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Publicação
Customer Review Analysis
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.94 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
Over the last years, Cerascreen has grown rapidly and expanded into more than 20
countries, always focusing on offering more diverse products, supplements, and services.
Unfortunately, it collected a lot of data during these years, which was not yet
stored, losing valuable insights. In a new initiative Cerascreen wants to be the most
trusted digital predictive health platform. Therefore, it intends to utilize its data to
understand its customers better and offer superior products and services according
to the customer’s needs. The focus of this internship report was to find a way to analyze
Cerascreen’s customers’ reviews to understand its customers better and respond
to properly the given feedback. In addition, since the reviews have not been stored
before, this report also deals with review retrieval. An exploratory data analysis of
the reviews’ ratings and texts was conducted to find the first significant insights. The
investigation found that although the overall review consensus was positive, it differed
by country, while the reviews’ length was related to their ratings. A topic model was
developed to find more information on what customers are talking about. The Model
was able to find several different topics, including product-, supplement-, and servicespecific
reviews. Lastly, a newly created key performance indicator about customers
satisfaction uses the new insights about the ratings and the review topics, which a
dashboard partially visualized through a dashboard.
Descrição
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
BERTopic Sentence Embeddings Text Mining Topic Modeling Unsupervised Learning