Case Study: Hotjar reduces data infrastructure costs 3x with Monte Carlo

How Hotjar Reduced Data Infrastructure Costs by 3x with Monte Carlo

Hotjar, a global product experience insights company, relies on data from tools like Facebook, LinkedIn, Salesforce, and Zuora to support more than 180 stakeholders. But its existing dbt-based testing approach left gaps in alerting for pipeline delays and data downtime, creating a risk of costly overages in systems like Segment.

To close those gaps, Hotjar implemented Monte Carlo for end-to-end data observability, monitoring, and field-level lineage. Monte Carlo alerted the team to an unusual spike in events to Segment just hours after it happened, helping Hotjar investigate and resolve the issue in about 2 hours instead of waiting 8 days for Segment’s own notice, and avoid nearly blowing through 80% of its MTU capacity.

Hotjar

Pablo Recio

Data Engineer