Overview

This is also where you land when you open a project.

Overview#

Overview is the summary layer, and it exists to answer one question in about ten seconds: has anything changed since the last time I looked?

It is deliberately not a place to do work. Every number here appears in fuller form on the screen that owns it, and the habit worth forming early is treating this page as a reason to open one of those screens rather than as an answer in its own right.

Panels and controls#

The KPI row across the top is four cards.

The KPI row

Card	The question it answers
GEO Score	How discoverable are we to AI engines, overall?
AI Discovery Reach	How often do we actually surface?
New Brand Citations	What started citing us since last run?
Brand Sentiment	How are we being described?

Below the row, LLM Performance Index breaks performance out per engine, with a Visibility Index and a Sentiment Score for each, which is where a healthy average hiding one weak engine becomes visible. Top Citations ranks the sources shaping your answers by Influence Strength, and Competitors shows your tracked competitors ranked by Share of voice. A trends panel tracks direction, and two widgets surface work waiting for a decision: Suggested content from the Content Scout and Brand reputation actions from the sentiment side.

While a project is still building, Overview shows the build card instead of partial numbers. That is intentional rather than a limitation: half-populated figures invite conclusions the data cannot yet support. See Getting started.

Reading the GEO Score#

The headline number is the GEO Score, an overall measure of how discoverable your brand is to AI engines on a 0 to 100 scale. Three things feed it, and the card's own tooltip names them: AI Discovery Reach, meaning how often AI engines surface your brand; Readiness, meaning how well your site is set up for AI engines to crawl and understand, taken from your page audit; and Brand Sentiment, meaning how positively AI engines describe you.

Discovery reach is the biggest contributor, which has a practical consequence the tooltip also states: the GEO Score and the AI Discovery Reach card usually move together. When they part company, the mover is one of the smaller ingredients, and that is worth noticing because the response differs. A score dragged down by readiness is fixed on your own site through Smart Audit; one dragged down by sentiment is worked through Sentiment and its aspects; low reach itself is the longer game of topics, prompts and gaps.

The score renders green from 80 up, amber through the broad middle, and red below 20, so the colour is a coarse verdict at a glance. Treat the bands loosely: the number is comparable against your own history, not against other companies, and the change badge beside it is measured against your previous completed run, so a quiet badge after a week of work usually means the next run has not happened yet rather than that the work did nothing.

AI Discovery Reach deserves its own sentence, because its definition is precise: the share of prompt runs in your latest completed run where an AI engine mentioned your brand, where a run is a single prompt on a single engine and every successful run counts toward the total whether you appeared or not. It tracks how often you surface, not where you rank, so you can place well in the answers you do appear in and still have low reach. Rank is Discovery Rank's job.

Interpreting results#

Read direction rather than value. A reach of 34% tells you very little by itself, because there is no universal number that counts as good and no benchmark that survives being applied across categories. The same card rising steadily across runs tells you something real, which is that whatever you have been doing is landing.

Treat a single run's movement as noise until proven otherwise. AI answers vary between runs for reasons that have nothing to do with you, which Reading trends covers properly. If something moved sharply since yesterday, ordinary variation is the more likely explanation, and it is worth ruling out before anybody sends an alarmed message.

Let the outlier decide your next click. If one engine's row in the LLM Performance Index is out of line with the rest, or one card moved while three held still, that is where the next hour goes, and the rest can wait until it does not.

Best practices#

• A page you can skim in under a minute and correctly conclude that nothing needs you today.
• Movement concentrated where you have actually been working, which is about as close to attribution as a dashboard can get you at a glance.
• The GEO Score and reach moving together. When they split, you have a readiness or sentiment story worth reading before it grows.

Next steps#

Where you go from here depends on why you opened it:

1. The score moved and you want to know why. Check which ingredient moved with it: reach points at Visibility and Gap analysis, readiness at Smart Audit, sentiment at Sentiment.
2. You want work to do. Skip Overview altogether and go to Gap analysis, which is the screen that produces tasks rather than readings.
3. You are checking whether last month's work paid off. Go to Tracked actions and read the movement against what you actually did, rather than trying to reconstruct it from memory.
4. You are reporting to somebody else. Use Brand reports rather than screenshotting cards, since a report covers a defined period and states its own basis, which a screenshot cannot.

Limitations#

Overview summarises, and that is all it does. Every number here appears in more useful form on the screen it came from, and no decision should be made from a card alone.

The GEO Score is Seerly's own composite. It is built for comparison against your own history, and there is no industry table of GEO Scores to rank yourself in.

It covers the engines your plan tracks and the prompts you have configured, in common with everything else in the product. See seerly.app/pricing.