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Quickstart

Create a project, choose prompts and model channels, run tracking, and review your first visibility result.

You can reach a useful first result with one project, a focused prompt set, and at least one configured model channel.

1. Create a project

Open Start tracking and enter the public domain for the brand you want to measure. Selfwin reads the site’s public metadata and uses it to prepare a project brief.

Review the proposed:

  • Project and brand name.
  • Primary domain.
  • Brand description.
  • Products, audience, category, and positioning.

The brief gives prompt generation and the Visibility Agent shared context. Correct it before generating a large prompt set.

2. Confirm the brand identity

In Settings, check the tracked brand name, aliases, and domains. Use aliases for normal spelling variants. Use a custom matching expression only when literal names are not precise enough.

Accurate identity matters because Selfwin reuses the same matching rules for visibility, share of voice, position, sentiment, and historical recalculation.

3. Add prompts

Open Prompts and either generate suggestions, add questions manually, or import a CSV.

A prompt should resemble a real question, for example:

What is the best no-code app builder for an internal operations tool?

Keep prompts at 200 characters or fewer. Assign a two-letter country code, a topic, and tags where useful. Suggested prompts do not run until you accept them.

4. Configure collection

Open Settings → Model tracking and enable the channels for which credentials or browser collection are available. Then choose:

  • Daily or weekly tracking.
  • Browser or provider API collection for scheduled runs.
  • The project time zone.

Browser collection and API collection can produce different answers. Treat them as separate model channels when comparing trends.

5. Run tracking

Select Run tracking from the application header. Selfwin creates one answer per active prompt and selected engine for the project’s current run date. Existing successful prompt-engine-day combinations are skipped, which prevents accidental duplicate data.

The run history reports completed, skipped, and failed items. A failed answer is not counted as an analyzed response in visibility metrics.

6. Read the first result

Open Overview after the run finishes. Check:

  1. The number of answers collected.
  2. How many active prompts are represented.
  3. Your visibility and the leading competitor.
  4. Which sources appear most often.
  5. The recent answers behind those numbers.

A first run is a snapshot, not a trend. Continue collecting on a consistent prompt and model set before treating small changes as a durable movement.

7. Run the Visibility Agent

When tracking data exists, open Visibility Agent and start an analysis. The agent classifies the clearest gaps, records its evidence, and creates draft actions.

Review those drafts in the Action queue. Approving an action does not publish it externally.

Next steps