Learn what meta-measures (ingredients) are, how they power AI personalization, and their complete lifecycle from creation to evaluation. Essential guide for workspace setup and optimization.
Meta-measures are criteria you define that your AI learns to recognize in your contacts. They're not just lists—they're patterns your AI finds by analyzing:
Each meta-measure is scored for every contact on a scale of 0–100. A score of 85 means the contact matches that ingredient very well. A score of 15 means they don't match it much.
For each ingredient, your AI tracks three signals:
1. Current Coverage — How often this ingredient appears in your contacts right now.
How many of your existing high-quality leads match this pattern? If only 5% of your best customers are "VP of Sales at SaaS companies," the AI marks that ingredient as low-coverage.
2. Content Power — How strongly this ingredient predicts quality.
When you write a message about a specific topic, does it resonate more with people who match this ingredient? If outreach mentioning "product ROI" converts better among finance-focused personas, that's high content power.
3. Audience Match — How well contacts align with this ingredient profile.
When the AI scans your contact list, how distinctly does this ingredient separate your best opportunities from the rest? If almost everyone is "interested in industry trends," that ingredient is low-value for targeting.
These three signals combine to determine each ingredient's overall strength and usefulness.