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I know the impact of ignoring buyer’s journey keywords all too well, and AI buyer journey mapping makes understanding your buyers’ questions even more important. Early in my SEO career, I generated two million clicks for an ecommerce store. The client and I were thrilled. The graph in Google Search Console was trending strongly upward.

The problem? I couldn’t attribute a single sale to those two million clicks. I had focused on generating traffic without building a keyword strategy for buyers.

I learned my lesson the hard way. Now, everything I do in SEO centers around the buyer and the end goal: a sale. But buyers don’t just research through traditional search results anymore. Buyers also use AI tools to explore problems, compare solutions, and ask for recommendations, sometimes without visiting a website.

How do I map my buyer’s journey to the questions they’re asking AI? I start with the keywords and questions that matter at each stage, then use them to identify potential AI prompts and plan content that helps buyers move toward a decision.

Table of Contents

• The Role of the Buyer’s Journey in Keyword Research
• Keyword Intents for Each Buyer’s Journey Stage
• How to Do Keyword Research for Each Stage of the Buyer’s Journey
• Tips for Doing Keyword Research Aligned With the Buyer’s Journey
• Buyer Journey Keyword Strategy Helps You Qualify Content’s Role
• Common Mistakes to Avoid When Mapping Keywords to the Buyer’s Journey
• Frequently Asked Questions About the Buyer Questions
• Turn your SEO strategy into a revenue-generating machine with buyer journey keywords.

The Role of the Buyer’s Journey in Keyword Research

The buyer’s journey includes the steps a potential buyer takes before they purchase. Understanding the buyer’s journey steps helps marketers identify the keywords buyers search for and the questions they may ask AI assistants as their needs evolve. Generally, the buyer’s journey has three stages.

1. Awareness: The buyer recognizes a problem or opportunity and begins researching it.
2. Consideration: The buyer understands the problem and evaluates potential solutions.
3. Conversion: The buyer evaluates specific providers or products and prepares to make a purchase decision.

Sometimes, it’s represented in a funnel, known as the marketing or conversion funnel. The stages of that funnel are:

• Awareness = Top of Funnel (ToFu)
• Consideration = Middle of Funnel (MoFu)
• Conversion = Bottom of Funnel (BoFu)

Understanding buyer’s journey keywords helps marketers connect search intent to content that supports buyers at each stage, from identifying a problem to choosing a provider. Recent suggests that 34% of shoppers use AI tools to compare products and conduct product research. Keyword research now needs to account for how buyers use AI tools to explore those same decisions.

A buyer might start with a traditional search query, then ask an AI assistant a more specific question that includes their goals, constraints, or business context. They may also ask follow-up questions as they evaluate their options. Mapping keywords to the questions buyers might ask AI tools helps marketers identify additional content needs at each stage of the journey, even when they can’t observe those individual AI conversations.

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Keyword Intents for Each Buyer’s Journey Stage

Each stage of the buyer’s journey reflects a different need. Keyword research helps marketers identify those needs and create content that meets buyers where they are. That doesn’t always mean pushing for a sale. Early-stage content, for example, can help buyers understand a problem and build familiarity with a brand before they’re ready to evaluate solutions.

Keyword research is also the starting point for AI prompt research. Traditional SEO still matters, and understanding the keywords buyers search for helps identify the topics and questions that content needs to address. But a keyword rarely captures the full context of what a buyer wants to know.

AI buyer journey mapping helps address the context of what a buyer wants to know. Buyers may use traditional search, AI tools, or both as they move through the journey. When asking an AI assistant for help, they can provide more context about their goals, constraints, and available options. A keyword such as “best CRM for small business” might become a question about which CRM would work for a 10-person sales team with a limited budget and specific integration requirements.

The keyword identifies the topic. The full question reveals the buyer’s needs. And those needs change as buyers move from understanding a problem to evaluating solutions and making a decision. Let’s look at how keyword and prompt research can help identify the questions buyers ask at each stage of their journey.

Awareness

Awareness-stage keywords are often problem-based and question-driven, such as “how to,” “why does,” or “what is.” These terms align with the buyer’s intent to learn about their situation without being pushed toward a particular product.

