Trappe Digital LLC may earn commission from product clicks and purchases. Rest assured, opinions are mine or of the article’s author.
Creating quality content has never been more challenging or important. With the rise of AI tools, content creators face a flood of mediocre, generic material. But there’s hope. By using AI strategically and maintaining high standards, you can produce content that stands out and delivers value to your audience.
Jeff Coyle, co-founder of Market Muse, joined me on Episode 681 of “The Business Storytelling Show” to discuss how to scale AI in content marketing while ensuring top-notch results. We also discussed the role of quality vs. quantity content and I want to discuss how to create good content here.
- Is AI-generated content really that bad?
- How can we use AI better?
- Scaling AI
- The right content velocity
- Creating quality content
Is AI-generated content really that bad?
“Absolutely,” Jeff asserts. “Everybody’s jumping to the end, and that’s the biggest mistake I’ve seen.”
Many content creators are skipping crucial steps in the editorial process, rushing from idea to final draft using AI tools. This approach ignores the expertise and unique perspective that make content valuable.
Jeff emphasizes that quality content requires more than just generating text. It involves understanding your audience, your brand voice, and your business goals. And let’s not forget your unique business story. AI can help, but it shouldn’t replace human insight and creativity.
How can we use AI to create good quality content?
Jeff suggests starting with a thorough inventory of your content creation process. Identify areas where AI can enhance work rather than replace it entirely. That could include:
- brainstorming ideas
- improving headlines or openings
- generating subject line options for emails
- analyzing existing content performance.
However, Jeff warns against relying solely on generic AI tools.
“If you’re going to use technology to help with strategy, how do you know that it’s predictive in any way if it’s not using any of your data?” he asks.
To create truly valuable content, incorporate unique business data, expertise, and brand voice into the AI-assisted process. This approach ensures that the output aligns with goals and resonates with the target audience.
Read next: Will AI replace writers?
What are some ways to scale AI in content production?
Jeff highlights several ways AI can help scale content production. Content auditing and inventorying can be streamlined with AI tools – which can help improve auditing processes and results. Predictive modeling using AI can forecast which content topics and formats are likely to perform well based on your historical data.
In the content creation process itself, AI can assist with briefing and outlining, ensuring that content aligns with brand voice and strategic goals from the start. During the editing phase, tools like Grammarly can help optimize content for clarity and engagement. Finally, AI can identify opportunities to repurpose existing content across different formats and channels, maximizing the value of your content assets.
Jeff emphasizes that scaling isn’t just about producing more content faster. It’s about increasing the effectiveness of the content strategy.
“Scaling the amount of best practice actions and motions your team takes is one of my favorite things with scaling AI,” he says.
Read next: Why tools like AI Writer are not the future of content
How to determine the right content velocity?
Finding the right balance between quantity and quality is crucial. Several factors can play a role:
- mission and goals
- the competitive landscape
- complexity of the topic
- audience’s information needs at different stages of their journey.
“I’m thinking about the competitive landscape. What’s out there? I’m thinking about the actual linguistics of this thing. What would it take to cover this thing as if I were an expert?” Jeff explains.
He recommends creating a comprehensive content plan that covers a topic from multiple angles and for different audience segments. This approach might lead to a higher content velocity than initially expected, but it ensures thorough coverage of the subject matter.
Read next: Overused AI words
How to maintain quality while scaling content production?
Jeff stresses the importance of integrating expertise and data into the content creation process from the start. Rather than generating generic content and then editing it heavily, train AI models on specific data and brand voice. Create detailed content briefs that incorporate unique insights, and use AI to augment human creativity, not replace it. Implement a robust editorial process that includes fact-checking and quality control.
“Get ahead of it. Put more of your thumbprint on it earlier in the process,” Jeff advises. This approach not only improves content quality but also boosts team morale by allowing subject matter experts to contribute meaningfully.
How often to evaluate and update AI tools?
The AI landscape is evolving rapidly, and Jeff recommends an ongoing evaluation process. Agreed.
“If you’re using a process or a solution for more than a year in the same way you’re probably behind,” he says.
However, this doesn’t mean constantly switching tools. Instead, always look for ways to enhance existing processes with new AI capabilities. Be wary of solutions that offer generic, one-size-fits-all advice.
“Unless you’re telling somebody how to truly differentiate and give blue ocean value, right now, it’s not good enough,” Jeff warns.
Final thoughts on how to create quality content
Creating quality content in the age of AI requires a strategic approach. Start by using AI as a tool to enhance processes, not as a replacement for human expertise.
“Don’t make fixing mistakes part of your process,” he said. “It’s self-defeating, and it also brings the morale of teams down.”
Instead, focus on getting it right from the start by combining AI capabilities with human insight and creativity.