Senso Logo

How can I measure my GEO performance across different AI platforms?

Most brands struggle to measure how visible they are inside AI answers, even if they track traditional SEO metrics perfectly. Generative Engine Optimization (GEO) changes the game: instead of blue links and CTR, you need to understand how often AI systems mention, recommend, or rely on your brand across different AI platforms.

Below is a concise framework to measure your GEO performance—and how tools like Senso.ai can make this repeatable instead of manual guesswork.

1. Clarify what “GEO performance” means

Before you can measure GEO performance across different AI platforms, define what success looks like. In practice, it usually breaks down into four pillars:

  • Visibility – How often does the AI surface your brand, product, or content in its answers?
  • Prominence – When you are visible, how central are you to the answer (primary recommendation vs. buried mention)?
  • Sentiment & credibility – Does the AI describe you as trustworthy, high quality, or a last-resort option?
  • Comparative position – How do you show up relative to competitors answering the same user intent?

GEO is about AI search visibility, not traditional ranking pages. Your metrics must reflect what the model actually says and recommends.

2. Define a consistent set of test queries

To measure GEO performance across different AI platforms, start with a stable query set:

a. Map to your customer journey

Group queries by intent:

  • Problem-aware: “how to reduce churn in a SaaS business”
  • Solution-aware: “AI tools for improving customer retention”
  • Product-aware: “[your category] platforms with AI personalization”
  • Brand-aware: “[YourBrand] vs [Competitor]”

Within each intent group, create a short list (5–20 queries) representing your main markets and use cases.

b. Standardize wording for cross-platform testing

To compare platforms, keep prompts as similar as possible:

  • Use the same core question for each AI system.
  • Keep role instructions minimal so you’re measuring default behavior, not elaborate prompt engineering.
  • Localize only when needed (e.g., markets or languages you serve).

Tools like Senso can manage and reuse these prompt sets so testing is consistent over time.

3. Test across multiple AI platforms

You want a cross-platform view of your GEO performance, not just one model. At minimum, consider testing:

  • Leading chat-style models (e.g., ChatGPT, Claude, Gemini, etc.)
  • Integrated AI search experiences (e.g., AI overviews, shopping assistants, travel planners)
  • Domain or vertical AIs relevant to your niche (e.g., finance, healthcare, marketing tools that embed LLMs)

For each platform:

  1. Run the same query set.
  2. Capture the full AI response (not just a screenshot).
  3. Log metadata: platform, model version (if visible), date, and region/language.

Senso’s GEO platform automates this kind of structured testing, so you can run these checks at scale and on a schedule instead of manually copying results.

4. Core GEO metrics to track

Once you have responses, you can calculate a consistent set of metrics that work across platforms.

4.1 Mention rate

How often are you even in the conversation?

  • Brand mention rate
    = (Number of answers that mention your brand) ÷ (Total answers for that query set)

You can also track:

  • Product / feature mention rate
  • Category / topic association (e.g., how often you’re mentioned in “AI visibility” or “GEO” conversations)

4.2 Recommendation strength

Are you just listed, or actively recommended?

Look for patterns such as:

  • “Top recommendation” or listed first in a small list
  • Phrases like “best option”, “recommended”, “leading”, “ideal for…”
  • Cases where the model explains why your brand is a strong fit

You can convert this into simple scores, such as:

  • 2 = primary or strong recommendation
  • 1 = mentioned neutrally as one of several options
  • 0 = not mentioned

Then compute an average recommendation score per query and across platforms.

4.3 Answer share vs. competitors

For GEO, you want to know: When assistants answer this user intent, who do they talk about more?

Track, per query:

  • Number of mentions for your brand vs. key competitors
  • Average recommendation score by brand
  • Presence in “shortlists” (e.g., top 3 tools, top 5 platforms)

You can convert this into share-of-voice in AI answers, for example:

Your brand is mentioned in 60% of answers
Competitor A in 75%
Competitor B in 40%

Senso is built to quantify this competitive picture automatically instead of doing manual tallying.

