A mobile-first demand-side platform for true bidding transparency

The Nero dashboards with different data and metrics.

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.

Dashboard with campaign performance

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.

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.

Demonstrating campaign set up

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.

Dashboard with 3D pop up with different metric options


Logo of platform

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

Standard Mobile DSPs
No dashboard view of bidding formula.
Visibility into the full combination of variables involved with executing a programmatic media buy from a centralized portal.
No option to bring programmatic in-house.
Users can choose if and when they transition to a self-serve DSP.
Limited account management and customer support when buying methods change.
Continue working with long-standing partners throughout the business life cycle.
Slower testing workflow.
Rapid model testing allows us to find better models with higher predictive accuracy.
Data processing constraints can limit the complexity of the models built, leading to lower predictive accuracy.
Improved data processing enables more complex models leading to higher predictive accuracy.
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