Our podcast just hit 100,000 downloads so far in 2023 thanks to a smarter content strategy and artificial intelligence. Here’s how it happened.
Marketing AI Institute’s podcast, The Marketing AI Show, just hit 100,000 downloads so far in 2023 over 28 episodes—a milestone that would have been unthinkable just 12 months ago.
In 2022, the podcast had just 4,800 downloads the entire year. In 2021, it had just 1,600. Today, episodes average 3,000 - 5,000 downloads each.
What changed?
What lessons can you learn about how to use AI in your own marketing?
Keep reading to find out.
Why the Initial Podcast Strategy Wasn’t Sustainable
Myself and Marketing AI Institute founder/CEO Paul Roetzer broke down the whole case study on Episode 55 of The Marketing AI Show. And it all started with an unsustainable podcast strategy.
Our original podcast idea was to have Paul interview experts each and every week. But that took a ton of Paul’s time to pull off—at least 5-7 hours per episode per week.
At the time, we also needed an outside production team to help us publish each episode since our team didn’t have professional audio and video editing experience. While it saved us some time, it also cost us upwards of $600 - $1,000 per month.
On top of it all, we just didn’t have the support internally to manage the podcast optimally and we weren’t able to hire for this type of role.
We pretty quickly realized:
This podcast strategy just wasn’t sustainable.
How a Change in Strategy Unlocked Growth
In late 2022, we changed up the strategy.
Instead of interviewing experts, Paul and Mike began to cover the top AI news each week on the podcast.
It was an efficient way to stay on top of AI news, and turn the Institute into a center for relevant AI trends and updates.
“The change in format was actually a content strategy change,” says Paul.
“How do we get fresh content on the site? How do we update the blog more regularly with fresh stuff, keep up on the news and the funding, and how do we then take that and amplify that out?”
We settled on a format where we did a deep-dive into three main topics each week in AI, then followed by several rapid fire topics we discussed briefly.
Listeners seemed to like the new format, which was now being produced consistently week in and week out—and our audience started to grow at a steady clip.
The podcast also created efficiencies across our content production process. In addition to the podcast episode itself, we also efficiently produced several content assets from each episode:
- An overall recap post with embedded audio and video, transcripts, and timestamps to promote the episode itself.
- Three blog posts spun off of our discussion of each main topic in a given week.
- Four YouTube videos, one for the whole post and one for each main topic discussion.
- Dozens of social media shares from pull quotes and excerpts from the episode and posts.
“We said ‘Let’s just use the podcast as the center of everything,’” Paul notes.
How AI Made the Podcast Massively Efficient
On top of the change in strategy, we heavily deployed artificial intelligence to make the execution of the strategy possible, successful, and wildly efficient.
We used AI to save dozens of hours of work across key use cases during the podcasting process:
- Research. We manually curate news during the preceding week as we’re following AI developments. Often, we’ll have dozens of links to process when it comes time to build the research brief for the week’s podcast. Though we still read every article, we use AI to summarize articles for quick reference and to explain or research follow-up topics.
- Script-writing. Sometimes, we use AI to write the first draft of the scripts used to introduce each topic. Or, we’ll use AI to write a script to get us started, then write the script for each topic on our own.
- Transcription. We use an AI tool called Descript to transcribe each podcast automatically minutes after it’s recorded.
- Audio/video editing. We also use Descript to edit the audio and video for each podcast episode ourselves, despite having no professional background in audio and video production.
- Blog post intros. Remember those scripts we use to introduce topics? They get rewritten by AI to become introductions (or first draft introductions) to our blog posts.
- Summarization. AI is used to summarize the transcript section for each of the main topics into bullet form. This is an invaluable reference that we then feed to a human writer (often Mike), so the writer can then write a value-driven post about the topic that connects the dots for the audience, includes unique insights and takeaways, and layers in our unique point of view and experiences.
- Promotion. We use AI to generate social shares, which are then reviewed or rewritten by human writers. We’re also experimenting with AI for automatically extracting sharable video clips from our longer podcast videos, so we can quickly create YouTube Shorts or videos for TikTok.
Thanks to these AI use cases, it takes Mike about 3-4 hours of work to prepare for and record the podcast. Paul’s time commitment is just 1.5 hours—30 minutes to jump in and review the brief before the episode and about 60 minutes of recording time.
This makes it very doable in your own organization to have your CEO or top leadership on a similarly structured and AI-supported podcast.
Some Important Lessons Learned
As part of our conversation on the podcast, Paul shared some important takeaways from this entire process.
- Be consistent. Sometimes, success simply depends on consistently showing up and creating as much value as possible. Our change in strategy had nothing to do with hitting metics. It had everything to do with creating as much value as possible every single week without fail.
- Look for AI use cases in the things you already do. You don’t have to transform your business overnight with AI to get value out of it. Look at what you already do and ask: Where can we use AI to make this more efficient and more creative? We literally broke down the podcast process into dozens of subtasks, then isolated where AI could easily be used to make the process faster and easier.
- Marketing is a very humbling profession. You never know what’s going to work. Sometimes, the things that work are by design: you carefully built a smart strategy and executed it flawlessly. But, many times, perseverance and luck play an outsized role. For instance, if ChatGPT hadn’t launched shortly after our change in podcast strategy, there’s no way we would be seeing the type of growth we’re seeing.
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