How to Do Keyword Research for AI Visibility: A Customer-Intent-First Approach

Traditional keyword research tells you what people search for. But does it tell you what customers are struggling with, what they compare before buying, or what stops them from choosing a product?

Not always.

With AI search, people ask detailed questions, explain their problems and compare solutions based on their specific requirements. Finding these questions requires more than looking at search volume in SEO tools.

You need to understand what your customers are actually asking.

In this guide, I will explain a practical approach to keyword research that combines Google Search Console, customer discussions, product reviews, sales conversations and community questions to find valuable content opportunities for both traditional search and AI search.

As explained in my deep dive on why websites rank on Google but don't appear in ChatGPT, AI answer engines break queries down into multi-step fan-out questions covering the entire customer decision path.

Table 1: Traditional Keyword Research vs. Customer-Intent AI Research

1. Start With Your Existing Google Search Console Data

Before looking for new keywords, understand what people are already searching for to find your business.

Open Google Search Console and go to the Performance report.

Filter queries using your main product or service keyword.

For example:

• HRMS software: Filter queries containing "HRMS".
• Web development: Filter queries containing "web".
• CRM software: Filter queries containing "CRM".
• Expense management: Filter queries containing "expense".

You can use custom regular expressions to collect different keyword variations into one report and export the results into a spreadsheet.

Now, don't treat every query as a keyword you need to target. Handpick the queries that have genuine business relevance. Look at their impressions, clicks and search intent. These queries are your starting point. To verify whether your URLs are technically accessible to AI crawlers, see our 10-point website audit for AI visibility.

2. Find Real Customer Questions on Reddit and Quora

Take each important keyword from Google Search Console and search for discussions around it on Reddit and Quora.

Don't just look for questions containing your exact keyword. Look for people who are:

• Comparing different products.
• Looking for recommendations.
• Discussing pricing and budgets.
• Considering switching from one product to another.
• Experiencing problems with existing solutions.
• Trying to understand which product suits their requirements.

For example, if your keyword is HRMS software, look for questions such as:

• "Which HRMS software is suitable for a small business?"
• "What should I check before switching HRMS platforms?"
• "Is an HRMS worth the cost for a company with 50 employees?"
• "Which HRMS software supports Indian payroll compliance?"

You can use ChatGPT or Claude to find and organize these discussions. Keep all the original questions in a separate spreadsheet. I call this your Question Memory.

3. Study Customer and Competitor Reviews

Your customers often explain what they like, dislike and expect from a product through reviews. Explore platforms such as Google Reviews, G2, Capterra, Trustpilot, and industry-specific review platforms.

Pay particular attention to negative reviews. The goal is never to downgrade others, but to find out what users struggle with so you can solve their problems.

Look for:

• Missing features.
• Difficult implementation.
• Poor customer support.
• Pricing concerns.
• Integration problems.
• Product limitations.

Do the same for your competitors. Their negative reviews can reveal problems that your product may be able to solve easily. For example, in our MyOperator growth case study, targeting competitor pain points and comparison intent drove a 200%+ organic surge and delivered 60% of all company leads. Add these questions, problems and product comparisons to your Question Memory.

4. Collect Questions From Sales Calls, Demos and Support Tickets

Your existing customers and prospects are one of the best sources of keyword and prompt research.

Go through your product demo recordings, sales conversations, webinar recordings, customer support tickets, support emails, and onboarding conversations.

You don't have to watch every recording manually. If you have call or webinar transcripts, use ChatGPT or Claude to extract the questions customers ask.

Look for repeated questions, objections, purchasing concerns and product requirements. For example: "Does this software integrate with our existing ERP?" "How long does implementation take?" "Can we migrate our existing employee data?"

Remember to remove confidential customer information before uploading transcripts to AI tools. Also make sure AI search bots can access and index these solutions properly by consulting our AI search crawler indexing guide. Add them to your Question Memory.

