Know where your brand appears. Know what to do next.
Map brand discovery across Muse, Meta AI and Meta Model API experiments. Understand Muse Spark and Muse Wonder in context, then discuss a custom measurement brief.
Muse is not included in standard monitoring or the standard trial. Collection feasibility, method, cadence and deliverables require agreement.
Enterprise custom coverage · confirm scope with our team
Bring your target market, prompt sample, preferred interface and reporting requirements. We will establish whether custom Muse coverage fits your project before you commit.
Muse
For a custom engagement, use these as acceptance criteria. Availability is confirmed during scoping, not promised by this page.
Muse is a personal AI agent. A request to research a purchase can involve prior context, connected tools and multiple steps. Record the recommendation and the action separately: being considered is different from being selected.
Muse, Meta AI and the Meta Model API are different surfaces. Spark and Wonder name model families; a result from a chosen API model does not reproduce an individual user’s agent, memory or integrations.
Mentions, citations and visits answer different questions. Keep them separate before deciding what to optimize.
| Signal | What it tells you | What to do with it |
|---|---|---|
| Brand mentions | Whether the brand is named in the sampled answers. | Find missing buying intents; inspect how the brand is described. |
| Citation Rate | The share of tracked answers citing your own domain. | Inspect the cited URLs and the facts your pages need to support. |
| Share of Model | Your share of brand mentions within the same answer set. | Compare the competitors actually named, using a stable prompt set. |
| Sentiment & answer position | The wording around a brand and its order in the answer. | Read the original context before interpreting a positive or negative label. |
| Referral visits | Attributed website sessions in your analytics. | Evaluate landing pages and key events separately from AI visibility. |
Choose a business type and build a small prompt set you can copy into your research workflow. These are editable examples—not live engine results or measured search demand.
Replace placeholders and select your target country and language in your tracking workflow. The starter runs in your browser; it does not query an AI engine.
Which wireless headphones brands should a first-time buyer consider?
Which wireless headphones options are worth comparing at different budgets?
How does [your brand] compare with other wireless headphones options?
What should I verify before choosing [your brand]?
Which reliable sources support the claims about [your brand]?
When should I choose an alternative to [your brand]?
Muse / Your workflow
Inspect
Look at where the brand enters a research or shopping journey, including the constraints supplied by the user.
Act
Create task-based prompt groups for discovery, comparison and verification. Keep private account context out of a shared public benchmark.
Keep the evidence: Task · constraints · account context
Inspect
Check whether the evidence comes from Muse, Meta AI or a direct model call.
Act
Label Spark and Wonder observations with their actual model identifiers and tools. Compare each with its own baseline.
Keep the evidence: Surface · model · tools
Inspect
Read product claims, linked sources and the destination suggested for the next step.
Act
Keep product facts, availability and merchant identity clear on your pages. Verify visits and completed actions independently.
Keep the evidence: Claim · source · destination
For Muse, agree the collection and delivery scope before this cycle starts.
Choose one market and a focused set of discovery, comparison and validation questions. Save the prompt list before measuring.
Inspect missing mentions, citation gaps and inaccurate claims. Prioritize by relevance to a real customer decision.
Improve a specific page or source. Record what changed and when, then compare equivalent observation windows.
Bring your target market, prompt sample, preferred interface and reporting requirements. We will establish whether custom Muse coverage fits your project before you commit.
Muse is not included in standard monitoring or the standard trial. Collection feasibility, method, cadence and deliverables require agreement.
Discuss Muse coverageMuse is not included in GEOly standard monitoring or its standard trial. Discuss an Enterprise custom research brief; collection feasibility, access, cadence and deliverables must be confirmed before work begins.
Specify the exact product or API, model where known, market, language, search settings and prompt sample. Agree what counts as a mention, a citation and a valid observation. A page about a platform does not mean collection is already available.
Spark and Wonder refer to Meta model families; official material uses Muse Wonder. Define whether you mean an API model experiment, Muse or Meta AI. These observations should not be pooled into one visibility score.
No. Monitoring helps you identify gaps and inspect changes. It does not control an engine’s answers or guarantee citations, rankings or traffic growth.
No. It builds research questions in your browser from your inputs. It does not run collection or show measured demand. Actual monitoring is configured separately.
Use the same prompt set, engine, market and language across equivalent windows. Inspect valid observation counts and raw answers, and annotate any collection or product-configuration changes.
No. A brand can be mentioned or cited without receiving a click. Use answer records to assess visibility and GA4 or your own analytics to assess visits and conversions.
References reviewed:
Start with the questions your customers ask. Follow the answers back to the pages that shape them.
Muse is not included in standard monitoring or the standard trial. Collection feasibility, method, cadence and deliverables require agreement.
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