Decision Trees - Hidden Hero of Contact Centers

Organizing information is one of the most challenging tasks of the modern age, making it useful even more so. Customer service agents now find themselves handling both more information and channels than ever before. At the same time,

this complexity makes consistency and accuracy difficult. But there’s a hidden hero to the rescue! Decision trees cut through the complexity and enable you to deliver quick and consistent customer support. They can make onboarding and training faster and even be integrated into other channels such as chatbots or virtual assistants like Alexa.

What Are Decision Trees? (and what they’re not)

Decision trees are support tools that use a flowchart or tree like model to visualize service and contact center processes. Since customer service is a form of personal troubleshooting with a customer, it is ideally suited to creating step-by-step guides for resolving customer issues. Decision trees depict this in chart form starting with a question node and then branching off into paths for yes and no that are followed based on the customer’s answer. This simple logic becomes a powerful tool that can be used to power many service processes and better enable your customer service professionals. 

Consistency is a prerequisite for improving your customer service.

In the past, decision trees were static charts or required coding skills. Today, they are interactive and guide the agent and customer step-by-step. This means agents can skip memorizing dozens or even hundreds of problems and solutions and won’t have to read through a wall of text in a Word document.

Why Decision Trees are Important in Customer Service

Consistency is a prerequisite for improving your customer service! By simplifying complex processes and reducing the amount of information agents are required to remember, they eliminate challenges such as:

• Difficulty finding information
• Long search times
• Agents sticking too closely to scripts
• Long onboarding and training times
• Inconsistent performance among agents or contact centers

When combined with the right knowledge management, they can be a real game changer in agents’ everyday work.

Using Decision Trees for Chatbots, Self-Service & More

Would you like to ensure that the same service inquiry is solved the same way in every channel in every interaction with the customer? Decision trees, particularly when integrated into your knowledge management platform can power multiple services and channels at the same time. That makes them a real force multiplier. Here’s where you can employ them:

1. Guided Dialogues for Agents

Guided dialogues are a kind of one-sided chat that walks an agent step-by-step through an inquiry. It provides the question to be asked and prompts the agent to enter the customer’s answer. The system tracks the entire inquiry process providing an overview of the case and the next step to take. This helps make even new employees as efficient as experienced agents and the hand-off from one department to another one is more transparent, because they can refer to the same previously answered questions.

2. Customer Service Chatbots

Decision trees are also ideally suited for managing chatbots. In low-context situations involving simple transactions or inquiries, they can ensure chatbots are useful and consistent.

Example use cases for chatbots include:

• Webinar registration
• Troubleshooting a printer problem
• Choosing a mobile phone plan
• Get an insurance quote
• Order pizza

In addition, the same decision tree can be used for both internal and external users which helps to reduce the editorial effort and raise transparency within all channels.

3. Voice Assistants like Alexa

Companies interested in using voice assistants like Alexa, Siri and Google Assistant for customer service are in luck. Since the use cases are like chatbots, the voice skill can act as an audio interface for an existing chatbot. One insurance company for example, did exactly that enabling customers to get policy information and soon make transactions via Alexa (powered by a chatbot in the background).

4. Self-Service Solutions

Starting with the initial problem, decision trees enable customers to troubleshoot interactively and be guided step-by-step through the process. This is both easier and preferable from a user’s perspective to navigating a long F.A.Q. or downloading help documents. Successful self-service requires both up-to-date information and a solid process underlying it. Decision trees integrated within your knowledge base provide both.

How Decision Trees Impact Your KPIs

With so much off their plate, agents can focus more on helping customers and less on searching and remembering things. The effects of this can be seen on the department level in higher First Contact Resolution rates (FCR), reduced Average Handling Time (AHT) and overall better customer experiences which impacts both NPS and CSAT. Decision trees contribute to:

1. Increased efficiency
2. Consistent performance
3. Better idea of handling time for inquiries
4. Higher agent satisfaction
5. Higher FCR & fewer transferred calls
6. Higher CSAT and NPS

Hire Agents to be People not to Memorize Information

Customer service representatives excel at dealing with people and having the experience and emotional intelligence to interact with a wide range of personality types and problems in many situations. We don’t hire them to memorize information or be search ninjas. That’s why empowering agents with the tools that let them focus on what they’re best at is a critical part of creating a consistently excellent customer experience.

Learn more about the power of decision trees in your knowledge base .

Topics: Knowledge Management

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