Historical Metrics Dashboard

The Historical Metrics Dashboard shows how your AI visibility changes over time. It displays trends in brand consistency, share of voice, mentions, citations, and gap opportunities, helping you measure the impact of your optimization efforts.

What You'll Learn

In this guide, you'll learn:

How to interpret each chart on the dashboard
Why AI metrics naturally fluctuate
How to identify real improvements versus normal variation
How to use time range filters effectively

Prerequisites

This dashboard requires data from AI Visibility Reports. Run reports regularly to populate historical data and track trends over time.

Understanding Data Variability

Important: AI output is non-deterministic by nature. Ask an AI assistant the same question twice and you may get different responses. This means your brand might appear in one answer but not the next, even for identical queries.

Because of this uncertainty, charts display data as ranges rather than exact values. The shaded bands around metrics represent typical variability (approximately ±8%). This is normal and expected.

What Counts as Real Change

Trust trends, not single points: One report showing 45% SOV and the next showing 50% doesn't necessarily mean improvement. But three consecutive reports trending upward likely indicates real progress.
Look for sustained movement: A metric that stays outside the confidence band for three or more consecutive reports probably represents genuine change.
Consider context: If metrics improve right after publishing major content, that's likely causal. Random improvements with no changes are probably just variation.

It's not uncommon to see small decreases in reports run close together. The goal is to capture statistically significant improvements over time, not to react to every fluctuation.

Charts Explained

Brand Consistency Over Time

This chart shows your consistency score (0-100) across all AI platforms. Brand consistency measures how reliably your brand appears when AI platforms answer questions in your space.

What to look for:

Upward trend: Your optimization efforts are working
Flat trend: You're maintaining position but not improving
Downward trend: Either you're slipping or competitors are improving faster
Large jumps: Often indicate new content or authority signals taking effect

The shaded band shows typical variation. Small changes within this band should be interpreted directionally, not as definitive improvements.

This dual-axis chart shows your Share of Voice percentage (left axis) and total mention count (right axis).

Share of Voice is your primary competitive metric. It shows the percentage of AI responses where your brand appears compared to all opportunities.

Mentions provide context for your SOV percentage:

Rising SOV with flat mentions means you're holding steady while competitors decline
Flat SOV with rising mentions means everyone's improving together
Rising both indicates you're genuinely growing visibility

Citations Over Time

Citations indicate how often AI platforms reference your domain as a source. This is a strong signal of authority and trustworthiness.

Citation patterns to understand:

Steady growth indicates building authority
Sudden spikes often follow publication of data-rich content
Citations often preceed mentions (you get cited first, and mentions are drawn from them)

Grounding Search Gap Trends

This chart tracks two metrics:

Gap count (area): Total searches where competitors rank but you don't
Average competitor rank (line): How well competitors are positioning

Interpreting gap trends:

Declining gaps: You're successfully closing visibility opportunities
Rising gaps: Competitors are finding new ranking opportunities
Improving competitor ranks: The competitive bar is rising
Declining competitor ranks: Optimization opportunities competitors haven't found