The success of a company depends on its ability to build and maintain long-term relationships with its most valuable buyers. Ecuadorian companies face the challenge of identifying, differentiating and segmenting their clients. In response to this need, this study seeks to identify an unconventional form of segmentation based on the expected monetary value of customer billing in the retail sector. To this end, a probabilistic model was implemented that is derived from the Pareto/NBD methodology with a Bayesian hierarchy approach to estimate the customer value (CLV), based on a RFM data structure that considers the recency, frequency and monetary value of customers. After the estimate, the respective segmentation of customers was made where 24% of them were found to generate 68% of sales, therefore, three-quarters of customers are considered unprofitable. This research proposes a more efficient segmentation alternative based on customer value in the context of a retail company.
Tourism is an increasingly important and dynamic sector for the Ecuadorian economy, this change has also been evident in the coastal province of Santa Elena. The search for continuous improvement in the service quality offered by restaurants has become an important factor to achieve customer loyalty. It is necessary to develop the service quality of the tourism sector to attract more visitors to the province. The objective of this study is to evaluate the service quality perceived by consumers in the third and fourth category restaurants located in Santa Elena, using the Dineserv scale, which was tested for its validity and reliability through the technique: factor analysis. As a result of the analysis carried out, it was found that the factors that prevail to achieve the satisfaction of third-category restaurants' customers are: comfort and reliability / speed, while the only component that influences the satisfaction of the clients of the fourth category restaurants is the speed / efficiency.
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