C5i Case Studies Identifying data patterns and mining insights about user behaviour to ensure maximum customer satisfaction

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	Identifying data patterns and mining insights about user behaviour to ensure maximum customer satisfaction C5i

Identifying data patterns and mining insights about user behaviour to ensure maximum customer satisfaction

C5i

Technology Category	Analytics & Modeling - Data Mining Analytics & Modeling - Real Time Analytics
Applicable Functions	Product Research & Development Quality Assurance
Use Cases	Predictive Quality Analytics Root Cause Analysis & Diagnosis
Services	Data Science Services
Challenge	Blueocean Market Intelligence’s client, a leading technology multinational, had huge volumes of user experience data and wanted to mine insights to enhance the user experience. The goal was to improve customer satisfaction by ensuring ease of navigation and user preferability. This included identifying patterns in data and making data cuts to suggest linkages in constituents which otherwise seemed to be absolutely disjoint. The client also wanted to give pointers to the software quality management team for ensuring better quality. The client was faced with key questions such as: Are users enjoying the experience as they navigate through the product? Is the GUI comfortable for the user? What causes bugs? How can the User Interface (UI) be improved? Read More
About Customer	The customer in this case study is a leading technology multinational company. The company operates in the Information Technology industry and has a large user base. The company has multiple products with various functionalities. The company was looking to improve its customer satisfaction by ensuring ease of navigation and user preferability. The company had huge volumes of user experience data and wanted to mine insights from this data. The company also wanted to improve its software quality and was looking for ways to identify patterns in data and make data cuts to suggest linkages in constituents which otherwise seemed to be absolutely disjoint. Read More
Solution	Blueocean Market Intelligence collated requisite data points on the SQL engine. There were five products with multiple functionalities. The available user data was correlated with various other pieces of information to drive meaningful insights. Based on frequency of occurrence of events, usage reports were prepared. These reports included slicing and dicing of data and analyzing different data points giving information, which was otherwise hidden. Also, root cause analysis was conducted for uncovering bugs and finding plausible solutions for bug fixing. Finally, dashboards were prepared for intuitive representation of information. For each of the functionality, user behavior was compared across products. For each of the product, analysis was conducted across various versions. The client approached with questions about user preferability of different applications. Using expertise in data analysis, Blueocean Market Intelligence prepared reports with key findings from the data pointers. Along with the important findings, recommendations were given for impactful execution. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Data Mining

Analytics & Modeling - Real Time Analytics

Applicable Functions

Product Research & Development

Quality Assurance

Use Cases

Predictive Quality Analytics

Root Cause Analysis & Diagnosis

Services

Data Science Services

Challenge

Blueocean Market Intelligence’s client, a leading technology multinational, had huge volumes of user experience data and wanted to mine insights to enhance the user experience. The goal was to improve customer satisfaction by ensuring ease of navigation and user preferability. This included identifying patterns in data and making data cuts to suggest linkages in constituents which otherwise seemed to be absolutely disjoint. The client also wanted to give pointers to the software quality management team for ensuring better quality. The client was faced with key questions such as: Are users enjoying the experience as they navigate through the product? Is the GUI comfortable for the user? What causes bugs? How can the User Interface (UI) be improved?

About Customer

The customer in this case study is a leading technology multinational company. The company operates in the Information Technology industry and has a large user base. The company has multiple products with various functionalities. The company was looking to improve its customer satisfaction by ensuring ease of navigation and user preferability. The company had huge volumes of user experience data and wanted to mine insights from this data. The company also wanted to improve its software quality and was looking for ways to identify patterns in data and make data cuts to suggest linkages in constituents which otherwise seemed to be absolutely disjoint.

Solution

Blueocean Market Intelligence collated requisite data points on the SQL engine. There were five products with multiple functionalities. The available user data was correlated with various other pieces of information to drive meaningful insights. Based on frequency of occurrence of events, usage reports were prepared. These reports included slicing and dicing of data and analyzing different data points giving information, which was otherwise hidden. Also, root cause analysis was conducted for uncovering bugs and finding plausible solutions for bug fixing. Finally, dashboards were prepared for intuitive representation of information. For each of the functionality, user behavior was compared across products. For each of the product, analysis was conducted across various versions. The client approached with questions about user preferability of different applications. Using expertise in data analysis, Blueocean Market Intelligence prepared reports with key findings from the data pointers. Along with the important findings, recommendations were given for impactful execution.

Impact #1	Resolved a functional glitch in one of the products used by 10% of the consumer base
Impact #2	Cognized business significance for future versions and enhanced user experience
Impact #3	Improved efficiency of the strategic and quality management team

Impact #1

Resolved a functional glitch in one of the products used by 10% of the consumer base

Impact #2

Cognized business significance for future versions and enhanced user experience

Impact #3

Improved efficiency of the strategic and quality management team

Benefit #1	Improved efficiency of the strategic and quality management team by 20%

Benefit #1

Improved efficiency of the strategic and quality management team by 20%

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Overview

Identifying data patterns and mining insights about user behaviour to ensure maximum customer satisfaction

Operational Impact

Quantitative Benefit