Erin Green is the founder of Audacious Labs and a leading learning product strategist with 20 years of experience designing high-impact experiences for some of the world’s biggest brands, including IKEA, Hilton, Amazon, and Google. Having generated over $20 million in custom course sales to corporate L&D leaders, she knows exactly what makes a learning product successful—whether it’s built for businesses or sold directly to consumers.
What sets Erin apart is her ability to blend science with strategy. She draws on learning science, behavioral science, psychology, and advertising by leveraging proven techniques from industries specializing in behavior change. As a result, she helps transform knowledge into scalable, results-driven learning products that captivate audiences, increase impact, and convert at scale.
1) When you look at the current course landscape, what do you think most creators misunderstand about what learners actually need?
I think most course creators are creating content they like to talk about and find interesting, but their course doesn’t actually address a pain point their audience is expressing. It’s an understandable approach because that is very natural human behavior. We want to talk about what we want to talk about, and we become experts in something because we’re passionate about it from a theoretical standpoint. So, I think that is probably one of the biggest misses: creating a course on an idea you want, rather than one that the marketplace is actually asking for. I see that as the biggest disconnect when I sit down with someone. They know what they want to teach. And it’s like, “Great, but how do you know that is what people want to buy?”
What is the best way to understand what the marketplace is asking for? There are two things. The first is talking to the market, and the second is doing some really good market research. I just launched a tool that does that. It does not replace the human conversation, but it does like 90% of what I used to do manually (and better!).
Another misunderstanding is that teaching is the same as enabling skill development, because those are actually two different things. I approach course creation from a behavioral science standpoint because, at the end of the day, learning is human behavior. Creating a great course goes way beyond good content. You need skill application, then feedback, and then contextualized feedback around that. These are the elements that actually help us change our behavior as humans.
We also have to think about the environment we’re in and the habits we have, because those are hard to break. And there’s a neuroscience to that, where we often have to unlearn to relearn. So, if we’re an expert creating a course and we’re not understanding human behavior, how humans create new habits, and what makes them implement a new skill (or not implement a new skill), then we’re not actually creating an experience that’s going to give the learner the best shot at changing their behavior. We might as well have them read a book or watch our YouTube videos.
Don’t get me wrong, those are great things as well, we all benefit from them. But, if it were super easy to understand how to apply something from just reading a book or watching a video, we probably wouldn’t have an obesity problem, and we’d all have the most profitable businesses from day one. We need more than just consuming content to learn.
2) What is the difference between “engaging content” and “effective instruction,” and how can creators avoid confusing the two?
The research shows that two primary factors affect the effectiveness of a learning experience. The first is that the learning material is contextualized. What does that mean? As a learner, it means I can practice the material in my own world and in real time. It means that when I’m interacting with the content, I see myself in the lessons. So, for example, when we look at enterprise leadership training, there’s a difference between an off-the-shelf leadership course and one that’s been customized for a specific organization. That’s because an organization’s unique culture really affects how leadership skills are applied and what success looks like.
So, contextualization is important. That actually proves difficult with self-paced asynchronous learning formats, but with AI, there are many new opportunities to improve. I’m working with a client right now on a course that uses AI role-play. The learners are getting live feedback. It is AI-simulated feedback, but the simulation itself is so intelligent that it responds directly to what the individual is saying, enabling contextualized feedback in a self-paced way. And feedback is the second primary factor that impacts the effectiveness of a learning experience.
One of the best ways I like to think about feedback is: imagine someone newly diagnosed with diabetes who is tracking their insulin levels multiple times a day. When they do this, they’re getting immediate feedback from their biometrics, as well as from how they feel based on what they eat, right? So it’s like you’re getting real-time feedback, and you’re like, “Oh, if I make this little adjustment here, it affects my numbers this way.” This is a classic example of a contextualized feedback loop.
To make content engaging, you need the same elements as any good Netflix video. There’s a story involved, there’s surprise, there are characters, and there are all the things that make a piece of content interesting. But, again, what makes it effective is that it’s contextualized and provides specific feedback back to you. However, I would still argue that the course must be engaging for it to be effective. Nowadays, our attention span is competing with Netflix, with TikTok, with our kids; we live in a distracted world. So, engaging and effective are different, but engaging is a prerequisite to being effective.
