website positioning has undeniably modified. To remain discoverable in search, AI, and past, manufacturers now want to trace visibility in AI Overviews, chatbots, and LLM responses.
And that’s the place Ahrefs’ Model Radar comes in.
It’s one of many fastest-growing instruments in AI model visibility, with 100M+ prompts, 6+ AI indexes, and requires zero setup.
Under, I share my favourite use instances and actionable workflows to show Model Radar’s insights into measurable progress on your model. Let’s dig in.
Not like conventional website positioning metrics, AI solutions are non-deterministic—they alter from question to question, and even the identical immediate can return totally different citations every time.
That makes it troublesome to trace model visibility in AI search manually.
Most AI instruments solely allow you to observe a handful of prompts to see how outcomes shift over time. Model Radar goes additional: it aggregates 1000’s of prompts and responses throughout a number of AI search platforms.
As a substitute of solely monitoring what you already know, it offers you a database of potential alternatives and concepts, serving to you see new progress angles as they emerge.
You possibly can seek for particular manufacturers, merchandise, folks, and/or subjects to see how varied AI search platforms reply to them, whereas additionally uncovering contemporary alternatives you won’t have thought to examine.
However, on the core of Model Radar are filters. That is the place the magic occurs.
The filters allow you to isolate actual situations the place the entity you searched seems or the place it doesn’t however ought to. For instance:
| Use case | Filter settings |
|---|---|
| Get stats about solely your branded searches. | Question accommodates {your model} |
| Get stats about all of your manufacturers and sub-brands. | Question accommodates {your model} AND {sub-brand 1} AND {sub-brand 2} and so forth. |
| Analyze when and the way AI contains your content material in responses. | Response accommodates {your model} |
| See how typically AI solutions hyperlink to your content material. | Quotation accommodates {your area} |
| Analyze how typically a specific web page will get cited in AI responses. | Quotation accommodates {URL} |
| See how a whole content material hub or web site phase performs in AI search. | Quotation accommodates {path} |
| Discover branded content material gaps you’ll want to fill, so that you management the reply. | Question OR response accommodates {your model} AND quotation doesn’t include {your area} |
| Discover when AI doesn’t suggest your model for a branded question. Uncommon state of affairs. Signifies a notion downside. | Question accommodates {your model} AND response doesn’t include {your model} |
| Discover unbranded queries for which you’ve sturdy visibility. | Question doesn’t include {your model} AND response OR quotation accommodates {your model} |
| Uncover unbranded subjects that AI strongly connects to your model. | Quotation accommodates {your area} AND response AND question don’t include {your model} |
| Assess your matter protection in AI responses. | Question OR response accommodates {matter} AND quotation accommodates {your area} |
| Assess model gaps towards rivals in AI responses. | Quotation doesn’t include {your area} AND quotation accommodates {competitor 1} OR {competitor 2} and so forth. |
| Discover content material angles or niches in your trade that aren’t coated by established rivals. | Question accommodates {your matter/trade} AND quotation doesn’t include {your competitor’s area(s)} |
The combos are infinite. You too can nest filters inside filters by creating teams.
As an example, should you needed to examine queries that don’t embrace your model and the place the response or quotation does, right here’s how you could possibly set that up:
When you perceive how the filters work, the following step is placing them into motion.
10 Model Radar workflows you need to use right this moment
Model Radar does greater than spot the place your model reveals up. It could actually additionally assist you to flip these insights into workflows that enhance visibility, shut gaps, and strengthen your aggressive place in AI search.
Under are ten sensible methods to do precisely that.
When auditing your model for efficiency in AI search, you’ll must assess each the result (mentions in AI responses) and the causes (model searches and visibility throughout the net).
Model Radar permits you to analyze each.
Begin by coming into your model identify and benchmarking your present mentions, citations, impressions, and AI Share of Voice:
- Mentions are the variety of outcomes that point out the entity not less than as soon as.
- Citations are the AI outcomes that cite the entity not less than as soon as as a supply.
- Impressions are mentions which can be weighted by Google search quantity to estimate potential publicity.
- AI Share of Voice is the proportion of name impressions out of the entire impressions for responses that point out any tracked model.
You are able to do this throughout 6+ AI indexes, like AI Overviews, ChatGPT, and Perplexity, to see which platforms regularly point out your model of their responses.
You too can simply examine progress in your model’s search demand and net visibility over time:
For those who handle a number of manufacturers, you possibly can add all of them to the model discipline to trace them as a gaggle and get their mixed metrics:
These stats are nice for getting directional suggestions on whether or not your model’s visibility is rising or declining in AI search.
