Driving integration adoption with programmatic SEO

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Recently, I started a new experiment after coming across a tweet from Tibo Maker that got me excited.

The tweet highlighted the potential of running SEO experiments, and since my blog at Lunch Pail Labs runs on Feather, I figured this was the perfect opportunity to try out Programmatic SEO (PSEO) for the add-ons I’m building.

What is programmatic SEO?

Programmatic SEO (PSEO) is an approach to search engine optimization where you create a large number of content pages targeting different long-tail keywords at scale. Instead of manually writing each page, you use templates and automation to quickly generate pages based on structured data, like use cases, product features, or industry-specific needs.

It’s especially useful for platforms or products that solve a variety of problems, as it allows you to create targeted pages that appeal to niche audiences without having to write every single one from scratch.

How I’m structuring the experiment

Here’s the breakdown of what I’ve done so far.

1. Creating use case guides

Each add-on has multiple use cases. For example, with the Liveblocks plugin, someone might only be interested in live cursors or presence tracking.

So, I’m starting with a step-by-step guide for each use case.

2. Promoting the guide with a blog post

Next, I write a short blog post promoting the guide. The idea is to give a quick overview of what you can build using the guide and link directly to it.

3. Optimizing for PSEO with Feather

I updated my Feather setup by adding new SEO properties—just blank fields for pseo_1,2,3,4—which I can customize based on each use case. Feather makes it easy to adapt the SEO properties as I create new pages.

4. Generating use cases with AI

To keep the content fresh, I generated a list of potential use cases using AI. This gave me various angles to approach the plugin from and made it easier to create targeted content.

For the live avatar guide, some potential use cases are:

Real-time user presence tracker for a chat app

User tracking for collaborative workspaces

Online user display for a social networking app

Online user tracking for team collaboration

5. Implementing the use cases

I modify the fields based on the use cases, also done with AI! This way, I can quickly tweak the content for each specific use case and roll out multiple pages efficiently.

Overall, setting this up has been straightforward. I’m excited to see how this PSEO experiment performs over the next few months and monitor clicks to see which posts get the most traction. If it works well, this could be a great strategy for promoting new tutorials and capturing various use cases for the plugin.

If you’re running similar experiments or thinking about using PSEO for integrations, feel free to follow along and share your experiences. I'd love to hear how it works for you! Send me a note.