Bigabid Case study

Bigabid uses Granulate to dramatically reduce bid timeouts, latency, and compute costs

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Bigabid is an advertising technology company specializing in mobile user acquisition & re-engagement for gaming, dating and productivity apps.

The company’s automated, real-time optimization tools, focusing on post-install events, harness the power of machine learning to give its top-tier clients an edge in a time-sensitive industry.

We achieved impressive improvements, with no time and effort. Within seconds from installation, Granulate was able to eliminate 90% of bid timeouts. We managed to reduce compute costs by 60%.
Amit Attias, CTO

The Challenge

Bigabid’s AI-driven media buying engine is at the heart of the operation.
To optimize the performance of its high frequency real-time programmatic bidder,
Bigabid needed to reduce latency, dropped requests,
and bid timeouts—without succumbing to a runaway increase in server costs.

The Results

After a short POC on two machines, Bigabid decided to deploy Granulate throughout its network. Within 5 days, Bigabid vastly improved performance, reducing cloud cost by 60%, eliminating 90% of bid timeouts and reducing p95 latency by 70%. The following graph shows the steep drop-off in latency:

Fewer Bid Timeouts
Reduced Cloud cost
Reduced P95 Latency

Bigabid turned to Granulate’s real-time low-level server optimization solution to slash bid timeouts, latency and dropped requests weighing down their quality of service and revenue growth. Using Granulate, Bigabid achieved dramatically improved performance while reducing compute costs by 60%, all within 5 days.