How to use Perplexity for content topic research.

*This post is in-progress and will be finished in the coming days.

Keyword-based content topics for SEO or socials is a tired game. 😴

It’s also increasingly obsolete, for a few reasons.

If you’re wondering why it’s obsolete, keep reading the next section.

If you’re already on game with me, jump here to learn how to use Perplexity for more advanced content topic research.

So, why is the old way of doing content topic research for SEO obsolete?

Well, I have a few answers.

1️⃣ Let’s start with the obvious one.

Your approach probably looks like this:

1. Analyze competitor’s content.
2. Do keyword research.
3. Identify informational queries in a content gap.
4. Build topic clusters.
5. Look at top-ranking results.
6. Write content for those queries.
7. Ta-da.

Except, that’s what everyone else is also doing.

If you’re mimicking your competitors, why would any user bother to come to you instead of them.

Content fundamentals, as I see them, dictate that your content should have unique expertise or experience behind it, delivering something no one else can.

Maybe you can do that with keyword-focused content, and maybe you’ll even rank well.

2️⃣ But that brings up our next problem.

Keyword rankings are obsolete.

We live in a world of generative AI now.

That means AI Overviews on Google, summarized answers with citations on Perplexity (more on this, shortly), or just question-answering with AI chatbots like Gemini or ChatGPT.

Even when we’re talking about search engine optimization, a dying field in my view, the SERPs today are so diversified with SERP features and personalization that it’s improbable you’ll be able to accurately portray the rankings of your content.

And even if you do, that’s leaving out part of the story …

What about your social content appearing in search for branded queries and beyond? What about Google Discover? How about unlinked mentions on third-party or offline publications? And, again, what about generative AI?

Ok then, how about using Perplexity’s answers and follow-up questions for content topic research?

This is where it gets good.

I recently read this Acer article endorsing Perplexity’s multiple use-cases. It’s worth a read.

But one use-case it didn’t mention was content topic research for SEO or even social media and video purposes.

What got me thinking about this was how the article mentioned Perplexity’s follow-up questions:

“One of the core strengths of Perplexity AI is its ability to engage in conversational interactions. After answering a prompt, the tool automatically suggests follow-up questions so users can refine their queries for more precise results. This dynamic approach sets it apart from other popular LLMs like ChatGPT and Gemini.”

– Perplexity AI: 7 of the Best Everyday Ways to Use This LLM (Acer)

Perplexity’s answers already synthesize information in crafty sections that can be mined for content topics or sections of topics, helping you build an outline.

But the follow-up questions represent to me an even greater area of exploration, allowing you to dig into your buyer’s journey to find content that might resonate with them as they’re trying to so solve a paint point relevant to your product or service.

Say we had a product that prevented clogged dishwashers.

We might want to write a post related to how to solve the problem, and then mention our solution as an alternative.

Judging from Perplexity’s answer, users might want a step-by-step guide:

But then why would they bother to come to our blog if they can get this information elsewhere?

Well, one reason might be because we have first-hand pictures or tips that no other site provides.

That’s the type of experiential content that a Gemini, ChatGPT, or even Perplexity couldn’t synthesize.

Something else that might provide insight, though, are the related questions:

What I see here are extra bits of information that we could include within a blog post.

We could also create dedicated content for some of these topics, like the third one about drainage.

That’s the type of topic that someone might want an expert opinion about.

Meanwhile, for simple questions like cleaning the filter, that could be a quick social media post or video on YouTube.

The goal isn’t to single out questions for topics like how keyword research has been done.

That’s old and tired.

The purpose is to analyze what bits of information a user would want to know along their user journey, and then provide unique insights about those using different content types.

The last question about an air gap in the sink might not be relevant to a post about a clog, for example, but it could serve as a separate topic.

I plan to build this post out and elaborate more fully on the potential of Perplexity for SEO and social content topic research.

Until then, enjoy the vibes:

Thanks for reading. Happy marketing! 🤗