oolo AI provides integrated anomaly detection and business intelligence for both sides of the ad market — for the advertisers who buy ads and the publishers who sell the ad space.
While much of the world is mesmerized by the promise of general artificial intelligence, oolo is making huge strides in the other direction — specialized artificial intelligence. That’s not because the company is contrarian, but because they understand that specialized artificial intelligence holds far greater business value.
It’s their focus on the ad market (at least for now) that allows oolo to integrate business intelligence into their anomaly detection. By mapping data expressions to business situations, oolo is able to translate statistical observations into real operational insights. Whereas most anomaly detection solutions are academic tools — requiring devoted data science and operations personnel to filter out the noise and translate outputs into appreciable business problems/opportunities — oolo is able to bake that context-aware expert analysis directly into their alerts; helping users follow-up in an immediate and straightforward manner.
oolo also stands out for its innovative approach to the task of detecting anomalies. Instead of simply establishing a baseline for each data permutation and running deviation analyses on live results, oolo uses machine learning to model normal performance and predict exact values for every permutation. Comparing live results to those predictions, oolo can identify anomalies with superior accuracy.
That superior detection is further enhanced by the fact that oolo’s core understanding and predictive models are always learning — improving with each newly ingested data point. Plus, customers can benefit from the revenue and growth forecasts that come built-into the product. Forecasts that are remarkably accurate — spotting problems on the horizon 9 days before comparable Google predictions and with 30% greater reliability, on average.
It’s those capabilities that have quickly made oolo an essential part of the daily routine for its users across UA, Monetization, Marketing, Planning, and AdOps teams. It’s also what helps the typical oolo user achieve such remarkable results:
- 1 hour 36 minutes saved daily (per user)
- 50% faster MTTR (Mean Time to Response)
- 29% increase in ARPU (Average Revenue Per User)
- 6% ad revenue uplift
But oolo’s boldness is not limited to its technological philosophy, its capabilities, or even to its transformative business impact. It is rooted in its fundamental mission.
Why should people spend their days wading through a sea of numbers searching for undefined points of interest? oolo is makes it so they don’t have to. oolo puts forth the argument, loudly and boldly, that in 2023 manual data review no longer makes sense. And the same goes for rigid and context-oblivious rule-based alerting systems.
Using people for mechanical data review at impossible scales is a waste of their talents; particularly when there’s technology that can do the job better — without the human error and the 9-5 time constraints.
In this way, oolo is fundamentally changing how employees and employers alike relate to office work. As Igor Bereslavski, Director of Growth at Supersonic explains, “oolo eliminates manual monitoring and allows us to focus on strategy instead of firefighting.”
A power tools in the hands of users, oolo spares office workers from soul-sucking data tasks, while optimizing their time, and maximizing their impact — amplifying existing capabilities and creating the breathing room needed to invest in more strategic and interesting work.
