For the longest time, link-building reporting was tied to DA/DR scores, organic traffic lift, and search rankings.
It still is now, but a new layer of link-building metrics has emerged due to things like:
Google’s AI Overviews
AI search platforms like ChatGPT, Perplexity, and Gemini
Zero-click searches
Since these factors have permanently altered the search landscape, a new set of KPIs is necessary to reflect your brand’s presence on AI search platforms.
As a result, if you stick with traditional metrics, you’ll only see a tiny piece of a larger picture. In fact, you may feel that your marketing strategy is failing due to large dips in organic traffic.
However, what these metrics won’t tell you is that your audience is likely getting exposed to your brand in different ways, like:
Discovering your brand through an AI Overview citation
Deciding to directly visit your brand’s website after being exposed to your brand
Choosing to convert into a customer based on a direct recommendation from ChatGPT
All of these actions can fuel leads and conversions, and the quality of your backlink profile can have a direct impact on them.
In this guide, we’ll teach you which new metrics you need to track to properly monitor your link-building strategy in 2025.
Here’s what we’ll cover:
Why traditional SEO metrics aren’t enough
The new layer of AI visibility metrics
Tools that will help you see the full picture
How we help clients report and learn from backlinks
Why Traditional SEO Metrics Still Matter, But Aren’t Enough
First, let’s explore why traditional link-building metrics don’t capture the true impact of your brand’s online presence anymore.
The biggest reason is that the classic SEO funnel is outdated.
For many years, the funnel looked like this:
Awareness stage (targeting informative keywords with blog posts and educational guides)
Consideration stage (targeting commercial keywords with comparisons and reviews)
Decision stage (targeting transactional keywords with service, product, and landing pages)
This funnel is so ingrained in marketers’ heads that it’s completely shaped the way SEO strategies are structured.
The problem is it’s a linear model, and modern AI-fueled search experiences are very much nonlinear.
Using a tool like ChatGPT or Perplexity, users are able to skip entire stages of the funnel. Sometimes, they even loop into a new funnel.
Here’s what we mean.
Let’s search for something like ‘What’s the best smart TV under $200?’ on Perplexity:
While there are a few links to roundup articles at the top of the page, there are also direct recommendations with purchase links:
This makes it effortless for users to jump from the awareness stage straight to the decision phase.
In this scenario, the user can completely bypass all your funnel content (educational blogs, buyer’s guides, etc.) and convert almost immediately.
Evidence shows that many users are doing just that.
According to the University of Virginia Darden School of Business, 60% of users report using AI to help with online shopping, and they trust the AI’s recommendations more than those of personal friends and family members:
Besides skipping stages, sometimes AI search assistants can loop users back to the awareness phase for a different product.
For instance, here’s what happens if we ask Perplexity to recommend some accessories for our new TV:
Now, we have started a new customer journey, resetting the funnel back to the awareness stage. This is why marketers call the AI buying stages a loop instead of a funnel.
Next, imagine that you’re one of the companies selling smart TVs listed in Perplexity’s reply, but you’re relying on standard SEO reporting measuring your performance.
You’d likely notice dropoffs in organic traffic, especially for top and middle-of-the-funnel content like blogs and buyers’ guides (even if they have lots of high-value backlinks).
This may lead you to believe that your SEO strategy isn’t working. That is, until you notice that your leads and conversions are actually up.
Traffic and impressions are down, but leads are rising. How is that possible?
It’s because you’re not tracking the right KPIs.
Granted, these traditional metrics are still useful for monitoring your organic search performance, but they fail to consider your performance on AI search tools.
For this reason, you shouldn’t abandon your existing link-building reporting model.
Instead, you should simply add to it.
The New Layer of Link-Building Reporting: AI Visibility and Citations
We’ve briefly covered how AI search tools influence customer buying behavior, but let’s dive deeper.
Research actually shows that visitors from AI tools convert exceptionally well and are more engaged than visitors from classic search engines.
Adobe was an early adopter of AI search optimization, and they captured some very interesting results.
By embracing generative AI as an online shopping assistant (and optimizing their content to appear in more AI responses), Adobe saw a 1,200% increase in traffic coming from AI platforms.
Their data also showed that AI visitors were 8% more engaged than organic visitors, and they browsed 12% more pages (and had a 23% lower bounce rate).