One of the vital worthwhile issues Model Radar does is assist you to defend your narrative by checking how your model is definitely talked about in AI responses.
It’s vital to identify inaccuracies, outdated messaging, or unfavourable sentiment earlier than they unfold, and proper the sources shaping them.
As an example, you possibly can examine for issues like:
- Incorrect firm particulars, like identify, deal with, or cellphone quantity, pulled from outdated sources.
- Inconsistencies in model messaging, like previous taglines or content material from previous web site designs.
- Model sentiment, like whether or not your model is talked about positively or negatively.
- How excessive up your model is talked about throughout the response
- What number of different manufacturers are additionally talked about within the response
- Whether or not your model stands out as a transparent alternative throughout the response
You are able to do this by looking for your model and navigating to the AI responses tab in Model Radar. Then, select the AI index you wish to analyze:
You’ll see a listing of responses that appear to be this:
For those who see 1000’s of responses, it helps to filter them into smaller teams. For instance, you could possibly look at:
- Queries containing your model to see what AI says about you on your branded searches.
- Queries containing a particular matter to see how strongly AI connects your model to the matter.
- Queries containing a competitor’s identify to see how typically AI recommends your model as a substitute of or alongside the competitor.
- Responses containing your model to see a listing of all queries (together with unbranded) you present up for.
- Citations containing your web site, even when the question or response doesn’t point out your model.
Search for patterns in what AI solutions say about you, particularly once they get issues flawed or when your branding is inconsistent. It helps to listing these queries and the sources cited so you possibly can overcome misinformation and model inconsistencies.
Repeat this course of for each AI search platform you wish to analyze. You might discover that totally different patterns emerge for every platform.
AI visibility isn’t nearly whether or not your model reveals up. It’s additionally about what subjects AI search platforms strongly affiliate you with.
Model Radar enables you to measure these connections by looking for your model and key subjects on the similar time:
It’s greatest to seek for one matter at a time to gauge the power of your model’s connection.
For instance, inside AI search, Toyota is extra strongly related to the subject of hybrid vehicles than SUVs (above) because it has the next AI Share of Voice and search demand:
You too can run a model search by itself and use the filters to evaluate issues like:
- Queries containing each your model and important matter. This helps you see what subjects or product classes searchers strongly connect with your model identify.
- Queries containing your model and responses containing a particular matter. This helps you see what subjects AI techniques point out when speaking about your model.
- Queries containing the subject and responses containing your model. This helps you see what unbranded searches AI techniques choose your model to be a part of the reply.
You should use these insights to benchmark the subjects you have already got a robust affiliation with in AI solutions.
To benchmark your model’s AI visibility towards rivals, search your model after which add a number of rivals like so:
You too can use our AI recommend function to robotically populate your prime rivals:
The Overview tab will present your model towards your rivals. You possibly can assess every model’s AI visibility metrics like mentions, impressions, and AI Share of Voice.
You too can see a platform breakdown to evaluate visibility in any AI search instruments that matter most to you.
Once you click on into every platform, you’ll be capable of entry the precise AI responses and queries that point out every model:
- Solely model: This report will present you queries and AI solutions the place the one model talked about is the one you’ve chosen. It’s nice for assessing brand-specific queries and responses.
- With others: This report reveals queries and/or responses that include all of the manufacturers you’re evaluating. It’s nice for assessing subjects which can be prone to point out you alongside rivals.
- Others solely: This report reveals queries that solely point out the opposite manufacturers you’re evaluating towards. It’s nice for locating subjects that point out your rivals however not you.
These reviews present directional progress over time and assist you to establish rivals which may be gaining in AI visibility somewhat shortly.
You too can use them to seek out matter gaps the place rivals are talked about, however your model isn’t. Begin by including a subject to your search after which examine the AI Share of Voice of every model for the matter:
You too can go to the Others solely report back to see AI responses in regards to the matter that solely include your rivals to get a way of content material gaps you could must fill.
Analyze the responses to see what subjects, options, and attributes every model is related to:
These AI responses are an important knowledge supply for analyzing your positioning towards rivals and likewise seeing how LLMs view your model in comparison with theirs.
This provides you leverage. You’re not simply monitoring rivals, you’re recognizing the place to increase visibility earlier than they pull forward.
You too can take a look at the Cited domains and Cited pages reviews to establish the highest sources mentioning every model:
These reviews present you the web sites which can be regularly cited in AI responses and the way seen every model is inside them. Search for sources that point out your competitor greater than you and see how one can improve your mentions inside them, too.
