It’s been a while since I’ve updated my blog here. For part of that time, I’ve been heads down building out the answer engine optimization (AEO) strategy for my company. With that, I’ve decided on some new scoring factors for my content prioritization framework to support AEO—citation share and commodity.
Citation Share
Do LLMs find this type of content you are considering worth citing? If not, then maybe it won’t be worthwhile in supporting your AEO initiatives. In order to determine this, you’ll need to have some AI visibility tool that tracks citations. While I prefer the citation share metric of Profound, you could also look at a count of citations with other tools like Semrush or Pi Datametrics.
In order to then weight this, I score it by whether the topic/article has some citation share and how it is trending.
0 - none & no competitors either
3 - none but competitors are
6 - some, trending up
9 - some, trending down (for your brand so it needs some optimizing) or competitors are up
Commodity vs. Non-Commodity
Back in April of this year, Danny Sullivan shared that “more than anything else,” the key to AI search success is “unique, authentic, non-commodity content.” Thanks to JC Chouinard for sharing this info in his Google Search Central Live Toronto coverage, and I hope he doesn’t mind me re-using his image below of Danny’s examples of commodity vs. non-commodity content.
One of the examples in the image shows how the commodity content of “Top 10 Things to Consider When Buying Running Shoes” is standard advice that anyone can pull together, while “Why This Customer’s Shoes Collapsed After 400 Miles: A Wear Pattern Analysis” is a deep dive that is more specific and harder for others, especially LLMs, to replicate.
And here’s how I weight this factor:
0 - sounds exactly like everyone else
3 - may have a little brand-specific content
6 - good amount of brand-specific content
9 - no one can imitate
What else are you considering as you try to prioritize content in this AEO AND SEO world?
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