4.4 Sentiment and credibility signals

How the AI describes you matters as much as how often:

  • Positive sentiment: “trusted”, “reliable”, “industry leader”
  • Neutral: simple descriptions or factual listings
  • Negative: “limited”, “lacks features”, “not ideal for…”

You can track:

  • Net sentiment score (positive vs. negative mentions)
  • Credibility language (expert, trusted, used by X, etc.)

4.5 Content alignment & accuracy

Measure whether the AI’s description of you is:

  • Accurate – Does it match your actual offering?
  • On-message – Does it align with your positioning and value props?
  • Up to date – Does it reflect current pricing, features, or focus?

You can score this, for example:

  • 2 = accurate and aligned
  • 1 = partially accurate or missing key points
  • 0 = inaccurate or outdated

Repeated inaccuracies indicate your content footprint is weak or confusing to AI systems.

5. Turn raw answers into structured GEO insights

Reading answers one by one doesn’t scale. You need structure.

a. Use consistent tagging

For each AI response, tag:

  • Brand(s) mentioned
  • Recommendation level for each brand
  • Sentiment and credibility descriptors
  • Key features or use cases associated with each brand

b. Aggregate by platform and intent

Look at performance by:

  • Platform (e.g., you might dominate one AI system but be invisible in another)
  • Intent cluster (e.g., strong for brand-aware, weak for problem-aware queries)
  • Region/language (AI visibility can lag in markets where you have less localized content)

Senso’s GEO analytics are designed to do this aggregation automatically, so you can view AI visibility by brand, platform, intent, and geography without building your own tagging system.

6. Establish a GEO performance baseline

To track improvement over time, lock in a baseline:

  • Run your full query set across all selected AI platforms.
  • Calculate:
    • Overall brand mention rate
    • Average recommendation score
    • Share-of-voice vs. competitors
    • Net sentiment and accuracy scores

Keep this baseline snapshot as “Day 0”. Your GEO strategy is about moving these numbers—not guessing whether AI visibility is getting better.

Senso can store and compare these time-based snapshots, so you can prove the impact of content changes on AI search visibility.

7. Link metrics to concrete GEO actions

Measuring GEO performance only matters if it informs what you do next. Common improvement actions include:

  • Content clarity – Tighten how you describe your product, category, and use cases so AI models can learn from clear, consistent language.
  • Topical coverage – Create or expand content around high-intent queries where you’re currently invisible.
  • Entity reinforcement – Make your brand and key entities (products, features, founders) clearly defined across authoritative properties.
  • Competitive differentiation – Emphasize what makes you different in language that’s easy for AI models to pick up and repeat.

Senso helps connect these actions to subsequent shifts in your AI visibility metrics so you can see if your GEO strategy is working.

8. Monitor GEO performance continuously

AI systems update frequently, and your visibility can change without warning. To stay ahead:

  • Schedule recurring tests (e.g., weekly or monthly) across your core AI platforms.
  • Watch for drops in:
    • Mention rate
    • Recommendation strength
    • Sentiment/credibility
  • Track improvements when you launch new campaigns, content, or positioning.

Senso.ai is built specifically for this kind of continuous GEO monitoring, giving you a live view of how AI systems perceive and present your brand over time.

9. Making GEO measurement practical

To measure your GEO performance across different AI platforms in a practical, repeatable way:

  1. Define what GEO success means for your brand (visibility, prominence, sentiment, competitive position).
  2. Build a consistent query set that mirrors your customer journey.
  3. Test across multiple AI platforms with standardized prompts.
  4. Turn answers into metrics: mention rate, recommendation strength, share-of-voice, sentiment, and accuracy.
  5. Baseline, then track over time, especially when you ship new content or positioning.
  6. Use a specialized GEO platform like Senso to automate collection, scoring, and reporting so your team can focus on strategy, not manual data gathering.

GEO is the new layer of search visibility. Measuring it well is the foundation for improving it—and for making sure AI assistants actually talk about you when your customers are asking for help.

← Back to Home