At this stage of the buyer journey, the buyer has identified a problem but doesn’t fully understand it or know whether a solution exists. They’re seeking general information or education to clarify the issue, which means a brand needs helpful, educational content that helps buyers better understand their problem or opportunity.

Example of a Buyer in the Awareness Stage and the Keywords to Support Them

Consider a sales manager who notices that their team isn’t consistently following up with leads. They might search for:

• Why doesn’t my team follow up with leads?
• How to motivate a sales team.
• Processes to manage leads.

If the sales manager turns to an AI assistant, they might ask a more contextual question: “My sales team keeps missing follow-ups with qualified leads. What could be causing this, and how can I improve our process?”

The buyer is still trying to understand the problem. They haven’t necessarily decided that they need a CRM or any other specific solution.

Content that explains common causes of missed follow-ups, outlines lead management processes, and offers practical ways to improve sales workflows can address this intent across traditional search and AI-assisted research.

Consideration

Consideration-stage keywords are often comparison- and solution-oriented, such as “best tools for,” “top strategies,” “[solution] versus [solution],” or “solution to [problem].” These searches indicate that the buyer is evaluating ways to address an identified need.

This stage of the buyer’s journey needs content that explains available solutions and helps buyers evaluate which approach fits their needs.

Example of a Buyer in the Consideration Stage

Let’s return to the sales manager. They’ve identified inconsistent lead management as the problem and are now exploring ways to solve it. Their searches might include:

• Best ways to automate sales follow-ups.
• CRM versus lead management software.
• Best CRM for a small sales team.

An AI-assisted research question might look like this:

“We have a 10-person sales team that struggles to track lead follow-ups. Should we improve our existing process, use an automation tool, or invest in a CRM? Compare the options based on cost, implementation time, and ease of use.”

This question goes beyond naming a product category. It asks for a comparison of possible approaches against the buyer’s specific requirements.

That context matters when mapping content to buyer intent. AI-search queries should account for buyer personas and buying stages, as well as the different pain points and features each buyer cares about. For marketers, this means consideration-stage content should do more than list product features. Comparison guides, use-case pages, and resources that explain implementation requirements or trade-offs can help buyers evaluate their options.

Conversion

Conversion-stage keywords are often specific and action-oriented, such as “buy,” “get a quote,” “pricing,” or “[product/service] near me.” Depending on the purchase, buyers may also search for product reviews, implementation details, or comparisons between shortlisted providers.

This stage of the buyer’s journey needs personalized content that resolves remaining purchase questions and makes the next step clear.

Example of a Buyer in the Conversion Stage

The sales manager has decided to purchase a CRM and narrowed the options to two providers. Before clicking “Start Free Trial” or booking a demo, they might search for:

• [CRM name] pricing for 10 users.
• [CRM name] integrations.
• [CRM A] versus [CRM B] implementation.

They might also ask an AI assistant: “Compare [CRM A] and [CRM B] for a 10-person sales team. Which features are included in each pricing tier, how long does setup typically take, and which integrations should we check before choosing?”

At this stage, accurate pricing pages, product documentation, integration details, and clear trial or demo information can help the buyer resolve outstanding questions. These resources also give AI tools information to draw from when answering purchase-specific prompts. The key things to understand are:

• Buyers have different information needs as they identify problems, evaluate solutions, and make purchase decisions.
• Not every buyer starts at Awareness or moves through the stages in a straight line. New information may send them back to an earlier stage.
• Buyers may move between traditional search and AI-assisted research throughout the journey.
• The three stages are broad categories. Their specific questions and needs vary by industry, business, and individual buyer, so marketers need to understand their own buyers’ journeys before mapping keywords and potential AI prompts to content.

How to Do Keyword Research for Each Stage of the Buyer’s Journey

With the context of the buyer’s journey, each phase, and some keyword ideas established, I’ll walk you through a step-by-step process of how I map the buyer journey with keyword research. When doing keyword research, it’s tempting to start from the top with the awareness stage, but I reverse this process and start at the bottom buyer journey stage, conversion. I start with conversion for two main reasons:

1. Conversion-driven keywords are the most important.
2. Starting with conversion keywords keeps me focused. You can quickly become overwhelmed by the content opportunities starting at ToFu.

Step 1: Prepare a Google Sheet.

Create a spreadsheet and save it somewhere easily accessible. Use it to organize keyword research and map keywords to the different stages of the buyer’s journey.

