🎯 Why this view exists?
In generative search, the final answer is only part of the story.
LLMs rely on two distinct layers:
Domains and URLs used as Sources to build their answer (influence)
Domains and URLs shown as Links in the final output (visibility)
These two layers often differ.
Together, they influence not only what is visible, but also how information — and brands — are represented in generative answers.
The Sources & Links view is designed to help you understand: which domains influence answers, which ones are surfaced to users, and how brand mentions are framed within these responses across engines.
To go further:
📊 What this view helps you analyse?
The Sources & Links view helps you understand which domains and URLs influence LLM answers, how they are surfaced, and how this varies across queries and engines.
#1 Main table: Comparing Domains and URLs at a glance
#1 Main table: Comparing Domains and URLs at a glance
This view lets you compare domains and URLs across three key dimensions:
1. Role in the answer
The Type column shows whether a domain is:
Source → used to build the answer
Link → visible in the final output
Source & Link → both influencing and visible
This makes it easier to understand how a domain contributes to generative answers.
2. Consistency across engines and queries
By looking at:
The Engines column
The Results column
The Presence rate
You can identify whether a domain appears occasionally or is consistently used across multiple engines and prompts, helping distinguish one-off appearances from recurring influence.
3. Brand mentions & Sentiment
The My Brand Mentions column shows whether your brand is mentioned within the source content or the generated answer, as returned by the LLM API
Specific note: mentions embedded directly within URLs are not included.
When a brand is mentioned, sentiment signals help qualify how it is framed, using a score ranging from -100 to +100, with a breakdown of positive, neutral and negative mentions.
This helps distinguish simple brand presence from the tone in which a brand is discussed.
#2 Domain details: Understanding content patterns
#2 Domain details: Understanding content patterns
When you click on a domain, you access the list of URLs associated with that source. This view helps you understand what kind of content the LLM relies on from a given domain.
You can observe:
Which URLs are used as Sources, Links, or both
How often each URL appears
Whether brand mentions are present at URL level
How brand sentiment varies across URLs from the same domain
Their content and structure by accessing those URLs directly from the interface
#3 Results details: linking domains, URLs and queries
#3 Results details: linking domains, URLs and queries
When clicking on the ‘Results’ number a domain or URL appears on, you access the details of queries by engine on which the item appears as a Source and/or as a Link.
The Results view shows:
The search queries (prompts)
The role played by the domain or URL for each query
Differences by engine
You may notice that:
The same query behaves differently across engines
A domain is a Source on one engine and a Link on another
Some queries rely heavily on Sources without showing Links
The same domain can mention a brand with different sentiment depending on the query or engine
This shows that the role a domain plays — and how brands are referenced — can vary depending on the query and the engine, rather than being fixed or universal.
💡 Reading cues: what common patterns can tell you
This section highlights common patterns observed in Sources & Links and how they are often interpreted.
These are signals to read, not rules.
A competitor appears frequently as Source & Link
A competitor appears frequently as Source & Link
This pattern is usually observed when content is:
trusted by the model to build its response
structured in a way that is easy to surface in the final output
It often appears on queries where:
the answer requires synthesis
the model needs both explanation and examples
This suggests the domain fits well with how LLMs combine reasoning and visibility.
A domain appears mainly as a Source
A domain appears mainly as a Source
This typically reflects content that:
explains concepts
provides background or context
supports the model’s reasoning process
This behavior is often seen on queries where:
understanding the topic matters more than pointing to a single reference
These domains influence how the answer is constructed, even when they are not visible to users.
A domain appears mainly as a Link
A domain appears mainly as a Link
This pattern is usually observed when content is:
easy to reference
clearly structured (lists, steps, summaries)
It often appears on queries where:
the model benefits from pointing users to concrete resources
Here, visibility is more closely tied to format and accessibility than to depth of reasoning.
Differences across engines
Differences across engines
When patterns vary by engine, this usually reflects:
different source selection logic
different preferences for structure, depth or citation
This reinforces the idea that LLM visibility should be interpreted engine by engine, rather than as a single aggregated signal.
The same domain behaves differently depending on the query
The same domain behaves differently depending on the query
You may notice that:
a domain is used as a source on some queries
and appears as a link on others
This reflects the fact that LLMs adapt how they use content based on the nature of the question, rather than applying a single rule.
✨ How to use this view effectively
Start by identifying which domains consistently act as Sources, even when they are not visible as Links. These domains often shape how answers are constructed and can reveal where influence happens before visibility.