Integrate AI into your marketing strategy with these practical, incremental steps that drive real results.
Marketers are starting to think big about AI in marketing. Different organizations will take various routes to achieve their goals. Some will hire expensive consultants and embark on a massive AI transformation.
Based on my experience watching companies undertake similar transformations, whether in agile marketing or digital transformation, this “big bang” approach is almost certainly doomed to failure.
Up to two-thirds of respondents (66%) say AI is either very important or critically important to the success of their marketing over the next 12 months, per the 2024 State of Marketing AI report. The organizations that make the most progress will think big about what is possible with AI in marketing, but they will start small, incrementally achieving success.
Though it seems modest, this approach is the key to building a solid foundation and gaining confidence in the potential of AI in marketing.
But where to start? Here are a few ideas to achieve some early wins by applying AI to marketing, building support for it and incrementally learning what works and what doesn’t.
4 use cases for applying AI to marketing
1. Content marketing
Most marketers start off using generative AI to help produce content in the form of blogs, emails, social media posts and other copywriting. There’s nothing wrong with using generative AI to create marketing copy. But remember, generative AI predicts an answer based on what has already been written about a subject. In other words, it is not original and unless it’s trained to do so, AI won’t generate content in your unique voice.
A better approach is to use generative AI as an assistant in the various stages of writing. For research, I prefer Perplexity.AI over ChatGPT or other large language models. It provides source citations for its answers. I often find myself reading the sources to get more context and detail than I get from the answers alone.
After completing my research, I outline the content by mapping out the key areas I want to cover and organizing my thoughts into a logical flow. Then, I ask ChatGPT to generate its own outline for the same topic. Comparing the two, I assess whether I’ve missed any important points or prefer the structure suggested by ChatGPT, making adjustments to my outline as needed.
My next step is to write a first draft without any help from AI. Once I have a first draft, I submit it to multiple LLMs (ChatGPT and Gemini, at the moment) and ask them, “How can this article be improved?” Based on the suggestions, I write a second, sometimes a third draft, which gets published.
2. SEO
AI can increase SEO productivity. Tools like ChatGPT generate keyword ideas and build content strategies. The key is to think of them as an add-on to your existing SEO tools, not as a substitute. ChatGPT does not have up-to-date information about search volumes and SERP results, for example.
For a complete guide to the different ways ChatGPT or any large language model can be used for SEO, check out “ChatGPT for SEO: Ultimate Guide, Tips & Prompts” from Backlinko.
3. Website audits
AI can be used to audit your website along a number of dimensions:
- Clarity and readability.
- Consistency.
- Copywriting persuasiveness.
- Design and layout.
- Navigation.
- Brand alignment.
- Tone of voice.
- Competitor benchmarking.
For a very useful overview of using ChatGPT or any large language model for auditing your website, check out “Does AI Like Your Site? 3 Turbo AI Website Audits.”
Here are three prompts you can use to audit your website:
Prompt for clarity, readability and tone
- “Analyze the site <insert URL here> for clarity, readability and tone. Suggest improvements to make the content more engaging, concise and aligned with our brand voice, which is modern and professional.”
Prompt for analyzing website design
- “You are an expert on website design. Based on the attached image, provide feedback on the visual appeal, layout, consistency and layout of elements, ensuring that they contribute positively to the user experience.”
Prompt for competitive analysis
- “Compare my site, <insert URL> with my competitors site, <insert URL> along the dimensions of clarity, readability, tone, user experience, copywriting persuasiveness, design and layout and navigation. Create a table with scores for each site on each dimension and suggestions for improvements to my site.”
4. Synthetic user research
If done well, synthetic user research has the potential to be one of the most compelling use cases for AI. Imagine if you could put all of your voice-of-the-customer (VOC) research into a custom version of ChatGPT and do user research on that synthetic persona. Every marketer could test ad copy, images, pricing, special offers and much more against this synthetic persona.
It would solve the single biggest challenge to making VOC research actionable. Today, most of your information about customers is spread out in multiple locations: emails, memos, reports, databases, etc. Marketers also tend to fall prey to the recency effect, where they overemphasize the most recent research they’ve heard. AI considers all data, with more consistent ways of weighing older and more recent information.
The technology to do this is available today, but it’s difficult for most marketers to build. You will need help from IT to develop and maintain synthetic personas. However, once built, it is very easy to use. You can ask questions to the custom GPT much like you’d ask a real customer and receive instant feedback.
For a primer on how to build a synthetic user, check out “Creating Synthetic User Research: Using Persona Prompting and Autonomous Agents.”
These are just a few use cases for achieving early wins with AI in marketing. Think about your own business and where you most need help, and then consult AI to see how it can help.
The potential is huge, so think big. But start small and get early wins with convincing business results documented before trying to embark on an AI transformation.
The post 4 ways to achieve early wins with AI in marketing appeared first on MarTech.
About the author
Jim has helped over 80 companies adopt Agile marketing, including organizations as diverse as T-Mobile, Salesforce, Best Buy Canada, Thales, Doxy.me, EQ Bank, Boston Private, CUNA, NAIT, Deseret Digital, SpaceSaver, Great Dane Trailers, Northern Arizona University, Netskope, Sprinklr, and Zenprise.
Earlier in his career, Jim spent 12 years at Microsoft in various roles including GM of SQL Server marketing and Vice President of Server Marketing. Jim was also CEO of three startups: GoAhead Software, Adometry, and InDemand Interpreting.
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