UBI Partnered with a Successful Fortune 500 Company to Analyse it’s Customer
Engagement and Experience
Situation & Objective
To identify the complaints received by a BFSI industry from their customers for a varied reasons and resolutions provided pertaining to the transactions and other services offered by the bank and highlighting the areas which requires improvement to provide seamless customer experience.
Solution Approach
Consolidation of Data:
- Generate interactive dashboards and reports that highlight areas requiring improvement and provide a holistic view of customer complaints.
- Gather data from multiple sources such as CRM, survey records, customer grievances, and feedback.
- Data is then consolidated and organized
- Store the consolidated data in a data warehouse for easy access and analysis.
Data Cleaning and Modelling:
- Utilize the AWS Redshift tool to clean and prepare the data for analysis.
- Perform data modelling to structure the data in a way that supports effective analysis.
Data Analysis and Synthesis:
- Utilize SQL (Structured Query Language) to crunch and analyse the data.
- Extract insights and patterns from the data to identify complaints and resolutions related to transactions and other services.
- Use statistical analysis techniques to uncover trends, patterns, and correlations within the data.
Visualization and Reporting:
- Feed the analysed data into a visualization tool like Tableau.
- Create powerful visualizations and reports to present the insights and findings.
Impact
Enhanced Customer Experience:
- Identification of complaints and resolutions enables the BFSI industry to address customer issues promptly.
- Improved customer satisfaction through timely resolution of problems. Insights from data analysis help management make informed decisions regarding customer service improvements.
Data-Driven Decision Making:
Insights from data analysis help management make informed decisions regarding customer service improvements.
Efficiency and Resource Optimization:
Visualization and reporting through Tableau provide a user-friendly interface for accessing and understanding the data, reducing the need for technical expertise
Consolidation and centralization of data reduce manual effort and time spent on data collection and organization.
Data cleaning and modelling automate the process of preparing data for analysis, saving time and improving efficiency.
