A Query Design Guide for Getting Chosen by AI Search
In B2B GEO, registering service names and company names alone is not enough.
Designing queries around the contexts in which buyers consult AI
—challenges, process improvement, tool comparison, and adoption decisions—
is the starting point for being chosen by AI.
B2B buyers don't necessarily ask AI "Should I contact Company ◯◯?" right away.
For example: "Where should I start to advance sales DX?," "What CRM tool do you recommend for small and mid-sized businesses?," "Tell me the difference between an MA tool and SFA," "Which suits our company better, ◯◯ or △△?"—in this way, they consult AI in the contexts of challenges, process improvement, tool comparison, and adoption decisions.
With Genview, we design these queries across three stages: TOFU, MOFU, and BOFU.
TOFU: The stage where the buyer doesn't know your service or company yet
TOFU is the stage where the user hasn't yet decided on a specific service name or company name.
At this stage, you check whether your service makes it into the candidate set for a given business challenge or improvement theme.
For example, for a CRM you would build queries starting from the user's challenge or business objective, such as "how to make customer management more efficient"; for an MA tool, "how to nurture leads"; for SaaS, "tools to make sales activities more efficient."
If your company doesn't show up here, from the AI's perspective it may not be recognized as a "representative service that solves that challenge."
MOFU: The comparison and consideration stage
MOFU is the stage where the user is comparing multiple services or companies.
At this stage, you check whether the AI can explain the reasons your company is chosen when compared against competitors.
For example, you register category-comparison and competitor-comparison queries such as "Compare recommended CRM tools for me," "Compare MA tools for small and mid-sized businesses," or "Tell me the difference between Company A and Company B."
In MOFU, it's important to look not only at whether your company is included as a comparison candidate, but also at which evaluation axes you are discussed on—features, price, track record, support structure, integrations, ease of use, and so on.
BOFU: The stage just before inquiry or adoption
BOFU is the stage where the user is checking their last concerns right before making an inquiry or adopting.
At this stage, you check whether the AI can accurately explain your service.
For example, these are queries like "What's the reputation of ◯◯?," "Is ◯◯ easy to use even for small and mid-sized businesses?," or "Which should I choose, ◯◯ or △△?"
In BOFU, you check whether the AI is putting out incorrect or outdated information about pricing, implementation period, support scope, systems it can integrate with, industries it excels in, and what it is and isn't suited for.
How to think about which queries to register for B2B
For B2B, we recommend including at least the following five contexts.
Context
Purpose
Query example
Challenge
See if you enter the candidate set for solving the business challenge
How can we make sales activities more efficient?
Process improvement
See if you're recommended for a concrete operational theme
What tools can make customer management more efficient?
Category
See if you're recognized within the service category
What are some recommended CRM tools?
Comparison
See the reasons you're chosen over competitors
Which is better, Company A or Company B?
Reputation
See if pre-adoption concerns are answered correctly
What's the reputation of ◯◯?
It's important to register not just service names and company names, but the words a person in charge is actually likely to use when consulting AI.
Ready-to-use query examples
TOFU Awareness-stage query examples
Tell me how to make sales activities more efficient
What should we do to nurture leads?
What tools can make customer management more efficient?
How can we get results in B2B marketing?
What should we do to increase the number of sales meetings?
How can we increase proposal opportunities to existing customers?
How can we automate follow-up after an inquiry?
How can we strengthen alignment between sales and marketing?
Where should a small or mid-sized business start to advance DX?
How can we improve sales management that depends too much on individuals?
Is ◯◯ easy to use even for small and mid-sized businesses?
Is ◯◯ expensive?
What kind of companies is ◯◯ suited for?
What is ◯◯'s support structure?
Can ◯◯ integrate with existing systems?
Which is better, ◯◯ or △△?
Tell me the pros and cons of adopting ◯◯
What should we check before contacting ◯◯?
Summary
In B2B GEO, rather than looking only at company names and service names, it's important to design queries for each context in which buyers consult AI.
In TOFU, the challenges and process-improvement themes of users who don't know your service yet. In MOFU, the consideration axes of users who are comparing multiple services. In BOFU, the concerns and reputation checks right before an inquiry or adoption.
By registering queries across these three stages, you can see how your service is recognized, recommended, and compared on AI.
Frequently asked questions
Q. Is it enough to register only queries that contain our own company name, like "What's the reputation of ◯◯?"
Queries containing your own company name (BOFU) are essential for checking how AI describes your company, but they aren't enough on their own. Many B2B buyers consult AI with a business challenge—like "how to make sales activities more efficient"—while they still don't know your service name. By also registering TOFU and MOFU queries that don't contain your name, you can check whether AI lists you as a candidate in the early consideration stage.
Q. If we're listed on comparison sites or review sites, will AI recommend us?
Being listed on comparison or review sites contributes somewhat to AI recognition, but it doesn't guarantee a recommendation on its own. Because AI assembles a picture of your service from multiple sources, consistency of information across your own site, comparison sites, and external media builds trust. Along with query design, it's important to organize the service information and case studies on your own site. For more detail, see our overview page on GEO for B2B.
Q. How can we check whether the queries we registered are producing results?
With Genview, you can continuously measure the appearance status and scores for each registered query across ChatGPT, Gemini, Perplexity, and more. You can track in numbers how AI's description changed—and whether the gap with competitors narrowed—before and after running a measure. We recommend starting with the free plan to check your current AI recognition and understand your starting point. See pricing plan details.