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Source publication
In this research, we evaluate the effectiveness of the buying funnel as a model for understanding consumer interaction with keyword advertising campaigns on web search engines. We analyze data of nearly 7 million records from a 33 month, $56 million (US) search engine marketing campaign of a major US retailer. We classify key phrases used in this c...
Context in source publication
Context 1
... buying funnel is the consumer parallel to the organization"s sales funnel, which frames the customer buying process from the producer"s point of view with the aim of funneling the potential customers to a successful transaction [Dubberly and Evenson 2008]. Although there are various labels for each stage, one common labeling system is Awareness, Research, Decision, and Purchase (see Figure 1), which is the labeling scheme that we use in this research. ...
Citations
... Analyses of search volumes on Google have been used in a variety of fields, including nature conservation . In marketing theory, awareness (the realization of the existence of a subject) generally precedes information seeking, and both are considered crucial components of intention and behavior formation (Jansen & Schuster 2011). Thus, information seeking behaviors such as internet searches can provide valuable insights pertaining to Aichi target 1. ...
The first target of the Convention for Biological Diversity (Aichi target 1) was to increase public awareness towards the values of biodiversity and actions needed to conserve it - a key prerequisite for other conservation targets. Monitoring success in achieving this target at a global scale has been difficult until recently. However, the increased digitization of human life in recent decades offers insight into people's interests at an unprecedented scale, which allows a more comprehensive evaluation of success towards Aichi target 1 than previously attempted. Here, we used Google search volume data to evaluate global interest in biodiversity and its conservation; and investigated their correlates across countries. We found that during 2013-2020 global searches for biodiversity increased, driven mostly by searches for charismatic fauna. However, searches for conservation actions, driven mostly by searches for national parks, decreased since 2019 likely due to the COVID-19 pandemic. We further found that economic inequality was negatively correlated with interest in biodiversity and conservation, while purchasing power was indirectly positively correlated through increased education and research. Our results suggest partial success towards achieving Aichi target 1, in that interest in biodiversity has increased widely, but not for conservation. We suggest that increased outreach and education efforts towards neglected aspects of biodiversity and conservation are still needed. Popular topics in biodiversity and conservation could be leveraged to increase awareness of other topics, with attention to local socioeconomic contexts. This article is protected by copyright. All rights reserved.
... A "feature" is defined as a functionality in the platform itself that is instrumental in the advertising process. For example, adjusting click price is a central feature in online ad platforms [30]. Features govern what is possible or not within the ad platform, for example, whether the advertisers can determine the price per ad click or whether the system does this on their behalf. ...
... In the case at hand, the power dynamics favor Google (and most online advertising companies that offer advertising platforms) over advertisers [58], as Google controls the majority of the critical aspects of online advertising exchange, including pricing [30], ad ranking [40,61], and matching search queries for a given ad [32]. Furthermore, the agent-Google-has detailed information about the events occurring in its ad marketplace and the algorithms that govern these events. ...
Businesses are increasingly delegating activities in the advertising process to dominant online advertising platforms. This delegation yields the ad platforms tremendous power, akin to the principal–agent dilemma discussed in economics. One of the major platforms is called Google Ads—this platform is the focal point of our study. Over the years, Google has made substantial changes to its platform’s features, which, in turn, govern what is possible and what is not for the advertisers. These changes impact the advertisers’ ability to act independently and make their own choices, referred to as human agency. To better understand this impact, we examined 362 industry news articles reporting changes in Google Ads from 2015 to 2020. The findings indicate that while most changes increase human agency, this effect is becoming weaker over time, driven by automation. To better understand advertisers’ attitudes towards automation, we surveyed 193 advertisers with Google Ads experience. Contrary to the popular belief that marketers are afraid of being replaced by algorithms, we found this to not be the case. Even though most advertisers indicated appreciation for maintaining their human agency, they did not perceive this agency being violated by the ad platform. However, we did observe interesting variability among respondents, reflected in three computational advertising attitude types: tinkerers, instrumentalists, and shepherds. We discuss the implications for advertisers in terms of strategizing in the face of reduced human agency and for ad platforms in terms of designing features that advertisers perceive as fair.
