How to Conduct B2B Market Research with AI

Learn how to leverage AI for B2B market research, combining qualitative and quantitative methods to uncover actionable insights.

Understanding your market is a cornerstone of business success, particularly in the ever-evolving world of B2B companies. With the explosive growth of artificial intelligence (AI), market research is undergoing a transformative shift. In a recent discussion on "How to Conduct B2B Market Research with AI", John Brzinski, an experienced B2B marketing leader, shared actionable strategies for conducting market research, identifying meaningful trends, and using AI to unlock deeper insights.

This article distills key lessons from the conversation and provides a comprehensive guide for professionals in product management, operations, and leadership roles. Whether you’re a startup founder or managing market insights at a mid-sized enterprise, this piece will help you design and execute impactful research strategies while leveraging AI tools to save time and improve decision-making.

Why Market Research Is a Non-Negotiable

Market research allows businesses to:

Stay aligned with their target audience’s needs.
Identify changes in the competitive landscape.
Adjust go-to-market strategies when sales pipelines or revenue trends fluctuate.

Brzinski emphasized that market research is not just a one-time activity but a continuous process. It involves gathering, analyzing, and interpreting data to understand customer pain points, shifting preferences, and emerging market opportunities.

When to Conduct Market Research

John Brzinski outlined a few scenarios where market research becomes critical:

Shifting Performance Metrics: A sudden change in customer acquisition rates, win/loss ratios, or revenue signals the need for immediate research.
Unfamiliar Sales Objections: If sales teams are hearing new objections, it’s time to investigate why.
Annual Persona Refresh: Businesses should refresh their buyer personas and competitive intelligence annually to ensure strategies remain relevant.

Incorporating AI in Market Research: Game-Changing Use Cases

AI is revolutionizing the way businesses approach market research. Brzinski identified several practical applications of AI tools that can enhance efficiency and insights.

1. Data Compilation and Ongoing Analysis

Modern organizations collect data from numerous sources, such as CRM systems, customer reviews, Slack conversations, and emails. Traditionally, collating and analyzing this information required significant manual effort. AI changes the game by automating this process.

How It Helps: AI can continuously monitor and analyze these data points, identify trends, and alert teams to notable changes in customer behavior or market dynamics.
Key Insight: While AI excels at analysis, businesses should rely on human experts to interpret findings and make strategic decisions.

2. AI as a Research Sparring Partner

AI can act as a collaborative partner for marketing teams by providing additional perspectives during analysis.

Example: After gathering data, teams can ask AI to identify patterns or correlations they might have overlooked.
Why It Matters: Even if AI’s conclusions aren’t always perfect, they often spark fresh questions or hypotheses for deeper exploration.

3. Streamlining Qualitative Analysis

Interview transcripts and qualitative data are rich sources of insights but are time-intensive to process. AI tools can summarize interviews, highlight recurring themes, and help researchers focus on the most critical findings.

Building an Effective Market Research Framework

Quantitative vs. Qualitative Research

Brzinski explained that there are two main approaches to market research:

Quantitative Research: Focuses on large-scale data collection (e.g., surveys) to identify measurable trends.
Qualitative Research: Involves in-depth, open-ended interviews with smaller groups to uncover deeper insights about customer mindsets.

Steps to Get Started

Define Objectives: What questions are you trying to answer? Align stakeholders on research goals to ensure clarity.
Collect Data: Tap into existing knowledge from sales, customer success, and professional services teams. Use surveys or interviews to fill gaps.
Segment Audiences: Ensure you’re addressing distinct customer groups separately.
Analyze and Share Insights: Combine qualitative and quantitative findings to create actionable recommendations for leadership and cross-functional teams.

How to Use AI for Surveys and Interviews

Brzinski highlighted innovative ways to incorporate AI into surveys and interviews:

Open-Ended Questions in Surveys: Ask for written responses to questions like, "What are three trends shaping your industry?" AI can analyze these responses at scale to uncover recurring themes.
Persona Stereotypes: During interviews, ask respondents about stereotypes of other stakeholders they interact with. This uncovers nuanced insights into team dynamics and decision-making psychology.

Securing Leadership Buy-In for Market Research

One challenge many professionals face is convincing senior leadership to invest in market research. Brzinski shared three scenarios that make a compelling case:

Problem-Driven Research: When revenue or churn metrics are underperforming, use market research to identify root causes.
Proactive Annual Research: Position annual research as a preventive measure to avoid future problems.
Thought Leadership Projects: Propose research as a way to create unique, data-driven content that positions your company as an industry leader.

To maintain leadership confidence throughout the process, provide periodic updates during longer-term research projects. Sharing interim findings keeps stakeholders engaged and reinforces the project’s value.

Challenges and Best Practices

Common Pitfalls

Failing to segment audiences, which can obscure meaningful insights.
Overrelying on AI for final conclusions without human validation.
Not aligning stakeholders at the outset, leading to unmet expectations.

Pro Tips from Brzinski

Use AI to save time but rely on human expertise for critical decisions.
Focus on actionable outcomes: Research should provide data that directly informs product development, sales strategies, or marketing campaigns.
Stay curious: Market research isn’t just a task - it’s an opportunity to uncover new ways to connect with your audience.

Key Takeaways

Always Stay Curious: Treat market research as an ongoing process, not a one-time event. Constantly collect and update data from sales, customer success, and professional services teams.
Incorporate AI Thoughtfully: Use AI to automate data compilation, analyze trends, and save time summarizing interviews. However, final decisions should always involve human oversight.
Blend Quantitative and Qualitative Approaches: Start with interviews to form a hypothesis, then use surveys to validate findings. Alternatively, reverse the process based on your starting point.
Engage Stakeholders Early: Align leadership on research goals and expected outcomes. Maintain buy-in by sharing interim findings during longer projects.
Look for Untapped Insights: Use creative methods, like open-ended survey questions or persona stereotypes, to gain deeper understanding beyond the surface trends.

Final Thoughts

Market research is not just a tool for understanding your audience - it’s a growth driver for your organization. By combining traditional research methods with AI-powered tools, professionals can uncover hidden opportunities, address emerging challenges, and drive smarter decisions across teams.

The key is balance: Lean into AI for efficiency and insights, but ground your findings in human expertise for truly transformative results. Market research isn’t just about data - it’s about understanding the human stories behind the numbers.

Source: "The future of B2B market research (real AI use cases inside), with John Brezinsky" - CMO Alliance, YouTube, Aug 7, 2025 - https://www.youtube.com/watch?v=0Igbi__P5hU