User Acquisition and Engagement in Digital News Media

Generating revenue has been a major issue for the news industry and journalism over the past decade. In fact, vast availability of free online news sources causes online news media agencies to face user acquisition and engagement as pressing issues more than before. Although digital news media agencies are seeking sustainable relationships with their users, their current business models do not satisfy this demand. As a matter of fact, they need to understand and predict how much an article can engage a reader as a crucial step in attracting readers, and then maximize the engagement using some strategies. Moreover, news media companies need effective algorithmic tools to identify users who are prone to subscription. Last but not least, online news agencies need to make smarter decisions in the way that they deliver articles to users to maximize the potential benefits. In this dissertation, we take the first steps towards achieving these goals and investigate these challenges from data mining /machine learning perspectives. First, we investigate the problem of understanding and predicting article engagement in terms of dwell time as one of the most important factors in digital news media. In particular, we design data exploratory models studying the textual elements (e.g., events, emotions) involved in article stories, and find their relationships with the engagement patterns. In the prediction task, we design a framework to predict the article dwell time based on a deep neural network architecture which exploits the interactions among important elements (i.e., augmented features) in the article content as well as the neural representation of the content to achieve the better performance. In the second part of the dissertation, we address the problem of identifying valuable visitors who are likely to subscribe in the future. We suggest that the decision for subscription is not a sudden, instantaneous action, but it is the informed decision based on positive experience with the newspaper. As such, we propose effective engagement measures and show that they are effective in building the predictive model for subscription. We design a model that predicts not only the potential subscribers but also the time that a user would subscribe. In the last part of this thesis, we consider the paywall problem in online newspapers. The traditional paywall method offers a non-subscribed reader a fixed number of free articles in a period of time (e.g., a month), and then directs the user to the subscription page for further reading. We argue that there is no direct relationship between the number of paywalls presented to readers and the number of subscriptions, and that this artificial barrier, if not used well, may disengage potential subscribers and thus may not well serve its purpose of increasing revenue. We propose an adaptive paywall mechanism to balance the benefit of showing an article against that of displaying the paywall (i.e., terminating the session). We first define the notion of cost and utility that are used to define an objective function for optimal paywall decision making. Then, we model the problem as a stochastic sequential decision process. Finally, we propose an efficient policy function for paywall decision making. All the proposed models are evaluated on real datasets from The Globe and Mail which is a major newspaper in Canada. However, the proposed techniques are not limited to any particular dataset or strict requirement. Alternatively, they are designed based on the datasets and settings which are available and common to most of newspapers. Therefore, the models are general and can be applied by any online newspaper to improve user engagement and acquisition

Data Science, Machine learning and big data in Digital Journalism: A survey of state-of-the-art, challenges and opportunities

Digital journalism has faced a dramatic change and media companies are challenged to use data science algo-rithms to be more competitive in a Big Data era. While this is a relatively new area of study in the media landscape, the use of machine learning and artificial intelligence has increased substantially over the last few years. In particular, the adoption of data science models for personalization and recommendation has attracted the attention of several media publishers. Following this trend, this paper presents a research literature analysis on the role of Data Science (DS) in Digital Journalism (DJ). Specifically, the aim is to present a critical literature review, synthetizing the main application areas of DS in DJ, highlighting research gaps, challenges, and op-portunities for future studies. Through a systematic literature review integrating bibliometric search, text min-ing, and qualitative discussion, the relevant literature was identified and extensively analyzed. The review reveals an increasing use of DS methods in DJ, with almost 47% of the research being published in the last three years. An hierarchical clustering highlighted six main research domains focused on text mining, event extraction, online comment analysis, recommendation systems, automated journalism, and exploratory data analysis along with some machine learning approaches. Future research directions comprise developing models to improve personalization and engagement features, exploring recommendation algorithms, testing new automated jour-nalism solutions, and improving paywall mechanisms.Acknowledgements This work was supported by the FCT-Funda?a ? o para a Ciência e Tecnologia, under the Projects: UIDB/04466/2020, UIDP/04466/2020, and UIDB/00319/2020

Revenue models in the context of online digital audio companies: Making an optimal choice between advertising and paid subscriptions