Alongside Adobe’s data analytics, they also conducted a survey of 5,000 U.S. customers about the use of AI search tools.
When asked, 92% of consumers felt that AI enhanced their shopping experiences, and 87% planned on using AI in the future for larger, more complex purchases.
Besides Adobe, research from Ahrefs found that AI search visitors convert 23x better than traditional organic search visitors.
These statistics all paint a clear picture; AI visibility pays off, so it’s definitely worth pursuing.
Here are the new link-building metrics you need to effectively monitor your AI search performance:
AI Overview Citations – How many keywords trigger Google AI Overviews (AIOs)? To focus on link attribution, measure how many AIO citations you generate after earning editorial backlinks and linked brand mentions. Granted, it takes time to see results (which vary from a few weeks to a few months), so you shouldn’t expect more AIO citations overnight.
General AI Citations – Besides Google AIOs, keep track of how often your brand gets mentioned on other popular tools like Perplexity, ChatGPT, and Claude. Remember, customers trust these tools, so getting them to recommend and cite your brand is extremely valuable.
Citation percentage growth – This KPI provides a quick and easy way to gauge how your AI search visibility is improving. For example, you could tell a client, “We saw a 120% increase in citations across all AI platforms this quarter.” This makes it clear that your link-building efforts are yielding tangible results (which is nearly impossible with standard SEO metrics now).
Topical authority backlinks – Track how many backlinks point back to content that LLMs like to cite, such as FAQ and Q&A pages, original research, and explainer pages. This type of content establishes topical authority, especially if others are linking to it.
Impression equity – This metric has to do with capturing ‘invisible influence’ through things like zero-click searches and AI searches. Pinpoint which backlinks and content trigger Featured Snippets, knowledge panels, and AI citations. These are your ‘invisible influencers.’
Editorial quality – You should split the brand mentions you earn into high-impact (premium editorial placements), medium-impact (guest posts on relevant blogs), and low-impact (mentions on community forums). That way, you’ll be able to track how impactful your editorial backlinks are on your AI search visibility.
With these new metrics, instead of telling clients something like, “We picked up 50 backlinks from DA 70+ sites,” your reporting will be more along the lines of:
“We gained 20 new AI citations this quarter, with brand visibility rising by 120% across all AI platforms. We also reinforced topical authority and entity alignment with 8 backlinks.”
Tools That Help You See the Full Picture
Knowing which metrics to track is only one piece of the puzzle. You’ll also need reliable tools to track your progress and generate reports for clients.
Here are the top tools we trust for monitoring AI search visibility.
Semrush AI Toolkit
Semrush now has a complete toolkit for monitoring your presence in AI search. This comes in especially handy if you already use Semrush to monitor your organic SEO, since you’ll be able to view your backlinks and AI citations in one spot.
Besides Google AI Overviews, Semrush’s AI Toolkit also tracks visibility across other popular LLMs like ChatGPT.
There are tools for analyzing competitors, researching user prompts, and gauging brand sentiment.
These features make it easy to track your AI citations and monitor the success of your link-building campaign.
LLMrefs
There is a free version of LLMrefs, but it has limited features and requires an email address to sign up. However, the free plan is still effective for researching popular AI prompts.
Also, the paid plan features a prompt explorer, rank tracker, and LLM citation score (which is handy for quickly gauging your visibility).
BrightEdge AI Catalyst
This tool offers a comprehensive look into your AI search performance, complete with prompt research, citation monitoring, competitor analysis, and brand sentiment.
It also tracks visibility across all AI platforms, including Google AIOs, Perplexity, ChatGPT, and Claude.
The AI Catalyst features a slick dashboard that contains a ton of helpful information, such as a chart comparing your brand versus your top 5 competitors (in terms of citations and mentions).
How We Help Clients Report and Learn From Links
In summary, link-building reporting looks drastically different now than it did just a few years ago. AI search metrics are the new norm, and failing to adapt could throw off your entire strategy.
It’s long been our duty to help clients understand link-building reporting, which is why we were so quick to adapt to this change.
Do you need help making sense of your link-building results?
Don’t wait to check out our detailed guide on link-building reporting, and book a call with our team to develop a refined, modern strategy.