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Banks don’t have the best reputation when it comes to customer experience. What’s more – the policies and processes they have to navigate are quite rigid and complex. The whole thing lays a challenging environment to meet, let alone exceed, customer expectations.
In an industry where the stakes are high and the demand for excellence is even higher, there is an urgency to find a tool that can simplify standard operating procedures (SOPs) to ensure compliance while improving customer experience. This is where decision trees in banking come into play.
Table of contents
Customer Service Challenges in Banking
The banking sector faces several challenges in delivering optimal customer service. These challenges can impact customer satisfaction, trust, and overall experience. Let’s talk about them.
1. Data Protection Threats
With the increasing frequency of data breaches and cyber threats, customers are more concerned than ever about the security of their financial information. Building and maintaining trust in the security measures of online banking platforms is a continuous challenge.
2. Absence of Personalization
Tailoring services to individual customer needs requires a deep understanding of customer preferences and behavior. Achieving effective personalization can be challenging due to limited data insights or inadequate knowledge management systems.
3. Lack of Personnel
Whether in physical branches or on customer service hotlines, long wait times can frustrate customers. Swift customer service is essential when it comes to customer expectations.
4. Lack of Self-Service
In an era where customers value autonomy, the absence of user-friendly self-service tools results in a less efficient banking experience.
What are Decision Trees?
Decision trees are simple flowcharts that help customers and employees make decisions. They break down complex problems into a set of questions. Based on the answers, they lead users to different solutions.
Benefits of Decision Trees in Banking
Decision trees in banking offer a structured and intelligent approach to addressing customer needs. Here’s how interactive decision trees contribute to enhancing CX in the banking sector:
1. Enables Low-Effort Self-Service
Decision trees empower customers with low-effort self-service options. Your customers can find answers to common questions, explore product information, or troubleshoot issues independently. This helps reduce their reliance on customer support and promotes a sense of control.
2. Enhances Customer Satisfaction
With quicker issue resolution, personalized guidance, and user-friendly interfaces, Decision trees contribute to overall customer satisfaction (CSAT). A positive experience further increases customer loyalty and encourages them to continue their relationship with the bank.
3. Omnichannel Experience
Decision trees ensure consistency in information and service delivery across different channels. Whether a customer interacts with your bank through a mobile app, website, or in-branch, the decision-making process remains standardized.
4. Personalized Guidance
Banks can use decision trees to provide personalized advice and solutions based on customer questions or needs.
5. Cost Savings
By automating certain aspects of customer interactions, banks can allocate resources more effectively, reducing operational costs and allowing staff to focus on more complex tasks.
How can Banks Implement Decision Trees?
Implementing decision trees in the banking sector involves a series of strategic steps, from initial planning to deployment and monitoring.
1. Define Objectives
Start by determining where to apply decision trees. It could be credit scores, fraud detection, customer segmentation or risk management. Establish clear objectives for each use case so that it is easy to track.
2. Collect Relevant Data
Decision trees are as effective as the data provided. So, make sure to gather relevant data and clean it to remove any inaccuracies and inconsistencies.
3. Pick the Right Tool
With so many tools available in the market, it can be a tough job to pick the right one for your bank. Pick a tool that leverages technology like AI and automation and supports decision tree algorithms. It should also be easy to integrate with your resisting tools.
4. Develop Decision Tree Models
Start with a clear objective and target audience for each tree. Structure the tree with concise and unambiguous questions leading to specific outcomes or recommendations.
5. Deploy and Monitor
Make the decision trees easily accessible to both customers and employees through websites, internal knowledge bases, or customer service channels. Monitor its adaptability and keep it updated.
Case Study
A leading banking startup delivers outstanding CX with Knowmax decision trees
Jupiter, a digital-born banking startup, delivers outstanding CX by empowering its frontline support teams.
How did it manage to do just that?
Knowmax’s decision tree tool!
View here:
