Prototipo de aplicativo Web con Machine Learning para visualizaciones interactivas en una distribuidora farmacéutica de Guayaquil utilizando regresión logística multinomial.
Fecha
2024-01
Título de la revista
ISSN de la revista
Título del volumen
Editor
Universidad de Guayaquil. Facultad de Ciencias Matemáticas y Físicas. Carrera de Ingeniería en Sistemas Computacionales
Resumen
El presente proyecto radica en su capacidad para satisfacer las necesidades y preferencias únicas
de los clientes potenciales, lo que aumenta la lealtad del cliente y las tasas de conversión. La personalización de la publicidad y las recomendaciones de productos reduce el derroche de recursos al dirigirlas a personas que tienen un interés genuino en los productos farmacéuticos, estos se posicionarán como un líder en su sector al adaptarse en un entorno multiclase y diverso, al mismo tiempo que genera valiosa información sobre el comportamiento del cliente que puede ser utilizada para tomar decisiones más informadas y mejorar continuamente su estrategia comercial. Lo que se busca, es, mejorar la relación con los clientes utilizando un modelo de Machine Learning que permitirá clasificar al cliente de acuerdo a sus características, otorgando una experiencia personalizada donde se, lograra individualizarlo y hacerlo sentir único, ya sea con publicidad o recomendaciones, para así las probabilidades de compran aumenten significativamente, esto a su vez se aplicara a visualizaciones en donde el departamento de BI podrá introducir nuevos clientes y predecir qué productos o servicios son altamente recomendables para el mismo, como resultado el área BI podrá tomar decisiones más certeras evitando así gastos que se pueden usar para otros fines en donde la organización puede aún más, obtener mejores beneficios.
His project lies in its ability to meet the unique needs and preferences of potential customers, increasing customer loyalty and conversion rates. and preferences of potential customers, which increases customer loyalty and conversion rates. The personalization of advertising and product recommendations reduces the waste of resources by targeting people who have a genuine interest in pharmaceutical products, which will position them as a leader in their sector by adapting in a multi-class and diverse environment, while generating valuable information about customer behavior that can be used to make more informed decisions and continuously improve their business strategy. The goal is to improve the relationship with customers by using a Machine Learning model that will allow classifying the customer according to their characteristics, providing a personalized experience that will achieve. This in turn will be applied to visualizations where the BI department will be able to introduce new customers and predict which products or services are highly recommendable for them. As a result, the BI area will be able to make more accurate decisions, avoiding expenses that could be used for the same, thus avoiding costs that could be used to improve the commercial strategy of the company. thus, avoiding expenses that can be used for other purposes where the organization can make even better profits.
His project lies in its ability to meet the unique needs and preferences of potential customers, increasing customer loyalty and conversion rates. and preferences of potential customers, which increases customer loyalty and conversion rates. The personalization of advertising and product recommendations reduces the waste of resources by targeting people who have a genuine interest in pharmaceutical products, which will position them as a leader in their sector by adapting in a multi-class and diverse environment, while generating valuable information about customer behavior that can be used to make more informed decisions and continuously improve their business strategy. The goal is to improve the relationship with customers by using a Machine Learning model that will allow classifying the customer according to their characteristics, providing a personalized experience that will achieve. This in turn will be applied to visualizations where the BI department will be able to introduce new customers and predict which products or services are highly recommendable for them. As a result, the BI area will be able to make more accurate decisions, avoiding expenses that could be used for the same, thus avoiding costs that could be used to improve the commercial strategy of the company. thus, avoiding expenses that can be used for other purposes where the organization can make even better profits.
Descripción
PDF
Palabras clave
MACHINE LEARNING, BUSINESS INTELLIGENCE, FARMACÉUTICA, ANÁLISIS DE DATOS, BIG DATA, PHARMACEUTICA, ANALYSIS OF DATA