How to Set Up AI Brand Monitoring in 5 Minutes

Create Your Brand Profile

After registering and verifying your email, Goeet drops you straight into brand creation. This is the core unit of tracking: a brand profile ties a specific brand name to an industry category and a geographic market. Every metric, query, and competitor comparison is scoped to this profile.

There are three fields to fill in:

You can create multiple brand profiles if you manage several brands or want to track the same brand in different markets. The Free Tier includes one profile; Starter supports five, and Pro supports ten.

Discover Competitors

After your brand profile is created, the next step is adding competitors. Competitor tracking is what turns Goeet from a vanity metric tool into something actually useful — you can see not just whether AI mentions you, but how you stack up against the brands you compete with every day.

There are two ways to add competitors:

Auto-Discovery. Hit the "Discover Competitors" button and Goeet uses the OpenAI Responses API with web search to find 3-5 relevant competitors in your category. It searches the current web, so the suggestions are based on real market data rather than a static database. For most brands, this gives you a solid starting set within seconds.

Manual Search. If auto-discovery misses a competitor you care about, use the manual search. Type in a brand name, and Goeet runs an LLM-powered lookup that validates whether the brand exists in your industry. This validation step matters: it prevents you from accidentally comparing a SaaS tool against a shoe brand that happens to share a name. The system checks industry relevance and will tell you if a brand does not belong in your category.

The hard limit across all plans is 7 competitors per brand profile. This is intentional — tracking too many competitors dilutes the comparison and makes the dashboard harder to read. Pick the ones that actually matter: the brands your sales team loses deals to, the ones your customers compare you against, and the market leaders in your category.

Custom Queries & Domain Restrictions

Standard queries cover the broad strokes — "What are the best project management tools?" and similar category-level questions. But you probably have more specific things you want to know. That is what custom queries are for.

A custom query is any question you want to ask the AI models directly. Examples:

• "Which CRM is best for a 20-person sales team in Australia?"
• "What do developers think of [your product] versus [competitor]?"
• "What are the most affordable options for [your category]?"

Custom queries let you test specific angles, phrasings, and scenarios that matter to your business. The results show up in the Query Logs page, not in the main dashboard metrics. This separation is deliberate: custom queries about your own brand would inflate your mention rate (the AI will almost certainly mention you if you ask about yourself by name), so they are kept separate from the standardized benchmarks.

Domain Restrictions let you scope a custom query to specific websites. When you bind domains to a query (e.g., reddit.com and g2.com), the LLM prompt is modified to instruct the model to focus its answer using information from those sites. This is useful for tracking what specific sources say about you, or for testing whether certain high-authority domains influence the AI's recommendation.

Each query can have multiple domain restrictions, and the relationship is OR — the model is asked to consider any of the listed domains. The domain suggestion feature will recommend relevant sites when you start typing based on your industry category.

Scheduling & Data Collection

Once your brand, competitors, and queries are configured, the data collection runs automatically. Here is how it works:

Automatic Daily Schedule. Goeet runs a full collection cycle every day at a set time (configured by the platform). This sends all your standard queries to every enabled AI model, parses the responses, extracts mentions, positions, sentiment, and source citations, and aggregates the results into your daily metrics. You do not need to do anything — the data simply appears on your dashboard each morning.

Manual Collect. If you do not want to wait for the next scheduled run, hit the "Collect" button on your dashboard. This triggers an immediate collection across all your brand profiles. It runs the same pipeline as the automatic schedule — same queries, same models, same parsing. The difference is timing: you choose when it happens.

Free Tier users get two manual collects per day and only ChatGPT and Gemini data. This is enough to see the system in action and understand the basic metrics. Paid plans unlock all five models and remove the daily limit, which matters if you are making changes to your online presence and want to check whether AI recommendations have shifted.

The collection pipeline processes queries in parallel across models, so a full run typically completes within a couple of minutes. You can check the status of an in-progress run from the dashboard — it shows which models have completed and which are still running.

Reading Your Dashboard

With data collection running, your dashboard starts populating. There are four core metrics displayed as trend charts, and understanding what each one tells you is important for making good decisions.

The dashboard also supports time granularity toggling — you can view data by day, week, or month. Daily view shows raw data points for the last 30 days. Weekly and monthly views aggregate the data using averages, which smooths out noise and makes trends easier to spot. For brands that have been tracking for a few months, the monthly view is usually the most useful for identifying whether your GEO strategy is actually moving the needle.

The competitor comparison view puts your metrics side-by-side with your tracked competitors. This is where the real insights live. You might discover that a competitor you assumed was dominant has a lower mention rate than you on three out of five models, or that a smaller competitor has better sentiment scores everywhere. These comparative insights are what inform actual strategy decisions — which models to focus on, which competitors to study, and where the gaps are that you can close.