The Complete Guide to AI Recommendations by Buyer Question Type

AI recommendations depend heavily on the type of question asked. Discovery questions reward helpful explainers, shortlist questions reward clear positioning and outside proof, comparison questions reward honest side-by-side facts, and brand-check questions reward consistent, accurate information. Mapping your content to these four types is the most reliable way to improve how often AI assistants recommend you.

Type 1: Discovery questions

Examples: “How do heat pumps work?”, “What should I look for in a payroll tool?”

The buyer is learning. The assistant usually explains and may name a few brands as examples. Brands that publish clear, neutral guides on the topic are more likely to be used as sources here.

• Write explainers that teach, not sell.
• Include buying criteria, which positions you for the next stage.
• Keep them factual and well organised.

Type 2: Shortlist questions

Examples: “Best heat pump installers in Lyon”, “Top payroll software for a 15-person startup”

This is where recommendations happen. The assistant names a few options. It tends to lean on sources that compare options: review platforms, directories, roundup articles and well-known publications.

• State plainly who you serve best, such as “for startups under 50 people”.
• Build honest reviews on the platforms your industry uses.
• Get listed in relevant directories and roundups through genuine outreach.

Type 3: Comparison questions

Examples: “Brand A vs Brand B for freelancers”, “Is a heat pump cheaper than a gas boiler?”

The buyer is choosing. The assistant looks for clear differences.

• Publish fair comparison pages, including where the alternative is a better fit.
• Present facts in short lists: price, features, support, contract length.
• Keep them current. Outdated comparisons are a common source of wrong AI answers.

Type 4: Brand-check questions

Examples: “Is [brand] legit?”, “What does [brand] cost?”, “Does [brand] deliver to Belgium?”

The buyer has nearly decided and wants reassurance. Wrong facts here can lose a sale at the last step.

• Keep a clear FAQ with prices, policies, delivery areas and contact details.
• Make sure every listing and profile shows the same facts.
• Respond professionally to reviews, including negative ones.

For fixing errors, see how to update brand info in AI tools.

Mapping your content

Make a simple table with the four types as columns. Under each, list the questions your buyers ask and the page that answers it. Empty cells are your content plan. Most businesses find they have plenty of type 1 content and very little for types 3 and 4.

What drives recommendations across all types

• Clarity: one consistent description of what you do and for whom.
• Relevance: content that matches the exact question.
• Corroboration: independent sources that say similar things about you.
• Freshness: current facts, especially for live-search assistants.
• Access: pages that crawlers can read.

What does not work

Fake reviews, paid placements disguised as editorial, and promotional posts across forums can break platform rules, and AI developers work to filter manipulation. They also do not survive scrutiny from real buyers. No one can guarantee a recommendation, so focus on the honest levers above. For the bigger picture, read how language models discover and trust brands.

How Keboost helps

Keboost tracks prompts of all four types across ChatGPT, Gemini, Claude, Perplexity, Copilot and others, shows where you and your competitors appear, and creates focused content for the gaps. Run a free AI visibility check to see which question types you are missing.