Analytics

Marketing is an industry of metrics. We live and die by CPC, CTR, CPA, and ROAS. We have spent twenty years building dashboards that track the user journey from the first impression to the final conversion.

But today, there is a leak in your dashboard. A massive, invisible leak.

Millions of potential customer journeys are starting - and ending - without ever generating a "session" on your website. They are happening inside the chat interfaces of AI models.

If you are ClickUp or Wrike in this scenario, you didn't just lose a click. You lost the consideration set entirely. And because this interaction happened inside a proprietary AI "Black Box," your analytics software reports it as... nothing. Just a decline in direct traffic that you can't explain.

To survive in this environment, we need to retire our obsession with "Rank" and "Traffic" and embrace a new, more difficult metric: AI Share of Voice (SOV).

The Death of the "Blue Link" Metric

In traditional SEO, "Rank" was a proxy for visibility. If you were Rank #1, we assumed you got ~30% of the clicks. If you were Rank #5, you got ~5%. It was a deterministic curve.

In the Agentic Web, this curve is broken.

• The "Winner Take All" Effect: AI models act as synthesizers. They don't want to overwhelm the user with 10 options. They want to provide the best answer. This means they often only mention 1, 2, or 3 brands. Being #4 is mathematically equivalent to being #100.
• Zero-Click Consumption: Gartner predicts that by 2026, search engine volume will drop by 25% due to AI chatbots. This doesn't mean people are searching less; it means they are clicking less. The value is being consumed on the platform.

Therefore, the new KPI for Brand Awareness is AI Visibility.

Defining AI Share of Voice (SOV)

In traditional media, Share of Voice measured your brand’s presence compared to competitors in print or TV. In digital, it meant search impression share.

In the AI era, AI Share of Voice is calculated based on three vectors:

1. Frequency: In a sample set of 1,000 relevant user prompts (e.g., "Best marketing tools," "Marketing software reviews," "Tools for CMOs"), how many times is your brand mentioned?
2. Primacy: When mentioned, where do you appear? Being the first noun in the sentence ("I recommend Aseon...") carries significantly more weight than being in a bulleted list at the bottom.
3. Exclusivity: Are you the only recommendation, or are you listed alongside ten competitors?

The Aseon Visibility Score

At Aseon, we synthesize these vectors into a single Visibility Score.

• 0%: You are invisible to the AI.
• 100%: You are the primary recommendation for every relevant prompt.

This metric allows you to benchmark your performance not against "Google's Algorithm," but against your actual competitors. If your competitor has a 60% visibility for "Enterprise Security" and you have 10%, you know exactly where you are losing market share.

The 3 Dimensions of AI Reputation

Measuring if you are mentioned is only step one. You must also measure how you are mentioned. Aseon breaks this down into three qualitative dimensions.

1. The Sentiment Dimension (The "Vibe Check")

It is possible to have high visibility and negative impact.

Scenario: The AI mentions you in every answer, but says: "Brand X is a legacy provider that is often criticized for high prices and outdated UI."

Result: You are "winning" Share of Voice, but losing customers.

Aseon Solution: Our Sentiment Analysis engine uses Natural Language Processing (NLP) to read the emotional tone of the citation. We flag negative or neutral mentions so you can address the root cause - usually by identifying the negative source data (e.g., a specific Reddit thread or G2 review) that is poisoning the well.

2. The Accuracy Dimension (The "Fact Check")

AI hallucinations are a brand risk.

Scenario: You launched a new "AI Feature" six months ago. But the AI is relying on training data from 2023. It describes your product as "a basic tool without AI capabilities."

Result: You are losing customers who want AI features, simply because the bot has outdated facts.

Aseon Solution: We track the Context Accuracy of mentions. If the AI is hallucinating features you don't have, or ignoring features you do have, you need to launch a targeted content campaign (GEO) to update the record in the sources the AI trusts (like Wikipedia, Wikidata, or press releases).

3. The Comparative Dimension (The "Rivalry")

Who does the AI think your competitors are?

Scenario: You think your competitor is Salesforce. But in the AI's "semantic map," your competitor is actually a small, niche player that has optimized their data better than you.

Result: Strategic Blindness. You are fighting the wrong war.

Aseon Solution: Our Competitor Analysis reveals the specific entities the AI associates with your brand. This "Semantic Neighborhood" analysis is crucial for positioning.

How to Report AI Metrics to the C-Suite

Your CMO doesn't care about "vectors." They care about growth. Here is how to frame AI Visibility for the boardroom:

• The "Pre-Purchase" Metric: Frame AI as the new "Digital Word of Mouth." Before a buyer visits the site, they ask ChatGPT. "If we aren't in that answer, we aren't even in the funnel."
• The "Reputation Defense" Metric: "We need to monitor AI to ensure our brand reputation isn't being damaged by hallucinations or outdated pricing data."
• The "Market Share" Metric: "Aseon identified that we are missing from the 'Enterprise' conversation in Gemini, while [Competitor] is dominating it. This is a clear opportunity for conquesting."