Marketers can’t track AI orders the same way they track rankings.
AI systems provide probabilistic responses that change even when users enter the same information. Therefore, you will need a different method of tracking.
We’ll explain fast tracking, show why it’s important to buying decisions (not just visibility), and walk you through how to build an accurate portfolio that points to real business results.
What is fast tracking?
Fast tracking is the process of monitoring the information that users enter into AI systems and the responses generated by those systems. Sometimes called search speed monitoring, it differs from ranking tracking, which monitors a website’s listing positions on search engine results pages.
AI systems rarely say things the same way twice, making tracking exact words pointless. But the essence of these responses – which species are mentioned, which sources are cited – trends in patterns over time. Those patterns are the ones to track.
To set up fast tracking for your product, follow our LLM fast tracking guide.
Read more: How to do quick AI SEO research
Why fast tracking is important
Fast tracking shows you how AI systems represent your product when customers decide what to buy, so you can shape that representation to win sales. It differs from AI visibility tracking, which measures the overall prominence of your brand in AI responses without distinguishing between high-value and low-value mentions.
Let’s say you manage fast tracking of the ACME Shoes brand. He found that users were typing two commands: “how to prevent injuries while working out” and “where to buy acme shoes.”
Of these two directions, “acme shoes purchase” has the greatest conversion potential and is worth following closely. Users have decided to find your shoes and want to know where to buy them. Give them this information (by publishing your store locations on your site, for example) and you’re in a good position to close the sale.
In contrast, “how to prevent injury while working” has a very low potential for conversion. People who ask “how to prevent injuries while working out” are still looking for a solution that may not involve buying running shoes, let alone your own. If you’re prioritizing information on a higher business weight, this is a less important track.
A quick portfolio outline
Your quick portfolio is a small, focused set of instructions that are organized for business impact, not vanity. Your quick portfolio is a small, focused set of instructions that are organized for business impact, not vanity. It includes four categories: revenue, reputation, competitors, and gap information. Each captures a different growth signal. 25 well-chosen tracks beat 500 random ones.
Here’s an example of a quick portfolio for an innovative software-as-a-service company:
|
Net worth |
Reputation notices |
Competitor information |
Gap information |
|
best [product] for [problem] |
what do people think [your brand] |
[competing product] vs [your product] | [competing product] vs [another competing product] |
| [your product] vs [competing product] |
is something [your product] excessive amounts |
“Of course [competing product] or [your product] better because [problem]” |
affordable [product] for [problem] |
|
is something [your product] it’s worth it |
what does [your product] so successfully |
other ways of saying [competing product] |
switch from [competing product] |
| [your product] features |
why users like [your product] |
who [competing product] best for |
[product use case] tools |
| [your product] review | [your product] the argument |
why use [competing product] |
hipa is compatible [product type] |
|
how to use [your product] |
[your product] measurements |
is something [competing product] easy to use |
|
| [your product] prices | |||
| [your product] demo | |||
|
it does [your product] combine with [another product] |
Now, let’s look at the four types of information in detail.
Net worth
Revenue calls for capture moments when users decide what to buy and your product offering can be the answer.
Prioritize revenue information because it has a direct impact on your bottom line, especially when you’re talking about your product or offering in words. That is a signal that the user considers you special over competitors.
Examples of income orders are:
- “the best [product] for [problem]”
- “[your product] vs [competing product]”
- “Of course [your product] it’s worth it”
Revenue tracking shows you what AI systems are saying about your product at the time of purchase, so you can refine that narrative to drive conversions.
Reputation notices
Reputation information reveals AI’s narrative about your product – the story users encounter when they ask AI systems about your reputation, prices, or quality.
Examples of shadow commands are:
- “What are people saying? [your brand]”
- “Of course [your product] overpriced”
- “what does [your product] very successful”
Reputation tracking allows you to monitor AI narratives about your brand and take action if they don’t reflect the truth.
For example, if the AI system misrepresents your product when users ask “what do people think [your brand],” those users will create a negative image and may move on to their competitors.
To counter this, find system AI sources that cite negative information and respond to those platforms with accurate context. You can also publish fixes to your site that may be picked up by AI systems later.
