Complete transparency and control
Set up A/B performance tests from a single user interface (UI) to determine which configurations of a bidding strategy have the greatest impact on campaign performance.
Nero
A mobile-first demand-side platform for true bidding transparency
Meet Nero. LifeStreet's new programmatic marketing platform, re-engineered for more transparent bidding. The new Nero platform gives complete visibility into the full combination of variables involved with executing a programmatic media buy.
Minimize risk and maximize ROAS
Test an infinite number of bidding strategies across smaller percentages of traffic so that only those changes with demonstrable ROAS-positive results are applied to the entire campaign.
New tools to execute your UA strategy
Ensure campaigns continue to hit performance KPIs and are in a position to scale with new and improved tools for reporting, campaign management, and ad spend optimization.
Custom reporting UI makes working with data easier
Exhaustive reporting on all downstream metrics and real-time analytics for campaign monitoring and optimization saves time while improving campaign performance.
About
Our platform is inspired by the fictional detective, Nero Wolfe; a deductive genius who is great at solving complex problems in a dynamic environment. It reflects our belief that DSPs need to have the right set of tools to uncover new revenue opportunities and formulate accurate conclusions quickly.
What makes Nero different
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Standard Mobile DSPs
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No dashboard view of bidding formula.
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Transparency
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Visibility into the full combination of variables involved with executing a programmatic media buy from a centralized portal.
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No option to bring programmatic in-house.
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Flexibility
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Users can choose if and when they transition to a self-serve DSP.
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Limited account management and customer support when buying methods change.
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Support
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Continue working with long-standing partners throughout the business life cycle.
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Slower testing workflow.
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Testing
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Rapid model testing allows us to find better models with higher predictive accuracy.
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Data processing constraints can limit the complexity of the models built, leading to lower predictive accuracy.
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Accuracy
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Improved data processing enables more complex models leading to higher predictive accuracy.
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