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            {
                "level": 2,
                "text": "What to track"
            },
            {
                "level": 2,
                "text": "The fixed prompt set"
            },
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                "level": 2,
                "text": "Scoring and reading the trend"
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                "text": "Tools: manual probes vs monitoring suites"
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                "text": "How often to probe"
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        "markdown": "---\ntitle: GEO Search Tracking: How to Monitor AI Search Visibility\ndescription: How to track generative engine optimization: citations, mentions and share of voice, the fixed prompt-set method, the 0-to-3 scale, and the probe cadence.\norganization: Neural Command LLC\ncanonical: https://nrlc.ai/en-us/insights/geo-search-tracking/\n---\n\n← Back to insights\n\nBy Joel Maldonado, Founder & AI Search Researcher, Neural Command LLC · SEO & AI visibility profile\n\nFour numbers, recorded on a schedule. Citations: how many answers link to your pages. Mentions: how many answers name your brand without linking. Share of voice: your mentions against your competitors' on the same prompt set. And position in the cited set: whether the engine reaches for you first, third, or not at all. A mention without a citation is visibility without traffic; a citation without a mention means the engine trusts the page but does not know the brand. You need both columns.\n\nThe method is the same as a visibility audit: write down the questions your buyers actually ask, keep the list fixed, and probe the same engines on the same schedule. A changing question list produces a meaningless trend, because you cannot tell whether you improved or the questions got easier. Ten to thirty questions across two or three engines is enough to start. The list is the instrument; do not swap instruments mid-measurement.\n\nScore each answer from 0 to 3: 0 for absent, 1 for the concept without your name, 2 for your name, 3 for your name with a link. Monthly deltas are the signal --- a 2 that holds for three months is stagnation, a 1 becoming a 2 is traction. Watch for mutation too: the engine naming you but describing you wrong is a content problem, not a distribution problem, and it shows up in the accuracy column before it shows up anywhere else.\n\nManual probing is asking the engines yourself on a fixed schedule and recording the answers --- it costs time and nothing else, and it keeps you close to the data. Monitoring suites automate the queries and give dashboards, and they are worth paying for once the prompt set is stable and you are tracking more questions than a person can run in an hour. Start manual, standardize the list, then automate. Semantic drift --- answers slowly changing meaning while keeping your name --- is the one failure mode dashboards miss and manual reading catches.\n\nMonthly is the floor. Engines ship, competitors publish, and a quarterly probe will tell you what happened last season instead of what is happening now. Weekly is justified while you are actively shipping content, and the probes themselves cost pennies when automated. Neural Command LLC runs this cadence in public --- its audit method documents the scoring, and its Ingestion Trials probe every seed at day 7, day 14 and day 21, publishing the zeros alongside the wins.\n\nWrite ten questions your buyers ask, probe two engines this week, score every answer 0 to 3, and put the results in a spreadsheet with a date column. That is the whole system. The free diagnostic runs the first pass against your host, and the AEO vs GEO breakdown explains what the scores mean for content.\n\n- What it checks and how to score it\n- Quote vs reach, and how to run both\n- How to log citations over time\n- Free first pass against your host\n\n\n---\n\nSource: https://nrlc.ai/en-us/insights/geo-search-tracking/\nPublisher: Neural Command LLC\nLicense: Editorial use with attribution\n"
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