How Generative AI Can Help the CMO Improve the Content Workflow
Generative AI exploded at just the right time for the CMO.
During this so-called year of efficiency, CMOs are often expected to reach the same growth targets but with smaller budgets. Generative AI can help them do that – and become even more effective in ways we’re still discovering. But first CMOs need to understand how generative AI can improve their work. In this post, I discuss how generative AI can improve the creation of marketing content, ranging from ideation to personalization.
The Wild Ride of Content Creation and Generative AI
For any CMO, content is the fuel for attracting customers and making them loyal. Content creation is not the alpha and omega, but content that attracts and converts customers is essential. Within the past few months, CMOs and their content marketing teams have been on a wild ride together since ChatGPT, Google Bard, and the new conversational Bing have cast a spotlight on the power of generative AI.
It is tempting for CMOs to become distracted by the proliferation of generative AI tools. But the tools in and of themselves are not the solution. Savvy CMOs focus on how generative AI can improve their content creation processes. That’s because processes remain relatively stable even if your approach changes. Here are some suggestions, courtesy of a lot of back-and-forth prompting between me and Google Bard:
Generating ideas: generative AI can be used to generate ideas for content, such as blog posts, social media posts, and email newsletters. This can help you to create better content. The key is to challenge generative AI with better prompts. Take the first answer you receive from a prompt and ask generative to create a more specific idea. And then your team should take that idea and shape it with their own imaginations. Don’t let generative AI do the thinking for you. Your content team should come up with a better idea than the one you got from your prompt.
Creating personalized content: generative AI can be used to create personalized content for your audience. This can help you to increase engagement and conversion rates. Try taking a piece of content and give generative AI a prompt to customize that content for an audience, and be as specific as you can down to different personas. Then your team should use those ideas as a starting point to add their own words and images.
Testing different versions of content: generative AI can be used to test different versions of your content. This can help you to identify the most effective content for your audience.
Automating tasks: generative AI can be used to automate tasks, such as creating social media posts. This can free up a team’s time so that they can focus on more strategic projects.
Here is a more detailed example of how generative AI can be used in marketing:
A company wants to increase brand awareness for its new product. They decide to use generative AI to create a series of blog posts about the product. The generative AI model is trained on a dataset of blog posts about similar products. The model then generates a series of ideas for blog posts that are relevant and interesting to the target audience. The content team takes those ideas and creates blog posts That are then promoted on social media and through email marketing. The results of the campaign are tracked and analyzed. The company finds that the campaign was successful in increasing brand awareness for the new product.
A typical marketing workflow with generative AI would include the following steps:
Define the goal: the first step is to define the goal of the marketing campaign. What are you trying to achieve with this campaign? Do you want to increase brand awareness, generate leads, or drive sales? Once you know your goal, you can start to develop a strategy to achieve it.
Research the audience: once you know your goal, you need to research your audience. Who are you trying to reach with this campaign? What are their interests? What are their pain points? Once you understand your audience, you can start to develop content that will resonate with them.
Create the content: the next step is to create the content. This could include blog posts, social media posts, email newsletters, or even videos. When creating the content, be sure to keep your audience in mind and focus on creating content that is relevant and interesting to them.
Promote the content: once you have created the content, you need to promote it. This could include sharing it on social media, emailing it to your subscribers, or even running paid advertising campaigns. The goal is to get your content in front of as many people as possible.
Measure the results: the final step is to measure the results of your campaign. Did you achieve your goal? If not, what can you do to improve your results next time? By measuring the results of your campaigns, you can learn and improve over time.
Does the above workflow to you sound familiar? It should. Generative AI doesn’t create a whole new workflow – or so far it hasn’t. Sure, it can make your workflow far more iterative and faster, but if you throw out your entire ways of creating content, you’re complicating your life needlessly. And as a CMO, you have enough on your plate as it is.
To be sure, it’s important to adopt generative AI with a clear-eyed understanding both the risks and advantages involved with the technology as we have blogged. All the concerns about generative AI are not going away. In fact, they are intensifying. But generative AI is not going away (as we have also blogged). So, let’s get on board.
Centific can help you flourish with generative AI. Our CMO.AI solution helps you discover the data patterns that matter, so you can create relevant experiences for each customer and move the digital needle.