Start with columns for the buyer’s journey stage, focus keyword, supporting keywords, search intent, and target page. Additional columns can be added for the buyer questions and potential AI prompts identified later in the process. Keeping everything in one place makes it easier to connect keyword research to the content buyers need, whether they’re using traditional search or AI tools.

I love to record my buyer journey keyword strategy in Google Sheets. For now, there’s no need to do anything fancy.

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Step 2: Identify your bottom-funnel keyword.

There are several ways to find bottom-funnel keywords, but I like to start with the search terms that are already generating conversions.

These keywords often reveal what buyers are looking for when they’re close to making a purchase. They can also provide a starting point for identifying the pricing, product, and provider-specific questions buyers might ask AI tools during the decision stage. Start with an active Google Ads account:

1. Sign in to .
2. Click “Insights and Reports,” then “Search Terms.”
3. Filter the table by the highest conversions.

The screenshot above shows a redacted Google Ads account for one of my clients. It demonstrates how to find search terms that have generated conversions.

Important note: A conversion doesn’t always mean a sale. In this example, the highest-converting keyword was excluded because it generated conversions but didn’t lead to sales. The ads manager excluded the term, so it likely isn’t a priority for SEO either.

Pro tip: Many high-converting search terms will include a brand name. I don’t automatically exclude them from my research. Branded queries can reveal valuable decision-stage questions about pricing, product capabilities, integrations, and comparisons with competing solutions. I review which terms are already performing well and which represent opportunities to improve content.

Research buyer journey keywords using SEO tools.

SEO tools such as Semrush provide keyword suggestions, search volume estimates, and search intent classifications. I like to use Semrush’s Keyword Magic Tool for this stage. Start with a head keyword that describes the product or service you’re selling. For this example, I’ve chosen “CRM.” To find potential bottom-funnel keywords, I follow these steps:

1. Enter the head keyword into the keyword research tool.
2. Filter the results by commercial and transactional intent to identify keywords associated with evaluating or purchasing a solution.
3. Manually review the suggested keywords. Look for purchase-specific terms related to pricing, demos, product features, and providers, then determine which belong in the Conversion stage.
4. Add the relevant keywords to the buyer journey spreadsheet.

Pro tip: Don’t worry too much about search volume and keyword difficulty. Generally, conversion keywords are the most difficult to rank for and often have lower search volumes. Remember the marketing funnel? The smallest section is at the bottom, where users in the buyer journey decrease.

Research buyer journey keywords using Google Search Console and GA4.

Google Search Console is another useful source of buyer journey keywords, especially when search performance data can be combined with conversion data from Google Analytics 4 (GA4). The goal is to identify pages that contribute to conversions and then examine the search queries bringing visitors to those pages. First, find converting landing pages in GA4:

1. Sign in to Google Analytics.
2. Open Reports and navigate to the landing page report.
3. Review landing pages using the conversions, key events, or revenue metrics relevant to the business.
4. Identify the pages contributing to the desired business outcomes.

Next, use Google Search Console to identify the search queries associated with those pages:

1. Sign in to Google Search Console.
2. Open the Performance > Search results report.
3. Add a page filter.
4. Enter the URL of a converting landing page.
5. Review the queries generating impressions and clicks for that page

Look for queries that indicate purchase intent, such as searches for pricing, demos, product features, or specific solutions.

Pro tip: Google Search Console doesn’t identify which individual queries generated conversions. I use GA4 to understand how a landing page performs and Search Console to identify the queries that bring visitors to it. Together, these reports help me prioritize keywords, but they don’t establish a direct conversion value for every query.

As I review bottom-funnel keywords, I make a note of any purchase-specific questions they suggest. We’ll use those questions in Step 7 to develop potential AI prompts and evaluate how a brand appears in AI-generated answers.

Step 3: Conduct keyword research for middle-funnel (consideration) buyer journey keywords.

The previous step provides a list of bottom-funnel keywords associated with buyers who are close to making a purchase. These keywords will generally be mapped to:

• Product pages.
• Service pages.
• Conversion-driven landing pages.

