5 Mistakes that AI Companies Make with Their Content Marketing Strategy (And How to Fix Them)
In today’s digital landscape, content marketing stands as one of the most effective ways to convey a message and engage with audiences. For AI companies and Generative AI products, where the product or service often involves complex technologies and concepts, the challenge is even greater.
Crafting the right content strategy can make a significant difference in how the brand is perceived and how the target audience interacts with it. We’ve seen it first hand! Dozens of companies raising money for their initiatives, but failing at retaining clients and paying customers after a few months of launched.
In this post, we dive deep into five common mistakes AI companies make when formulating their content marketing strategies. Let’s get started!
Content Marketing Strategy for AI Companies: Avoid This!
1. Not Simplifying Technical Concepts
AI is a complex domain, filled with terms like “neural networks”, “deep learning”, and “machine learning algorithms”. WHO CARES?
While these might be everyday lingo for techies, they can be overwhelmingly complex for the average reader (like me and most of my readers). One of the primary mistakes AI companies make is not breaking down these concepts into easy-to-understand, relatable content.
Remember, the goal is to make your audience understand and trust your product, not overwhelm them with technical jargon. Most of my job when clients come to me for crafting their marketing strategy resides in understanding what is it that they want to communicate, and boiling it down to a plain and simple language that anyone could understand.
Solution
Adopt a ‘Layman’s Approach’. Before publishing any piece of content, ensure that someone outside of the AI sphere reviews it. If they can understand the concepts without further clarification, you’re on the right track. Utilizing visuals, analogies, and real-world examples can also aid in breaking down complex ideas.
2. Neglecting Storytelling
Humans are hardwired to connect with stories. They evoke emotions, foster empathy, and can make even the most intricate subjects relatable. AI companies sometimes make the error of presenting data and facts without wrapping them in compelling narratives.
Whether it’s the story of how the AI was developed, its potential impact, or even a case study, integrating storytelling can transform dry information into memorable content.
Solution
Identify Relatable Angles. Start by identifying a human-centric element to your AI story. How does the technology impact daily life, or how has it made a difference in a particular industry? Engage with customers and gather testimonials or success stories that can be woven into your content.
3. Focusing Solely on Written Content
While blog posts, whitepapers, and ebooks have their place in content marketing, the digital age offers a myriad of mediums.
Video is still king, taking over 50% of the share of how people consume media, search and learn. Videos, podcasts, infographics, webinars, and interactive demos can convey complex AI concepts in digestible and engaging ways. By sticking solely to written content, AI companies miss out on reaching broader audiences who might prefer other formats.
Most AI companies do not have a YouTube channel, but expect their customers to stay loyal by paying a monthly subscription. A YouTube channel for the AI company brand or Generative AI product, with resources and tutorials, can be a key differentiator against competition.
Solution
Diversify Your Content Offerings. Experiment with different formats like videos, infographics, or podcasts. For instance, a video demonstration of how your AI product works in real-time can be much more impactful than a written explanation. Conduct regular surveys or polls to gather feedback on which formats your audience prefers. Hire an expert.
4. Ignoring Feedback and Engagement
Content marketing isn’t just about broadcasting information; it’s also about listening. Some AI companies fall into the trap of viewing content as a one-way street. However, by paying attention to comments, shares, and feedback, companies can gain valuable insights into what resonates with their audience. This feedback loop can help refine future content, making it more targeted and effective.
Solution
Foster a Two-way Conversation. Actively engage with your audience through comments, forums, and social media channels. Hosting Q&A sessions or webinars can also provide direct feedback. Employ analytics tools to measure engagement metrics, and consider that data when planning future content.
5. Not Keeping Up with Trends and Developments
The world of AI is fast-paced and ever-evolving. A content marketing strategy that was effective a year ago might not hold the same weight today. AI companies can make the mistake of resting on their laurels, producing the same type of content without keeping an eye on industry shifts and emerging trends. Regularly updating and revisiting the content strategy ensures that the company remains relevant and ahead of the curve.
Solution
Regularly Update and Review. Make it a practice to conduct quarterly content reviews. See what’s trending in the AI world (hey, we cover that on our blog!), be it new technologies, ethical considerations, or industry applications. Subscribe to industry journals, attend AI conferences or webinars, and always be in the loop.
Conclusion
Content marketing for AI companies can be a challenging but rewarding endeavor. By avoiding these common pitfalls, companies can craft strategies that not only educate their audiences but also establish their brand as a trusted, authoritative voice in the AI space.
Remember, in the world of AI, it’s not just about showcasing the intelligence of machines but also about connecting with the hearts and minds of humans.