Objectives of the Study This study sets out to examine the digital Internet audio market through eight case companies and their business models, and determine whether future entrants into the market should focus their monetization efforts on advertising-based models or subscription-based models. The main objective of the study is to provide an educated guess on which revenue models future entrants should emphasize based on the current situation in the market today. Academic background and methodology The study is based on research into business models, targeted and mobile advertising, and winner-take-all market characteristics in platform industries. A widely used business model evaluation framework is described and used to assess the selected case companies to examine the current characteristics of players in the market in detail. The results of the empirical study are then used as a basis for formulating key findings about the market and to formulate a recommendation for future market entrants concerning their potential choice of revenue model and value proposition. Findings and conclusions The study finds that digital Internet audio companies are roughly divided into two camps: subscription-based companies offering on-demand music and advertising-based companies offering streaming audio in various different collections of feature sets. Despite many negative arguments against selling advertising, the study finds that it is still a smarter market to enter into given the winner-take-all tendencies of the subscription-based market and the significant funding incumbents are competing with against each other already. Future avenues for research are opened in studying whether a winner-take-all market truly does emerge in subscription-based online music, in how strongly Internet audio advertising ends up growing, and how a revenue model is determined and then paired with a logical value proposition that fits it

Motivations in the adoption and conversion of Music Freemium Services

Mestrado Bolonha em MarketingCom o recente avanço tecnológico, é possível ouvir música de novas maneiras. Isto resultou no aumento do valor de mercado da música e no surgimento de diversos serviços de streaming on-demand com o modelo de negócio freemium. Estes serviços têm sucesso, especialmente, quando os seus utilizadores convertem a sua subscrição de free para premium. O presente trabalho propõe-se a estudar quais as motivações que levam os consumidores a adotar uma plataforma de streaming de música, e quais as motivações e características de utilizador que levam à conversão para o serviço premium. Alguns estudos dedicaram-se a explicar o porquê desta conversão, mas pouco foi pesquisado no que toca às motivações dos consumidores para distinguir entre diferentes plataformas. Para aprofundar estas questões, este estudo analisa um conjunto de motivações e caraterísticas de utilizador como variáveis explicativas em conjunto, de forma original, não encontrada na literatura. Deste modo, os dados foram obtidos através de um inquérito online, com uma amostra de 231 utilizadores portugueses de plataformas de streaming. Os resultados principais apontam que a satisfação, valor percebido e ubiquidade são motivações estatisticamente significativas que influenciam positivamente a escolha de diferentes plataformas. Para além disto, as mesmas motivações, bem como a idade e ocupação (características de utilizador) mostraram-se impactantes no que diz respeito à conversão, sendo relevante do ponto de vista teórico e do ponto de vista prático. No entanto, os resultados destacam a influência negativa da satisfação e idade nesta compra. Isto significa que um utilizador altamente satisfeito não se converte e de modo semelhante, quanto mais velho for o utilizador, menos provável é que a compra ocorra. Não há evidência estatística que as motivações de descoberta, exclusividade, social e personalização e as restantes características de utilizador influenciem a conversão de utilizadores free em utilizadores premium.With the recent technological advancement, music is being experienced in new ways. This resulted in the rising value of the music market and the surge of diverse on-demand streaming services with the freemium business model. These services thrive especially when its users convert their subscription from free to premium. The current dissertation aims to study what motivations drive consumers to adopt different music streaming platforms and what motivations and user characteristics leads them to convert to the premium service. Several studies endeavoured on explaining this phenomenon, but little research was dedicated on what are the motivations for consumers to distinguish between different platforms. To enhance comprehension in this matter, this study analysis a group of motivations and user characteristics as explanatory variables together as a set, in a original way, not found on the literature. Thus, data was obtained via an online questionnaire, with a sample of 231 Portuguese users of streaming platforms. The main results suggest that satisfaction, perceived value and ubiquity are statistically significant motivations that positively influence choosing a different platform. Regarding subscribing to the premium service, the same motivations, as well as age and occupation (user characteristics) present influential results, which poses relevancy from a theorical point of view and managerial point of view. However, the findings highlight satisfaction and age as negative influences for this purchase. This means that highly satisfied free users don’t convert and similarly, the older the consumer, the less likely the conversion happens. No statistical evidence was found in discovery, exclusivity, social and personalization motivations alongside the remaining user characteristics for the conversion of free users into premium users.info:eu-repo/semantics/publishedVersio