Later, I’ll discuss keyword mapping to explain where to place each keyword. Before creating more content, though, I like to make sure I have resources that support those bottom-funnel pages. That means identifying the questions buyers ask when they understand their problem but are still evaluating potential solutions. Consideration-stage content can include:

• Product and solution comparisons.
• Case studies and customer success stories.
• Customer reviews and testimonials.
• Use-case guides and articles that explain different approaches to solving a problem.

Some of these pages may already exist on the website. I like to start by reviewing them in Google Search Console to see which queries are generating impressions and clicks. To do this, follow the steps from the previous section and filter the search performance report by page. Look for keywords that indicate buyers are comparing solutions, evaluating specific capabilities, or researching how a product might work for their situation.

For example, a sales manager researching CRM software might search for “CRM vs. sales automation software” or “best CRM for a small sales team.” These keywords can also help you identify the more detailed questions buyers might ask AI tools, which we’ll explore in Step 7.

Don’t overlook review-related keywords. Buyers evaluating solutions may look for other resources before making a purchasing decision, including:

• Customer experiences
• Product limitations
• Independent assessments
• Testimonials
• Customer stories pages
• Third-party reviews

Pro tip: If a consideration-stage question has low search volume, it’s not necessarily worth dismissing. Some content is valuable because it helps buyers evaluate their options, even if it doesn’t attract significant organic traffic. These resources can also support sales conversations, email campaigns, and other marketing activities.

Step 4: Conduct keyword research for top-of-funnel (awareness) buyer journey keywords.

Finally, I identify keywords for the Awareness stage, where buyers are beginning to understand a problem. As they move toward Consideration and Conversion, their questions become more specific to potential solutions and providers.

I return to Semrush’s Keyword Magic Tool, remove the commercial and transactional intent filters, and look for informational keywords and questions that could inspire educational content.

For example, a sales manager might search for “why is my sales team missing follow-ups?” or ask an AI assistant, “What’s causing my team to miss lead follow-ups, and how can we improve our process?”

Prioritize questions buyers actually need answered rather than chasing high-volume keywords. AI-generated answers give buyers another way to explore early-stage questions, sometimes without visiting a website, so content should clearly address the problems and concepts they’re researching.

Important note: Keyword research tools provide useful inspiration, but there’s no replacement for talking to customers and the people who work with them. Sales and customer service teams can share which questions come up most often, who the target audience is, what problems buyers are experiencing, and what information they need to move forward.

Step 5: Understand search intent and SERP analysis.

At this point, the keyword map may already indicate where some keywords belong. Some bottom-funnel keywords are relatively straightforward. For example, “CRM demo” suggests that the buyer wants to see the product in action, so a demo page would be a logical destination. Other keywords require more investigation.

I like to start by searching Google in a private browsing window to reduce the influence of my usual search history. Then, I review the search engine results page (SERP) to understand how Google interprets the query and what types of content are appearing.

Let’s use “best CRM for sales and marketing teams” as an example.

Here’s what I look for when analyzing the results:

• Which pages are ranking? Are the results primarily product pages, comparison guides, review sites, or informational articles? This helps me understand the type of content Google is surfacing for the query.
• Which SERP features appear? Look for People Also Ask questions, videos, review snippets, and AI Overviews. These can reveal related questions and content formats worth investigating.
• What information do the results emphasize? Look for recurring topics, such as pricing, integrations, product features, or comparisons between providers.

From this analysis, I can identify the content formats and information buyers may expect to find when searching for that keyword. For example, if the results include several comparison guides and review sites, a product page alone might not fully address the buyer’s intent. A comparison article or use-case guide could be a better fit.

AI-search connection: SERP analysis can reveal related questions and information needs that may also be relevant to AI-assisted research. I make a note of these alongside my keywords and use them in Step 7 to develop potential AI prompts.

Pro tip: SERP analysis is a starting point, not a set of instructions to copy competing pages. Combine insights from search results with customer research to determine which content will best address buyers’ needs.

Step 6: Map keywords to pages.

Once the search intent behind the keywords is clear, the next step is to map them to the right content. This process is called keyword mapping. It involves assigning a primary keyword and relevant supporting keywords to the page that best addresses the buyer’s needs.

Not every keyword needs its own page. Some questions share the same intent and can be answered together, while others require more specific content. A good example is Google’s People Also Ask feature. For the search “road bike for women,” questions might include:

• What is the best road bike for ladies?
• What size road bike do I need for a woman?
• Which bike is best for females?
• Are road bikes good for weight loss?

