# Peer Benchmarking

*AI Data & Analytics Team*

How you stack up against the cohort that matters

Your AI analytics team builds peer cohorts on your own definition — same size, same vertical, same stage, same geography — and benchmarks every KPI you care about against the group.,Sources blend public data, industry surveys, and authorized peer-network exchanges so the numbers reflect reality, not vendor marketing.,Output is a quarterly benchmark book: where you lead, where you lag, what the median looks like, what changed.

## Benefits

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## How It Works

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## At a Glance

- **Custom** Peer cohort definition
- **Quarterly** Refresh cadence default
- **20+** KPIs benchmarked per book
- **3+** Source types triangulated

## Beat The Vendor-Marketing Median

## FAQ

### How are private-company KPIs sourced?

Industry surveys, peer-network exchanges (anonymized), authorized estimates, and triangulation from public proxies.

### Can we contribute our data to the network?

Optional. Contributors get access to higher-resolution peer data in exchange.

### What confidence do we have in the numbers?

Every KPI carries a confidence band. Thin-data benchmarks shown with explicit caveats.

### Can it integrate with our board reporting?

Yes — benchmark slides drop straight into your board deck template.