... In the world of marketing, the different models are labeled as "buying-", "purchase-", or "brand-funnel" too (e.g. Jansen & Schuster, 2011). It is obvious: in science and practice, there are many labels for the same topic. ...
This study analyzes the various stages of the customer journey (CJ) concept using the example of the lingerie product area. The fields of Customer Journey Management, Customer Relationship Management , and Customer Experience Management, which have so far been largely considered separately, are summarized into a comprehensive framework. In the second part, the study uses a representative survey of 1,050 women of generation X to establish the validity of the model empirically. It additionally analyzes in how far the data requires the expansion of the model by a secondary vertical meta-level to capture interlinkages not considered within a purely linear model of the CJ. The result, a two-dimensional network structure of the CJ, illustrates the links between different parts of the CJ and the requirement of a multidimensional approach towards the customer journey. Finally, the study presents an approach on how to model the willingness-to-pay as the central part of the CJ by implementing an artificial neural network (ANN) approach. The results show the ANN is ideally suited for such a complex background. The resulting model combines high explanatory power with the potential to increase it further by successively including newly available customer data, thus offering additional benefits for practitioners.
... Traditional data typically have little information on awareness and decision phase as indicated by question marks. Alternative data typically occupy more than one spot in the funnel, as indicated by the arrow on the right stretching across all phases, in support of Jansen and Schuster (2011) who conclude that the process is more complex than the simple linear representation. ...
Worldwide macroeconomic data suffer from three fundamental problems - high dimensionality, a staggered release schedule, and poor data quality. Nowcasts are a popular set of tools that address the first two problems, and the advent of alternative or Big Data offers a chance to address the poor data quality. In this chapter, I provide an overview of nowcasting techniques, discuss the need for an ex-ante hypothesis to guide alternative data selection, and compare typical alternative datasets to traditional data on several quality dimensions such as timeliness and granularity. Finally, I present a case study that establishes that search data can statistically and economically significantly improve US government employment data along the timeliness and accuracy dimensions - a novel result. The case study nowcasts revisions to Non-Farm Payrolls (NFP) three months in advance of the government data, proves these revisions are news and not noise in the framework of Mankiw et al. (1984), controls for Wall Street
analyst predictions, and finds that machine learning techniques such as random forest and elastic net provide a substantial improvement over traditional linear regression methods.
... Years after the original formula came out together with a large number of variations, Barry and Howard (1990) transformed Lewis' foundations to explain in three stages how consumer responses to advertising worked; the cognitive or thinking part, the affective or feeling part and, finally, the conative or doing part. Nowadays, marketers have been updating this framework regarding the applications in demand, especially with the birth of e-commerce (Jansen & Schuster, 2011). Some authors, such as Chohan and Paschen (2021), have merged the stages of Desire and Action while including a postpurchase stage to fit the current investment circumstances: the Recurring Action ( Figure 4). ...
Non-Fungible Tokens, popularly known as NFTs, have started to define an entire spectrum of trends in the creative industries: especially regarding art, sports and music market-related scenarios. Following in the footsteps of crypto, welcoming NFTs into the market has brought nothing but a paradigm shift when apprehending the value of a digital product, both for the company and the consumer. This trend, which began with sharing simple content creator posts on social media, has already dazzled companies like Adidas, Gucci or Pizza Hut.
Beyond unlocking a billion-dollar market, this new technology has opened an unprecedented debate regarding the usefulness, authenticity and, especially, the value that a digital cultural asset might have within audiovisual media.
This project aims to detect the key factors affecting marketing strategies for NFTs through a consumer study based in Germany. The task involves finding out which dissemination channels, influencers and content consumption habits are involved in developing such strategies.
