Top 5 LLM Prompts to Generate FAQs from Support Tickets

Customer support tickets are a goldmine of insights into your users' most pressing questions and concerns. Yet many organizations struggle to transform this valuable data into accessible, self-service resources. The solution? Using Large Language Models (LLMs) to automatically generate comprehensive FAQs from your existing support ticket data.

In this post, we'll share five powerful LLM prompts that can help you extract meaningful FAQ content from customer support tickets, reducing support volume while improving customer satisfaction.

Why Generate FAQs from Support Tickets?

Before diving into the prompts, it's worth understanding why this approach is so effective:

• Real customer language: FAQs generated from actual tickets use the language customers naturally use
• Addresses actual pain points: You're solving problems customers actually have, not what you think they might have
• Reduces support volume: Self-service options can deflect up to 60% of support requests
• Improves customer experience: Customers get instant answers instead of waiting for support responses

Now, let's explore the five essential prompts for transforming your support tickets into powerful FAQ content.

1. Question Extraction and Categorization

Support tickets are messy. Customers write when they're frustrated, confused, or in a hurry. They might describe three different problems in one email or bury their real question under paragraphs of backstory. This prompt helps you cut through all that noise to find the actual questions people are asking and figure out which ones come up over and over again.

Prompt:

Analyze the following customer support tickets and extract the underlying questions customers are asking. Group similar questions into categories and identify the top 10 most frequent question types.

Support Tickets:
[INSERT TICKET DATA]

For each question category, provide:
- The core question in customer-friendly language
- Frequency/commonality score (1-10)
- Category (e.g., "Account Management", "Billing", "Technical Issues")
- Key themes or variations of the question

Format your response as a structured list with clear categories.

Why this works:

Instead of guessing what customers might want to know, you're looking at what they're actually asking. This prompt spots the patterns you might miss when you're dealing with tickets one by one, so you can focus your FAQ efforts on the stuff that will actually help the most people.

2. FAQ Answer Generation from Solution Patterns

Your support team has already solved these problems dozens of times. They know which explanations work, which steps people skip, and what follow-up questions always come next. This prompt takes all that hard-won knowledge and turns it into FAQ answers that actually work because they're based on real conversations with real customers.

Prompt:

Based on these customer support tickets about [SPECIFIC ISSUE/CATEGORY], create a comprehensive FAQ answer that addresses the core customer question.

Ticket examples:
[INSERT 3-5 RELATED TICKETS WITH RESOLUTIONS]

Create an FAQ answer that:
- Directly addresses the customer's question
- Provides step-by-step solutions when applicable
- Uses friendly, non-technical language
- Includes preventive tips to avoid the issue
- Mentions when to contact support for escalation

Question: [EXTRACTED QUESTION FROM PROMPT 1]
Answer: [YOUR GENERATED RESPONSE]

Why this works:

You're not reinventing the wheel here, you're capturing what already works. When your support team successfully walks someone through a problem, there's gold in that conversation. This prompt finds the common threads in those successful interactions and packages them up for everyone else.

3. Conversational Tone Optimization

Nobody reads FAQs when they're having a great day. People land on your help pages when something's broken, they can't figure something out, or they're worried they messed up. Your FAQ answers need to meet them where they are emotionally, not just give them a cold list of steps.

Prompt:

Review these customer support tickets and rewrite the following FAQ entry to better match the emotional tone and concerns expressed by customers.

Original FAQ:
Q: [QUESTION]
A: [CURRENT ANSWER]

Customer tickets showing frustration/emotion:
[INSERT TICKETS SHOWING CUSTOMER SENTIMENT]

Rewrite the FAQ answer to:
- Acknowledge common customer frustrations
- Use empathetic language
- Provide reassurance where appropriate
- Maintain a helpful, solution-focused tone
- Include proactive communication about known issues

New FAQ Answer:

Why this works:

When you acknowledge how people actually feel when they need help, they're more likely to trust your guidance. This prompt helps you write FAQs that sound like they come from a human who gets it, not a robot who's never dealt with a frustrated customer.

4. Gap Analysis and Missing FAQ Identification

Here's what happens: you write great FAQs, pat yourself on the back, then six months later realize customers are asking completely different questions. Products change, people use things in unexpected ways, and new problems pop up. This prompt helps you spot the gaps before they turn into support headaches.

Prompt:

Compare our current FAQ section with recent customer support tickets to identify gaps and missing information.

Current FAQ Topics:
[LIST EXISTING FAQ CATEGORIES/QUESTIONS]

Recent Support Tickets (last 30 days):
[INSERT RECENT TICKET SUMMARIES]

Identify:
1. Questions customers are asking that aren't covered in our FAQ
2. Existing FAQ entries that need updates based on new ticket patterns
3. Seasonal or trending issues that should be temporarily featured
4. Technical topics that need simpler explanations

For each gap identified, provide:
- The missing question in customer language
- Priority level (High/Medium/Low) based on ticket volume
- Suggested FAQ category placement
- Brief outline of what the answer should cover

Why this works:

Your customers are constantly teaching you what they need help with, you just have to listen. This prompt systematically compares what you think people need to know with what they're actually asking about, so your FAQ stays useful instead of becoming digital shelf decoration.

5. FAQ Performance Optimization

The ultimate test of FAQ effectiveness isn't how comprehensive it looks, it's whether customers still need to contact support after reading it. This prompt analyzes "FAQ failures" to understand why customers bypass self-service options, revealing opportunities to refine both content and presentation for maximum deflection impact.

Prompt:

Analyze support tickets that were submitted after customers potentially viewed our FAQ section. Identify why the FAQ didn't resolve their issue and suggest improvements.

FAQ Entry Being Analyzed:
[INSERT FAQ Q&A]

Related Support Tickets After FAQ Publication:
[INSERT TICKETS THAT CAME IN DESPITE FAQ EXISTENCE]

For each ticket, determine:
- Was the FAQ answer unclear or incomplete?
- Did the customer have a unique variation of the problem?
- Was the FAQ difficult to find or poorly categorized?
- Does the answer need more detail or different formatting?

Provide:
1. Revised FAQ answer that addresses the gaps
2. Suggestions for better FAQ organization/categorization
3. Additional related questions that should be included
4. Keywords to improve FAQ searchability

Why this works:

This prompt creates a continuous improvement loop by learning from failures rather than just successes. It identifies specific friction points in the self-service experience and provides actionable insights for making FAQs more discoverable, understandable, and complete.

From Frustrated Customers to Helpful Resources

Every support ticket represents a moment when someone got stuck and needed help. These prompts help you honor those moments by turning individual struggles into resources that help everyone else avoid the same problems.

The best part? You're not guessing what people need, you're learning from what they've already told you. Start with your most recent batch of tickets and see what stories they're telling you about where customers get confused, what language they use, and what really matters to them.

Your FAQs will stop being the thing nobody reads and start being the thing that actually helps. And isn't that the whole point?

Want to stop manually digging through support tickets to figure out what your customers actually need? Scout can automatically analyze your ticket data and surface the patterns that matter. Give it a try and see what your customers have been trying to tell you.