Scalable Audience Reach Estimation in Real-time Online Advertising

Online advertising has been introduced as one of the most efficient methods of advertising throughout the recent years. Yet, advertisers are concerned about the efficiency of their online advertising campaigns and consequently, would like to restrict their ad impressions to certain websites and/or certain groups of audience. These restrictions, known as targeting criteria, limit the reachability for better performance. This trade-off between reachability and performance illustrates a need for a forecasting system that can quickly predict/estimate (with good accuracy) this trade-off. Designing such a system is challenging due to (a) the huge amount of data to process, and, (b) the need for fast and accurate estimates. In this paper, we propose a distributed fault tolerant system that can generate such estimates fast with good accuracy. The main idea is to keep a small representative sample in memory across multiple machines and formulate the forecasting problem as queries against the sample. The key challenge is to find the best strata across the past data, perform multivariate stratified sampling while ensuring fuzzy fall-back to cover the small minorities. Our results show a significant improvement over the uniform and simple stratified sampling strategies which are currently widely used in the industry

Leveraging analytics to produce compelling and profitable film content

Producing compelling film content profitably is a top priority to the long-term prosperity of the film industry. Advances in digital technologies, increasing availabilities of granular big data, rapid diffusion of analytic techniques, and intensified competition from user generated content and original content produced by Subscription Video on Demand (SVOD) platforms have created unparalleled needs and opportunities for film producers to leverage analytics in content production. Built upon the theories of value creation and film production, this article proposes a conceptual framework of key analytic techniques that film producers may engage throughout the production process, such as script analytics, talent analytics, and audience analytics. The article further synthesizes the state-of-the-art research on and applications of these analytics, discuss the prospect of leveraging analytics in film production, and suggest fruitful avenues for future research with important managerial implications

Integrating digital analytics in strategic marketing decision making : An absorptive capacity approach

Over the last two decades, digital analytics has evolved from simply monitoring clicks to ever more complex campaign analyses and evaluations of marketing communication performance. However, the rapid rate of technological development has overshadowed the strategic importance of digital analytics for marketing practitioners and researchers alike. This has led to a situation, where the technical execution of digital analytics has become known relatively well but its practical benefits and purposes have been left without much attention. This research aims to breach this research gap by answering the question: how can companies integrate digital analytics in their strategic marketing decision making. This is a qualitative single case study, the focus of which is the company Unilever. The empirical data comprises eight semi-structured interviews as well as two digital analytics reports supplied by the case company. Literature on the absorptive capacity theory and strategic marketing decision making was used as a basis for the analysis of the data. The research findings suggest that it is possible to use digital analytics to generate strategically relevant knowledge on actual customer behaviour, wants and interests. The findings also indicate that digital analytics as a concept is broad and consists of several analytics subclasses, each with their distinctive characteristics and purposes. Furthermore, the findings highlight the challenges and obstacles that companies face in their attempts to integrate digital analytics in their strategic decision making processes. The main theoretical contribution of this study is to illuminate the strategic relevance of digital analytics. Digital analytics should not be viewed simply as a tool to monitor on-going marketing campaigns; in the right hands, it can generate valuable insights to support strategic marketing decision making. Another significant contribution is the conceptualisation of digital marketing knowledge. This research presents strong evidence to support the statement that the knowledge generated through digital analytics is fundamentally different from that of conventional consumer and market research. Companies can therefore use digital analytics to generate new insights on their customers, competitors and markets. In order to unleash this potential, companies must strive towards a flexible organisational structure and processes, offer purposeful employee training and support, develop a functional data management platform and be strategically committed towards developing their digital analytics capacity. Finally, this study provides research avenues for future research on the utility of digital analytics as a decision support tool. Further longitudinal analysis or a multiple case study on this research topic would work toward confirming, refuting or supplementing the results of this study

The Generation Z Audience for In-App Advertising

Abstract Purpose: The audience for in-app mobile advertising is comparable in size and viewing rate to that for TV but divides its attention across a highly fragmented selection of apps, each competing for advertiser revenue. In market, the assumption is that this audience is deeply segmented, allowing individuals to be contextually targeted on the apps that define their interests and needs. But that assumption is not supported by the Laws of Double Jeopardy and Duplication of Viewing which closely predict usage in other mass media. Our purpose is to benchmark in-app audiences against these laws to better understand market structure. Method: We collected nearly three thousand hours of screen time data from a panel of Generation Z respondents and tested the predictive validity of two models against observed interactions with twenty-three popular apps in six categories over a week. Findings. Results show that contrary to industry assumptions, this audience for in-app advertising is not segmented. Engagement on individual apps and sharing rates between apps and app formats is predicted well. Originality/Value: Many authors have called for consistency in metrics to compare on and off-line media performance. This study bridges that gap, demonstrating how reach and frequency measures could inform digital scheduling for contextual targeting. Implications Optimising in-app advertising for short-term activation only limits its potential for brand-building. These findings encourage advertisers to schedule online campaigns for brand reach as well as sales lift, by advancing current understanding of audience behaviour

