Programmatic Buying Research Articles

Teaching Programmatic Buying in a Media Planning Class

Programmatic advertising has come to dominate the landscape of digital media planning. To prepare ad majors for their future careers in the industry, it is essential to teach students programmatic buying and provide them with hands-on experience. In this article, the authors present their approach of integrating teaching programmatic buying into a media planning course. A key feature of their educational package is a custom digital media buying tool developed by the authors. They hope this article will benefit other college educators in this field and spark further discussions on best teaching practices of programmatic buying and digital media planning.

Reconfiguring human-machine relations in the automation age: An actor-network analysis on automation’s takeover of the advertising media planning industry

In this age of “big data”, automated technologies have entered into the advertising media planning industry to significantly alter the client servicing process. This process involves the planning and buying of media spaces to target consumers with relevant advertisements. This study examines how the roles of human advertising media planning professionals are transforming vis-à-vis the machines by using actor-network theory and in-depth interviews with senior professionals in the field. Findings reveal how these actors conceive of automation, and map out important changes to human–machine relations through the advertising media planning process, from the conception of the media brief and media plan, to the programmatic buying of advertising spaces, tailoring of creative assets, and reporting of results.

IS-DT: A New Feature Selection Method for Determining the Important Features in Programmatic Buying

Traditional data-driven feature selection techniques for extracting important attributes are often based on the assumption of maximizing the overall classification accuracy. However, the selected attributes are not always meaningful for practical problems. So, we need additional confirmation from the experts in the domain knowledge to determine whether these extracted features are meaningful knowledge. Moreover, due to advances in mobile devices and wireless environments, programmatic buying (PB) has become one of the critical consumer behaviors in e-commerce. However, it is extremely difficult for PB service providers to build customers’ loyalty, since PB customers require a high level of service quality and can quickly shift the purchases from one website to another. Previous studies developed various dimensions/models to measure the service quality of PB; nevertheless, they did not identify the key factors for increasing customers’ loyalty and satisfaction. Consequently, this study used an importance–satisfaction (IS) model as domain knowledge and proposed a new IS-DT feature selection method. This new IS-DT method combined the IS model and the decision tree (DT) algorithm to extract useful service quality factors for enhancing customer satisfaction and loyalty in PB. An actual case was also provided to illustrate the effectiveness of our proposed method. The results showed that for increasing customer satisfaction, the highest impact factors included “problem solving”, “punctuality”, “valence”, and “ease of use”; for building customer loyalty, the most important factors were “expertise”, “problem solving”, “information”, “single column”, “voice guidance”, “QR code”, “situation”, “tangibles”, “assurance”, “entertainment”, and “safety”. Our IS-DT method can effectively determine important service quality factors in programmatic buying.

Digital audio and programmatic ad buying: status and prospects in the post-pandemic context

This article examines the implementation of programmatic buying in the digital audio sector. The sustained growth present in the different markets helps the consolidation of this medium that brings enormous benefits to commercial communication. The main aim of this research is to understand the current situation of the programmatic audio advertising buying sector. In order to address the object of study, an exploratory approach has been carried out by applying a qualitative and quantitative methodology developed with professionals from the sector and supported by the collaboration of entities such as IAB and Programmatic Spain. The results show that there is a greater commitment by brands to invest in digital audio due to its flexibility and the ability to send segmented messages with greater effectiveness and consumer engagement. As a non-invasive medium, the inclusion of digital audio in media plans has a direct impact on listener’s attention. Data shows that there has been a significant increase in the consumption of streaming music, online radio, and podcasts. Nevertheless, investment is still focused on traditional radio and the results of the study show a reluctance to plan integrated campaigns. Moreover, the difficulty in measuring return on investment is a major deterrent to the investment attracted. Professionals interviewed say that the market provides transparency and quality guarantees, as opposed to other problems such as fraud in data measurement that have slowed down investment in the past.

