Two speakers discuss measuring AI search success. They reject traditional traffic metrics in favor of share-of-voice, measured by mention and citation rates, plus branded search volume. While overall Google traffic declined, branded searches for the company rose, showing their AI investments worked.
for that team, what is the true north metric?
Is it just visits from the content? Is it specific keywords you're going after, traditional SEO type of metrics where you want to rank for them? And now in the LLMs, is it number of assets published?
Yeah.
And what, how do you, how do you measure it? Great question.
Uh, this, I do like roundtables every once in a while with some of our like customers. It's the number one thing that comes up. And then the follow-on question is, how do you attribute it? Definitely at the, the top of the funnel, what we care about is and like mention and citation rate. So think of it as like share of voice. There are certain questions that we care about, and when we look at the names that are generated in the responses to those questions, are we getting mentioned? Like literally, are we in the conversation? That was like the number one thing that we care about. And if we're appearing in more conversations, how we then look to attribute it is through our brand search volume going up. And if more people are literally like searching for AirOps, sure, there's underlying lots of brand activity that we go do. And there's lots of other channels that contribute to it. But as we've seen direct kind of traffic come in, sorry, as we've seen less traffic come in from Google per se, we've seen our branded search traffic go up. And then I think it's like the correlation of the two of those just show us that AI search and what we're investing in content engineering is working. So TL;DR is kind of share of voice percentage for the queries we care about. That's one big North Star metric. And then our branded search queries, that just shows that we're becoming more and more seen by the people we want to.