... This includes work by information science faculty like Bar-Ilan (2007a;2007b), Furner (2007), Saracevic (1999), Smith (1981), Spink et al. (2001), andZimmer (2008). Fairness in information retrieval is (Gao & Shah, 2020a, 2020b) and Jansen (Eastman & Jansen, 2003;Jansen & Schuster, 2011). ...
This paper reviews literature pertaining to the development of data science as a discipline, current issues with data bias and ethics, and the role that the discipline of information science may play in addressing these concerns. Information science research and researchers have much to offer for data science, owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral perspectives to issues within natural science disciplines. Information science researchers have already contributed to a humanistic approach to data ethics within the literature and an emphasis on data science within information schools all but ensures that this literature will continue to grow in coming decades. This review article serves as a reference for the history, current progress, and potential future directions of data ethics research within the corpus of information science literature.
... J o u r n a l P r e -p r o o f box systems and application programming interfaces (APIs) when using data from the major platforms (e.g., Jansen & Schuster, 2011;Jiang et al., 2018;P. Wang et al., 2003;Y. ...
This reflection article addresses a difficulty faced by scholars and practitioners working with numbers about people, which is that those who study people want numerical data about these people. Unfortunately, time and time again, this numerical data about people is wrong. Addressing the potential causes of this wrongness, we present examples of analyzing people numbers, i.e., numbers derived from digital data by or about people, and discuss the comforting illusion of data validity. We first lay a foundation by highlighting potential inaccuracies in collecting people data, such as selection bias. Then, we discuss inaccuracies in analyzing people data, such as the flaw of averages, followed by a discussion of errors that are made when trying to make sense of people data through techniques such as posterior labeling. Finally, we discuss a root cause of people data often being wrong – the conceptual conundrum of thinking the numbers are counts when they are actually measures. Practical solutions to address this illusion of data validity are proposed. The implications for theories derived from people data are also highlighted, namely that these people theories are generally wrong as they are often derived from people numbers that are wrong.
... Similar to a marketing funnel, in e-commerce, a "conversion funnel" is used to describe the trajectory of consumers browsing e-commerce websites through Internet advertising or search systems, and finally converting the search into sales. (Jansen & Schuster, 2011) [35]In digital marketing funnel, consumers may find products they desire through advertisements or keyword searches on the web. Subsequently, social media is used to compare prices and consumer reviews to target websites or platforms. ...
... Similar to a marketing funnel, in e-commerce, a "conversion funnel" is used to describe the trajectory of consumers browsing e-commerce websites through Internet advertising or search systems, and finally converting the search into sales. (Jansen & Schuster, 2011) [35]In digital marketing funnel, consumers may find products they desire through advertisements or keyword searches on the web. Subsequently, social media is used to compare prices and consumer reviews to target websites or platforms. ...
... (runthecompany, 2020) [36] The "purchase funnel," "sales funnel," "marketing funnel," or "customer funnel" is a consumer-focused marketing model that is used illustrate the theoretical CJ of customers purchasing products or services. (Jansen & Schuster, 2011) [35]Studies have investigated multiple stages along the purchase funnel to investigate manufacturers perspective on managing national brands (NBs) and the influence of in-store retailer-specific activities on the purchase decision. (Lamey et al., 2018) [37] Through purchase funnel, data analytics provide insights on customers, such as their behaviors, their incoming channels, and purchased contents. ...