Programmatic Buying of Long-Tailed Traffic Ads Eliminating Differences between Dominant Culture and Subculture

This article proposes to analyse the mode of long-tailed traffic ads of programmatic buying and takes this mode as a much different one to the mode of traditional media buying. The mode of long-tailed traffic of programmatic buying is a supplement of traditional one, and it is also a way to optimize and redistribute the capital from advertiser. This mode could guide the capital into the long-tailed areas of medium, particularly into the subculture concerned medium to stimulate its content reproduction. Meanwhile, the price system of this mode is to assess the value of every single user’s attention and then make a real-time bidding for it. This price system is also much different from the traditional one, which assesses the value of diverse medium. The mode of long-tailed traffic of programmatic buying negates value difference existing among different types of content and media, and insists there is no distinction between the primary and the secondary among content and media. The differences between dominant culture and subculture have been eliminated and the structure has been deconstructed.

The Role of Technology in Building a Competitive Advantage – Programmatic Buying and Its Impact on the Competitiveness of an Organization

Abstract Research background: Recent years have brought a real explosion of new tools and methods of conducting market activities based on new technologies. Solutions based on new technologies carry great development potential for an organization. There is a belief that new technologies – in particular, programmatic buying (analyzed in this article) – also impact an organization’s ability to compete. Programmatic buying (PB) is a tool but also a new model of sales and purchase of advertising, under which the current package approach (traditional) has been replaced by a fully automated individualized approach. Purpose: The aim of the article is to assess the impact of technology on an organization’s ability to compete with the example of PB. Research methodology: The empirical basis is both qualitative and quantitative research conducted in 2018–2019. Results: The empirical material provides the basis for rejecting the main research hypothesis which claims that the usage of PB increases the effectiveness and efficiency of advertising and thanks to this on a companies’ ability to compete. PB has a positive impact only on the effectiveness and efficiency of graphic ads. The same relation was not observed in terms of video ads. Nevertheless the results are not clear. It is recommended to deepen the analysis. Novelty: Due to the fact that programmatic buying is a relatively new technologic solution there is no research that proves its impact on the marketing activities efficiency as well as its role in building the competitive advantage of a company, especially on the Polish or European market. This research starts the discussion of the role of PB in companies’ market activities and fits in the dispute of the significance of new technologies.

A Study on Consent of the GDPR in Advertising Technology Focusing on Programmatic Buying

Online targeted advertising which conveys its advertising message to a target individual based on an accumulated data analysis across multiple external websites about a user's online activity. Basically, the targeted advertising is based on programmatic buying. In the past, advertisers could use a limited advertising space to attract potential customers such as a full-page advertisement at an influential daily or out-of-home(OOH) in the downtown. The advertisers had to win an auction, e.g. a private auction at offline venue, in order to get the space. Nowadays, however, as increasing online media’s influence, e.g. web portal, influencers’ blog, demand for the online advertising inventory is increasing faster than ever. The inventory can be supplied into the advertising market, because it has a feature as intangible resource. Under this circumstance, a method of the traditional action between advertisers and publishers became no longer working in the era of digital media. Hence, programmatic buying was introduced, because it provides that connect between advertisers’ demand and publishers’ supply automatically through an algorithm has already been set up. Moreover, the algorithm can support that advertisers the ability to reach potential customers. Using a personal data helps to select the potential customers. The personal data has been collected on the basis of individuals’ consent. The targeted advertisement is good for potential customers, giving them better access to information about what is being offered, however, it also has privacy risk to users. Therefore consent for marketing purposes become increasingly important in due course. Article 4(11) of the General Data Protection Regulation (GDPR), which was adopted on 14 April 2016, and became enforceable beginning 25 May 2018, states that “any freely given, specific, informed and unambiguous indication of the data subject's wishes by which he or she, by a statement or by a clear affirmative action, signifies agreement to the processing of personal data relating to him or her”. Usually, to use a web portal, the potential customers as user has to consent for the personal data to be used for marketing purposes, at the same time, the web poral as online media, known as publishers in programmatic buying, has a role to supply(or sell) advertising inventories for advertisers. Supply Side Platforms(SSPs) help publishers manage and sell the advertising inventories. Advertising exchanges(Ad exchanges) as mediators, connects between SSPs and Demand Side Platforms(DSPs), which is in charge of managing advertisers’ demand to buy the inventories. Advertisers conduct to bid in real-time to serve advertising impressions to webpage visitors. The highest bidder ‘wins’, and their advertisement will be presented on the webpage to the potential customer via the Real-Time Bidding(RTB) process. The whole process simultaneously takes place in milliseconds based on the authorism in embedded platform. Furthermore, the participants use multiple DSPs and/or SSPs to enable more accurate targeting of advertisements to individuals, i.e. potential customers, and to gain higher revenue, hence, it is hard to figure out that each of participants comply with Article 4(11) of the GDPR, step by step. Although the Article 29 Working Party(WP29) provides ‘Guidelines on consent under Regulation 2016/679’(Guidelines) to help the European Union Member States comply with it, and interpret a notion of consent in GDPR. However, in practice, it is hard to be applied in all cases. In this article, the author will analyze discuss the issue relating to consent of the GDPR in the programmatic ecosystem in accordance with WP29’s Guidelines. Hence the author will suggest participants, data protection authorities, and lawmakers to comply with Article 4(11) of the GDPR in practice, considering a feature of the RTB process.

