Data on post bank customer reviews from web

• Main Authors: Andrei Plotnikov, Alexey Shcheludyakov, Vadim Cherdantsev, Alexey Bochkarev, Igor Zagoruiko
• Format: Article
• Language: English
• Published: Elsevier 2020-10-01
• Series: Data in Brief
• Subjects: Data mining; Text mining; Reputation management; Online behaviour; Client satisfaction
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340920310465

This document describes a set of customer feedback data concerning the Post Bank. We collected data from 16,659 feedback lines using the Beautiful Soup package from the authoritative site banki.ru is selected as the source of data for collection. The dataset is compiled to monitor the level of trust of bank customers in its banking service. The data presents text reviews for 2013 - 2019 and includes, with or without ratings. Scientists can predict feedback ratings with an empty value in the future. We added additional columns to the dataset with official comments of bank employees, as well as values for the fog-index by Gunning parameter, which is used for the readability of the text. The data can be useful for customer service managers to identify problems in customer service and solve these problems, to assess the dynamics of the appearance of positive and negative reviews of bank customers.