Browsing by Author "Pinheiro, Paulo"
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- An actionable knowledge discovery system in regular sports servicesPublication . Pinheiro, Paulo; Cavique, LuísThis work presents an actionable knowledge discovery system for real user needs with three steps. In the first step, it extracts and transforms existing data in the databases of the ERP and CRM systems of the sports facilities and loads them into a Data Warehouse. In a second phase, predictive models are applied to identify profiles more susceptible to abandonment. Finally, in the third phase, based on the previous models, experimental planning is carried out, with test and control groups, in order to find concrete actions for customer retention.
- A bi‐objective procedure to deliver actionable knowledge in sport servicesPublication . Pinheiro, Paulo; Cavique, LuísThe increase in retention of customer in gyms and health clubs is nowadays a challenge that requires concrete and personalized actions. Traditional data mining studies focused essentially on predictive analytics, neglecting the business domain. This work presents an actionable knowledge discovery system which uses the following pipeline (data collection, predictive model, retention interventions). In the first step, it extracts and transforms existing real data from databases of the sports facilities. In a second step, predictive models are applied to identify user profiles more susceptible to dropout, where actionable withdrawal rules are based on actionable attributes. Finally, in the third step, based on the previous actionable knowledge some of the values of the actionable attributes should be changed in order to increase retention. Simulation of scenarios is carried out, with test and control groups, where business utility and associate cost are measured. This document presents a bi-objective study in order to choose the more efficient scenarios.
- Determinação de padrões de desistência em ginásiosPublication . Pinheiro, Paulo; Cavique, LuísO mercado do Fitness regista uma taxa de abandono na ordem dos 40 a 45%, taxa que é considerada muito elevada, tendo em consideração outros sectores de mercado. Este trabalho tem por principal objetivo, através de técnicas de Classificação, determinar o algoritmo mais adequado para encontrar padrões que permitam prever quais os utentes que irão abandonar ou cancelar a sua inscrição num próximo período, atendendo ao padrão de perfil dos utentes que desistiram nos últimos meses, ao seu padrão de consumo e utilização e a eventuais dados demográficos que se venham a considerar relevantes para o estudo em questão.
- Determinação de padrões de desistência em ginásiosPublication . Pinheiro, Paulo; Cavique, LuísO problema da retenção e das causas que levam à desistência da frequência do ginásio é uma questão que os ginásios e academias de fitness tentam há muito entender e consequentemente evitar. Tendo em atenção que a indústria do Fitness tem apostado na instalação massificada de sistemas avançados de Customer Relationship Management (CRM) existem atualmente bases de dados com dados históricos de grande valia. Este projeto tem por objetivo aplicar técnicas de classificação a estas bases de dados de forma a encontrar um método adequado para determinar padrões que permitam prever quais os utentes que irão abandonar ou cancelar a sua inscrição num período próximo, atendendo ao padrão do perfil de comportamento dos utentes que desistiram nos últimos meses, e criar uma ferramenta que forneça informação que permita aos gestores desses ginásios tomar medidas que permitam prolongar a duração da frequência dos utentes.
- Extracting actionable knowledge to increase business utility in sport servicesPublication . Pinheiro, Paulo; Cavique, LuísThe increase in retention of customer in gyms and health clubs is nowadays a challenge that requires concrete and personalized actions. Traditional data mining studies focused essentially on predictive analytics, neglecting the business domain. This work presents an actionable knowledge discovery system which uses the following pipeline (data collection, predictive model, loyalty actions). In the first step, it extracts and transforms existing real data from databases of the sports facilities. In a second step, predictive models are applied to identify user profiles more susceptible to dropout. Actionable rules are generated based on actionable attributes that should be avoided, in order to increase retention. Finally, in the third step, based on the previous actionable knowledge, experimental planning is carried out, with test and control groups, in order to find the best loyalty actions for customer retention. This document presents a simulation and the measure of the business utility of an actions sequence to avoid dropout.
