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Modelos para incremento da retenção em serviços desportivos regulares : análise preditiva e ações de fidelização
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| 2.18 MB | Adobe PDF |
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Abstract(s)
Atrair 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.
Attracting a new customer can cost up to five times more than keeping a current customer satisfied and therefore the ability to detect, as early as possible, which customers will abandon or fail to purchase a particular product or service, as well as measures which can be implemented to avoid this abandonment or break in sales are issues that all companies would like to see answered. This work presents an intelligent system that generates actionable knowledge based on real data and oriented to customer’s loyalty actions in regular sports services where high drop out rates occur. According to Database Marketing’s steps the system evolves in three phases: in a first phase, data obtained in the ERP and CRM systems databases existing in the sports facilities, from which it extracts, transforms and loads data in a Data Warehousing; in a second phase, predictive models are applied to identify profiles more susceptible to drop out; and finally, loyalty actions are applied to each one of the found profiles in order to increase loyalty and the retention rate.
Attracting a new customer can cost up to five times more than keeping a current customer satisfied and therefore the ability to detect, as early as possible, which customers will abandon or fail to purchase a particular product or service, as well as measures which can be implemented to avoid this abandonment or break in sales are issues that all companies would like to see answered. This work presents an intelligent system that generates actionable knowledge based on real data and oriented to customer’s loyalty actions in regular sports services where high drop out rates occur. According to Database Marketing’s steps the system evolves in three phases: in a first phase, data obtained in the ERP and CRM systems databases existing in the sports facilities, from which it extracts, transforms and loads data in a Data Warehousing; in a second phase, predictive models are applied to identify profiles more susceptible to drop out; and finally, loyalty actions are applied to each one of the found profiles in order to increase loyalty and the retention rate.
Description
Keywords
Serviços desportivos Clientes Data mining Fidelização Análise preditiva Taxa de retenção Sport services Data mining Predictive analytics Loyalty
Citation
Pinheiro, Paulo - Modelos para incremento da retenção em serviços desportivos regulares [Em linha] : análise preditiva e ações de fidelização. [S.l.]: [s.n.], 2018. 122 p.