Brand Mention Detection
See when and how Claude includes your brand in its answers across topics and intents.
Measure how often Claude recommends, references, and cites your brand. Monitor competitor mentions, uncover prompt patterns, and prove impact with clean reporting.
Claude grew 12.8× in 2025 — faster than any other major AI platform (Previsible, 2025). Unlike ChatGPT, Claude doesn’t rely on a live Bing search index. It draws more heavily from training data and its Constitutional AI reasoning, which means the factors that get you cited in Claude answers are genuinely different from what works on ChatGPT. You can’t infer your Claude visibility from your ChatGPT data. They need to be tracked separately.
Built for marketing and growth teams to understand & improve visibility in Claude chat and AI‑generated answers.
See when and how Claude includes your brand in its answers across topics and intents.
Track which sources Claude cites when mentioning your brand—and which citations your competitors win.
Reveal the prompts that trigger mentions, the phrasing that suppresses them, and priority gaps to close.
Benchmark your presence vs. key competitors by topic, persona, and geography.
Understand how Claude’s answers vary by country, city, and intent—then localize your strategy.
Get notified when visibility dips or competitors gain ground. Export executive‑ready summaries.
Improve how often Claude selects your brand for key queries and intents.
Understand why Claude prefers rival brands and close the gap with precision.
Attribute AI visibility to sessions and conversions with clean reporting.
From discovery to measurable lift—designed for speed and clarity.
Baseline Claude visibility, entity/topic mapping, competitor set.
Content evidence, entity pages, schema, and answer hubs.
Templates, governance, and PRs to scale improvements.
Visibility, citations, and conversion impact over time.
Support for Claude, analytics, and data pipelines.
Track brand mentions and cited sources in Claude’s answers using your prompts and test sets.
Import prompts, golden sets, and personas to standardize tracking and comparisons.
Connect analytics for AI‑origin sessions and Search Console for corroborating signals.
Most teams assume their ChatGPT visibility tells them something about their Claude visibility. It doesn’t. The two platforms work differently, cite sources differently, and respond to different optimization signals. Here’s what that means in practice.
ChatGPT searches Bing in real time when answering product questions. Claude draws primarily from its training data and Constitutional AI reasoning. What gets you cited in one doesn’t automatically transfer to the other — which is why brands that dominate ChatGPT are often invisible in Claude, and vice versa.
Claude handles much longer prompts and tends to produce more detailed, nuanced answers than ChatGPT. That’s great for B2B buyers doing serious research — and it means the way Claude frames your brand (not just whether it mentions you) matters enormously for how buyers perceive you.
Claude’s Constitutional AI approach makes it more cautious about recommending brands it can’t clearly verify from its training. Brands with strong entity definitions, clear E-E-A-T signals, and consistent third-party coverage get recommended more confidently. Brands that rely only on their own site copy get hedged.
Claude has become the preferred AI assistant for enterprise and B2B research. If your buyers are evaluating software, professional services, or technical solutions, they’re likely using Claude for that research — and your Claude visibility is directly connected to pipeline, not just brand awareness.
| Signal | ChatGPT | Claude |
|---|---|---|
| Knowledge source | Bing live search + training data | Primarily training data + Constitutional AI reasoning |
| Response style | Concise, link-heavy | Detailed, analytical, long-context |
| Key citation trigger | Bing index presence, schema, third-party sources | Training data coverage, E-E-A-T signals, brand entity clarity |
| Primary audience | General consumer + SMB | Enterprise + B2B research |
| Can you infer from the other? | No — they must be tracked independently | |
Manual checking — opening Claude, running prompts, copying responses into a spreadsheet — works for a one-off baseline. It falls apart fast when you need to track 50 prompts across 5 competitors weekly. Here’s the systematic approach.
List the exact questions your buyers are asking Claude about your category — product comparisons, how-to queries, recommendation requests, and buyer-journey-stage questions. Aim for 30–50 prompts across at least three intent types. These are the queries your brand should be appearing in, and tracking starts with getting specific about them.
Run your full prompt set and document for each response: does your brand appear, in what position, with what sentiment, and who else gets mentioned? This baseline tells you where you stand before any optimization work — and becomes the benchmark you measure every future improvement against.
For every prompt where a competitor outperforms you, identify what’s driving their visibility — which third-party sources Claude trusts about them, how clearly Claude can identify their entity and category, and whether their content is more directly answering the intent of the query. These gaps become your to-do list.
Manual tracking breaks down at scale. AIPosition runs your prompt set automatically on your chosen schedule, tracks changes over time, and alerts you when visibility drops or a competitor gains ground. What takes hours manually happens in the background while you focus on the work that actually moves the needle.
Organize prompts into: recommendation queries (“best X for Y use case”), comparison queries (“X vs Y”), alternatives queries (“alternatives to [competitor]”), and how-to queries (“how do I accomplish Z?”). Each type reveals a different dimension of your Claude visibility — and each responds to different optimization approaches.
Get visibility in days. Improve mentions, citations, and share‑of‑voice in Claude answers.
Straight answers about what we track, how it works, and what to do with the data.
We track brand mentions (yours and competitors'), cited sources, prompt coverage across topic types, sentiment per response, and your position in Claude’s answer — first mentioned, secondary, or absent. You get a complete picture of how Claude talks about your brand across the prompts your buyers actually use, not just a mention count.
Very much so. ChatGPT uses Bing’s live web index. Claude draws more heavily from training data and Constitutional AI reasoning. That means the optimization levers are different: schema and Bing indexation matter most for ChatGPT; entity clarity, E-E-A-T signals, and training-data coverage matter most for Claude. You can’t infer one from the other — they have to be tracked separately.
Yes. You can run prompt checks across markets, cities, and languages to see how Claude’s recommendations shift by region. This is especially useful for brands with different positioning across markets, or for identifying where a local competitor is dominating Claude responses you should own.
Connect GA4 and Google Search Console to see Claude-origin sessions and assisted conversions alongside your visibility metrics. When your citation rate goes up, you can see whether that correlates with traffic and pipeline. You can also export executive summaries for stakeholders who need the "so what" without the raw data.
No technical work required. Use our presets to get started quickly, or import your own prompt library. GA4 and Google Search Console integrations are click-through — no developer, no API keys, no custom implementation. Most teams have their first audit running within 20 minutes of signup.
Your first visibility audit runs within 24 hours. You’ll see which prompts trigger mentions, where competitors appear instead of you, and which sources Claude is drawing from. Ongoing tracking runs on your schedule — most teams check monthly trends rather than weekly snapshots, since Claude’s responses vary enough run-to-run that weekly data creates noise.