Elevate your content marketing with AI: Tactics, trends, and pitfalls
There’s a good quote in our generative AI professional usage survey about blogs. Have you read it? It’s short and pithy and goes something like this: GenAI isn’t just for writing blog posts.
As the managing editor of the Contentful blog, I have to say that this is a MASSIVE relief. Just imagine if blogs were the sole application for the earth-shattering, paradigm-smashing, galaxy-shaking technology of generative AI. The pressure I’d be under to deliver! My goose would be cooked!
Joking aside, GenAI has quickly established itself as one more tool in the production of posts for our company blog. Our position is that we will never knowingly publish AI generated content verbatim – that would be foolish at best, and disrespectful to our readers at worst. But GenAI has proven itself useful for ideation and the outlining of posts. And the survey results show that other content marketing professionals are doing exactly the same.
All of which is to say that deploying AI in content marketing can have a positive impact on how you and your brands connect with your audiences. This article delves into the practical applications of AI in content marketing, plus industry insights and future trends, and should provide a useful resource for marketers seeking to elevate their strategies.
First, what is content marketing?
So that we have a common understanding of the topic under discussion, let’s lay down a definition of content marketing upfront. For the purposes of this post, I’m going to refer to a definition offered by Wikipedia that's sturdy and unimpeachable.
“Content marketing is a form of marketing focused on creating, publishing, and distributing content for a targeted audience online.”
A nice and simple explanation. Nothing to dispute there, right? Well, except the “online” part, since a big example of content marketing in practice are B2C print magazines which are packaged with customer loyalty programs.
As a practitioner of content marketing, I would seek to attract attention and generate leads for Contentful, grow our customer base and sales, increase brand awareness, and foster a community of loyal customers.
The basis of good content marketing is identifying and understanding the needs of your customers. Thereafter, you have the information you need to produce a wide variety of short- and long-form assets, ranging from case studies, white papers, ebooks, podcasts, infographics, newsletters, social media campaigns and … blog posts!
Two other things to note: First, content marketing involves producing a regular stream of content at a steady cadence, and secondly, it should all fall within the framework of a content marketing strategy. We’re not going to cover content marketing strategy here, that’s a meaty topic all by itself, but the Content Marketing Institute has a handy primer here.
What are the use cases for AI and content marketing?
This is a Big and Important Question. But first, how are people using AI for content marketing? According to the Contentful GenAI Survey, the main tasks that respondents use GenAI with are very much content-related: researching a content or technical topic, creating a draft, or creating an outline.
But there are several important areas not directly related to content too, like testing applications, writing code, or cleaning up data. This is a relevant caveat to the topic under discussion here: for all the focus in the media and elsewhere on GenAI “producing content,” it’s actually being used in many different ways — often further upstream as part of a broader process — and not necessarily for the last mile of content production.
Current usage areas for GenAI
In terms of outputs, respondents to the survey indicated that they and their colleagues are already using GenAI in a wide variety of specific areas. Producing technical documentation and product descriptions rank highest according to respondents themselves (or others in their organizations using GenAI in the process). But the net is cast even wider than that, with a good chunk of folks using GenAI in the production of graphics and charts, audio, video, marketing banners, and (surprise!) blog posts.
Different priorities for content marketing professionals
Now if you’re parsing this data carefully, you’ll rightly want to know the distinction between technical and non-technical personnel. After all, a content marketing manager has a different set of skills compared to a developer advocate. We have a picture of these findings in the survey, too.
While there’s a fair amount of overlap, the areas in which technical and non-technical users are using GenAI reflect different priorities and objectives. The pendulum swings toward technical respondents for things like coding and technical documentation, and then back toward non-technical folks for tasks like PR and blog posts (there we go again).
What are the advantages of using AI for content marketing?
Now that we have a clear picture of what kinds of content marketing assets are being made with GenAI, we can talk about the benefits. And there are tangible advantages to incorporating GenAI into your workflow. Let’s go through several of them in this section.
1. Enhanced content creation
If you’re already using the Contentful Composable Content Platform, integrations like the AI Content Generator and AI Image Generator (both powered by OpenAI) can help you to generate quality content and images at scale, and can be used for everything from blog posts and social media snippets to email campaigns and ad copy.
Again, this is not to advocate for last-mile content production. Common sense dictates that responsible individuals absolutely should review, edit, and revise their content before it goes live. But tools like these do assist in ideation and early drafting. Taking this into account, the marketing efforts of you and your team can be made more efficient and effective.
Practical Tip: Use GenAI to create initial drafts of content or imagery, then have your team refine and personalize it to maintain your brand's unique voice.
2. Personalization and audience segmentation
Customizing your message to your audience is foundational to content marketing. Personalization and audience segmentation is a technological solution that builds on this philosophy, where content delivery on your website – or any other digital channel – is customized to the viewer based on experimentation, A/B testing, and known characteristics.