There are such a lot of prospects right here, relying on what aggressive insights matter most to your stakeholders.
Model Radar can assist your content material technique by:
- Figuring out pages or content material hubs that must be cited in AI responses however aren’t
- Discovering matter gaps towards your rivals
- Uncovering untapped subjects your rivals have but to find
For instance, you possibly can run a clean search in Model Radar by leaving all fields empty. Then, use the quotation filter and add a particular URL:
This can present you all AI responses that cite this URL. To research a whole web site phase, use the path setting as a substitute.
For those who seek for particular pages which can be core to your model however they’re not being cited in lots of AI responses, this could possibly be a possibility to rewrite the content material and optimize it higher for AI visibility.
Optimize the pages with:
- Clearer, extra direct writing
- Utilizing BLUF (backside line up entrance)
- Hierarchical heading construction
- Declarative sentences
You can additionally use AI Content material Helper to take away any guesswork. Simply add the principle question you’d prefer to optimize the web page for and the web page URL.
Then, the instrument will assist you to establish the perfect intent for the content material robotically:
Our staff has designed AI Content material Helper for the AI period. It makes use of comparable math and processes to AI search engines like google and yahoo.
For instance, it identifies associated fan-out queries and calculates cosine similarity for every matter. As you write, a coloured spotlight seems exhibiting you ways properly you cowl every matter in your content material:
Because you’ll be working with present content material on the reside web page, begin by assessing how self-contained every matter is. You might must reorganise the construction in case your subjects are scattered everywhere in the place.
When you’ve contained sections on like subjects collectively, then work on rewriting them for readability.
That’s the place beginning with the bottom line up front helps. It’s the thought of beginning with crucial data. People and AI search engines like google and yahoo prioritise introductory sentences, so don’t waste your phrases right here. Get straight to the purpose as a substitute.
You too can use Model Radar that will help you uncover alternatives your rivals have but to write down about, increasing your topical protection.
Begin by coming into your important matter:
Then, take a look at the queries and solutions for every AI search platform you care about exhibiting up on. Attempt filtering the queries or responses to exclude your model and rivals.
You’ll be left with a listing of untapped queries for which you’ll be able to create content material to extend your AI visibility earlier than your rivals. Pop these into AI Content material Helper to get on the spot content material roadmaps you possibly can ship to your writers right away.
There are two methods to seek out your hottest pages getting talked about in AI responses.
The primary is in Model Radar and is good you probably have not arrange AI monitoring in your net analytics instrument. Enter your model identify and navigate to the Cited domains report.
Sidenote.
You too can run a clean seek for this course of. By including your model identify, you pre-filter the database to indicate you high-intent, related queries and responses that include your model identify.
By working a clean search, you will note all AI queries and responses in our database that cite your area (when you observe the following steps), guaranteeing you don’t miss something. However you could discover extra outcomes that appear irrelevant or of weaker intent.
Scroll till you see the listing of all domains and click on on the worth underneath “Pages” on your web site:
For those who ran a clean search, attempt utilizing the Area identify filter (underneath the graph) to slim your search:
Both method, you’ll find yourself with a listing of pages in your web site that present up in AI responses ranked in descending order.
The second technique is to examine your analytics instrument towards this listing to see which pages folks click on on from AI platforms. Simply since you’re cited in AI responses doesn’t imply folks will click on the pages.
You should use instruments like Ahrefs’ Net Analytics to get this knowledge.
What you’re searching for is a listing of the highest pages visited most from AI platforms:
Cross-check these pages towards these in Model Radar. For every one, examine the responses the web page is cited in:
That method, you possibly can establish the patterns of queries and responses that result in larger click-through charges to your web site from AI searches.
You possibly can repeat this course of for every AI index to establish click-through patterns between AI Overviews, ChatGPT, and so on.
Totally different AI platforms want several types of content material. With Model Radar, you possibly can analyze cited pages to see which codecs dominate on your matter — whether or not it’s statistics posts, lists, skilled guides, instrument comparisons, or unique analysis.
To search out these, seek for both your model, a competitor, or a subject. Then, take a look at the Cited pages report:
Search for patterns in the kind of content material that’s most regularly cited for the subject. As soon as you already know the codecs AI leans on, you possibly can adapt your content material technique to match.
The aim is to align your content material with what AI already trusts, so your model has the next likelihood of being cited, and so you keep management over the narrative in AI-generated responses.
You possibly can simply measure the expansion or decline of your model mentions across the net in Model Radar’s Net Visibility reviews:
This report reveals you all of the locations across the net the place your model is talked about. By checking the Net pages report, you’ll get a full listing of the precise pages and your model point out inside them.