3) If a course is meant to change behavior, what’s important to keep in mind?
The first step is to properly diagnose where your audience is and accurately identify their pain points. To do this, I draw heavily on the world of marketing: pains and gains, ‘jobs to be done’ theory, value proposition canvas, etc. If I’m not properly diagnosing my audience’s pains and gains, focusing on what they’re trying to accomplish, and the jobs they have to do in their work, then I’m missing the mark.
Early analysis, market research, end-user conversations, and empathy work all make a huge difference in whether your course actually hits the mark for your audience. A risk I’ve seen with creators who have a million followers is that they’re probably going to make a lot of money off their course anyway (whether it’s good or not). But then I have to ask, “Is that ethical?” You’re taking your audience’s money, but are you truly delivering on your promise? If you’re just chopping pre-recorded webinars into pieces, are you being respectful of them?
Then, how can you hyperfocus your course on what’s really important? We underestimate how many times we have to repeat ourselves for someone to actually understand what we’ve said. A recent study suggests we can repeat ourselves seven times and that still might not be enough to cement a concept. Moreover, you may think you are being repetitive, but your audience likely welcomes it. In fact, they may not even notice that you’ve repeated yourself.
So, to change behavior, you might spend two or three hours on a main topic, let your students practice the concept, break it down over several weeks, and do not move on until the feedback loop indicates they get it. Our brains can only handle so much, and we generally overestimate how much the brain can actually retain.
4) If someone wants to become “a better learner” this year, what is the first habit you would recommend they build? And, what’s a common misconception about learning that you believe it would behoove any learner to ‘unlearn’ and reframe?
The one thing to get good at (as a learner) is contextualizing the information that you’re receiving. For example, if I’m listening to a webinar and get the transcript, I will create a GPT model to pull insights. This GPT gives me a deep dive into the webinar’s content, but it also explains how the learnings apply to my business. It’s the modern version of reading a book, highlighting it, and taking notes in the margins. It is the act of synthesis. Now, we just have AI to help us do it so much faster (and better).
And, so, we’re back to the importance of contextualization and feedback. If you can design ways to get yourself feedback, whether that’s being part of a cohort or study group, or creating tools like GPTs that will give you feedback, the key is to reflect on the learning and take action.
Consuming more information, consuming more courses, this is not going to make you smarter, and it’s not going to make you more skilled. You’re way better off choosing what you want to focus on (keeping it small), and then deciding which resources are available to you to contextualize the information and create feedback loops.
Regarding the second part of your question, a big misconception is that you don’t have to unlearn to learn. In many cases, for our brain to make those new connections, and for those connections to happen seamlessly, we have to untrain what we were doing wrong. For example, if you’re working on your soft skills in communication, let’s say we’re giving feedback to an employee who’s struggling, they need to unlearn their old model of communication for the new one to really stick. The problem is that the teaching models we use today are outdated. They were created without an understanding of behavior change, emotional intelligence, or behavioral science. These models of learning were created decades ago, and people have just kept using these antiquated paradigms and passing them on.
Unlearning is not as hard as you might think, but we often don’t take this important step. And, unfortunately, relearning is really difficult without unlearning first.
5) If you had to write a ‘learner operating manual’ for extracting maximum value from a course, what would the first three rules be, and how would someone self-evaluate whether they were on the right track?
- Rule one: make the material contextually relevant. Take the content and self-reflect on it. Not just in your head, but using AI tools to help you.
- Rule two: learn out loud. The act of explaining what you’re learning to someone else actually helps you further cement it. People used to be afraid to do that; now there’s a whole ‘learn in public’ movement, which is great! It’s socially acceptable to be imperfect now.
- Rule three: make it small. Keep your window of focus small enough to avoid overwhelm. Why? When we’re in emotional overwhelm, our brain shuts down. Our working memory holds so much less than we think. As a learner, you need to own your own experience. Work with your brain, not against it.
So contextualize, share what you know, and don’t overwhelm yourself. If you can, I would add that you physically interact with the ingredients you’re learning about. I think that’s important, too. No one can learn to actually cook without getting in there and throwing ingredients into a pot. Learning doesn’t happen passively; you have to make learning active to be successful.