Why Interactive Decision Trees are the Future of Customer Service and Support

Getting good help quickly is important when customers have an issue with a product or service. Long wait times on support calls frustrate everyone. New smart interactive tools called decision trees promise to transform customer service in the future. This article explains what decision trees are, why they help companies and customers, and how to create great ones.

What is an Interactive Decision Tree?

An interactive decision tree is a customer service tool that works using yes/no questions. Customers answer simple questions about their problem. Based on their answers, they get directed through different steps and information specific to their situation. It is like an intelligent flow chart or map guiding users efficiently.

Decision trees allow customers to:

• Quickly diagnose their own issue through Q&A steps
• Avoid waiting to explain problems to agents
• Feel more independent yet supported

Leading brands already use decision trees to power self-service options online. But the future potential remains largely untapped.

Benefits of Decision Trees over Traditional Customer Service

Resolution Rate Improvements with Decision Trees

Well designed decision trees offer advantages over traditional call centers or basic FAQ lists both for businesses and customers:

Benefits for Companies:

• Lower call volume and staffing costs
• Faster issue resolution times
• Improved customer satisfaction
• Increased self-service containment
• Deeper service insights from structured data

Benefits for Customers:

• Independence to solve own problems
• No hold times or repeating information
• Consistent answers not agent-dependent
• Quick access anytime 24/7/365

With such clear mutual upside, decision trees present a true win-win innovation.

Creating Engaging and Effective Decision Trees

Designing intuitive and useful decision trees involves both science and art. Following guiding principles drives great results:

• Keep Language Simple – Use plain everyday words. Avoid technical jargon. Assume no prior topic knowledge.
• Lead With Customer Intent – Structure questions based on real-life customer needs rather than internal business processes. Adopt the user mindset.
• Limit Choices – Present just 2-5 options at each step. Too many overwhelms users. Binary yes/no options work best at the start.
• Direct Don’t Dump – Guide visitors purposefully vs presenting everything. Curate content specifically matching the user’s stated situation.
• Incorporate Multimedia – Combine text Q&A with videos, images, tooltips. Visuals and audio increase clarity helping retention.

Focusing design on user thought flow and simplicity powers effortless customer journeys via decision trees.

Teaching Customers Through Decision Trees

Interactive decision trees can do more than just help fix problems. Some companies also use them to teach people how to do things by themselves the best way.

For example, a tablet maker has a step-by-step tree that shows you which accessories pair best based on how someone will use their device. It asks simple questions like “Will you mostly use your tablet at home or for travel?” Then it guides you to the right add-ons like cases, styli, and wireless routers fitting your needs.

Banks use decision trees to explain how to set travel notices on debit cards, adjust auto-savings amounts, and monitor credit scores too. Guiding people interactively often works better than overwhelming them with long article lists most won’t fully read. Conversation-style interactions stick in people’s minds better even when self-navigating online.

Decision trees transform customer support articles into tailored tutorials. They empower users managing their services independently while still offering helpful recommendations. Interactive education features will surely expand as companies explore more possibilities with decision trees, moving beyond mere troubleshooting to establish true self-service partnerships.

Advanced Decision Tree Functionality

Basic decision trees have existed for decades but current iterations unlock new possibilities through smart features like:

• Integration with customer and product databases to pull relevant user configs
• Chatbots to enable conversational dialogs beyond static trees
• Predictive algorithms personalizing guidance based on known user details
• Automated translation into different languages
• Back-end content management systems simplifying tree creation & updates
• Built-in analytics revealing tree performance insights

These enhanced functionalities will proliferate making decision trees dynamic and intelligent assistants.

Decision Tree Uses Across Customer Service

Decision trees already assist customer service and success across many sectors but remain underutilized. Expanded applications powering self-service include:

• Troubleshooting – Help users diagnose device or system faults themselves.
• Sales/Buying – Guide complex purchase decisions with interactive comparisons.
• Account Updates – Assist changing plan, payment or contact info without agents.
• Appointment Setting – Enable scheduling medical exams, car repair or deliveries.
• Feedback Collection – Query user satisfaction after service calls.
• Education/Training – Teach multifaceted skills interactively through choices.

Virtually any customer, patient or user journey can unfold reliably via tailored decision trees. Their simplicity and flexibility drives exponential possibilities.

Expert Decision Tree Tips

Here are pro tips elevating decision tree outcomes:

• Use data to identify top customer intents and pain points
• Collaborate across teams – don’t silo knowledge
• Start with a flowchart sketch before technology
• Keep initial decision trees simple then iterate
• Set key metrics like containment rate for improvement goals
• Allow some user questions to exit trees into other support channels

With foundational content and smart functionality, decision trees create customer experiences that were previously unimaginable.

Designing Decision Trees to Match Users’ Reading Levels

Designers change self-service decision trees to match how well people read. Adults usually read at an 8th-grade level, but some read at a lower level. To help them, writers use simple words and short sentences. They also use audio, pictures, and videos to make things clear, especially for hard topics.

For people who can’t see well, adding descriptions to images and transcribing videos helps. Using clear colors and highlights helps them navigate too. Translating decision tree content into different languages also helps people around the world use them easily.

When decision trees are designed to work for everyone, more people can independently solve problems. This way, everyone gets good service and can fix issues fast.

Addressing Common Concerns About Decision Trees

Can trees support complex issues?

Well-designed decision trees handle multifaceted diagnoses via tiered question sequences bridging knowledge gaps.

Are customers receptive to decision trees?

Surveys show over 85% of customers prefer platforms enabling independent issue resolution. Most welcome intelligent Q&A guidance.

How do trees interoperate with other channels?

Blended models allow users to exit to live chat or agent calls when needed. Integrated knowledge centers also underpin all channels.

Final Thoughts

Interactive decision trees are like helpful guides in various fields. They make customer service better by quickly giving the right help for different situations. These trees let problems get fixed fast, and people can help themselves. They are simple and smart, making a future where customers can easily get help whenever they need it.