LLM Brand Tracker

Create and manage query groups — the sets of buyer questions you run across the LLMs. Run a group on demand or schedule it.

Query Groups

No query groups yet. Create one to get started.

Automatically re-run a query group on a cadence (daily/weekly/etc.) and post a summary to Slack when each run finishes.

Scheduled Runs

No schedules yet. Create a schedule to run a group automatically.

The raw data behind every tab — Answers (one row per LLM response, click to read it) and Citations (one row per cited URL). Filter by run, engine, or status.

Run LLM Segwise Mentioned Segwise Citation

Date	Run	LLM	Model	Query	Mentioned	Citation	Error
Loading…

The raw data behind every tab — Answers (one row per LLM response, click to read it) and Citations (one row per cited URL). Filter by run, engine, or status.

Run LLM From Segwise

Date	Run	LLM	Model	Query	Citation URL	Segwise?
Loading…

How citations move across runs. Flat = a ranked list of URLs with share % and gained/dropped between two runs. By query = each query's citations rising/declining/dropped across the runs you pick.

Newer run (current) Older run (compare to) LLM Sort

Include (any term, comma-separated) Exclude (any term) Subset — "of these, how many also contain"

Quick include:

#	Citation	Older count · share	Newer count · share	Change newer − older	Subset
Select a run to begin.

Which brands/domains the LLMs cite most for your queries — your share of voice vs competitors. Pick a run; add your competitors to tag them, or show every ranking domain.

Run Compare to Competitor domains (comma-separated) Show all domains

Rank	Brand	Citations	Share	Δ vs compare
Select a run.

How citations move across runs. Flat = a ranked list of URLs with share % and gained/dropped between two runs. By query = each query's citations rising/declining/dropped across the runs you pick.

Runs to compare (pick 2–5)

LLM

Include (any term, comma-separated) Exclude (any term)

Quick include:

	Query	Runs	Citations	🔴 Dropped	🟠 Declining	🟢 Rising/New
Select runs and Apply.

A snapshot of where you stand right now in one run: for each query, how many engines mention/cite Segwise — and which queries you're absent from. Expand a query to see the citations to write from. (To compare runs over time, use Content Gaps.)

Coverage — where are we (not) showing up?

Run LLM Show

Query	LLMs answered	Mentioned	Cited	Status
Select a run.

Your content to-do list: queries where we lost a mention or citation (refresh that page) or were never cited (write net-new). Expand a row to see your dropped pages and what's winning now. (For a single-run snapshot of where you stand now, use the Coverage tab.)

Content Gaps — where we're losing mentions & citations

Runs to compare (pick 2–5, oldest→newest)

LLM

OpenAI Anthropic Gemini

Show

Each run cell shows two lines — M mentions and C citations — as x/y (LLMs hitting it / LLMs that answered), with a dot per engine: O OpenAI · A Anthropic · G Gemini (filled = present). The Status column gives the verdict for each: "Dropped" = fell to 0, "Declining" = below peak, "Absent" = never there. Rows with no citation now expand → your dropped pages to refresh + what's cited now to beat.

Query
Pick 2–5 runs to compare.

Topline scorecard for a run: Segwise mention & citation totals, the per-engine split, and custom citation breakdowns — compare against any earlier run.

Topline

Run Compare to

By LLM

LLM	Answers	Mentioned	Cited
—

Citation breakdowns

Label Include (any term) Of which (subset, optional)

Per-Run Summary

Run ID	Date	Total Calls	Segwise Mentions	Segwise Citations
No runs yet.

Configure your LLM API keys, pick the model per engine, and set a Slack webhook for run notifications.

API Keys

Slack Notifications

Sends a summary to Slack when each run completes. How to create a webhook

Slack

Models

OpenAI Model

Anthropic Model

Gemini Model

Response

Running…

0%

Starting…