Click, click, ad: the proportion of relevant (vs. irrelevant) ads matters when advertising within paginated online content

Applying the ad-context congruence framework, priming theory, and associative network of memory model, two experimental studies (N1 = 445; N2 = 449) investigated the effects of displaying different proportions of thematically relevant and irrelevant ads in online paginated stories on brand recognition memory (sensitivity and criterion bias), ad and brand evaluations, ad clicking intentions, and brand purchase intentions. Studies 1 and 2 found that the brands advertised in context-irrelevant ads were recognized better than the brands advertised in context-relevant ads. Encoding of irrelevant ads was associated with a conservative criterion bias, especially when these ads were presented in the condition with the high proportion of relevant ads. Ratio of relevant to irrelevant ads affected recognition of these ad types differently. Attitudes and behavioral intentions toward relevant ads were more positive than toward irrelevant ads. Theoretical implications of the study are connected to the advancement of the two-dimensional construct of thematic ad-context congruence. Practical implications are discussed in relation to paginated web formats, contextual advertising, and programmatic buying.

Soft Floors in Auctions

Several of the auction-driven exchanges that facilitate programmatic buying of internet display advertising have recently introduced “soft floors” in addition to standard reserve prices (called “hard floors” in the industry). A soft floor is a bid level below which a winning bidder pays his own bid instead of paying the second-highest bid as in a second-price auction most ad exchanges use by default. This paper characterizes soft floors’ revenue-generating potential as a function of the distribution of bidder independent private values. When bidders are symmetric (identically distributed), soft floors have no effect on revenue, because a symmetric equilibrium always exists in strictly monotonic bidding strategies, and standard revenue-equivalence arguments thus apply. The industry often motivates soft floors as tools for extracting additional expected revenue from an occasional high bidder, for example a bidder retargeting the consumer making the impression. Such asymmetries in the distribution of bidder preferences do not automatically make soft floors profitable. This paper presents two examples of tractable modeling assumptions about such occasional high bidders, with one example implying low soft floors always hurt revenues because of strategic bid-shading by the regular bidders, and the other example implying high soft floors can increase revenues by making the regular bidders bid more aggressively. This paper was accepted by Juanjuan Zhang, marketing.

Understanding Programmatic Creative: The Role of AI

In this article, we expand the concept of programmatic advertising to include programmatic creative as a vital component. While artificial intelligence (AI) has already automated the media buying process, the advertising creative process still requires extensive human efforts. Such discrepancy calls for AI to transform the advertising creative process. We provide a framework for understanding and investigating programmatic creative by drawing evidence from the advertising industry in China. We specifically discuss how big data and machine learning algorithms underpin programmatic advertising. We argue that AI will integrate programmatic buying and programmatic creative in the future. We also discuss the technological, regulatory, and legal challenges faced by programmatic creative. We argue that new theories and methods are needed to conduct research in this area and provide guidance for the advertising industry.

