AI marketing for B2B SaaS: where to start?
Instead of using AI to experiment with completely new channels or tactics, start by automating parts of your existing processes
I wanted to share some insights based on the conversations I've been having with fellow B2B SaaS marketers lately.
After working with over a hundred B2B SaaS companies over the years, I've noticed they all face similar challenges - they need more leads, and now they're also asking how to properly implement AI in their marketing (beyond just asking ChatGPT basic questions).
The AI overwhelm problem
The main feedback I get from marketers is that the AI field feels too overwhelming.
There are so many tools, approaches, and possibilities that people don't know where to begin with it.
If you're feeling this way too, you're not alone!
Start with your core goals
Whenever I feel stuck or overwhelmed, I always go back to asking: "What's the main goal?"
For most B2B SaaS businesses I work with, it's usually to increase MRR (Monthly Recurring Revenue).
And how do we increase MRR from a marketing perspective? By generating more qualified leads.
To get more leads, you need to be interesting to the right target group.
This is where the right marketing strategy comes in.
Using AI for target group research
AI is incredibly useful for researching your target audience. Tools like Genspark or Manus AI can help you understand:
Pain points (both practical and emotional)
Desires and needs
Buying motivations
For example, if you're selling farm management software, AI research might reveal that your buyers struggle with:
This information gives you a solid foundation for creating messaging that resonates with your target audience.
Identify what's already working
Before diving into new AI experiments, look at what's already working in your marketing:
What content formats perform best?
Which offers convert better?
What weekly activities consistently drive results?
Start automating repetitive tasks
This is where AI can make an immediate impact. Look at your regular content production:
Blog posts
LinkedIn Carousels
Email newsletters
Social media posts
Instead of using AI to experiment with completely new channels or tactics, start by automating parts of your existing processes that you already know work well (but take you a lot of time).
For example, if you regularly publish blog posts based on expert input, you could:
Have your expert provide bullet points or voice notes
Use AI to research and expand on those points
Have AI create a first draft
Add your human edits and expertise
This approach saves time while maintaining quality.
Experiment manually first, then automate
My recommendation for new marketing experiments: do them manually first, then automate once you understand what works.
For example, if you want to start creating short-form videos to enhance your CEO's personal brand on LinkedIn, begin by:
Creating videos manually
Understanding how the algorithms work
Learning basic editing techniques
Figuring out what hooks and scripts work best
Only after you know what makes a good video should you start automating parts of the process with AI.
The compounding benefits
By improving your existing marketing activities with AI:
You'll save time
You can increase your publishing frequency
You'll have more bandwidth for high-quality human edits
You'll create space for new experiments
You'll gather more data to guide your strategy
This approach helps you implement AI in a way that gives you a real competitive advantage without feeling overwhelmed.
Ready to transform your marketing with AI?
If you'd like to dive deeper into setting up a successful AI marketing system, I've put together all the resources you need at AI Marketing Masters.
Until next time,
Annika
P.S. What's your biggest challenge with implementing AI in your marketing right now? Hit reply and let me know - I'd love to address it in a future newsletter!