SCALE
성과 측정 및 확장

They are causal metrics that manage the cause, not just the result. AI visibility counts (AI Recall) and rankings (Summary Position) are outcome values beyond our control.

Team HAI manages the causal variables that create these outcomes as core KPIs: strategic coverage (territory size), structural differentiation (distance from competitors), and intent alignment (accuracy). In other words, we improve the causes to inevitably produce the desired results.

Whether they can explain the cause of performance.

• Vanity Metrics: Simple impression counts and clicks. These are just results and don't explain 'why they increased,' making them unhelpful for strategy development.

• Causal Metrics: Coverage (territory size), Differentiation (distinctiveness), Alignment (relevance) provided by Team HAI. These are the causes (X) that produce results, so improving them leads to better outcomes (Y).

To avoid gaming penalties and create sustainable growth. When you rapidly flood content to boost rankings, the vector coordinates shift dramatically, and AI may recognize this as spam or noise and erase it from memory.

Our solution monitors changes in the vector center point over time, sending warning signals when abrupt fluctuations are detected to guide gradual and stable authority building.

An optimization feature that increases performance efficiency as projects progress. Initially, industry average weights are used, but as data accumulates, AI analyzes which variables have the greatest impact on our brand's performance (AI SOV).

For example, it identifies whether improving media structure or content relevance is more effective, giving marketers clear guidance on where to concentrate resources.

It scores the nuance and role when AI mentions our brand.

Rather than just being mentioned (Recall), higher scores (100/80 points) are awarded when cited in positive contexts like 'representative' or 'recommended.' In contrast, being used as a comparison target or negative example receives lower scores.