WELCOME TO DIGITAL TRANSFORMATION ERA: FROM PROOF-OF-CONCEPT TO BIG DATA INSIGHTS CREATION

Digital transformation (DT) is no longer an optional strategic priority, but the direction for managers of traditional firms that their success is built in the pre-digital era. With all hype around DT opportunities, it is rather a highly complex challenge that affects many or all segments of a firm and more so at the early stages of DT. Firms at the early stage of DT face the challenge of choosing among a big variety of existing and emerging technologies on the market, neglecting technological uncertainty, navigating through the technological solutions ocean, and avoiding hype-driven decisions while being technology competence-less. With this respect, the phase preceding any adoption or rejection of a new DT initiative and aiming at the first meeting and proving feasibility and commercial opportunities becomes increasingly important. The thesis investigates three particular phenomena of the earliest Digital Transformation (DT) stage, that are seemingly well-known and intuitively clear but suffer from the lack of empirical and conceptual evidence base as well as theoretical ground on closer inspection, namely, proof-of-concept, data-driven decision-making, and Big Data insights creation. Focusing on the three aspects of the early stage of DT allows building a research agenda that consists of complementing each other parts. Three-essays research was run with three related objectives. Each objective is addressed by conducting independent research using comparative methods. The thesis applies the qualitative approach as the overarching, with the relative to the three essays methodologies, namely, qualitative case study, ethnography, and participatory observation. The thesis uses qualitative methods to derive main findings and quantitative methods based on novel computational techniques to add more nuances to the results. This allows a new empirical and conceptual perspective on the earliest stages of DT. The findings suggest that a) cognitive biases drive what I labeled as perceived technology potentiality, moreover, technology awareness develops step-wise as PoC is run moving from borrowed technology awareness to minimum acquired technology awareness and enhanced technology awareness. These findings were used to explain how PoC dynamic changes with time. Further, findings show how b) different types of traps (cognitive and data) drive managerial trust in data when data-driven decision-making is first used. The findings were taken as the ground to build the three traps zones notion, where the decisions and trust in data are driven by different combinations of traps. Finally, findings reveal that c) Big Data dimensions have their related sub-dimensions, differences and similarities of which led to the discovery of the two effects of Big Data dimensions, namely, Proliferation and Additive. These findings helped to explain how exactly Big Data dimensions participate in the Big Data insights creation and to build the conceptual matrix of Big Data insights creation. In this vein, the research contributes to the technology innovation literature by shedding light on the phenomena of the earliest stage of DT and by initiating the first comprehensive conversation on PoC, data-driven decision-making, and Big Data insights creation. Further, the research contributes to the existing literature on managerial cognition, decision-making, and Big Data usefulness. Finally, contributions to methods in the technology innovation field are drawn

Viewability: An Exaggerated Crisis

This thesis addresses the ongoing debate surrounding Viewability within the digital advertising industry. Since advertising is the lifeblood of many publishers and sites across the web, it is vital that brands and marketers derive value from this relationship. The Media Rating Council and Making Measurement Make Sense Movement both over exaggerate the value of Viewability in the digital advertising marketplace. By examining a plethora of articles and regulatory standards, I have been able to conclude that Viewability is a soft metric that does not provide media insights into the success of a given campaign. By conducting interviews and reviewing articles from the advertising trade press, I have determined that marketers, advertising agencies and publishers must work in tandem to achieve a solution that is both sustainable economically and administrable on a mass scale. The implementation of corporate-specific Viewability standards for marketers would lead to a greater autonomy over the analysis of the success of a particular campaign. Publishers’ refocus on website redesign and roll out of innovative advertising units can drastically contribute to value generation for marketers. In addition, both the MRC and 3MS pivot towards traffic fraud would warrant greater fiscal control over industry media spending and an improved analysis of campaign data. Viewability across the digital advertising industry is simply a singular cog in the wheel of digital media injustice. If the MRC and 3MS refocus their efforts towards fraudulent traffic while adopting a laissez faire approach to tackling Viewability, both organizations will greatly aid in the growth and prosperity of a free and open Interne