MSE, MAD), the EBA model outperforms the mixed logit and the probit in a majority of categories in terms of both in-sample fit and holdout predictions. The results show significant differences in the estimated price elasticity matrices between the EBA model and the comparison models. In addition, a simulation shows that the retailer can improve gross profits up to 34.4% from pricing based on the EBA model rather than the mixed logit model. Finally, the results suggest that empirical IO researchers, who routinely use mixed logit models as inputs to oligopolistic pricing models, should consider the EBA demand model as the appropriate model of demand for differentiated products

Keyword Search Patterns in Sponsored Link Advertisements

Over time, an online user searching for information about an idea or product may enter multiple search engine queries, thus creating a keyword search pattern from which the user’s intent may be inferable. Our research seeks to establish the relationship between these patterns and user actions, specifically their purchase behavior. To test our hypotheses, we examine a unique dataset from a large Asian travel agency; the dataset includes search engine and on-site behavior from over a million users during a one year span. We have developed a typology for the coding of search queries used and determining the level of specificity and breadth as well as content type for each of well over two million unique searches. Once coded, our analysis will allow us to identify types of patterns and test our hypotheses, thus providing important findings regarding the relationship between search patterns and behavior

DESIGNING OPTIMAL MARKETING MIX STRATEGIES FOR A NEW CONSUMER DURABLE AND PAY-PER-CLICK MARKETING

Ph.DDOCTOR OF PHILOSOPH

An Empirical Analysis

학위논문(석사) -- 서울대학교대학원 : 경영대학 경영학과, 2021.8. 명준구.With the emergence of new technologies and due to the recent COVID-19 pandemic, e-commerce and its subsequent e-marketplaces are constantly gaining attention. Simultaneous to the popularity, competition is becoming fierce for both e-marketplace operators and its participating sellers. As a result, they are striving for a competitive edge. Incorporating decision-supporting services in e-marketplaces can be considered as a strategic activity for the platform operators, which can enhance the performance of sellers actively using such services. We therefore hypothesize that the usage of decision support systems will lead to an enhanced performance of e-marketplace participants, i.e., sellers. By utilizing a secondary data provided by one of the leading e-marketplace operators in Korea, we have empirically found out that usage of decision support systems, namely, seller dashboard and review systems, lead to an increase in sales, which is the measurement of a seller’s performance. This study will serve as a literature for DSS effectiveness, e-marketplace success strategies, and will provide theoretical implications for the resource-based view and competitive dynamics theory by adding an empirical evidence for those field of study. Also, this study possesses managerial implications for not only e-marketplace operators seeking success, but sellers within the platform also.IT의 발전과 함께 특히 최근 COVID-19 팬데믹의 영향으로 전자상거래는 꾸준한 성장과 관심을 받고 있다. 하지만 이와 동시에 경쟁 역시 치열해지고 있기 때문에, 전자상거래 플랫폼 운영사들과 플랫폼에 참여하는 판매자들은 경쟁우위를 점하게 위해 노력을 하고 있는 실정이다. 이를 위한 한가지 전략적 방안으로는 전자상거래 플랫폼 내에 의사결정 지원도구를 제공함으로써 판매자들을 돕는 방법이 있다. 이에 따라 실제 이러한 의사결정 지원도구가 실제 전자상거래 플랫폼 참여자에게 도움이 될 것이라는 가설을 세우고 연구를 진행하였다. 한국의 한 전자상거래 플랫폼의 데이터를 제공받아 분석한 결과, 대시보드 및 리뷰 시스템의 의사결정 지원도구를 사용한 경우 매출이 증가하여 판매자의 실적이 유의미하게 개선되었다는 사실을 확인할 수 있었다. 본 연구는 의사결정 지원도구의 효과성, 그리고 전자상거래 플랫폼 성공 요인에 관한 문헌으로서 그 의의가 있다고 할 수 있고, 자원기반이론 및 역동적 능력 이론에 관한 실증이라는 점에서 의의를 찾을 수 있다. 또한, 전자상거래 플랫폼 운영사뿐만 아니라 판매자들에게도 경영적인 시사점을 줄 수 있을 것이다.Table of Contents Chapter 1. Introduction 1 1.1 Study Background 1 1.2 Study Goals and Question 3 Chapter 2. Literature Review 5 2.1 E-marketplace 5 2.2 Decision Support Systems 9 2.3 Platform Strategy 10 Chapter 3. Hypotheses Development 12 3.1 Hypotheses and Research Model 12 Chapter 4. Research Methodology 17 4.1 Propensity Score Matching 17 4.2 Variables 18 Chapter 5. Data Analysis and Results 21 5.1 Data Description 21 5.2 Data Analysis 25 5.3 Results 27 Chapter 6. Discussion and Conclusion 31 6.1 Implications 31 6.2 Limitations and Further Research 32 6.3 Conclusion 33 References 35 국문 초록 40석

Taking Stock of the Digital Revolution: A Critical Analysis and Agenda for Digital, Social Media, and Mobile Marketing Research

Marketing has been revolutionized due to the rise of digital media and new forms of electronic communication. In response, academic researchers have attempted to explain consumer- and firm-related phenomena related to digital, social media, and mobile marketing (DSMM). This paper presents a critical historical analysis of, and forward-looking agenda for, this work. First, we assess marketing’s contribution to understanding DSMM since 2000. Extant research falls under three eras, and a fourth era currently underway. Era 1 focused on digital tools and platforms as consumer and marketer decision aids. Era 2 studied online communications channels (e.g., online forums) as word of mouth marketing “laboratories,” capturing the potential of DSMM for social information transmission. Era 3 embraced the notion of “connected consumers” by considering various antecedents and consequences of socially interconnected consumers in marketplaces. Era 4, currently starting, considers mobile marketing and brings psychological and social theories to bear on emergent DSMM issues. Second, we critique the DSMM literature and advance a series of recommendations for future research. While we find much to applaud, we argue that several problems limit the relevance of this research moving forward and suggest ways to alleviate these concerns moving forward