Prompt-Level Research: How Customers Ask for Products in AI Tools (and How to Map Content)

What is Prompt-Level Research?

Prompt-level research is when brands study the specific questions and requests that customers commonly type into AI search platforms. Doing so helps ecommerce brands understand customer intent better, allowing them to cater their content to customer queries.

For example, “best dog lead” is a great search for finding dog lead recommendations in Google. However, with AI searches, users are getting more specific and conversational, with queries like “what is the best dog lead for a small dog that pulls on walks?”

How AI Product Prompts are Different from Search Keywords

AI prompts are typically more specific and informal than Google searches. Users type in long, casual questions as if they’re asking a friend, which is different from the brief keywords used in search engines.

Customer prompts often include details like budget, personal situation, use cases, problems to solve, comparisons between options, preferences, and restrictions. They’re usually framed as a request for advice or recommendations.

Some examples of AI queries include:

• “What should I buy for a puppy that pulls on the lead?”
• “Which skincare products are best for dry, sensitive skin?”
• “What’s a good gift for someone who works from home?”
• “Compare down jacket vs puffer coat for winter travel.”

Common Prompt Types Ecommerce Brands Should Map

1. Problem-Based Prompts

This is when customers mention a problem they’re having and ask for a solution. This could include “what can I use for a dog that slips out of a collar?,” “what should I buy for frizzy hair in humid weather?,” and “what is the best mini fridge for a small office?”

To cater to these types of prompts, you can create:

• Problem-solution guides
• Product recommendations
• FAQs
• Collection page buying guides

2. “Best For” Prompts

Customers enter this type of prompt when they’re looking for the best product for a specific situation. They might type prompts like “best dog lead for training,” “best jacket for Melbourne winter,” or “best skincare product for beginners.”

Create this type of content to appeal to “best for” prompts:

• Best-for sections on product pages
• Buying guides
• Comparison articles
• Collection page recommendations

3. Comparison Prompts

Sometimes, customers ask AI engines to compare product types, materials, sizes, or brands. They might ask to compare ceramic and stainless steel bowls or fleece and suede jackets. 

These prompts pair well with content like this:

• Comparison articles
• Comparison tables
• Category page comparison sections
• FAQs

4. Suitability Prompts

If customers want specific, personal advice, they might ask if a product is suitable for these needs. “Is this jacket suitable for travel?” and “are single-ingredient dog treats good for puppies?” are just two examples of what people might search for.

To rank for suitability prompts, create this content:

• Product FAQs
• Use-case sections
• Best-for and not-best-for sections
• Buying guides

5. Budget and Value Prompts

Many customers love to save money, so they might search for items within a certain price range. They might use terms like “affordable,” “best value,” or “under $100” in their search to specifically seek out deals.

These aspects are great for price-related queries:

• Price-based guides
• Value comparison content
• Collection filters
• Product descriptions that explain value and durability

6. Trust and Brand Prompts

Some customers want to know if a specific brand is reliable before purchasing from them. This could be a brand-focused query like “is [brand] good quality?” or a question seeking advice, such as “where can I buy trustworthy skincare products in Australia?”

You can enhance your brand’s credibility with these:

• About page content
• Review sections
• Testimonials
• Brand comparison content
• Trust signals
• External mentions and PR

How to Find Prompt Ideas

To get an idea for what your customers are searching for, look at real questions from:

• Customer emails
• Live chat transcripts
• Product reviews
• Site search data
• Google Search Console queries
• People Also Ask results
• Reddit, forums, and social media
• Sales team conversations
• AI tools themselves

The goal isn’t to copy common customer prompts exactly, but instead, you should be trying to understand the language, context, and intent behind them. Then, use that information to create helpful, relevant content across your site.

How to Map Prompts to Website Content

Product Pages

Product pages can rank for queries about specific products, features, materials, and use cases. Include clear product summaries, best-for sections, FAQs, specifications, benefits, and use-case examples to help your page get noticed in product-related prompts.

Collection Pages

Collection pages work well for broader category prompts. A strong collection page should do more than just list products. It should also include buying guidance, comparison sections, shop-by-use-case content, category FAQs, and links to related guides to provide context to AI platforms and search engines.

Blog Articles and Guides

Blog content caters to deeper educational prompts. You could include articles that help customers choose products, compare options, or find products for different situations. Writing about common mistakes, care guides, and problems/solutions can provide more helpful context.

About and Trust Pages

Brand pages can make your credibility, values, and other details clear to people asking about your brand. Include your brand story, business details, reviews, media mentions, guarantees, and shipping/returns information on your website so AI engines can easily find your company’s information.

Simple Prompt Mapping Template

When researching customer prompts, follow this guidance to help you understand queries and create content around them:

1. Customer Prompt – What are customers searching? (Example: “what is the best water bottle for hiking?”)
2. Search Intent – What is the purpose of the query? Are they seeking advice, recommendations, or solutions?
3. Best Content Type – Determine what type of content will relate to the query best, whether that’s a product, collection, or buying guide.
4. Existing Page or New Page – If you already have a page that addresses this query, update it. If not, create a new page with beneficial content.
5. Key Answer – Make sure the prompt is clearly answered in your content.
6. Related Links – Link to related products, collections, and guides to help AI engines understand how concepts are related on your site.
7. Trust Signals – Include reviews, product details, and safety guidance whenever relevant.

Common Mistakes to Avoid

As you’re optimising your site for common prompts, avoid these mistakes:

• Only researching short keywords
• Ignoring long, conversational questions
• Creating generic content that doesn’t clearly answer the prompt
• Only using blog posts for answers without improving product and category pages
• Not linking prompts back to commercial pages
• Not including reviews and customer support questions
• Writing for AI tools instead of real customers
• Publishing lots of thin articles without helpful details

Quick Checklist

Now that you know the basics of prompt-level research, here’s a checklist to help you get started:

• Collect real customer questions
• Categorise prompts by intent
• Identify problem, comparison, suitability, and best-for prompts
• Map each prompt to the right page type
• Improve product and collection pages first
• Create guides for deeper questions
• Add FAQs when relevant
• Connect related pages using internal links
• Add reviews and trust signals
• Keep answers clear, specific, and beneficial

Prompt-Level Research Helps Your Site Reach Common Queries

Researching prompts is the key to helping ecommerce brands understand how customers ask AI tools for advice. By understanding these queries, brands can more easily incorporate helpful information into their content.

The goal isn’t to chase every possible prompt, but instead, it’s to map common customer questions to the right content. When brands build clear product pages, helpful supporting content, and strong trust signals, it’s easier for both AI systems and customers to find and understand them.