The simplest example would be a website selling pet food, where the homepage is customized with relevant offers and messaging depending on whether your furry friend at home is a dog or a cat. Personalization specialists Ninetailed have a success story about this exact scenario with mutual customer Pets Deli.
NB: Contentful users can download the Ninetailed integration from our Marketplace and start experimenting for themselves.
GenAI can support personalization and audience segmentation too. With the right set of prompts, marketers can create and fine-tune content which is tailored to specific audience segments. This is then stored in your content platform and retrieved when it’s needed to enhance engagement and conversion rates downstream.
Industry Insight: According to a McKinsey report, personalized marketing can deliver five to eight times the ROI on marketing spend and lift sales by 10% or more. Source.
3. SEO and keyword optimization
SEO and GenAI is a big topic, one we’ve covered in great detail in this excellent post. With regard to content marketing, the SEO discipline can make use of GenAI in a way that’s supportive rather than disruptive. One simple approach would be to use it to analyze and generate search metadata for your content.
Editor productivity tools on the Contentful Marketplace like Surfer SEO, meanwhile, support you in crafting optimized copy using real-time SEO guidelines, e.g., length, content structure, and keyword density. If the task of keyword optimization has you scratching your head, for example, you can use Surfer SEO to make optional suggestions as to where those keywords can be placed in the copy.
Practical Tip: The intersection of AI and SEO continues to be complex and rapidly evolving, and it’s something that practitioners should keep a close eye on. For an in-depth walkthrough on optimizing SEO with Contentful, refer to this guide.
4. From machine translation to GenAI
For folks engaged in transcreating content marketing assets from one language to another, you’ve probably already used machine translation tools in some form. According to experts like Lokalise, machine translation works by analyzing patterns in large volumes of bilingual data, and generating translations based on the probability of certain words and phrases occurring together in different languages.
The advent of GenAI, however, promises to take things even further. “Machine translation is still valid as a quick and cost-effective way to translate large volumes of non-critical content,” Rachel Wolff, Content Marketer and Copywriter at Lokalise, writes. “But, if you need more accurate, contextual, and on-brand translations, then AI translation is your best bet.”
Wolff cites the potential for GenAI to learn and evolve, process complex language, translate with context, and more. Lokalise has a dedicated integration in the Contentful Marketplace, where content marketers have the option of using one or the other, selecting the right tools for the job as needed.
Industry Insight: 65% of consumers prefer information in their own language, and 40% won’t buy from a website that isn’t available in their native language. Source.
Pitfalls to avoid
So, the future is looking rosy? Mmmmaybe, but with some caveats. Here are three pitfalls (at minimum) to avoid if you decide to apply AI to your content marketing.
Over-reliance on automation
In theory, GenAI can dramatically enhance your content marketing efforts. However, it’s essential that you don’t rely purely on automation of your workflow and processes. Human creativity, experience, and oversight are absolutely critical to ensure that your content remains authentic and aligned with your brand values. I considered adding a source here to underline the point, but the value of human intervention should be self-explanatory … ?
Overlooking ethical considerations
Responsible AI is a thing. We wrote a blog post about it and interviewed our friends at Writer. Transparency and attribution are important things to keep in mind using AI in content creation. Maintain ethical standards to avoid potential backlash, demonstrate your sources, and respect your audience – they shouldn’t have to wade through a tsunami of crap just to get to the good stuff.
Neglecting data quality
The effectiveness of GenAI depends very much on the quality of data it’s trained on. Or, put another way, data quality is now the primary factor limiting GenAI adoption. Ensure that the dataset you’re accessing is accurate, up-to-date, and free from biases to achieve the best results. If your organization is about to train a large language model (LLM) on your own data, then having structured content in place is a great advantage upfront. It means that your data is organized and formatted in a consistent manner, which can significantly improve the training process and the performance of the LLM.
Wrapping up
On balance, GenAI presents an intriguing new pathway for content marketing, offering fresh opportunities for effectiveness, personalization, and innovation. This is good! By integrating AI tools and techniques into your content marketing strategy, you can create compelling content that resonates with your audience and drives business growth.
It’s a swiftly evolving field, however, and the pace of new developments can be dizzying. The onus is on all of us to stay informed about emerging trends, to balance AI capabilities with human creativity, and to always prioritize ethical considerations to harness the full potential of AI in our content marketing efforts.
And for those forward-thinking marketing professionals who do embrace GenAI? They’re not only keeping pace with industry changes, but also setting new standards for excellence and innovation in content marketing. At the very least, it should lead to the production of (more) incredible and amazing blog posts.
See also: 7 takeaways from our survey on generative AI professional usage
