Share of Model (SoM) is the percentage of AI-generated answers that surface your content, brand, or links compared to the total answers returned for a given set of queries. Unlike search engine visibility, which focuses on rankings for individual keywords, SoM tracks how often your business appears as a cited source or recommendation across an AI platform's output.
As AI search platforms grow, monitoring SoM becomes critical. You cannot optimize what you do not measure. This post walks you through tracking SoM across major platforms, identifying which topics drive your visibility, and spotting gaps where competitors are winning.
Why SoM Matters More Than Individual Rankings
Search engine optimization traditionally measures success by keyword ranking (position 1–10). AI platforms do not rank. Instead, they generate answers that cite sources or recommend brands. A single query may pull from 3–8 sources across one answer.
SoM tells you whether your content is in that pool. If your SoM is 15% across 100 tracked queries, your content appears in roughly 15 answers. If your competitor's SoM is 30%, they are cited twice as often. This directly affects traffic, credibility, and customer discovery.
Traditional rankings assume one winner per query. SoM assumes multiple winners per query. The shift changes how you measure success.
Set Up Your Query Tracking List
SoM measurement starts with a defined list of queries. You cannot track "all queries." Instead, pick 50–200 keywords that matter to your business. These should represent your core topics, product categories, and customer problems.
Your query list should include:
- Informational queries (how-to, comparison, definition)
- Commercial queries (product, pricing, reviews)
- Brand queries (your name, competitors' names)
- Long-tail variations (3–5 word phrases your audience searches)
Start with 50 queries if you are new to SoM tracking. Add 25–50 more each quarter as you identify patterns. Avoid queries with zero search volume or purely local intent unless your business is location-specific.
Store your list in a spreadsheet or tracking tool with columns for query, category, search volume, and platform. This structure makes it easy to spot which topics drive the most visibility.
Run Queries Manually Across Platforms
The simplest way to start is manual tracking. Run each query on the major AI platforms and note whether your content, brand, or links appear in the generated answer.
Focus on these platforms first:
- ChatGPT (OpenAI). Free and paid versions; paid users get web search in some regions.
- Perplexity. Cites sources directly in answers; easy to spot your visibility.
- Claude (Anthropic). Web search in Claude.ai; cites sources.
- Google AI Overview (formerly SGE). Appears above organic results in Google Search.
- Microsoft Copilot. Uses Bing and web results; cites sources.
For each query, note:
- Did your domain appear (yes/no)?
- Was your content cited as a source or recommendation?
- Which competitor domains appeared?
- What position was your link (first, middle, end of answer)?
Record results in a table. After running all 50–100 queries across 3–5 platforms, you will see which topics and platforms drive the most visibility for your brand.
Identify Patterns and Gaps
Once you have baseline data, look for patterns. Do you appear in answers for product queries but not how-to queries? Are you cited on Perplexity but missing from ChatGPT? Do competitors dominate specific topics?
Calculate your SoM by category:
- SoM for "how-to" queries: (appearances in how-to answers) / (total how-to queries tracked) = X%
- SoM for "product" queries: (appearances in product answers) / (total product queries tracked) = Y%
- SoM by platform: (appearances on ChatGPT) / (queries tested on ChatGPT) = Z%
Gaps reveal opportunity. If your SoM is 5% for comparison queries but 25% for product reviews, invest in comparative content. If you rank well on Google but have zero SoM on Perplexity, your content may not be discoverable to Perplexity's crawler or may lack the depth/structure the platform prefers.
Optimize Content for AI Visibility
SoM tracking shows you the gap. Content optimization closes it. AI platforms favor content that is direct, well-structured, and cites credible sources.
Adjust your content strategy based on SoM gaps:
- Add direct answers. AI models pull from content that answers questions in the first 1–2 sentences. If your how-to posts bury the answer in the third paragraph, restructure them.
- Use schema markup. Structured data (FAQ, HowTo, Article schema) signals to crawlers and AI systems what your content covers. Platforms may pull from schema fields when generating answers.
- Expand topic depth. If competitors appear in answers and you do not, their content may cover more angles or cite more sources. Add related subtopics, examples, and linked resources.
- Improve crawlability. AI crawlers need to access your content. Check that robots.txt does not block crawlers, pages load fast, and internal links are clear.
Do not optimize solely for AI. Content that works for AI also works for human readers. Clarity, structure, and credibility benefit both.
Track SoM Over Time
SoM is not static. Run your query list quarterly or monthly to spot trends. Set a baseline (month 1), then measure month 2, month 3, etc. Track whether your SoM grows, shrinks, or stays flat.
Create a simple dashboard or spreadsheet with columns for platform, query category, baseline SoM, and current SoM. Calculate month-over-month change. This reveals whether your optimization efforts are working.
A 5–10% SoM increase over three months is realistic. Larger jumps may signal a viral piece of content or a major platform algorithm shift. Declines warrant investigation: Did a competitor publish a stronger resource? Did the platform change its citation preferences?
Use Tools to Automate Tracking
Manual tracking works for 50–100 queries, but scales poorly. Several tools now offer SoM or AI visibility tracking.
