Advanced Matching ⚙️

Advanced Matching is for when random pairing isn’t enough. You build matching rules using constraints (what must always be true) and preferences (what’s nice to have), and CoffeePals pairs people inside those rules — with a fallback policy for anyone left over.

How it works

1. You choose the audiences to draw from — channels, teams, or attribute-defined groups.
2. You add constraints. These are hard rules every pairing must satisfy. Examples: must be from different departments, must share a language, must not have been matched before, must include someone with a specific skill.
3. You add preferences (optional). These are soft rules with priority weighting. Examples: prefer different offices when possible, prefer pairing by shared interest when the data exists.
4. On match day, CoffeePals evaluates every rule and forms groups that satisfy all constraints and score best against your preferences.
5. Unmatched people fall back to your policy — leave them out, add them to an existing group, or form new fallback pairings.

Who it’s for

• Structured mentorship programs where seniority, function, or other attributes must line up
• Cross-functional initiatives needing precise pairings by role, skill, or location
• Programs that need guarantees — like “never match the same two people twice in a row”

What you’ll configure

• Audiences — the source groups participants come from
• Constraints — hard rules like must differ, must match, must be from, or must not rematch
• Preferences — soft rules with priorities that shape pairing when multiple options are valid
• Unmatched policy — leave out, add to existing, or form fallback groups
• Attribute surveys — auto-collect missing data your rules need

Ready to bring this to your team?

Setup takes about five minutes. CoffeePals handles the matching, the messaging, and the follow-up, so you can just watch the conversations happen.