Although these questions relate to the same general topic, they don’t all address the same need. For example, “What is the best road bike for ladies?” focuses on choosing a particular type of bike, while “Which bike is best for females?” could refer to several types of bicycles. Depending on the search results and the business’s product offering, these questions might warrant separate pages or fit within a broader buying guide.

Meanwhile, “What size road bike do I need for a woman?” addresses a more specific purchasing question that a road bike sizing guide could answer.

I use SERP analysis to determine whether keywords share the same intent and whether one page can answer the related questions thoroughly. I avoid creating separate articles for every keyword variation when the content would substantially overlap.

Important note: Keyword mapping should reflect the audience and business. For example, a business that only sells road bikes might choose to group several related buying questions into one comprehensive guide rather than creating separate pages for bicycle categories it doesn’t offer.

I like to record my buyer journey keyword map in Google Sheets. Here’s what my sheet looks like:

I record a draft title, the page’s focus keyword, supporting keywords, and buyer journey stage. This helps me understand where each keyword belongs and which questions the content needs to answer.

The keyword map also provides a starting point for AI buyer journey mapping. In the next step, we’ll use these keywords and their associated buyer questions to develop potential AI prompts and evaluate whether your content appears in relevant AI-generated answers.

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Step 7: Map buyer questions to AI prompts.

A keyword identifies the topic, while customer research helps reveal the underlying question and the context buyers bring to it. That context can then inform a potential AI prompt. The goal isn’t to turn every keyword into a longer sentence. It’s to understand what buyers need to know at each stage and investigate how AI tools respond to those questions.

Start with the keywords and pages in the spreadsheet. Then, use customer interviews, sales conversations, support tickets, and search data to identify the questions buyers have about each topic. These sources can help develop realistic AI prompts that reflect the audience’s needs.

For example, let’s return to the sales manager researching ways to improve lead follow-ups. Here’s how their questions might change throughout the buyer’s journey:

When a relevant question isn’t adequately answered by existing content, I return to the keyword map to determine whether an existing page needs more information or whether the question warrants a separate resource. For example, if AI-generated comparisons repeatedly discuss CRM implementation requirements that the product’s existing content doesn’t address, that may reveal an opportunity to expand a use-case guide or product documentation.

Once the prompt library is organized by buyer’s journey stage, the next step is to test the questions in the AI tools buyers are likely to use. I record the results in my spreadsheet to establish a baseline and compare future responses. I recommend tracking the following:

• Prompt and buyer’s journey stage, which is the exact question tested and whether it represents Awareness, Consideration, or Conversion.
• AI tool and test date, which is where and when the prompt was tested, since AI-generated answers can change over time.
• Brand presence, which is whether the brand appears in the answer and how it is described.
• Competitor presence, which looks at whether competing brands appear in the response.
• Cited sources that look at the pages or third-party sources the AI tool references, including whether it cites the brand’s website.
• Content opportunities, which looks at the questions existing pages don’t adequately answer or information that is missing from the content.

For example, if a CRM appears in answers to general lead management questions but is absent from comparisons for small sales teams, I review the sources cited in those comparison answers. I may find that the existing content doesn’t clearly explain which team sizes, workflows, or use cases the product supports.

I repeat the tests using a consistent prompt library to identify changes over time. Then, I compare what I observe in AI-generated answers with traditional performance metrics, including search impressions, clicks, conversions, and revenue. Run these tests manually or use a platform such as to track configured prompts and review brand visibility, competitor mentions, and citation insights.

Pro tip: Keep the keyword map, hypothesized prompts, and AI-visibility observations together. That makes it easier to connect a missing brand mention or unanswered buyer question to the page that may need updating.

贬耻产厂辫辞迟’蝉 provides the keyword research foundation, and marketers can extend that work with additional columns for buyer questions, potential prompts, and visibility observations.

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Tips for Doing Keyword Research Aligned With the Buyer’s Journey

Here are some tips to help guide keyword and AI prompt research aligned with the buyer’s journey.

Ask customers what they searched to find the business.

This tip is easy to implement, especially when mapping the B2B buyer journey, because the person on the other end of the phone likely knows why they’re asking how they found you. Buyers may also appreciate the diligence.

