WPML Support Wizard.

Overview

WPML serves a large global user base with varying technical knowledge. A significant portion of support requests were repetitive, often caused by known issues, misconfigurations, or environment problems.

The goal of this project was to design a guided support experience that helps users resolve issues independently before contacting support by using structured flows and AI-assisted classification.

The Problem

The existing support flow had a few critical issues:

• Users went directly to support without attempting basic troubleshooting
• Support teams handled a high volume of repetitive requests
• Many issues could be resolved faster with guided steps
• Lack of structured input made debugging slower and required back-and-forth communication

This resulted in longer resolution times, higher support costs, and frustration on both sides.

The Goal

• Reduce unnecessary support tickets
• Help users resolve issues on their own
• Improve quality of incoming support requests
• Shorten time-to-resolution
• Introduce AI to classify issues early in the flow

The Solution

1. Guided Support Wizard

Instead of a single contact form, users go through a step-by-step wizard that adapts based on their issue.

• Structured flow replaces open-ended input
• Each step reduces uncertainty and guides decision-making
• Users understand what’s happening and why

2. AI-Based Issue Classification

At the start of the process, user input is analyzed to determine:

• Is this a bug
• A configuration issue
• Or a general question

Based on this, the system dynamically routes users into the most relevant path:

• Debugging steps
• Known issues
• Documentation suggestions

This prevents users from going down irrelevant paths.

3. Compatibility & Environment Checks

The wizard surfaces common technical issues early:

• Plugin/theme compatibility
• Minimum requirements (PHP, memory, etc.)
• Outdated versions

Instead of just listing problems, each item includes:

• Clear explanation
• Suggested action
• Simple decision buttons

Example pattern used throughout:

• “I applied this and my problem is resolved”
• “I applied this but it didn’t help”
• “I’m going to ignore this issue”

This creates a feedback-driven flow, not a static checklist.

4. Known Issues & Solutions

Users are presented with relevant known issues based on their setup.

• Expandable solutions with clear instructions
• Option to mark resolution success
• Ability to continue if nothing helped

This reduces dependency on support agents for well-documented problems.

5. Progressive Disclosure & Control

The system balances guidance with flexibility:

• Users are encouraged to follow steps
• But can skip when necessary
• Clear warnings explain consequences of skipping

Example:

• Skipping debug info shows impact on support time
• Modal explains benefits (“reduces wait time by 5 hours”)

This builds trust instead of forcing behavior.

6. Debug Information Collection

Before contacting support, users are guided to provide structured debug data.

• Clear explanation of why it matters
• Reassurance about privacy
• Direct link to retrieve data

Result:

• Better quality tickets
• Faster resolution
• Fewer back-and-forth messages

7. Clear Resolution Exit Points

At multiple steps, users can:

• Confirm issue is resolved → exit flow
• Continue troubleshooting
• Escalate to support

This avoids forcing users through unnecessary steps once their issue is solved.