Ethical implications of digital advertising automation: The case of programmatic advertising in Spain

Ineffective traditional advertising planning methods, the growing advertising saturation of digital media, and the disrupting influence of the digital players in the advertising sector have created a need for new methods and tools for advertising in today’s ubiquitous Internet. Programmatic advertising is currently considered one of the most efficient forms of automation in the new online advertising environment and is excelling in major advertising markets like the US and United Kingdom. In Spain, however, there are still some important unaddressed questions regarding the level of implementation on a national and regional scale and the ethical implications derived from the implementation of this new technology. To address these points we have carried out qualitative research using a panel of experts with relevant background on the use of programmatic buying technology on a daily basis. The results stress the need for adapting capabilities in a rapidly evolving advertising sector, in which new technologies give rise to new complex processes with important ethical and reputational implications. We have identified a major contradiction between professionals’ views and users’ perceptions; the responsible use of these tools and the ability to identify the consequences of them appear to be a professional and functional challenge.

Teaching Digital Analytics with Google’s AEK

Teaching Digital Analytics with Google’s AEK Hairong Li (bio) Advertising education is in constant evolution to better meet the needs of future professionals in an ever-changing advertising business. With the proliferation of digital media, vast amounts of user data are cumulated as a byproduct of normal media consumption, and by appropriate privacy protection, they are a gold mine for consumer insights. When users visit a website, search for a product online, make a post on Facebook, buy a product online, or use a location-based service from a smartphone, they leave their digital footprints. Such real-time data have greatly benefited the operations of numerous websites and mobile apps, the services of major research firms such as Nielsen and comScore, and the business of a new generation of data aggregators, warehouses, and analytics. As a result, Big Data has played a greater role in the creation, placement, and evaluation of advertising, especially in the ways of consumer engagement. Consumer insights—through often-real-time digital analytics that show how consumers search for product information, what makes them like a product, what they say online, and where they buy a product—are shaping almost every aspect of advertising practice. Thus, the knowledge about and skills in collecting, processing, managing, analyzing, and reporting large volumes of consumer data have become a sought-after competency of advertising students. It is imperative to develop curricula and conduct research on Big Data-related topics such as computational advertising, social listening, programmatic buying, and advertising analytics, as some advertising programs in the US and other countries have already started. For example, a pre-conference on Big Data for advertising research and education was held at the American Academy of Advertising (AAA) conference in Atlanta, Georgia, on March 27, 2014, where expert panelists from industry and academia explored how Big Data approaches could be introduced in advertising research and education.1 During the first-of-its-kind pre-conference, panelists shared academic studies with Big Data methods, cases of using Big Data in advertising campaigns, possible topics of computational advertising courses, and perspectives on emerging issues. The large audience at the full-day pre-conference indicated a wide interest among the AAA members. As a follow-up, a pre-conference on computational advertising was planned for the AAA conference in Boston, Massachusetts, on March 23, 2017, with digital analytics as a focus for presentations and discussion.2 Early efforts indicate, however, that teaching digital analytics in the classroom is challenging, because shareable materials to build a fundamental understanding of analytics, including real world business data and the opportunity to perform a diverse range of analysis using an analytics tool, are not easily accessible to most advertising instructors and students. The Purpose Thus, the purpose of this article is to share our experience in developing and teaching a digital analytics course for undergraduate advertising majors. This online course covered the basic concepts of digital analytics and actual use of live data to generate consumer insights on key aspects of e-commerce. Digital analytics is a large and complex subject, and it includes web analytics, mobile analytics, and social analytics. This introductory course was designed to focus on web analytics, but it also covered parts of mobile analytics and social analytics that were directly related to web analytics. For example, traffic sources from mobile devices and social media platforms were explored, as they are becoming increasingly important in understanding multichannel users. The course objectives were for students to acquire knowledge about the mechanism of digital analytics, the ability to organize, interpret, and report data for consumer insights, and the skills to effectively use digital analytics tools to complete assigned tasks. This knowledge, together with these abilities and skills, should prepare students for an entry level data analyst position in advertising agencies, media outlets, and client companies. Students would get access to a real e-commerce site that was equipped with Google Analytics to practice with live data, using Google’s Analytics Education Kit (AEK), an education outreach program that is to be officially released in 2017. Analytics Education Kit (AEK) The course was facilitated with Google’s AEK. The AEK provides a number of resources to overcome...

Real-Time Bidding Rules of Thumb: Analytically Optimizing the Programmatic Buying of Ad-Inventory

Real-Time Bidding Rules of Thumb: Analytically Optimizing the Programmatic Buying of Ad-Inventory