Share of Voice
(SOV) Analysis

Memory Engineering is Team HAI's core philosophy of inscribing brands into AI parameters, and SOV is the key metric that measures those results.

SOV mathematically measures how often and in what contexts AI mentions our brand within a specific market or category. It serves as a report card that validates whether Memory Engineering is working effectively.

SOV analysis doesn't simply count mentions; it uses Vector Triangulation techniques to understand the competitive landscape in three dimensions.

1. Battlefield: Defines the entire AI query domain for the category.

2. Reference: Maps competitors' SOV distribution to calculate market averages.

3. Position: Visualizes in 3D where our brand's SOV stands relative to competitors, identifying which areas are strong and which are weak.

Context Authority scores the nuance and role with which AI mentions our brand.

Rather than simple recall, higher scores are given when cited in positive contexts like 'representative' or 'recommended'. This Context Authority is reflected in SOV score calculation, so even with the same mention frequency, a higher proportion of positive contexts results in a higher SOV.

No need to hire specialists. Team HAI handles complex vector calculations and data analysis internally, presenting results to marketers as intuitive signals (Green/Red) or clear action guides.

Marketers only need marketing sense about what customers are curious about, not complex formulas, to fully leverage the platform.

These brands can actually see more powerful effects than mass-market brands. Team HAI's Gap Visualizer technology specializes in finding Empty Nodes—areas with high purchase conversion rates that competitors miss, rather than competing for crowded main keywords.

By capturing high-value areas with clear purchase intent even with low search volume, you can become the overwhelming #1 authority in your field with minimal budget.