Embedded analytics costs stem from data warehouse compute, storage, and analytics service licensing.

To control costs, monitor query patterns and implement caching, limit high‑cardinality filters, and schedule heavy queries during off‑peak hours.

Vendors offer various pricing models: per user (seat), per metric or usage‑based (query volume).

Usage‑based pricing aligns costs with value but requires forecasting; seat-based pricing is predictable but can discourage broad adoption.

Evaluate your customer base and usage patterns to choose the right model.

MageMetrics currently offers flat‑rate plans and is rolling out volume‑ and seat‑based pricing; its usage analytics and guardrails help customers forecast spend and prevent surprises.