Prospects of Mobile Search

Search faces (at least) two major challenges. One is to improve efficiency of retrieving relevant content for all digital formats (images, audio, video, 3D shapes, etc). The second is making relevant information retrievable in a range of platforms, particularly in high diffusion ones as mobiles. The two challenges are interrelated but distinct. This report aims at assessing the potential of future Mobile Search. Two broad groups of search-based applications can be identified. The first one is the adaptation and emulation of web search processes and services to the mobile environment. The second one is services exploiting the unique features of the mobile devices and the mobile environments. Examples of these context-aware services include location-based services or interfacing to the internet of things (RFID networks). The report starts by providing an introduction to mobile search. It highlights differences and commonalities with search technologies on other platforms (Chapter 1). Chapter 2 is devoted to the supply side of mobile search markets. It describes mobile markets, presents key figures and gives an outline of main business models and players. Chapter 3 is dedicated to the demand side of the market. It studies users¿ acceptance and demand using the results on a case study in Sweden. Chapter 4 presents emerging trends in technology and markets that could shape mobile search. It is the author's view after discussing with many experts. One input to this discussion was the analysis of on forward-looking scenarios for mobile developed by the authors (Chapter 5). Experts were asked to evaluate these scenarios. Another input was a questionnaire to which 61 experts responded. Drivers, barriers and enablers for mobile search have been synthesised into SWOT analysis. The report concludes with some policy recommendations in view of the likely socio-economic implications of mobile search in Europe.JRC.DG.J.4-Information Societ

Big Data Ethics in Research

The main problems faced by scientists in working with Big Data sets, highlighting the main ethical issues, taking into account the legislation of the European Union. After a brief Introduction to Big Data, the Technology section presents specific research applications. There is an approach to the main philosophical issues in Philosophical Aspects, and Legal Aspects with specific ethical issues in the EU Regulation on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (Data Protection Directive - General Data Protection Regulation, "GDPR"). The Ethics Issues section details the specific aspects of Big Data. After a brief section of Big Data Research, I finalize my work with the presentation of Conclusions on research ethics in working with Big Data. CONTENTS: Abstract 1. Introduction - 1.1 Definitions - 1.2 Big Data dimensions 2. Technology - 2.1 Applications - - 2.1.1 In research 3. Philosophical aspects 4. Legal aspects - 4.1 GDPR - - Stages of processing of personal data - - Principles of data processing - - Privacy policy and transparency - - Purposes of data processing - - Design and implicit confidentiality - - The (legal) paradox of Big Data 5. Ethical issues - Ethics in research - Awareness - Consent - Control - Transparency - Trust - Ownership - Surveillance and security - Digital identity - Tailored reality - De-identification - Digital inequality - Privacy 6. Big Data research Conclusions Bibliography DOI: 10.13140/RG.2.2.11054.4640

How to improve customer retention and lifetime value on subscription-based models: In company project with "The Bam and Boo" toothbrush

The present In-Company project aims to study how subscription-based business models can improve their retention and customers lifetime value. This project was made in collaboration with ‘The Bam and Boo’ Toothbrush, a Portuguese brand bamboo toothbrushes subscription service that is in the market since June 2017 and currently accounts with more than 22.000 active subscribers. To achieve these project results we have used quantitative data from the company database reports, and qualitative data collected on a focus group session with a group of participants that resembles the brand’s target. From this data we were able to trigger some critical stages of retention and consumption patterns, and valuable insights regarding consumers behaviors and purchase profiles. Some of the critical questions that needed to be answered were related to – understand the moment of customers churns, which are the motives that led customers to make this action, and how is the company able to improve its customers lifetime and value. We present solutions on areas such as Communication, Customer Relationship Management, Product, and Organizational Strategy, in order to improve the company retention rates and overall results. For that the company should consider delivering a more personalized service and content to its customers, run a stronger email marketing strategy, rethink its portfolio, and share the company values and mission with its community.O presente projeto-empresa visa estudar de que forma conseguimos melhorar a retenção e o valor dos clientes em modelos de subscrição. Este projeto foi realizado em colaboração com a empresa 'The Bam and Boo', um serviço de subscrição de escovas de dentes de bambu. A marca portuguesa está no mercado desde Junho, 2017 e atualmente conta com mais de 22.000 subscritores ativos. De forma a alcançar os resultados propostos neste projeto recorremos a dados quantitativos, obtidos através da base de dados de clientes da empresa, e dados qualitativos, recolhidos de uma sessão com um grupo focal no qual os participantes representavam o target da marca. Assim, foi-nos possível detetar pontos críticos em relação aos padrões e comportamento dos consumidores, e os seus perfis de compra. As questões principais que pretendemos responder neste projeto são – compreender o momento em que os clientes desistem das suas subscrições, por que motivos o fazem e de que forma a marca pode aumentar o valor e a retenção dos seus clientes. Apresentamos soluções em áreas como – comunicação, gestão e relacionamento com os clientes, produto e estratégia da organização; com o fim de melhorar as taxas de retenção e os resultados da empresa como um todo. Para isso, a empresa deve reconsiderar algumas das suas políticas e oferecer um serviço mais personalizado e diversificado aos seus clientes, montar uma estratégia de email marketing mais forte, reconsiderar o seu portfólio de produtos, e a forma de partilha dos seus valores e missão com a sua comunidade