It’s price analyzing your model mentions on different web sites for just a few causes:
- Replace outdated details about your model
- Present appropriate data to attenuate inaccurate responses in AI search
- Discover potential partnership alternatives with websites that regularly point out you positively
- Assess common model sentiment across the net (optimistic, impartial, unfavourable mentions)
- Get your model talked about intently to your most well-liked subjects or different large manufacturers in your trade
As a low-hanging fruit alternative, you could possibly additionally take a look at the Cited domains and Cited pages reviews to seek out pages that each point out your model and get cited most in AI solutions.
Your model mentions on these pages make an even bigger influence on how your model is represented in AI responses. That is vital to observe as a result of most AI citations on your model come from third-party web sites, not your personal.
For instance, in AI Overviews, Zapier, YouTube, and Reddit are cited extra regularly for queries about Ahrefs than our personal web site:
Sixteen pages on Zapier’s website that point out Ahrefs is all it takes to be cited in 1,431 AI responses that additionally point out Ahrefs.
The model mentions on these pages are extra worthwhile than on pages that aren’t being cited in AI responses. Not solely are AI search platforms regularly referencing this content material, however they’re additionally utilizing it to summarize details about your model.
Normally, the web sites cited greater than yours are chosen as a result of they’ve comparability content material or suggest the perfect instruments for varied conditions:
When you gained’t be capable of management the entire details about your model on third social gathering websites, you possibly can not less than establish patterns and determine why AI responses could embrace misinformation about you.
And, the place doable, attain out to make your on-line model footprint extra constant, one point out at a time.
For those who create new content material or wish to increase the visibility of particular pages in your website, it may well assist to get extra hyperlinks on to these pages.
Over time I’ve spent auditing web sites and their website positioning visibility, many websites have had only a few hyperlinks to inside pages, preferring to advertise the homepage most. Whereas that’s nice for model visibility, it may well result in gaps in matter alignment and authority.
To shut these gaps, run a subject search in Model Radar and take a look at the Cited pages report:
For those who see your content material exhibiting up within the outcomes, do a fast audit to make sure data accuracy and freshness. Additionally be sure to extend the enterprise worth throughout the content material by including your most vital product options and analysis.
For those who see another person’s content material, add it to your outreach prospecting listing to get talked about throughout the content material. It additionally helps to work with the PR staff (if your organization has one) to align on-line model visibility efforts.
In relation to user-generated content material, like on boards and social media, you could possibly contemplate becoming a member of the conversations that regularly get cited in AI responses.
For instance, you need to use the domains filter to get a listing of all subreddits:
You too can search for mentions of competing merchandise and purpose to hitch the conversations to lift extra consciousness of your product.
Simply don’t overdo it, many of those communities dislike apparent model promotions.
For those who do wish to add a robust promotional message in these areas, contemplate paying for advert actual property. Whereas it might indirectly assist with visibility in AI responses, it can get you in entrance of latest audiences who take a look at the thread as a result of it’s been cited in conventional and AI search outcomes.
Begin by monitoring whether or not persons are looking for your model in AI search.
Enter your model identify after which head to the Search demand tab.
The search quantity graph reveals whether or not search demand is rising primarily based on what number of branded searches happen over time.
Rising search quantity signifies extra persons are searching for your model. Rising search question rely reveals key phrase breadth the place customers are asking extra various questions on you, from long-tail queries to feature-specific searches.
Drill down into the Search queries report back to see the precise branded key phrases folks use. It will likely be pre-filtered to indicate queries that include your model identify:
This reveals how audiences body questions on your product, which options get consideration, and what associations they’re making together with your model.
Take a look at these reviews each infrequently and monitor new branded queries which can be being searched on totally different platforms.
Subsequent, benchmark and monitor visibility towards rivals.
Add your prime rivals to the search and head to the Overview tab:
Right here you possibly can monitor your AI Share of Voice alongside prime rivals.
You too can add particular subjects you want to monitor over time to see how a lot share you seize in that area or whether or not you’re dropping visibility to rivals.
By monitoring demand, mentions, and share tendencies over time, you possibly can refine your technique and join AI visibility to broader advertising influence.
Take management of your AI visibility with Ahrefs’ Model Radar
Staying seen in AI search isn’t a one-time job, it’s a self-discipline.
By constantly monitoring demand, mentions, and share of voice, you possibly can adapt your technique and guarantee your model shapes the narrative the place folks search.
Able to see how your model stacks up? Discover Model Radar and begin turning AI visibility into measurable progress right this moment.
