Inside an Otterly.ai GEO Report: How to Read the Numbers That Matter

‍TL;DR: An Otterly.ai GEO report contains four numbers worth reading in a specific order: citation rate tells you how often you show up at all, share of voice tells you how that compares to named competitors on the same prompts, source-level breakdown tells you which specific pages are earning the citations, and sentiment tells you whether what gets said about you is actually favorable. Reading citation rate alone and stopping there is the most common way teams misread this data, because a rising citation rate with falling share of voice usually means the whole category is growing, not that you're winning it.

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A GEO report from Otterly.ai, or any comparable measurement tool, presents a lot of numbers at once, and most people scan for the single headline figure: how often did we get cited. That number matters, but reading it in isolation misses most of what the report is actually capable of telling you.

Why the report has four numbers, not one

Citation rate answers a narrow question: are you showing up. It doesn't answer whether you're winning relative to competitors, which specific content is doing the work, or whether the visibility you're getting is actually good for the brand. Each of the four core numbers in a GEO report answers a different one of these questions, and reading only the first one is the equivalent of judging a company's financial health from revenue alone, without ever checking margin, cash position, or debt.

The four numbers, in the order they should be read

Why citation rate needs share of voice to mean anything

A citation rate that climbed from 8% to 14% over a quarter looks like clear progress until it's checked against what competitors did over the same period. If the whole category's citation activity grew because more companies started publishing GEO-optimized content, a rise from 8% to 14% might still represent a falling share of voice if competitors grew from 5% to 20% over the same window. purple path's breakdown of what a full GEO visibility audit measures covers this exact relationship between the two numbers in more depth; reading an Otterly.ai report through that same four-part lens is what turns a single dashboard export into an actual strategic read.

Why the source-level breakdown is the section most reports skim past

The source-level breakdown, showing which specific URLs are getting pulled into cited answers, is usually the most detailed and least glamorous section of a GEO report, and it's the one that most directly tells you what to do next. A team that only checks the top-line citation rate has no way of knowing whether its citations are coming from one strong evergreen guide or spread thin and unpredictably across a dozen weaker pages. That distinction matters enormously for what gets published next: doubling down on the format and structure of the one piece that's actually earning citations is a much clearer strategy than guessing at what to write based on the aggregate number alone.

Why sentiment is the section most likely to contain a real surprise

Sentiment analysis inside a GEO report checks whether the content of a citation is actually favorable, neutral, or unfavorable, and whether it's accurate. This is the section most likely to surprise a team that's been celebrating a rising citation count, because a citation isn't automatically good news. An engine citing an outdated price point, a discontinued feature, or a mischaracterized positioning statement is a citation working against the business, and it shows up as a positive number in the citation rate column while being a genuine problem in the sentiment column. Reading citation rate without checking sentiment can mean celebrating exactly the wrong trend.

How to read a monthly report in the right order without getting overwhelmed

A practical reading order: check citation rate first for a general pulse, then immediately check share of voice against the two or three most relevant named competitors to put that pulse in context, then scan the source-level breakdown for which specific pages are driving any change, and finally review sentiment for anything flagged as negative or inaccurate that needs a direct fix. This order takes roughly the same amount of time as scanning the whole report unsystematically, but it produces a genuinely different, more actionable read.

Why a single month's report should never be read in isolation

Any individual month's numbers are a snapshot, and GEO visibility moves for reasons that aren't always about your own content: model updates, competitor publishing activity, and the natural aging of previously-cited pages all shift the numbers independent of anything you did that specific month. purple path's analysis of why LLM visibility decays over time covers these mechanisms directly; a single Otterly.ai report is most useful when compared against the prior period's numbers, not read as a standalone verdict on how the month went.

Turning the report into a decision, not just a status update

The point of reading all four numbers together is to arrive at a specific action, not just an updated understanding. A falling share of voice despite a rising citation rate is a signal to check what competitors are publishing that's outperforming your content on shared topics. A concentrated source-level breakdown, with most citations tracing back to one or two pages, is a signal to build more content in that same format and depth rather than spreading effort thin across many shorter pieces. A negative sentiment flag is a signal to update or correct the specific page in question immediately, since it's actively working against the brand every day it goes unaddressed. Each of the four numbers points toward a different, specific next step, which is the actual value of reading the full report rather than the headline figure alone.

Why comparing month over month matters more than any single month's absolute value

Beyond reading the four numbers in the right order within a single report, the more valuable habit is tracking each number's trend across consecutive months rather than reacting to any single period's absolute value. A citation rate of 12% means very little on its own; a citation rate that moved from 8% to 12% over three consecutive months, while share of voice held steady against named competitors, tells a clear and specific story about genuine progress. Building a simple running log of these four numbers month over month, rather than treating each report as a standalone document, turns the exercise from a monthly status check into an actual longitudinal record worth referencing when planning future content investment.

Why it's worth sharing this reading framework beyond the marketing team

A GEO report often only reaches the marketing team, which means the nuance behind the four numbers rarely makes it into a board update or a broader company conversation about go-to-market performance. Sharing a simplified version of this same four-part framework with sales leadership or the executive team, even briefly, helps set realistic expectations about what a rising or falling citation number actually means, rather than letting a single headline figure get over-interpreted by someone who wasn't part of building or reading the full report themselves.

Frequently Asked Questions

How often should an Otterly.ai report actually be reviewed in this level of detail?

Monthly is a reasonable cadence for the full four-number review described here, with lighter, faster checks of citation rate alone in between if the content library and competitive landscape are especially active.

What's a healthy share of voice for a company just starting to invest in GEO?

There's no universal healthy number, since it depends heavily on how competitive the specific category is and how many competitors are actively investing in GEO themselves. The more useful practice is tracking your own share of voice trend over time relative to the same named competitors, rather than comparing against an external benchmark.

Can the source-level breakdown reveal problems with older content specifically?

Yes, and this is one of its most useful functions: a page that used to earn citations and has stopped appearing in the source-level breakdown is a direct signal that specific page has gone stale or been displaced, which is more actionable than a general drop in the overall citation rate.

Is a negative sentiment flag always something to correct on the page itself?

Usually, yes, if the negative sentiment stems from outdated or inaccurate information on your own page. If the negative sentiment stems from a third-party source being cited alongside your brand, the fix is different and may require more targeted outreach or content specifically addressing that third-party narrative.

Does this four-number framework apply to GEO tools other than Otterly.ai?

Yes, the underlying logic, citation rate, comparative share of voice, source-level attribution, and sentiment, applies broadly across GEO measurement tools, even if the specific report layout or terminology varies between providers.

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Reading your next GEO report with this four-number framework turns a dashboard export into an actual set of decisions. Talk to purple path about interpreting your own GEO data through its Otterly.ai partnership.