Deep Monitoring and Business Observability Innovator, oolo AI, Announces Launch of Automated A/B Test Monitoring

oolo’s automated A/B test monitoring puts another powerful tool in the publisher arsenal — helping them reach conclusions quicker and more accurately.

oolo AI, the force behind push-button Business Observability offering, has announced the extension of their Deep Monitoring to A/B tests. The firm offers smart, AI-powered alerting and analytics designed specifically for digital publishers and advertisers.

Combining machine learning with industry expertise, oolo inspects monetization and UA data for any unusual developments. The system processes massive amounts of information to assess not just whether anomalies are statistically significant but to what extent they will impact the business. Understanding the relationships shared between all the different data factors and the underlying business allows oolo to trace each anomaly to its root cause. It also allows for follow up to be prioritized based on impact and the available levers of control.

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“oolo helps A/B testers arrive at conclusions quicker and with a precise understanding of the potential impact.”

— Yuval Brener

Commenting on the launch of A/B test monitoring, oolo Co-Founder and CEO Yuval Brenner offered some perspective. “Trial and error is the oldest and most trusted tool that humans have for improving and perfecting our various undertakings. A/B testing is how businesses approach trial and error in a scientific way. But in practice, there’s still a lot of eyeball-based assessment and imprecision. This is what we’re changing. oolo helps A/B testers arrive at conclusions quicker, with greater convenience and confidence, and with a precise understanding of the potential impact.”

oolo’s offering is specifically geared to monetization and growth teams from the digital publishing industry — a $333B market spread across websites and applications. Digital publishers derive much of their revenue by selling ad space on their digital properties. Most of these transactions are brokered programmatically through ad networks and devoted servers. To match ad buyers to sellers, each side defines a large number of requirements and limitations. The real-time auction interactions that result from these definitions determine when what ad is placed where. This together with technological dependencies and constraints creates a long and complex value chain that publishers use to pull in revenue.

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A break or mis-calibration at any point along that chain results in lost revenue. oolo uses AI and context-aware relationship mapping to help publishers monitor, maintain, and maximize that value chain. In an effort to get as much value as possible out of their operations, publishers continuously run experiments in the form of A/B tests.

oolo’s automated A/B test monitoring puts another powerful tool in the publisher arsenal — helping them reach conclusions quicker and more accurately. The system’s automated analysis is able to identify statistically significant and business-impacting differences between the A group and B group, even when results appear comparable to the naked-eye.

Concluded Yuval Brener, “In this market, where supply and demand is constantly fluctuating and there are so many interrelated factors at play, our tailor-made A/B test monitoring helps publishers easily review and assess their experiments and keep the iterative process moving at full speed. It’s just another way that Deep Monitoring empowers publishers to better optimize their ad placements, improve efficiencies, and grow revenue.”

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