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How to Find the Best B2B Marketing Keywords for Your Business in the AI Era
Your buyers are asking layered, high-stakes questions. If your content only scratches the surface, you’re out of the game.
AI-powered search has rewritten the rules. It’s no longer about volume. It’s about visibility in LLMs, depth of answers, and how well your content mirrors real buyer conversations.
Traditional keyword research focused on search volume and keyword difficulty. That was built for a Google-only world. That world is gone.
B2B marketers now compete across AI search tools, voice platforms, and content-rich ecosystems.
To win, you need more than keywords. You need to understand how your ideal customers speak, why they search, and what signals authority.
This article gives you a new framework for finding the best keywords for your business. It uses Voice of Customer data, AI visibility metrics, and a clear focus on buyer intent.
Built for how B2B decisions are made today.
Inspired by insights from the CXL Cohort on Content Strategy for the AI Era, led by Alex Birkett, we’ll guide you through how to rethink B2B marketing keywords to stay ahead.
Search Volume Won’t Save You Anymore
Classic keyword research focuses heavily on monthly search volume and keyword difficulty. While once effective, this approach is increasingly insufficient for B2B contexts in the AI age.
AI search platforms like ChatGPT, Perplexity, and Bing AI have introduced what we call a “search everywhere” mindset.
Buyers no longer rely solely on Google but seek answers across multiple AI-driven platforms, social media, and niche communities.
Generic top-of-funnel content and keyword stuffing tactics are becoming less effective. AI can quickly summarize and filter vast amounts of information, reducing click-through rates to broad, surface-level content.
Moreover, the rise of multi-threaded conversations means users engage in complex, layered queries that reflect real buying journeys. These cannot be captured well by isolated keywords alone.
This shift signals the need to move from keyword-centric SEO to intent- and conversation-centric content planning, a critical evolution in modern B2B keyword research.
The New Framework: Prioritizing Voice of Customer and ICP-Driven Research
At the core of modern B2B keyword research lies Voice of Customer (VoC) research. VoC captures authentic customer language, pain points, and intent, revealing what buyers truly want and say, often in ways search volumes can’t measure.
Equally important is understanding your Ideal Customer Profiles (ICPs). ICPs provide the context to align your content with the multi-threaded buyer journeys unique to your business.
VoC research employs qualitative methods such as customer interviews, sales and support call transcripts, surveys, forums, social listening, and community engagement. These methods gather unstructured data that reflects real customer conversations.
Tools like Day.AI and Fireflies help transcribe and organize call data, while internal resources like Slack or Notion can be mined for relevant insights.
AI platforms such as ChatGPT and Notebook LM can then synthesize and cluster this data, helping you build actionable B2B topic roadmaps.
This approach empowers you to find bottom of funnel keywords OR low funnel keywords grounded in genuine customer intent, not just raw search numbers.
Integrating Competitive Analysis and AI Visibility Metrics
Competitive research remains vital. Benchmarking your competitors helps identify content gaps and opportunities to differentiate your messaging.
However, new metrics are emerging to measure success in AI-powered search environments:
- LLM (Large Language Model) Visibility: Tracking how often and where your content ranks within AI-generated answers on platforms like ChatGPT and Perplexity.
- Referral Traffic from AI Platforms: Setting up dashboards in Google Analytics 4 (GA4) or Looker Studio to monitor visitors coming from AI tools.
- Self-Reported Attribution: Asking prospects how they discovered your business. Many now report finding you via AI-driven search, an invaluable insight for ROI measurement.
For example, some B2B marketers have seen measurable increases in leads reporting AI referrals after adjusting their content strategy to align with AI visibility metrics.
Combining these insights with traditional SEO data enhances your ability to prioritize AI keyword research B2B opportunities effectively.
Auditing Existing B2B Content for AI Impact and Opportunity
Auditing your existing content is essential in the AI era.
AI-powered search often displays overview snippets and summaries that can reduce click-through rates to generic content.
Perform audits to identify:
- Where AI-generated summaries may be stealing clicks.
- Topical gaps where competitors or AI tools dominate answers.
- Content lacking authentic voice of customer SEO B2B language or subject matter expert depth.
Use tools like Ahrefs and SEMrush alongside AI visibility reports to assess which pages need updating.
Refresh content by adding proprietary data, expert quotes, and deeper insights. This re-establishes your authority and increases your chances of being the preferred source in AI summaries and traditional search.
Practical Steps to Build a B2B Content Roadmap in the AI Era
Here’s a step-by-step approach to building a modern, AI-aligned B2B content roadmap:
- Collect and Synthesize ICP and VoC Data: Use qualitative research to understand your audience’s real language and intent.
- Map Customer Pain Points to Product Differentiation and Messaging: Connect buyer needs directly to your unique value propositions.
- Conduct Competitive Landscape Analysis: Identify gaps and opportunities in your niche.
- Use AI Visibility and Referral Metrics: Prioritize topics and channels where AI and LLM visibility can drive impact.
- Audit Existing Content: Refresh for AI compatibility and add depth.
| Action Item | Tools / Notes |
| Conduct interviews, survey customers | Fireflies, Day.AI, Slack mining |
| Create pain point-to-product mapping | Internal workshops, CRM data |
| Analyze competitors’ content & gaps | Ahrefs, SEMrush |
| Track AI referrals & LLM visibility | GA4, Looker Studio, AI tools |
| Audit and refresh existing pages | SEO tools, expert contributions |
Remember, AI-driven search is evolving fast.
Ongoing experimentation and iteration are key to long-term success.
Why Becoming a Credible Source Matters More Than Ever
Keyword research evolution ties closely to brand authority and trust signals needed by AI and LLMs.
“Hard to fake” signals such as expert authorship, unique insights, first-person experience, clear citations, and consistent brand mentions have never been more important.
Building credibility boosts your inclusion in AI-generated summaries and recommendation algorithms, making you the obvious choice for buyers.
In B2B, this means aligning marketing with sales, product marketing, and customer success to deliver content that demonstrates deep expertise and addresses specific customer challenges.
Turn Insight into Action: Build a Keyword Strategy That Wins
Relying solely on raw search volume data will leave your B2B marketing strategy behind.
By embracing voice of customer research, focusing on your ideal customer profiles, and tracking AI visibility metrics, you’ll develop a modern keyword and topic strategy that drives real business results.
This shift is an opportunity to create deeper, more credible content that outperforms across both traditional search and AI-powered platforms.
For those seeking deeper, hands-on frameworks and expert guidance, explore CXL’s AI in B2B Marketing program to accelerate your journey.
If you want a proven framework to align your experts, editors, and strategists, I highly recommend reading Alex Birkett’s Editorial Cabinet model. It offers a practical and repeatable approach to content production without sacrificing depth or quality.
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