Customer Lifetime Value Prediction in Non-Contractual Freemium Settings: Chasing High-Value Users Using Deep Neural Networks and SMOTE

In non-contractual freemium and sharing economy settings, a small share of users often drives the largest part of revenue for firms and co-finances the free provision of the product or service to a large number of users. Successfully retaining and upselling such high-value users can be crucial to firms\u27 survival. Predictions of customers\u27 Lifetime Value (LTV) are a much used tool to identify high-value users and inform marketing initiatives. This paper frames the related prediction problem and applies a number of common machine learning methods for the prediction of individual-level LTV. As only a small subset of users ever makes a purchase, data are highly imbalanced. The study therefore combines said methods with synthetic minority oversampling (SMOTE) in an attempt to achieve better prediction performance. Results indicate that data augmentation with SMOTE improves prediction performance for premium and high-value users, especially when used in combination with deep neural networks

Implantação da avaliação da dinâmica temporal e espacial de processos neurais na eletroencefalografia

TCC(graduação) - Universidade Federal de Santa Catarina. Centro de Ciências Biológicas. Biologia.Uma das ferramentas para avaliação dos processos neurológicos é a eletroencefalografia (EEG), que apresenta diversas técnicas para o estudo das atividades neuronais, suas intercomunicações e funções. Este trabalho apresenta um método para a utilização de duas técnicas de EEG em conjunto, Potencial Relacionado a Evento (ERP) e Tomografia Eletromagnética de Baixa Resolução (LORETA). A técnica de ERP tem o intuito de identificar, no tempo, atividades relevantes para estudo, enquanto a técnica de LORETA é uma tomografia de baixa resolução, identificando de onde provém o sinal registrado na EEG. Por meio do método proposto, é possível identificar os locais no tempo onde ocorrem as atividades relevantes (com o ERP) e analisar a dinâmica espacial cerebral de forma sequencial durante esse período (com a LORETA).One of the tools for evaluation of neurological processes is electroencephalography (EEG), which presents several techniques for the study of neuronal activities, their intercommunications and functions. This work presents a method for the use of two EEG techniques in conjunction, Event Related Potential (ERP) and Low Resolution Electromagnetic Tomography (LORETA). The ERP technique aims to identify, in time, relevant activities for study, while the LORETA technique is a low resolution tomography, identifying where the EEG signal comes from. By means of the proposed method, it is possible to identify the locations in the time where the relevant activities occur (with the ERP) and to analyze the cerebral spatial dynamics in a sequential way during that period (with LORETA)

Privacy-centric digital advertising: implications for research

Yesterday's digital advertising relied on cross-website and cross-app user identity to measure, target, and optimize ads. Spurred by regulatory pressure, today's digital advertising is evolving to become more privacy-protective. Apple and Google are leading this movement by sunsetting old technologies and building more privacy-centric alternatives. Marketing academics and practitioners, in turn, must learn to adapt to this new reality. We outline these new advertising approaches and their implications for advertising strategy, targeting, and measurement. We propose key questions and an agenda for researchers to help shape the privacy-centric future of digital advertising.https://papers.ssrn.com/abstract_id=3947290First author draf

COVID-19 Demand Shocks Revisited: Did Advertising Technology Help Mitigate Adverse Consequences for Small and Midsize Businesses?

Research has investigated the impact of the COVID-19 pandemic on business performance and survival, indicating particularly adverse effects for small and midsize businesses (SMBs). Yet only limited work has examined whether and how online advertising technology may have helped shape these outcomes, particularly for SMBs. The aim of this study is to address this gap. By constructing and analyzing a novel data set of more than 60,000 businesses in 49 countries, we examine the impact of government lockdowns on business survival. Using discrete-time survival models with instrumental variables and staggered difference-in-differences estimators, we find that government lockdowns increased the likelihood of SMB closure around the world but that use of online advertising technology attenuates this adverse effect. The findings show heterogeneity in country, industry, and business size, consistent with theoretical expectations

Epidemiology of Barrett’s Esophagus and Esophageal Adenocarcinoma

Barrett’s esophagus (BE) is a common condition, and is the precursor to esophageal adenocarcinoma, a disease with increasing burden in the western world, especially in Caucasian males. The incidence of BE increased dramatically during the late-20th century and incidence estimates continue to increase, with a prominent male:female ratio. The prevalence is between 0.5 – 2.0 percent. A number of anthropomorphic and behavioral risk factors exist for BE including obesity and tobacco smoking, but GERD is the strongest risk factor, and the risk is more pronounced with long-standing GERD. Esophageal adenocarcinoma (EAC) is the most common form of esophageal cancer in the U.S. Risk factors include GERD, tobacco smoking, and obesity, while NSAIDs and statins may be protective. A major factor predicting progression from non-dysplastic BE to EAC is the presence of dysplastic changes seen on esophageal histology, although a number of issues limit the utility of dysplasia as a marker for disease. Length of the involved BE segment is another risk for progression to high-grade dysplasia and cancer. Biomarkers have shown promise, but none are approved for clinical use

To Be or Not to Be … Social : Incorporating Simple Social Features in Mobile Game Customer Lifetime Value Predictions

Mobile games make up the largest segment of the games industry, in terms of revenue as well as players. Hundreds of thousands of games are available with most being free to download and play. In freemium games, revenue is predominantly generated by users making in-game purchases. As only a small fraction of users make purchases, predicting these users and their Customer Lifetime Value are key challenges in Game Analytics and currently barely explored in academic research. Furthermore, while social factors have been shown to be essential for retention in games in general, the impact on retention and monetization in mobile games is unexplored. In this paper, the problem of defining social features in freemium casual mobile games is addressed through a case study with over 200,000 players. The study evaluates the influence of specific types of social interactions typical of casual mobile games, on predictions of premium users and Customer Lifetime Value by applying classifiers and regression models respectively. Results indicate that social activity does not correlate with the tendency to become a premium user, but that social activity increases over time in a cohort

Spin fluctuations in nearly magnetic metals from ab-initio dynamical spin susceptibility calculations:application to Pd and Cr95V5

We describe our theoretical formalism and computational scheme for making ab-initio calculations of the dynamic paramagnetic spin susceptibilities of metals and alloys at finite temperatures. Its basis is Time-Dependent Density Functional Theory within an electronic multiple scattering, imaginary time Green function formalism. Results receive a natural interpretation in terms of overdamped oscillator systems making them suitable for incorporation into spin fluctuation theories. For illustration we apply our method to the nearly ferromagnetic metal Pd and the nearly antiferromagnetic chromium alloy Cr95V5. We compare and contrast the spin dynamics of these two metals and in each case identify those fluctuations with relaxation times much longer than typical electronic `hopping times'Comment: 21 pages, 9 figures. To appear in Physical Review B (July 2000

Preparedness of the CTSA's Structural and Scientific Assets to Support the Mission of the National Center for Advancing Translational Sciences (NCATS)

The formation of the National Center for Advancing Translational Sciences (NCATS) brings new promise for moving basic and discoveries to clinical practice, ultimately improving the health of the nation. The CTSA sites, now housed with NCATS, are organized and prepared to support in this endeavor. The CTSAs provide a foundation for capitalizing on such promise through provision of a disease-agnostic infrastructure devoted to C&T science, maintenance of training programs designed for C&T investigators of the future, by incentivizing institutional reorganization and by cultivating institutional support