Digital Insights

There is not doubt that podcasts are on the rise. According to Backlinko:
🔹Over 584.1 million podcast listeners worldwide
🔹55% of the US population 12+ listen to a podcast at least once a month
🔹Podcast ad spending is estimated to hit $4.46 billion in 2025

So I wondered if AI engines were indexing the audio. I asked that question to ChatGPT, Gemini, CoPilot, Claude and Perplexity. Of those AI engines, ONLY Google was able to crawl audio files.

Google was the standout because it has has its own speech-to-text (STT) technology called Google Cloud Speech-to-Text. It is an AI service that was designed to convert audio into text transcriptions. It is also something you can see at work in YouTube.

All of the other AI Engines were NOT able to crawl audio files. Specifically, ChatGPT said:

🗨I don’t pull in raw podcast audio. When I “browse,” I’m limited to text that’s already on the web—so if a podcast episode has a published transcript or detailed show notes, I can read those, but I don’t stream or transcribe the audio myself. My underlying training may include some publicly available podcast transcripts, but not the audio files.🗨

What does that mean? If you are not:
🔹Creating web pages for your podcast
🔹Providing full transcript text
🔹Making your brand / web the owner of that transcript content

Your information is not going to be include in search AI results with the potential exception of Gemini.

It doesn’t matter if you are talking about ‘traditional’ search or ‘ai’ search, providing technology crawlers with your content as data has so many advantages.

It is the difference between having a gallon of crude oil that can be processed to put in your gas tank – OR – you can just put gas in the car. Schema is like providing the Google and ChatGPT gasoline instead of crude oil.

How Content is Interpreted

Although these technologies have come a long way to understanding content on a website, they still can’t see the content, but it really gets interpreted from the code used. When a human ‘sees’ online content, they can use structure and color and memory to determine a message.

Crawlers and AI engines are smart and can figure most things out with machine learning and IA. But why leave that to chance?

Why Generate Schema

By generating schema for your focus content online, you give search engines and LLMs extra help interpreting your content. It helps create a deeper understanding of type, meaning, and intent. Providing content as data also allows crawlers be more efficient because they are built to understand schema markup. It isn’t left for interpretation.

As I like to say, I don’t like to let Google interpret anything for me.

Adding Schema Markup

You can do this by adding semantic Schema Markup to your web pages. Schema Markup was developed by the big search engines like Google, Yahoo, and Bing. It is a dictionary of structured data. Since it follows a standardized set of data, it can more rapidly and confidently understand the content. That allowing the search engines to have a higher degree of confidence they are presenting content that better aligns with a users search intent.

I remember about a decade or so ago that people declared Email was dead. Let’s just say that Email has remained an incredibly viable marketing channel for B2B and B2C companies.

Now, there is a new cry! Search Engines are dead and CHATGPT is the Search Killer.

Yes, ChatGPT has taken on 2% of the “Search” market. It is growing, useful and getting a lot of buzz. However, it is a different beast. Why should I explain when AI can do it for me.

When doing research for a client, I asked CHATGPT if “how many people search for these types of products on CHATGPT”

🚨RESPONSE (with some editing to protect the client)🚨

ChatGPT isn’t a traditional search engine, so there’s no publicly available “search-volume” data for queries people make here. In other words, we can’t tell you “X people ask about [client topic] on ChatGPT each month”—those logs are private to OpenAI and not exposed as analytics.

However, in practice:

Marketers and R&D teams do use ChatGPT to:

👉 Brainstorm product-positioning language

👉 Get product or service ideas

👉 Compare products

To gauge real-world demand, you’ll still want to rely on:

✅ Search engines (Google Keyword Planner, SEMrush, Ahrefs) for hard volume data.

✅ E-commerce platforms (Amazon, Walmart) for “autocomplete” and page-view metrics on product terms.

✅ Specialized forums and Q&A sites (Reddit’s r/foodscience, Stack Exchange) to see how often these topics come up.

If you’re looking to optimize your online presence, focus on channels where volume is measurable (Google, Amazon, YouTube) and use ChatGPT as your creative “idea engine” rather than your volume tracker.