The retail industry provides customers with goods or services. Analyzingthe purchase behavior of customers is critical for expanding thebusiness. Therefore, managing the repurchase intention of customersis crucial. A sequence of purchase behaviors by each customer constitutesa set of purchase customer journeys (purchase CJs), whichdetail purchase pathways and repurchase behaviors. Purchase CJs arethe actual retail transaction data. This study investigated purchaseCJs and proposed a purchase funnel called CJ graph (CJG) bymeasure theory and knowledge space theory with actual retail transactiondata. To achieve this objective, a customer journey block (CJB),denoting “touchpoint,” is defined as a series of purchase behaviors duringa period and used as the base of this method. Each touchpointis allotted a measurable function, named purchase measure (PM).By integrating all the CJBs of purchase CJs, the purchase measuregraph (PMG) can be constructed as the primary structure ofthe PM knowledge structure. Finally, when all CJs are coordinatizedwith CJ codes, knowledge space theory is used to develop the customerjourney graph (CJG). In this method, knowledge bases are usedas the spanning framework of the CJ knowledge space, and the filteringproperty of the purchase funnel is illustrated. Furthermore, to validate the feasibility of the proposed method, a set of two-year andone million transactions retail data generated from more than thirty-sixthousand customers was segmented by recency, frequency, and monetary(RFM) model. Thus, the corresponding PMGs and CJGs of various(12, here) customer segments are detailed, and the resultant knowledgebases of the primary purchases and secondary re-purchases are appliedto analyze and predict the customer purchase behaviors accurately.
... consideration) and lower funnel (i.e. decision and purchase) (Jansen and Schuster, 2011). Scholars have applied the marketing funnel theory to research several phenomena, including generated content on social media (Colicev et al., 2019) and sponsorship activities in the sport sector (Visentin et al., 2016). ...
Purpose
The elevation of a residential building, or façade, affords aesthetic and functional value to tenants. Façades embody the design of the core product, i.e. the building’s unit. When carefully executed, they contribute to the attractiveness, livability and sustainability of urban areas. The purpose of this study is to show how façades influence consumer decision, and to identify the consumers affected more by façades, i.e., product design.
Design/methodology/approach
Hinging on notions from product design and appearance, this research underscores the ways by which façades affect potential tenants. It also proposes that personality dimensions (i.e. concern with own physical appearance and view of achievement) identify the tenants affected more by façades. A study involving 1,091 consumers was performed to test the hypotheses.
Findings
Functional and aesthetic façades facilitated the tenant decision to buy or rent a living unit in three ways: attraction, convection and conversion. Two tenant segments (performers and egotists) were the most affected by façades. Hence, key consumer segments including self-actualizers would be less influenced by product design.
Practical implications
Construction companies should focus on delivering functional, aesthetic and well-maintained façades to boost satisfaction and sales. They should view the resources allocated to this purpose as an investment. Certain tenants are more affected by façades. Companies should identify the consumer segments more affected by design cues to better respond to their preferences. Policymakers are encouraged to set guidelines that foster well-executed façades in urban areas.
Originality/value
This research underscored the ways by which the façades of residential buildings shape consumer decision. In addition, it provided a typology to help pinpoint the tenants more affected by façades. Finally, it elaborated design theories in the context of residential building façades, which can be used by future researchers to understand the role of façade in fulfilling tenants’ needs and expectations.
... Search engine marketing (SEM) is a marketing practice that firms use to promote their products or services on the Search Engine Results Pages (SERP). Search engine marketing, also called keyword advertising, focuses on the allocation of ads that appear on the SERP to users' needs (Jansen and Schuster 2011) with advertisers paying the search engine an amount for each user's click. 2 Firms invest in advertising on search engines with the aim of increasing their visibility among the results of an online search (Berman and Katona 2013). This investment is based on a specific keyword (search query) that users use in their search. ...
Sponsored advertising on search engines is one of the fastest growing online advertising marketplaces. The space available for paid ads, or positions, is sold using auctions and payment is calculated considering the number of clicks each position receives. Two mechanisms are generally used in position auctions: Generalized Second Price (GSP) (e.g. Google, Yahoo!) and Vickrey–Clarke–Groves (VCG) (e.g. Facebook). To understand which mechanism guarantees the highest payoff to market players (search engines and advertisers), a multi-agent simulation is developed in Netlogo. Using the generated data, a supervised learning-based analysis on search engines and bidders’ payoffs is made using linear regression models and regression trees. Results suggest that the average payoff for auctioneers (the search engines) and bidders (the advertisers), the price for each position, and first bidder’s payment, are significantly different in the GSP and VCG mechanisms. We also found the mechanism that generates the highest payoff for the search engine is the VCG, while for the bidders it is the GSP.
