Using Google Learn About for SEO content topic research.

As an SEO, I’m always on the lookout for new opportunities to mine content topics that aren’t keyword focused.

So much of strategic discussions today relate to entity-based optimization and buyer’s journeys.

It’s not about getting clicks for the sake of it, but addressing user’s pain points by answering their queries with high-quality, helpful content.

I’ve written about using Perplexity for topic research, as well as other lesser-known options.

But I’ve recently stumbled upon a new tool to explore: Google Learn About.

It’s still experimental, but I’ve heard it described as a new take on Wikipedia.

What I find interesting for topic research, though, are Learn About’s suggested topics.

The suggested topics along the left side and bottom of a chat provide valuable insight into potential topics for SEO content on a buyer’s journey.

Let’s do a quick example related to SEO.

I asked a very simple and high-level question: what is SEO?

I first get back this nice answer:

Let’s say I next wanted to mine for content topics related to SEO.

I can scroll to the bottom of that answer and reference the related follow-up questions as possibilities:

With some slight adjustments, each of these could stand on its own as a piece of content.

There are also suggested topics on the lefthand side that mention related entities:

I can use those entities as the basis for content topics or leverage them for additional searches to get more related questions:

Some questions may work best as standalone content topics, while others may be more beneficial as subsections.

This is also a nice way to establish a pillar-cluster model with internal linking between related articles.

In short, Learn About offers yet another way to leverage AI tools for SEO topic content research beyond keyword research.

I’ll expand this post with more examples in the future, as well.

Thanks for reading. Happy marketing! 🤗

Related posts