Using AI to power small, time-strapped, budget-strapped marketing teams

Hi,

For startups with small teams and big ambitions, using AI well is fast becoming a necessity. And we’re not talking about just using AI tools to churn out a load of half baked content. It’s about using it in the right ways to give small marketing teams extra capacity to focus on creativity without adding cost.?

On Monday I spoke with Alex Ford, a fractional go-to-market consultant and FinTech founder, to pick his brain on how AI is reshaping the marketing landscape for lean teams. He had a treasure chest full of amazing tips, so much so it’s been hard to cover it all here so I’ll really recommend catching up on the full discussion (here).

In the meantime, here are the highlights.

First and foremost, AI is NOT, and never will be, a replacement for deep customer understanding or creative intuition

AI tools can’t replace the value of direct conversations with your customers. Regular interviews remain absolutely essential to understanding your audience’s pain points and motivations. And moving from ideation to actionable hypotheses is still very much a marketer's domain.?

Where AI comes in is by adding more power to these processes so they can be done bigger, better and faster. But the effectiveness of any output still needs an initial spark based on human insight.

I think we can all spot the AI-generated content out there… It feels formulaic and unauthentic. Using specific frameworks or methodologies (like April Dunford’s positioning methods) within your prompts can improve output, but it can’t replace the nuanced voice of a skilled copywriter.

Think of AI as your “junior assistant” - it can do a lot of the heavy lifting, but it still requires guidance and oversight?

AI’s strengths lie in its ability to take on repetitive tasks, give your research capabilities a boost, and spark new ideas. Alex shared some of the practical applications:

• Research and data gathering: AI tools can find and summarise reports and process things like interview transcripts much more quickly than we could do ourselves?
• Content support: Don’t use AI to write from scratch, use it to help you build structures for things like emails and blogs based on source content, rewrite drafts and adjust tone?
• Analytics: Tools like GPT for Sheets or Excel help analyse campaign performance or forecast trends without needing to know how to use complex formulas

Using AI to accelerate testing and learning cycles

AI allows you to generate variations of copy, design, and targeting parameters quickly. Tools like BannerBear or Pencil Pro can programmatically create ad creatives, enabling you to A/B test ideas at scale.

• Hyper-personalisation: With AI, even small teams can create campaigns for micro-audiences that feel bespoke and relevant. As Alex noted, this level of hyper-segmentation would have been cost (and time) prohibitive in the past.
• Real-time feedback loops: By automating data analysis, AI shortens the time from campaign launch to actionable insights. Alex recommends using tools like GPT for Sheets to quickly identify what’s working—whether it’s click-through rates, conversions, or sentiment—and optimise accordingly.
• Fail fast, learn faster: Iterative testing is a marketer’s playground. AI reduces the cost and time of failed experiments, encouraging teams to try new ideas without fear of wasting resources. Launch a campaign, gather insights, tweak, and repeat.

The efficiency gained here isn’t just about speed—it frees up marketers to focus on the zero-to-one creative tasks that AI can’t replicate, like working on new strategies or spending time with customers to find new insights.

The rise of Generative Engine Optimisation (GEO) is transforming SEO strategies

As search engines now incorporate generative AI overviews, it’s giving marketers a new challenge on the SEO battlefield:

• Zero-click searches: People are increasingly making decisions based on the AI-generated summaries at the top of the page, skipping traditional website visits
• Content credibility: Large Language Models (LLMs) rely on available data, making high-quality, accessible content more critical than ever
• Sentiment sensitivity: Alex shared an example of where a competitor's blog post negatively influenced AI-generated content about another brand. Because AI models often rely on existing online content, if a competitor publishes a blog post with negative sentiments about your brand, these tools may incorporate that perspective into their outputs. The thing to focus on here is monitoring online content and managing your brand's digital reputation.?

Prompts matter - AI tools are only as effective as the instructions they’re given

Alex emphasised the importance of well-crafted prompts to ensure AI aligns with your specific needs and brand voice. Here’s how you can make your prompts work harder:

• Tailor them to your business: Don’t rely on default AI capabilities, you need to train the model by providing examples of your tone of voice, preferred writing style, and formatting rules. Alex suggested feeding the tools you use with specific copywriting frameworks you want to work with (e.g., PAS: Problem-Agitation-Solution).
• Be specific: Clear and detailed prompts lead to better outputs. For instance, instructing the tool you’re using to “write in UK English with no full stops at the end of bullet points” can save a lot of time in manual edits!?
• Iterative refinement: Back to the junior team member reference… Treat it like you’re onboarding someone: guide it, refine its approach over time, and provide feedback to improve results.
• Experiment across tools: Different AI models have unique strengths. For example, Claude is good with tone of voice, while ChatGPT-4 is stronger with analytical or structured tasks. Trying multiple tools with consistent prompts will help you find the best fit.?

By investing time upfront in crafting and refining your prompts, you’ll stand a much better chance of getting high-quality outputs.

Start with familiar territory

When you’re exploring AI tools, begin with topics you already know well. This can really help you evaluate the tool's strengths and weaknesses. For instance, if you’re an expert in, say, fitness, test a few AI tools with tasks related to that area and get a feel for how well it can interpret the topic. Once you’re familiar with its capabilities (where it does well and where you need to be more mindful of its limitations), apply those learnings to your work and how you incorporate AI into your workflows.?

Explore new tools and keep learning

AI is evolving rapidly, and it feels like new tools are emerging daily! It’s hard to know where to start, so Alex recommended some of his favourites to begin experimenting with:

• ChatGPT for Sheets/Excel for data analysis and forecasting
• Otter.ai for transcribing interviews and identifying key themes
• Bannerbear for generated scalable ad creative
• Make.com for integrating AI workflows

Catch up on all of the discussions so far

So far we’ve covered the power of brand and how to measure the value of it,? creating a culture that drives growth and setting OKRs, and started to explore some of the tactical elements like building a community and leveraging AI to supercharge your team. And we’ve got more to come!?

If you’ve missed any of the sessions so far, you can catch up on them all here.?

Talk soon,

Lucy ??