Implementing Customer Analytics for Personalized

Banking in a Major Bank

Challenge

Insights needed by a bank on their customer’s behavior to provide personalized services and increase customer retention

Services Utilized

Data Strategy, Data Analytics

Results

Implemented advanced analytics to generate 15% more customer retention

The bank grappled with issues in customer understanding, personalization, and retention, leading to high dissatisfaction and missed revenue opportunities.

The bank faced significant challenges in understanding the following customer preferences:

• Providing personalized services

• Improving customer retention

• These issues led to high customer dissatisfaction, attrition rates, and missed opportunities in cross-selling and up-selling.

Through a multi-disciplinary team and a robust AWS-based architecture, the bank integrated and analyzed data to drive personalized customer experiences.

An in-depth discovery phase was conducted to understand the business context and the technological implications.

Approach & Architecture

• Data Storage & Processing: Utilized AWS services like Amazon Redshift, Amazon S3, and Amazon RDS.

• Data Integration: Integrated data from various sources, including transaction records and customer interactions, using Informatica and custom Python scripts.

• Data Analysis & Modeling: Employed Amazon SageMaker for campaign analysis, customer segmentation, and behavior analysis.

• Reporting: Used Tableau for interactive reporting.

• Team Structure

• The team was composed of data engineers, data scientists, AWS and Informatica experts, business analysts, and Tableau developers.

The bank achieved a 15% improvement in customer retention, leading to increased customer satisfaction and higher revenues.

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• Deeper Customer Understanding: Achieved a more nuanced understanding of customer preferences.

• Enhanced Personalization: Enabled more personalized offerings for customers.

• Improved Retention: Customer retention rates improved by 15%.

• Increased Revenue: The improvements in customer satisfaction led to higher revenues.

• By leveraging a comprehensive approach that included advanced analytics and cloud technologies, the bank successfully overcame its challenges, leading to significant improvements in customer satisfaction and revenue.

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Lee Ebreo

VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.

Selah Ben-Haim

VP of Engineering at Prominence Advisors

Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).

Ben Crawford

Senior Product Manager at Enova Financial

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Mark Friedgan

CEO at CreditNinja

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René Pfitzner

Co-Founder at Experify

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Chief Information Officer at Integra Credit

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Lee Ebreo

VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.

Selah Ben-Haim

VP of Engineering at Prominence Advisors