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Data Collection by Survey

Data Collection by Survey

The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...

Review and Preview

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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...

Review and Preview

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Health Information Technology and Healthcare Information System

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Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses

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Published on: September 11, 2023

Data on post bank customer reviews from web.

Andrei Plotnikov¹, Alexey Shcheludyakov¹, Vadim Cherdantsev²

¹Perm National Research Polytechnic University, 29, Komsomolsky Av. 614990, Perm, Russian Federation.

|September 5, 2020

Summary

This summary is machine-generated.

This study analyzes 16,659 Post Bank customer reviews from 2013-2019 to gauge banking service trust. Findings aid in predicting customer feedback and improving service quality.

Keywords:

Client satisfaction Data mining Online behaviour Reputation management Text mining

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Published on: February 13, 2015

Area of Science:

Business Analytics
Natural Language Processing
Customer Relationship Management

Background:

Customer feedback is crucial for service quality assessment.
Monitoring customer trust requires analyzing textual reviews.
Banki.ru is a key platform for Russian banking customer feedback.

Purpose of the Study:

To compile and analyze Post Bank customer feedback data from 2013-2019.
To develop a dataset for predicting customer feedback ratings.
To provide insights for customer service managers.

Main Methods:

Web scraping using Beautiful Soup from banki.ru.
Data compilation of 16,659 feedback entries.
Inclusion of Gunning Fog Index for text readability.

Main Results:

A comprehensive dataset of Post Bank customer reviews was created.
The dataset includes official employee comments and readability metrics.
Potential for predicting missing feedback ratings was identified.

Conclusions:

The dataset offers valuable insights into customer trust dynamics.
It enables identification and resolution of customer service issues.
Useful for assessing trends in positive and negative customer feedback.