Once I’ve built a good rapport with a prospect, I ask what they searched for to find the business. I also ask what questions they had while researching their options and whether they used AI tools along the way.

These conversations can reveal the context behind a search, including the buyer’s goals, constraints, and follow-up questions. That information helps me move beyond individual keywords to develop more realistic potential AI prompts.

Start with buyer needs.

My process for buyer journey keyword research starts with buyer needs, and I can’t stress the importance enough. It’s very tempting to go to the tools and start finding keywords, but I prefer to focus on conversions and work backward from there, discovering impactful keywords that actually help buyers.

The same principle applies to AI prompt research. Rather than turning every keyword into a longer question, I consider what buyers need to understand, compare, or confirm at each stage of their journey.

Talk to sales and customer service representatives.

No one knows customers like sales and customer service representatives. I ask them which questions buyers ask frequently and what content could address common apprehensions and build trust.

I also ask about the details buyers provide when asking those questions. Their budget, team size, existing tools, and specific requirements can help reveal how a broad keyword might translate into a more contextual question asked of an AI assistant.

Remember to repurpose content.

Although keywords and SEO are incredibly important, it takes time to rank in the top spots of Google. In the meantime, content can reach buyers through other means: ads, emails, social media, etc.

The same content can also address questions buyers may ask AI tools. I review existing articles, comparison guides, and product pages before creating something new to determine whether they already contain the information needed to answer relevant buyer questions.

Refer to Google Search Console regularly.

Google Search Console (GSC) data updates frequently. I keep a close eye on search queries, clicks, and impressions, looking for new opportunities to add relevant keywords to existing content.

I like to look at high impressions and low clicks to spot keywords people are searching for. Those queries can also provide a starting point for identifying related buyer questions to investigate through AI prompt research.

Feeling conflicted about SERPs? Do the integral thing.

Sometimes, a keyword map or SERP analysis doesn’t quite feel right. I always say that doing what’s right for the buyer and the business comes first.

The same goes for AI-generated answers. Just because an AI tool emphasizes a particular topic or cites a competing page doesn’t mean the content strategy needs to follow suit. I use those observations alongside customer research to determine what information buyers actually need.

The right content may still rank or appear in AI-generated answers, even if it doesn’t quite align with what the current results appear to prioritize. There’s always an opportunity to revisit the content and make adjustments later.

Buyer Journey Keyword Strategy Helps You Qualify Content’s Role

SEO is notorious for being tricky when it comes to tracking its contribution to sales. It’s not like ads, where keywords can have sales assigned to them. Instead, organic search data primarily shows clicks and impressions.

AI search adds another layer of complexity. Buyers may discover a brand through an AI-generated answer without visiting its website. Even when they do click through, it can be difficult to connect that visit to a specific AI response or determine how it influenced a later purchase.

However, there is a major benefit to buyer journey mapping: not everything is created to convert. Some content helps buyers understand a problem, while other content supports their evaluation of solutions or helps them make a purchase. This means tracking can be adjusted according to the role each piece of content plays.

Here’s how I approach measurement across traditional and AI search:

• Track awareness-stage performance. For ToFu content, monitor organic clicks, impressions, newsletter signups, and return visitors. For relevant AI prompts, track whether the brand appears in generated answers and whether its content is cited.
• Measure content’s contribution to the buyer journey. Use segment analysis to compare purchasers with users who viewed an article before making a purchase within a defined time frame. This helps show how content supports the buyer journey, even when it isn’t the final page visited before conversion.
• Track conversions from bottom-funnel pages. Monitor sales, demo requests, and other conversions from pages targeting bottom-funnel keywords. Review AI-generated answers to relevant purchase-stage prompts to see whether the brand appears and whether its pricing, product information, or other decision-stage content is cited.
• Monitor brand visibility across AI-generated answers. Use a consistent set of prompts organized by buyer journey stage to track brand mentions, competitor presence, and citations over time. These observations help identify visibility gaps, but they don’t establish how many buyers saw an answer or whether it led to a sale.
• Use paid search data to identify organic opportunities. Keywords that generate conversions through ads may also be worth targeting organically. They can also provide a starting point for identifying purchase-specific questions to investigate in AI-generated answers.

