New Ways to Enforce Banking with Sentiment Analysis

Introducing Our Client

We had the great opportunity to assist a banking enterprise having its head office in St.Petersburg, London. They had huge anticipations for improving customer experience by implementing the most updated techniques available in the market. With lesser experience in the area, they were trying hard to expand their business boundaries with effective social media strategies and online banking methods. But they had confusion regarding what they really lacked.

Challenges They Had

Our client had strategies to monitor their sales and revenue generation. But, apart from numerical details telling how many people made transactions and how much revenue was generated, they needed to identify what people think about the services they provided. They are required to develop a method to understand the emotion of their customers to know their level of satisfaction. When customers move from paper works to online transactions, it was essential for them to move forward and expand their business boundaries gaining more consumer trust.

To be more precise, the challenges for our client were related to collecting client feedback from various platforms like social media, emails, messages, notifications, and other online or offline resources. In addition, they faced hurdles in handling large sets of organizational data comparing and analyzing their patterns using the available workforce. Even though they made strategies to collect and analyze, they failed to arrive at intelligent conclusions. We had some resolutions for them with our updated methods of sentiment analysis.

What Resolutions Did We Provide?

We identified that the exact requirement of our client was to know the responses of their clients. For that, collecting data from whatever areas the brand involves is essential. We designed strategies for collecting consumer data from social media sites, client reviews, customer surveys, and many others to conduct precise sentiment analysis with AI-driven tools.

Since customer experience gets influenced by various devices like mobile phones, online applications, and many more, we utilized automated tools to extract data directly from relevant sources like them. By using Natural Language Processing (NLP) techniques, we collected customer feedback from naturally written or spoken sentences. We could reduce the time and effort spent in this regard. As a result, it emphasized a granular level of emotion analysis through aspect-based sentiment analysis. The net result was getting a powerful insight into the customer's opinion.

Benefits They Got

With our AI-driven sentiment analysis method, our clients got the chance to improve their business performance in many ways.

• They got a proper understanding of the pros and cons of their business functioning with data-driven insights.
• Establish a precise voice of the customer across various touchpoints with less effort and time.
• They got the facility to track consumer behaviors and analyze their changes in real-time with changing market policies.
• Our machine learning tools handled thousands of files at a time and brought results more precisely.
• The results they got empowered their employees to maintain a better relationship with their regular customers by understanding their needs.
• It helped them to make improvements both online and offline. It can become an asset for them to have marketing innovations to thrive in business competition.

The assistance of Allianze Technologies in developing sentiment analysis strategies is available for your business too. Know more about it by reaching us at [email protected]