Group your prompts into the topics your buyers actually think in, like zero trust, SOC 2 compliance, pricing, or migration. Then see share of voice per topic against every competitor in one matrix. You stop asking whether visibility is up and start asking which subject a rival owns, which is the only version of the question you can act on.
No credit card required. Your topics in about a minute.
| Topic | You | Rival A | Rival B | Rival C |
|---|---|---|---|---|
| Zero Trust | 42% | 28% | 18% | 12% |
| Pricing | 35% | 30% | 20% | 15% |
| Migration | 31% | 25% | 24% | 20% |
| SOC 2 Compliance | 6% | 51% | 30% | 13% |
Your visibility score is 46 and holding. Underneath it you are strong on brand questions, fine on category questions, and invisible on every compliance question a regulated buyer asks. The average hides the exact thing that costs you enterprise deals.
Four hundred tracked prompts in one flat list. No way to ask a simple question like "how are we doing on identity governance," so the analysis never gets done and the list becomes decoration.
You are behind a rival overall, but nobody can say where. Without a subject level view, the competitive conversation stays at the level of vibes and the roadmap never gets a target.
The same data, cut the way a marketing team actually plans.
Name your topics manually, or let AI suggest them from your brand context.
Add prompts one by one, or bulk import into a topic.
Every tracked prompt rolls up into its topic automatically.
The matrix shows your share of voice against rivals, per topic.
Apply a topic across visibility, responses, citations and exports.
A flat prompt list in. A subject level map of who owns what out.
Topic grouping sounds like a folder feature until you try to make the numbers mean something. Share of voice is only comparable if every topic contains a coherent set of prompts, which is why we let you build topics both ways. Name them yourself when you already know how your category segments, or let the model propose topic names from your brand context, your site, and the prompt library you are already tracking. Most teams do both: accept the suggested skeleton, then rename and merge until it matches how their buyers actually talk. Bulk import exists because nobody is going to hand sort four hundred prompts, and a feature people abandon at step one is not a feature.
The second problem is that a topic view is worthless if it only lives on one screen. If you can see that you are weak on compliance questions but cannot then filter your citations, your engine responses, and your exports to that same set, the insight dies in the dashboard. So the topic filter runs across the platform. Find the weakness in the matrix, then follow it straight into the raw answers and the sources behind it, without rebuilding the segment by hand each time.
Create a topic in a few seconds and name it whatever your team already calls it. Or start from AI-suggested topic names generated from your brand context, which is faster when you are staring at a large library and do not want to design a taxonomy from scratch. Either way the structure is yours to rename, merge and reshape as your category shifts.
Assign prompts individually when precision matters, or bulk import them into a topic when you are setting up. The point is that the taxonomy gets finished in an afternoon rather than sitting half built for a quarter.
The matrix is the payoff. Topics down one axis, you and your rivals across the other, and a clear read of who owns which subject in AI answers. Strength you did not know you had shows up as fast as the weakness you suspected, and both are specific enough to brief someone on.
You are outpaced 8 to 1 on this subject.
Once a topic exists, it becomes a lens. Filter visibility trends, engine responses, citation sources and exports to a single subject, so the investigation that starts in the matrix can finish in the raw data. Reporting gets easier too, because "here is how we did on compliance questions this quarter" is now one filter rather than a manual rebuild.
| A flat prompt list | GrackerAI Prompt Topics |
|---|---|
| One blended visibility number | Share of voice per subject |
| Competitors compared overall | Competitors compared topic by topic |
| Manual sorting, abandoned halfway | Manual, AI-suggested, or bulk imported |
| Segment rebuilt for every question | One topic filter, used platform wide |
| Reporting assembled by hand | Topic-scoped exports |
| Strength and weakness averaged together | Both visible, separately, in one matrix |
A blended score tells you almost nothing you can act on. A topic matrix tells you exactly where to brief your team next.
Topics organize the library the prompt generator builds from real buyer demand.
Topic level share of voice is where head-to-head comparison becomes actionable.
Filter citation sources to a single topic and see who the engines trust on that subject.
Get your free AI Visibility Score in about a minute. See exactly where you stand, where competitors are beating you, and the ranked fixes to get into the answer. No credit card, no commitment.
Free in about a minute. Trusted by 500+ B2B and security teams.
