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AI Marketing in 2025: Turning Data into Competitive Advantage

Learn the three core areas that separate winning marketing teams from the rest...

Welcome, AI Strategists

💫 Current thoughts: Week three of my series on data - I write about the data foundation for successful AI. While everyone else is focused on the next latest shiny object (aka DeepSeek), there’s still foundational work we all need to do for successful AI implementation. Read more in this week’s blog.

Also, seriously, can we get some better naming for these things?? Both OpenAI and Google now have a model called Deep Research. And while I get it - they do research, this naming stuff is driving me crazy - though I will say, the tech is impressive. I’ll be writing more about that next week.

This Week's Breakdown

Weekly Blog

AI News Roundup for SMB Decision-Makers and Marketing Professionals

Prompt of the Week:

Here’s a good prompt to help you do a little research. I recommend ChatGPT or Perplexity for this since it has web search as part of the ask. Remember, don’t get AI just for AI’s sake, determine your key challenges and then research. And as always, don’t buy before you try and then if you do buy, I recommend only monthly licenses - the pace of change is so fast - you don’t want to be locked in.

 

I’m interested in exploring specific AI tools or solutions to address the following challenges in my business:

  • [Challenge 1: e.g., improving customer segmentation.]

  • [Challenge 2: e.g., automating repetitive tasks in marketing operations.]

  • [Challenge 3: e.g., gaining actionable insights from data without advanced technical expertise.]

Please recommend AI tools, platforms, or frameworks for each challenge, tailored to our current tech stack ([List of Tools]) and industry. Include:

  1. Tool Features: What key functionalities make these tools ideal for solving our challenges?

  2. Implementation Guidance: How should we approach integrating these tools into our workflows with minimal disruption?

  3. ROI Potential: What benefits can we expect in terms of time, cost savings, or improved outcomes?

  4. Scalability: How well do these tools adapt as our needs grow or evolve?

If possible, share real-world examples or case studies of similar companies using these tools successfully.

 

Just Because

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