Bibliographic citations
Clemente, B., (2021). Segmentación de lectores digitales registrados de un sitio web informativo con el algoritmo de análisis Cluster k-means [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/4845
Clemente, B., Segmentación de lectores digitales registrados de un sitio web informativo con el algoritmo de análisis Cluster k-means []. PE: Universidad Nacional Agraria La Molina; 2021. https://hdl.handle.net/20.500.12996/4845
@misc{renati/245171,
title = "Segmentación de lectores digitales registrados de un sitio web informativo con el algoritmo de análisis Cluster k-means",
author = "Clemente Rivera, Brian Erick",
publisher = "Universidad Nacional Agraria La Molina",
year = "2021"
}
Due to the wide diversity of the company's business, an important group of media, a lot of information is generated, more specific and detailed each time; and this is where the Business Intelligence management comes in, which centralizes all these data from different sources and platforms in order to analyze them and provide support to the different areas that require a detailed analysis to support a sale, an acquisition, project development, etc. One of these specialized requirements has to do with the integration of data from different digital sources such as those generated on websites, social networks; or traditional ones such as advertising revenue generated for the company, audience database, among others, as they will allow to address more complex analysis to find more specific, differential and relevant findings. This monograph is about the development of a new methodology for segmentation of registered users on the website, in which it has been proposed to consider the type of content they visit according to the section in which the notes are hosted and complementing them with personal, sociodemographic, location and other information available in the business, all this supported by the cluster analysis, specifically the k-means algorithm. For data preprocessing, cleaning, construction of the data set and execution of the methodology, R software was used, which has multiple functions that helped with these tasks. These six clusterings found will allow offering clients a new sales product, which will also provide an advantage for consumers since they will be able to specify the specific audience they want to impact, significantly improving the results that would be obtained, unlike the traditional method of digital advertising.
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