5. Explore Google Search Suggestions and Related Questions

Search for each of your important business keywords in Google. Collect relevant suggestions from Google Autocomplete, People Also Ask, Related searches, and relevant search result snippets.

These sources help you discover additional ways people express their requirements in everyday language. Don't simply collect every suggested keyword. Keep the ones that are relevant to your product, audience and customer problems.

6. Find Questions in Industry Forums

Every industry has communities where people discuss problems and look for solutions. Identify forums that are relevant to your business.

For example, a SaaS company targeting HR professionals can explore HR communities, payroll forums and business management discussions. Look for questions about product selection, implementation, pricing, integrations and common problems. Add the relevant questions to your Question Memory.

7. Explore Questions in YouTube Comments

Find popular YouTube videos related to your product, service or industry. Look for videos with meaningful engagement, especially tutorials, product comparisons, reviews and problem-solving content.

Don't stop at watching the video. Go through the comments. People often use the comment section to ask questions that the video hasn't answered (e.g., "Does this work for small businesses?" "Is there a cheaper alternative?"). Add these questions to your Question Memory.

8. Explore Influencer Videos and Social Media Discussions

Repeat the same process with relevant industry influencers and social media discussions. Look for posts discussing your product category, common customer problems and competing solutions.

Read the comments and identify questions that reveal customer expectations, product-related doubts, common misconceptions, buying preferences, and unresolved problems. Add the findings to your Question Memory.

Table 2: Where to Find Real Customer Questions (The 8 Channels)

9. Turn Your Question Memory Into Keyword and Prompt Opportunities

Collecting questions is not the final objective. The real work starts when you identify the common problems and decisions behind them.

Group similar questions into topics. For example:

1. HRMS software for small businesses.
2. HRMS pricing and affordability.
3. HRMS payroll capabilities.
4. HRMS implementation and migration.

This forms the core of our Hybrid Engine Optimization (HEO) framework, which bridges standard search rankings with generative AI answer citations.

Table 3: The 4 Customer Intent Stages & What Content to Build

10. Why Question Memory Is More Valuable Than a Keyword List Alone

Traditional SEO tools are useful. They help you understand search volume, keyword difficulty, competition and search demand. But they don't tell you everything about your customers.

Consider the difference:

The first column helps you understand what people search for. The second helps you understand their problems, requirements and decisions. You need both.

Question Memory doesn't replace traditional keyword research. It adds the customer context that keyword databases alone cannot provide.

11. How to Use Question Memory for SEO and AI Search

Once you have identified the most important topics, use them to build your content strategy.

For traditional SEO:

• Validate relevant keywords using search volume and SERP data.
• Identify the right search intent.
• Study competing pages.
• Create useful articles, product pages and comparison pages.

For AI search:

• Understand how customers describe their problems in natural sentences.
• Cover the requirements and constraints behind their questions directly.
• Provide clear product comparisons and practical explanations.
• Support claims with reliable evidence and facts.
• Make important information accessible to search engines and AI systems in clean HTML.

You can also build a list of important customer prompts and periodically test them across ChatGPT, Claude, Gemini and Perplexity. To track your visibility across AI engines without expensive tools, read our guide on how to measure AI search visibility for free.

Table 4: High-Intent Content Formatting Checklist for AI Search

Final Thoughts

Keyword research shouldn't start and end with a list of keywords from Semrush or Ahrefs.

Start with the searches that already bring people to your website. Understand the questions they ask across communities, reviews, sales conversations and other customer touchpoints. Bring all these questions together in one place.

Build your Question Memory.

The real opportunity is to identify the recurring problems, requirements and purchase decisions behind those questions. Those are the topics worth covering on your website. For high-growth SaaS and enterprise migrations, this strategy drives sustainable pipeline, as showcased in our Seismic Enterprise SEO Case Study.

If you want to know if your website is ready for AI search engines, you can request an AI visibility audit.

Don't just research what people search for. Understand what they are trying to solve.