The goal is to understand how content supports buyers at each stage of their journey. Traditional search performance, conversion data, and AI visibility observations provide different pieces of that picture, even when they can’t be tied to a single sale.

Common Mistakes to Avoid When Mapping Keywords to the Buyer’s Journey

Before creating content, there are a few mistakes I see marketers make when mapping keywords to the buyer’s journey.

1. Choosing keywords based on search volume alone.

A high-volume keyword might bring traffic to a website, but that doesn’t mean it addresses a question buyers are asking. I’d rather target a more specific keyword that helps the right person move forward than chase traffic that has little relevance to the business.

2. Assuming every keyword belongs to one buyer journey stage.

Search intent isn’t always clear-cut. Someone searching for “best CRM software” might be comparing options for the first time or narrowing down a shortlist before requesting a demo. I use SERP analysis and customer insights to determine which questions the content needs to answer.

3. Creating a separate page for every keyword or question.

Closely related keywords often share the same intent. Creating multiple pages that answer essentially the same question can lead to overlapping content. I use keyword mapping to group related questions and decide when a topic needs its own page.

4. Treating SEO keywords as exact AI prompts.

A keyword such as “CRM for small business” can inspire several questions a buyer might ask an AI assistant, but it doesn’t reveal exactly how people phrase those questions. I use customer conversations, sales insights, and keyword research to develop realistic prompts, then test them rather than assuming they represent actual buyer behavior.

5. Measuring success by rankings and traffic alone.

Rankings and organic traffic are useful, but they don’t reveal whether content is helping buyers evaluate solutions or whether a brand appears in relevant AI-generated answers. I look at engagement and conversion data alongside AI visibility measures, such as brand mentions and citations for the prompts I’m tracking.

The goal isn’t to assign every possible keyword or prompt to a page. It’s to create a useful map of the questions buyers need answered and make sure they can find those answers as they move toward a decision.

Frequently Asked Questions About the Buyer Questions

How do I map buyer journey keywords to AI prompts?

Start with the keywords and buyer questions identified for each stage of the journey. Then, consider how someone might ask an AI assistant for the same information.

For example, the keyword “CRM for small business” might inspire a prompt such as “What should a small sales team look for when choosing a CRM?” Customer conversations and sales insights can help make these prompts more realistic. Record them alongside the relevant keywords, buyer journey stages, and content in the spreadsheet.

Remember, these are potential buyer prompts, not a record of exactly what people are asking AI tools.

How can I measure whether my brand appears in AI-generated answers?

Start by creating a list of prompts relevant to buyers and testing them in the AI tools being monitored. Record whether the brand is mentioned, whether its website is cited, which competitors appear, and which sources the answers reference.

Repeat the tests over time using a consistent set of prompts. AI-generated answers can vary between runs, so I look for patterns rather than treating one response as a definitive measure of visibility.

What are common mistakes in AI buyer journey mapping?

The biggest mistake is assuming that traditional search keywords reveal exactly what buyers ask AI assistants. Keywords are a useful starting point, but AI prompts can include more context, follow-up questions, and specific requirements.

I’d also avoid focusing only on prompts that mention the brand, treating a single AI response as representative, or creating new content for every prompt variation. Instead, I map related questions to the buyer journey, identify where existing content can answer them, and track visibility across a consistent set of relevant prompts.

Turn your SEO strategy into a revenue-generating machine with buyer journey keywords.

Since using buyer journey keywords and building a strategy from the bottom-of-funnel keyword, I’ve felt much happier with my SEO. Upward-trending graphs are still deeply fulfilling and exciting, but generating revenue — and being able to demonstrate SEO’s contribution to it — is far more valuable.

Keyword research remains an important foundation for understanding buyer intent and building an SEO strategy that supports revenue. But as buyers use AI tools to research problems, compare solutions, and evaluate providers, marketers also need to understand the more contextual questions behind those keywords.

Mapping both keywords and potential AI prompts to the buyer’s journey helps connect content to buyers’ needs, identify gaps in traditional and AI search visibility, and keep the focus on what matters: helping buyers make informed decisions.

Editor's note: This post was originally published in May 2025 and has been updated for comprehensiveness.

Keyword Research Template

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• Search Volume
• CPC
• Ranking
• Keyword Difficulty

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