Competitor information
Competitor reporting is similar to income statements but focuses on your competitors. They reveal whether AI programs present your product as a relevant alternative when users are researching competing products.
Examples of competitor commands are:
- “[competing product] vs [your product]”
- “Of course [competing product] or [your product] better because [problem]”
- “Other ways of saying [competing product]”
By following your competitor’s information, you will identify the areas where your product loses, to sharpen your position to increase market share.
Gap information
The Gap encourages more conversations where your competitors are mentioned and your brand is not mentioned. Each gap is an opportunity to increase brand awareness and capture new sales.
Unlike revenue commands and competitor information, where your product is already part of sales conversations, gap information shows conversations you’re not in completely.
What makes information “gap” is not the words themselves but the AI’s response: your product doesn’t exist.
Examples include:
- “[competing product] vs [another competing product]”
- “It’s affordable [product] for [problem]”
- “change from [competing product]”
Get gap instructions to invest in content and channels that influence purchase decisions.
If fast tracking is appropriate (and not profitable).
Fast tracking is a tool, not a KPI. It’s only worth doing if you can collect meaningful data, interpret it, and act on it.
For example, fast tracking is appropriate if:
- You choose a portfolio for representative information. Your content should reflect how users typically use AI systems to find information about your product and offerings.
- You produce content. An active content engine allows you to publish quickly to fill covered tracking gaps.
- You can publish where AI systems look. Open web pages, public forums, third-party review sites, and social media are all fair game. Content locked behind logins or paywalls will not affect AI responses.
Conversely, fast tracking should not be done (yet) if:
- You want one reporting number. Effective fast tracking involves tracking a lot of metrics, and you’ll need to interpret them thoroughly to get useful insights.
- He expects stability from week to week. The AI system’s responses are not deterministic. Trying to figure out why they’re called differently each time (even if they reveal your brand) is a waste of resources.
- Your site does not have SEO basics in place. AI systems tend to cite sites with strong organic search visibility, so a site that doesn’t perform well in search will struggle to appear in AI results. Tackle SEO basics first before preparing for AI programs.
How to read informational data
To read the informational data, look for three signals that show whether your product is gaining authority: frequent mentions, mentions in advance of citations, and long-lasting citations.
Here is more information on each signal:
- State the frequency: How often user feedback and AI responses mention your product. This is the basis of whether your product is at the top of the right buying decisions. Pay attention to the long-term trend rather than the fixed summaries, and remember that frequency alone does not indicate sentiment.
- The movement is from the spoken to the quoted: That AI systems are talking about your product, not just saying it. As your authority grows, your product evolves from an invention to a source worth citing. Check that those quotes are from sources that influence purchasing decisions, not just any high-traffic site.
- Citation frequency: How often AI systems quote your product across multiple runs of the same information. This signal shows how strong your quotes are without the possible nature of AI responses. Hardness alone doesn’t tell you why you’re being cited, though. The reason could be your authority, or it could be the competitors lack of authority.
Converting information data into action
Turn data into action through on-site and off-site content strategies that position your brand as something to be talked about, cited, and purchased.
These content strategies fall into one of three categories:
- Source strategy: Identify the AI platforms from which you respond to information in your category. Then build a credible presence on those platforms. Not as a product promotion, but as a genuine engagement. For example, if AI systems frequently cite Reddit, contribute important answers to industry threads (with affiliate disclosure), publish on Quora or Stack Exchange, or get coverage on third-party review sites from your tracked answers.
- Closing the gap: Once you have identified the commands where your competitors appear but you don’t see them, put your mark in the conversation. If your product rarely appears in orders about your competitors, create comparative content that positions your offering as a viable alternative.
- Narrative correction: If AI’s narrative about your product is inaccurate or lacking, speak to the source. For example, if AI answers cite negative Google reviews about a recent price increase but don’t include your reasoning for it, respond to those reviews with context. As AI systems incorporate that context, their interpretations of your price become more complete and accurate.
To research and track information, use Semrush’s AI Visibility Toolkit.
First, use the toolkit’s Quick Research tool to research and create a shortlist based on a quick portfolio outline.
Once you’ve seen these instructions, set up the AI Visibility Toolkit’s Quick Track tool to automatically track them over time.
Try the AI Visibility Toolkit for free: