Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection

Churn modeling is important to sustain profitable customer relationships in saturated consumer markets. A churn model predicts the likelihood of customer defection. This is important to target retention offers to the right customers and to use marketing resources efficiently. The prevailing approach toward churn model development, supervised learning, suffers an important limitation: it does not allow the marketing analyst to account for campaign planning objectives and constraints during model building. Our key proposition is that creating a churn model in awareness of actual business requirements increases the performance of the final model for marketing decision support. To demonstrate this, we propose a decision-centric framework to create churn models. We test our modeling framework on eight real-life churn data sets and find that it performs significantly better than state-of-the-art churn models. Further analysis suggests that this improvement comes directly from incorporating business objectives into model building, which confirms the effectiveness of the proposed framework. In particular, we estimate that our approach increases the per customer profits of retention campaigns by $.47 on average

The Role of Socio-Demographic Factors in the Coverage of Breast Cancer Screening:Insights From a Quantile Regression Analysis

Background: In Flanders, breast cancer (BC) screening is performed in a population-based breast cancer screening program (BCSP), as well as in an opportunistic setting. Women with different socio-demographic characteristics are not equally covered by BC screening. Objective: To evaluate the role of socio-demographic characteristics on the lowest 10th and highest 90th quantile levels of BC screening coverage. Methods: The 2017 neighborhood-level coverage rates of 8,690 neighborhoods with women aged 50-69 and eligible for BCSP and opportunistic screening were linked to socio-demographic data. The association between socio-demographic characteristics and the coverage rates of BCSP and opportunistic screening was evaluated per quantile of coverage using multivariable quantile regression models, with specific attention to the lowest 10th and highest 90th quantiles. Results: The median coverage in the BCSP was 50%, 33.5% in the 10th quantile, and 64.5% in the 90th quantile. The median coverage of the opportunistic screening was 12, 4.2, and 24.8% in the 10th and 90th quantile, respectively. A lower coverage of BCSP was found in neighborhoods with more foreign residents and larger average household size, which were considered indicators for a lower socioeconomic status (SES). However, a higher average personal annual income, which was considered an indicator for a higher SES, was also found in neighborhoods with lower coverage of BCSP. For these neighborhoods, that have a relatively low and high SES, the negative association between the percentage of foreign residents, average household size, and average personal annual income and the coverage in the BCSP had the smallest regression coefficient and 95% confidence interval (CI) values were -0.75 (95% CI: -0.85, -0.65), -13.59 (95% CI: -15.81, -11.37), and -1.05 (95% CI: -1.18, -0.92), respectively, for the 10th quantile. The neighborhoods with higher coverage of opportunistic screening had a relatively higher average personal annual income, with the largest regression coefficient of 1.72 (95% CI: 1.59, 1.85) for the 90th quantile. Conclusions: Women from relatively low and high SES neighborhoods tend to participate less in the BCSP, whereas women with a relatively high SES tend to participate more in opportunistic screening. For women from low SES neighborhoods, tailored interventions are needed to improve the coverage of BCSP

Consensus guidelines for the use and interpretation of angiogenesis assays

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference