Building a go-to-market strategy for a new B2B service is a familiar challenge for any marketing professional. Starts with a blank canvas and have to map out the entire universe for a client: Who are the customers? What is the competition doing? And how do we actually reach them?
I was in this exact situation a couple of times, tasked with developing a complete awareness content strategy for clients in the B2B space. It was a complex project that required deep research, close team coordination, and many hours of manual work. While the manual process was effective, I knew that using AI could significantly increase its speed and efficiency.
Before we dive into the process, it’s important to clarify what a ‘content strategy’ truly is. It’s not just a list of article ideas. A real strategy is the foundational blueprint you create before a single word of content is written. The steps I’m about to outline, creating personas to understand who you’re talking to, and analyzing competitors to find where you can win, are the most critical parts of this blueprint. This strategic work determines every piece of content that follows.
Here’s a look at how I did it back then, and how AI play a part in it.
Part 1: The “Then” – The Manual Strategic Process
Our client’s goal was to generate awareness for their heavy machinery and vehicle rental service, targeting other businesses. The audience was niche and as the consultant, my job was to build the content strategic foundation.
The Manual Approach
Persona Creation: The first step was understanding the customer. This involved desktop research on persona, reading industry forums, and analyzing any initial data the client could provide. I pieced together profiles of procurement managers and project leads, trying to understand their daily challenges and priorities. This process took quite awhile of synthesis to produce just two or three solid personas.
Competitor Analysis: Next, I had to map out the competitive landscape. I spent significant time, discussion with the sales team of the company (client visit also useful to gain additional insight), manually searching Google and using tools like Ahrefs to identify competitors. I would visit their websites, read their blog posts, and analyze their backlink profiles to understand their strategy. It was a time-consuming process of detective work to figure out their positioning and value proposition.
Agency and Team Coordination: With a strategy taking shape, I had to coordinate with other teams. I worked with the social media team to ensure our messaging was human and approachable, making it easy for potential clients to connect with us. I also briefed the creative team on the content direction. This involved detailed meetings and documents to ensure everyone was aligned.
This manual process worked. It was thorough and grounded in real analysis. But it was slow. Each step was a significant time investment, delaying the move from strategy to execution.
Part 2: The “Added” – The AI-Enhanced Workflow
With the Added AI workflow, my core strategic thinking wouldn’t change, but it would be dramatically different in speed and efficiency. AI tools would act as a powerful assistant, supercharging each step of the process.
The AI-Assisted Approach
AI for Rapid Persona Development: Instead of spending hours or even days on research, I’d start with an AI model like Gemini or Claude. I’d feed it market research reports, industry articles, and my own initial analysis. A prompt could look something like this:
- “Act as a B2B marketing strategist. Based on the attached market data for the Indonesian construction industry, draft four detailed buyer personas for a heavy machinery rental service. Include their job titles, primary goals, daily pain points, and where they look for information online.”
The AI would generate detailed draft personas in second. The key here is that these are drafts. I would then validate and refine them using the client’s actual customer list and my own expertise. This is not about replacing judgment, but about automating the initial heavy lifting.
AI for Deep Competitor Analysis: Manually tracking competitors is grueling. Today, I’d use an AI-powered research tool like Perplexity, or even the advanced search capabilities in Gemini. These tools can synthesize information from across the web in seconds. My goal is to get a quick, accurate landscape view. For truly ground-level insights, I might use Grok to tap into real-time conversations on X (Twitter).
It’s important to remember that AI can sometimes “hallucinate” or invent facts. Because of this, cross-checking the information is a mandatory step. I would use the AI’s output as a starting point, a map that tells me where to look. From there, I’d dive into the primary sources to verify the key insights. This approach helps in framing From Keywords to Context: Preparing Your Content for Google’s AI-Powered Search, ensuring the strategy is built on a solid foundation.
AI for Creative Briefing and Coordination: Briefing a creative agency requires clear communication. Instead of just writing a document, I’d use AI image generation tools to create a visual mood board. I could generate examples of the photographic style, color palettes, and overall aesthetic I’m imagining for the brand. This gives the creative team a much stronger, more tangible starting point for their work. The final decision still rests with human designers, whose insights are invaluable, but the process of getting there becomes much faster. This is similar to the challenge I discussed in “The B2B Keyword Mess,” where AI helps clear the initial clutter so you can focus on the important details.
Key Takeaways
- AI Accelerates, Not Replaces: The core principles of B2B strategy remain the same. AI tools just help you get through the foundational research and data processing stages much faster.
- Human Validation is Crucial: AI-generated outputs like personas and competitor analyses are first drafts, not final products. They must be checked and refined with human expertise and real-world data.
- Focus on Higher-Level Thinking: By automating the manual work, AI frees up the strategist to focus on what truly matters: interpreting the data, identifying unique opportunities, and making the final strategic decisions.
In the end, the goal is to build a winning strategy. My experience has shown me that while the tools may change, the strategic thinking behind them is what drives success. Today’s AI simply allows us to apply that thinking more quickly and effectively than ever before.
Frequently Asked Questions (FAQ)
Q: Won’t using AI for personas make them generic and less accurate? A: They can be, but only if you accept the first draft without any refinement. The key is to use AI for speed, not for the final answer. You should provide the AI with your specific market data, and then take the draft it produces and validate it against actual client interviews, sales data, and your own industry knowledge. Think of it as a starting point, not the finish line.
Q: What’s the biggest mistake people make when using AI for competitor analysis? A: The biggest mistake is trusting the AI’s output blindly. AI models can “hallucinate” or misinterpret data. You must treat an AI-generated summary as a well-organized research brief, not as absolute fact. Always click on the sources or conduct your own searches to verify key claims before building them into your strategy.
Q: How can I convince my boss or client to approve using AI in our process? A: Focus on efficiency and better outcomes. Frame it as a way to deliver a more comprehensive strategy in less time. You could explain, “By using AI to automate the initial research, I can spend more time analyzing the competitive landscape and identifying an innovative market position for us.” Showing the “then vs. now” workflow makes the benefits tangible.
Q: What is a simple first step to integrate AI into my current workflow? A: Start small and simple. The next time you have to research a new topic, ask an AI research tool like Perplexity in addition to your standard Google search, then compare the results. Or, when you need to write a difficult email, ask Gemini or Claude to draft a version for you. Seeing its utility in small, daily tasks builds confidence for larger strategic work.
Q: How do you manage team collaboration when AI is involved in the strategy phase? A: Transparency is essential. Clearly define where AI has been used (for example, “This persona is an AI-generated draft for our discussion”). Use AI-generated materials, like mood boards or research summaries, as shared starting points for brainstorming sessions. This ensures the team views AI as a tool to kickstart collaboration, not a black box that dictates the final answer.
