Abstract
In this study, we present a novel cost-sensitive approach for uplift modeling in the context of cross-selling and workforce analytics. We leverage referrals from sales agents across business units to estimate the individual treatment effects of incentives on the cross-selling outcomes within a company. Uplift modeling is employed to predict relationships between salespeople that should be encouraged based on the probability of successful cross-selling – defined when a customer accepts the product suggested by sales agents. We conducted experiments on data from a Chilean financial group, evaluating both statistical and profit metrics. Exploring various machine learning classifiers for predictive purposes, we observed a significant improvement over the current approach, which exhibits an uplift below 0.01. Finally, we show that selecting the best classifier with profit metrics results in a 31.6% improvement in terms of average customer profit. This emphasizes the importance of defining an adequate compensation scheme and integrating it into the modeling process.
It is of utmost importance for marketing academics and service industry practitioners to understand the factors that influence customer satisfaction. This study proposes a novel framework to analyze open-ended survey data and extract drivers of customer satisfaction. This is done automatically via deep learning models for natural language processing. According to 11 drivers acknowledged by the marketing literature to determine customer experience, the data is cast into a multi-label classification problem. This expert system not only supports the automatic analysis of new data but also ranks the drivers according to their importance to various service industries and provides important insights into their applications. Experiments carried out using 25,943 customer survey responses related to 39 service companies in 13 different economic sectors show that the drivers can be identified accurately
E3 es una metodología novedosa que ayuda a ejecutivos y dueños de empresa a diseñar y a gestionar(Experiencias) de clientes, de acuerdo con la propuesta de valor de la compañía (Efectivas) y haciendo un uso adecuado de los recursos que dispone la organización (Eficiente). Es E3 porque se necesita que las 3 “Es” sean simultáneamente bien gestionadas para asegurar el éxito de las organizaciones. El libro presenta el marco conceptual donde se describen las 3 Es y la relación entre estas dimensiones, un sistema de medición, una propuesta para aplicar la metodología en la práctica en cualquier organización, y tres estudios de casos que ilustran la metodología.