Look for tools that:
- Monitor multiple AI platforms (ChatGPT, Perplexity, Claude, Google AI Overview)
- Track your domain and competitors automatically
- Report SoM as a percentage or count
- Show trends over time (weekly, monthly)
- Segment results by query category or topic
Many SEO tools (Semrush, Ahrefs, Moz, SE Ranking) are adding AI visibility modules. Dedicated AEO tools also exist. Evaluate based on your query volume, platform coverage, and budget. Start with a free trial to confirm the tool tracks the platforms you care about most.
Align SoM with Business Goals
SoM is a metric, not an outcome. High SoM does not automatically drive revenue. Align SoM tracking with business goals to make it actionable.
Ask yourself:
- Which query categories drive the most customer intent (product, comparison, how-to)?
- Where do you want to rank in AI answers (top source, cited alongside competitors, or simply present)?
- Which platforms do your customers use (ChatGPT, Perplexity, Google Search)?
If most of your customers use ChatGPT and Perplexity, prioritize those platforms. If your revenue comes from product queries, focus your SoM optimization there first. Do not chase SoM across all platforms and all queries equally.
Reality Check: Limitations of SoM Tracking
SoM is useful, but has limits. AI platforms change frequently. A query may return different answers on different days, different devices, or in different regions. Your SoM for a single query is a snapshot, not a guarantee.
Additionally, appearing in an AI answer does not always drive traffic. Some users read the AI answer and leave without clicking your link. Others click but do not convert. SoM measures visibility, not engagement or revenue. Pair SoM tracking with traffic and conversion metrics from your analytics to understand the real impact.
Finally, AI platforms are still new. Best practices for optimization are evolving. What works today may change as models improve or platforms adjust their citation algorithms. Treat SoM tracking as a starting point, not a final answer.
What to Do Next
Start by picking 50 high-intent queries relevant to your business. Run them manually across ChatGPT, Perplexity, and Google Search (to check AI Overview). Record which of your pages appear. After one month, run the same queries again and compare. If your SoM is low, audit the top-ranking competitors' content and identify gaps you can fill. Consider a free assessment of your AI search visibility to benchmark your starting point and prioritize topics for optimization.
FAQs
How often should I track SoM?
Monthly or quarterly is standard. More frequent tracking (weekly) is useful if you are actively publishing new content or testing optimization changes. Less frequent tracking (annually) works for mature content strategies with stable SoM.
What is a good SoM percentage?
This depends on your market and query set. If you are tracking 50 queries and appear in 10 answers, your SoM is 20%. In competitive markets, 10–20% is realistic. In less competitive niches, 30–50% is achievable. Compare your SoM to your top 3 competitors to gauge relative performance.
Do I need to track all AI platforms?
No. Focus on platforms your audience uses. If your customers primarily use ChatGPT, start there. Add Perplexity and Google AI Overview if they drive traffic. Ignore niche platforms unless your audience uses them.
Can I improve SoM by paying for ads?
No. SoM measures organic visibility in AI-generated answers. Paid ads do not appear in AI answers (yet). Focus on content quality, structure, and crawlability to improve SoM organically.
People Also Ask
How is SoM different from search rankings?
Search rankings measure your position (1–10) for a single keyword. SoM measures how often your content is cited across all answers for a query set. One search ranking is per query; one SoM is an aggregate across many queries and platforms.
What content types perform best in AI answers?
Direct answers, how-to guides, comparisons, and expert resources perform well. AI models favor content that answers questions clearly in the opening sentences, uses structured data, and cites credible sources. Long-form, comprehensive content also ranks well because it covers multiple angles.
Can I see which AI platforms are sending traffic to my site?
Yes. Check your analytics tool (Google Analytics, Hotjar, etc.) for referral traffic from ChatGPT, Perplexity, Bing, and other AI platforms. Look for referrer domains or traffic sources labeled with the platform name. Note that some traffic may be unattributed if the platform does not pass referrer data.
How do I know if a competitor is optimizing for AI?
Run your tracked queries and note which competitors appear most often in AI answers. Then audit their top-performing content for clues: Do they use schema markup? Are their how-to posts structured with clear steps? Do they cite sources? Do they update content frequently? These signals suggest intentional AI optimization.
What is the difference between SoM and answer engine optimization (AEO)?
SoM is a metric (how often you appear). AEO is a practice (optimizing content for AI visibility). SoM measures the outcome of AEO efforts. You use AEO tactics to improve SoM.
Should I optimize for Google AI Overview or ChatGPT first?
Prioritize based on traffic. If most of your organic traffic comes from Google Search, optimize for Google AI Overview first. If your audience uses ChatGPT, start there. Ideally, optimize for both, but allocate resources to the platform that drives the most customer intent for your business.
Can small businesses compete on SoM?
Yes. SoM is less crowded than traditional search rankings. Niche businesses can achieve high SoM by creating deep, authoritative content on specific topics. AI models reward expertise and relevance over domain authority, so a small business with better content can outrank larger competitors in AI answers.
How long does it take to see SoM improvements?
4–12 weeks is typical. AI crawlers index content slower than search engines. After you publish or optimize content, allow 2–4 weeks for crawling, then another 2–8 weeks for the platform to incorporate your content into its answer generation. Monitor SoM monthly to track progress.
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How to Monitor Your Share of Model Across Major AI Platforms
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