AI entering the search space has disrupted and changed a lot of things — one of those areas being tracking. AI search doesn’t track the same metrics as traditional SEO, leaving a lot of people wondering what they should focus on tracking.
Most recently, there’s been buzz about share of search.
So, is share of search the new KPI to track?
We sat down with AI SEO expert, Sarah Berry, to get her thoughts.
Is share of search the new KPI to focus on?
Sarah: It’s a KPI to focus on.
Just as how people search is expanding with Google, ChatGPT, Meta, etc. so is how we’re measuring our search performance. Share of search is one KPI that helps us understand our visibility in search experiences and competitiveness in the marketplace, but it doesn’t tell the full story. For example, what’s the brand sentiment around your share of search?
You could have the biggest share of search out of your competitors, but terrible brand sentiment surrounding it. This creates operational blindness for both search optimization teams and leadership branches. And the end result is the same — it doesn’t benefit the business and its goals for becoming a market leader.
That’s why share of search is best used in conjunction with other KPIs, like:
- Brand sentiment
- Brand attributes (similar to long-tail keywords, there’s value in owning the niche attributes of your target market vs. being a jack-of-all trades)
- Prompt coverage rating (are you appearing for the conversations that matter to your bottom-line vs. the ones for pure bragging rights?)
The problem for a lot of businesses, though, is how to track this accurately and effectively.
Is share of search a reliable leading indicator of AI search performance?
Sarah: To a point.
Share of search focuses on your share vs. your competitors share. That limits its scope. What about the brands you aren’t tracking, like informational sites that guide users on how to maintain their lawn or industry associations that list recommended partners for companies needing an accounting firm?
Like all KPIs, share of search provides one piece of the puzzle when it comes to a brand’s performance (in this case, in AI search).
That’s why platforms like OmniSEO® (which provides AI search performance tracking and guided optimizations) monitor not only the competitors a business wants to track but also shares when there are new kids on the block.
This information gives business leaders and AI search teams a fuller, more complete story on their AI search performance.
Outside of share of search’s definition, companies also have to consider some of the factors that influence AI search performance, like:
- Training data: LLMs have an end date on their training data, like being trained up to January 1, 2025. Anything after that (like the results of the 2026 Winter Olympics) is unknown to them unless they use their web search capabilities. So, companies can see a delayed shift once an LLM has its training data updated, which can make share of search a lagging indicator.
- Trending: Using the 2026 Winter Olympics as an example, consider the competitors for an event. The competitor that places first will likely experience a greater share of search because of their placement, plus the scale of coverage afforded to the Winter Olympics. However, that can decline in the time between now and the next Winter Olympics. This factor provides context when using share of search as a KPI in general.
- Competitor list: Share of search is most impactful when it’s benchmarking your brand against competitors that are optimizing for search experiences (whether traditional or AI, as SEO is foundational to AI search performance). Otherwise, you’re not really tracking your performance — you’re just patting yourself on the back each month.
How should marketers rethink share of search when brand discovery increasingly happens in LLMs rather than traditional search?
The fact of the matter is marketers need to rethink how they’re tracking share of search because Google Sheets isn’t going to cut it when search has expanded to almost 10 different search experiences. And it’s understandable why marketers are turning to Google Sheets and manual data entry. AI search visibility tools are expensive, often costing $100+ / month with serious limitations on prompt and platform tracking.
You can’t effectively use share of search (or other metrics, like brand sentiment) with those kinds of limitations.
It’s self-promotional, but OmniSEO® was built for this very reason. It was built by SEOs that understood the constraints marketers are under (and the workarounds they’re using) to measure, understand, and improve AI search performance.
That’s why OmniSEO® provides tracking, monitoring, and recommendations to help teams understand their place in the market and grow it without needing a dedicated line item for it in their marketing budget.
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