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Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.
A sustainable strategy for O-trifluoromethylation of electron-deficient phenols by combining electrochemical synthesis with flow technology is presented. The reaction is optimized by screening experiments to establish a fast and efficient flow protocol. Simultaneous anodic oxidation of Langlois reagent and the phenols in a micro flow cell leads to direct preparation of trifluoromethyl ethers in yields up to 90%. This one-step protocol is tolerant of several functional groups, shows good regioselectivity and works without any chemical oxidants and catalysts by using electrical current as an inexpensive and sustainable reagent.
Background and Aims: In patients with advanced liver cirrhosis due to chronic hepatitis C virus (HCV) infection antiviral therapy with peginterferon and ribavirin is feasible in selected cases only due to potentially life-threatening side effects. However, predictive factors associated with hepatic decompensation during antiviral therapy are poorly defined.
Methods: In a retrospective cohort study, 68 patients with HCV-associated liver cirrhosis (mean MELD score 9.18±2.72) were treated with peginterferon and ribavirin. Clinical events indicating hepatic decompensation (onset of ascites, hepatic encephalopathy, upper gastrointestinal bleeding, hospitalization) as well as laboratory data were recorded at baseline and during a follow up period of 72 weeks after initiation of antiviral therapy. To monitor long term sequelae of end stage liver disease an extended follow up for HCC development, transplantation and death was applied (240weeks, ±SD 136weeks).
Results: Eighteen patients (26.5%) achieved a sustained virologic response. During the observational period a hepatic decompensation was observed in 36.8%. Patients with hepatic decompensation had higher MELD scores (10.84 vs. 8.23, p<0.001) and higher mean bilirubin levels (26.74 vs. 14.63 µmol/l, p<0.001), as well as lower serum albumin levels (38.2 vs. 41.1 g/l, p = 0.015), mean platelets (102.64 vs. 138.95/nl, p = 0.014) and mean leukocytes (4.02 vs. 5.68/nl, p = 0.002) at baseline as compared to those without decompensation. In the multivariate analysis the MELD score remained independently associated with hepatic decompensation (OR 1.56, 1.18–2.07; p = 0.002). When the patients were grouped according to their baseline MELD scores, hepatic decompensation occurred in 22%, 59%, and 83% of patients with MELD scores of 6–9, 10–13, and >14, respectively. Baseline MELD score was significantly associated with the risk for transplantation/death (p<0.001).
Conclusions: Our data suggest that the baseline MELD score predicts the risk of hepatic decompensation during antiviral therapy and thus contributes to decision making when antiviral therapy is discussed in HCV patients with advanced liver cirrhosis.
Customer loyalty is a critical measure for success, showing if a firm's product is received well by its customers. To understand its development over time, two fundamental questions must be answered: (I) How will current customers' loyalty develop, and (II) will new customers' loyalty differ from current customers' loyalty? The authors empirically answer these questions based on a data set including ~500 B2B web technologies with jointly ~325 million customers spanning over 24 years. They show that loyalty hardly develops and, if so, it rather decreases than increases. The loyalty of current customers rarely changes and, if so, rather increases than decreases. New customers are most likely less loyal than current customers. These results show that by failing to account for these underlying developments, stakeholders, in most cases, draw the wrong conclusions about product value measured via customer lifetime value.