- Modelos para incremento da retenção em serviços desportivos regulares : análise preditiva e ações de fidelizaçãoPublication . Pinheiro, Paulo; Cavique, LuísAtrair um novo cliente pode custar até cinco vezes mais do que manter um cliente atual satisfeito e por isso a capacidade de detetar, o mais cedo possível, quais os clientes que irão abandonar ou deixar de adquirir um determinado produto ou serviço, bem como as medidas que podem ser implementadas para evitar esse abandono ou quebra nas vendas são questões que todas as empresas gostariam de ver respondidas. Neste trabalho é apresentado um sistema inteligente que gera conhecimento acionável (“actionable knowledge”) baseado em dados reais e orientado para acções de fidelização de clientes de serviços desportivos regulares onde ocorrem elevadas taxas de cancelamento. Seguindo os passos do Database Marketing o sistema evolui em três fases: numa primeira fase, parte de dados obtidos nas bases de dados dos sistemas ERP e CRM existentes nas instalações desportivas, dos quais extrai, transforma e carrega dados num Data Warehousing; numa segunda fase são aplicados modelos preditivos para identificar perfis mais suscetíveis de abandono; e por fim, são aplicadas ações de fidelização direcionadas a cada um dos perfis encontrados com o objetivo de aumentar a fidelização e a taxa de retenção.
- Modelos para incremento da retenção em serviços desportivos regulares: análise preditiva e ações de fidelizaçãoPublication . Pinheiro, Paulo; Cavique, LuísAs instalações desportivas que oferecem serviços desportivos regulares têm vindo a adotar sistemas ERP e CRM, existindo atualmente bases de dados com dados históricos de grande valia. Neste trabalho demonstramos que aplicando modelos preditivos a estes dados é possível identificar perfis de abandono. Com base nos perfis encontrados é realizado um planeamento de experiências, com grupos de teste e controlo, com vista a encontrar ações concretas de fidelização.
- Regular sports services: dataset of demographic, frequency and service level agreementPublication . Pinheiro, Paulo; Cavique, LuísThis article describes a dataset of different services acquired by users during the period in which they are active in a sports facility as well as their behavior in terms of frequency of the sport facility itself and the type of classes they prefer to attend. Each observation in the dataset corresponds to one user, including the features of subscriptions and frequency. Data were collected between June 1st 2014 and October 31st 2019 from a database of an ERP solution operating in a sports facility in Lisbon, Portugal. From this database, it was possi- ble to perform operations of extraction, transformation and loading into the dataset. The dataset with real data can be useful for research in ar- eas such as customer retention, machine learning, marketing, actionable knowledge and others. Although we present real data from users of a sports facil- ity, in order to comply the GDPR legislation, the attributes that could identify the users were removed making the data anonymized.
- Telco customer churn analysis: measuring the effect of different contractsPublication . Pinheiro, Paulo; Cavique, LuísCustomer retention is nowadays a challenge that requires concrete and personalized actions. Traditional data mining studies focused on predictive analytics, neglecting the business domain. This work aims to present an actionable knowledge discovery based on specific, actionable attributes and measuring of their effects. It is common to use matching, and propensity score approaches in healthcare to evaluate causality. After performing matching using the actionable attributes in this analysis, the causal effect is quantified. This work concludes that the difference between having a yearly contract versus having a monthly contract affects the churn of around 34%.
- Uplift modeling using the transformed outcome approachPublication . Pinheiro, Paulo; Cavique, LuísChurn and how to deal with it is an essential issue in the telecommunications sector. Within the scope of actionable knowledge, we argue that it is crucial to find effective personalized interventions that can lead to a reduction in dropouts and that, at the same time, make it possible to determine the causal effect of these interventions. Considering an intervention that encourages clients to opt for a longer-term contract for benefits, we used Uplift modeling and the Transformed Outcome Approach as a machine learning-based technique for individual-level prediction. The result is actionable profiles of persuadable customers that increase retention and strike the right balance between the campaign budget.