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Why Choose Dynamic Decision Tree For New-age Customer Support?

8 mins read

Instant, personalized, and connected experiences are prerequisites of customer service that new-age customers look for while dedicating their loyalty to businesses today. Organizations are increasingly moving towards technological solutions to utilize their information resources optimally to maximize customer satisfaction.

To this end, dynamic decision trees leverage AI-powered Knowledge Management solutions to organize and disseminate information geared to achieve maximum customer satisfaction and improved brand-customer relationships in the long run. 

What Are Dynamic Decision Trees? 

A decision tree is a graphical tree following an if-then workflow to guide users with the next best action steps to troubleshoot a problem.

There is an increasing need for technological sophistication in a fast-paced customer service world to manage skyrocketing customer expectations. This is where a dynamic decision tree helps businesses to manage customer expectations while reducing support costs

A dynamic decision tree has AI elements and machine learning backing to take an intuitive approach toward problem-solving.

Instead of the static decision tree approach used in service hotlines, where customers have to go through all the steps, a dynamic decision tree enables users to reach the most relevant input and skip or jump steps for faster resolutions. 

With Knowledge Management solutions, decision trees can be created, organized, managed, and distributed across digital and assisted channels, resulting in enterprise-wide benefits. 

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3 Reasons To Use Dynamic Decision Trees For Support Teams

1. Reduce average handle time by guiding agents with the next best action step

 A dynamic decision tree sorts out all the information for agents as guided steps to follow during customer calls. This reduces AHT by saving agents’ time in figuring out the problem and helps them focus on the solution stage.

2. Improve first call resolution with efficient call scripting 

With dynamic decision tree scripts, agents can quickly identify the root cause of the problem and help customers with solutions at the first go itself. This reduces the number of repeat calls and improves FCR at contact centers.   

3. Deliver mistake-proof customer service

A troubleshooting process involves multiple steps which need to be followed in the right order to achieve resolutions. A dynamic decision tree ensures agents do not miss any action and deliver mistake-proof customer service in compliance with the company’s standard operating procedures(SOPs). 

Function Of Dynamic Decision Trees In Chatbots

1. Improve customer satisfaction with instant solutions

AI Chatbots are a go-to self-service option for customers. A dynamic decision tree can be integrated with modern chatbot solutions employing natural language processing (NLP) to engage humanly with customers and guide them through troubleshooting issues independently. This increases customer satisfaction with instant and accurate answers. 

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2. Minimize customer effort with guided instructions

With clickable options in chatbots guiding customers to reach the solutions, dynamic decision trees minimize customer effort spent on explaining their issues at length. Minimizing customer effort significantly improves customer satisfaction. 

Core Features Of Knowmax Dynamic Decision Trees

1. No-code DIY capability for content creation

  • Knowmax decision tree builder is a no-code do-it-yourself (DIY) platform that enables users to create decision trees from scratch without needing a single line of code or exclusive technical skills.
  •  Once the core issue has been identified, questions can be created, and multiple user responses can be added, representing possibilities. 
  • Guidance tips can be added with the relevant steps, and nodes can be linked to skip or jump unnecessary steps. Any user response can be edited or deleted during the creation process without disrupting the flow of the decision tree. 
add-user-response

2. Autotraverse feature to reduce resolution times

  • Knowmax Knowledge Management solution can be integrated with existing CRM platforms to auto traverse customer information for any step of the decision tree flow.
  • With the auto traverse capability, agents do not have to probe through every question manually and can instead focus on critical steps that require manual entries. This reduces the chances of agent error and fast-tracks the troubleshooting process.
  • For customers, the auto traverse function means faster resolutions without repeating information with service reps. This results in increased customer satisfaction and reduced support costs.

3. Content interlinking for improved information access

  • Knowmax decision tree software enables content interlinking to access information faster and more efficiently from a unified dashboard. 
  • While creating a dynamic decision tree with Knowmax, support articles, FAQs, pictures, or video files created on the platform can be accessed and attached with the steps, or external files can be uploaded from the device.
  • Content interlinking empowers agents with relevant information at their fingertips and augments their problem-solving skills to create better customer experiences. 
CRM-integration

Why are dynamic decision trees the best way to reach new-age customers expectations?

1. Easy navigation across channels creates consistent customer experiences

  • Dynamic decision trees are user-friendly and easier to navigate for agents and customers alike. 
  • With an omnichannel Knowledge sharing platform for decision trees, customers receive uniformly high-quality experiences whether they call an agent for support or access a chatbot. 
  • Omnichannel customer experience is the way forward for businesses looking forward to increasing customer retention and engagement through multi-channel communication. 

2. Empowers agents to ask the right questions to customers

  • Using dynamic decision trees for call center scripts empowers agents with a clear direction to approach customer issues and enables them to ask the right set of questions that lead directly to the solution stage.  
  • Contact center metrics like AHT, FCR, and Customer satisfaction improve significantly when agents are confident and know exactly what to ask the customer.

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3. Customized experiences improve customer satisfaction

  • Providing personalization is fundamental to achieving higher customer retention in a cut-throat customer service world. 
  • Integrated decision trees give businesses a competitive edge by taking customer context into account to deliver customized experiences that new-age customers expect today.

Conclusion

The fastest way to reach a solution is to make the right decisions at each step. As the name suggests, a dynamic decision tree empowers stakeholders to make improved decisions in real-time.

In customer service, this empowers support teams to reach accurate resolutions faster without compromising the service quality and for customers to troubleshoot issues independently.

For organizations, employing dynamic decision trees for customer service and support automation is a direct pathway to improving operational excellence while bringing down costs. 

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