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First Look – Medio


Medio started in 2004 with a mobile-first focus on predictive analytics for customer engagement and monetization. Since then they have grown to over 80 people with a cloud-based solution designed to help companies boost engagement and monetization opportunities with their customers on mobile and other IP-connected devices.

Medio specializes in personalized real-time information and recommendations and deal with limits on mobile bandwidth, privacy concerns and the like.  Companies use Medio across the life cycle of a customer—acquisition, engagement, monetization and retention. The Medio platform currently analyzes over 30 billion monthly events and delivers over 2 billion decisions monthly.  Medio’s customers include Verizon and Rovio—the developers of Angry Birds.

The Medio platform (inGenius) collects relevant data, especially from the mobile space, analyzes it using tailored algorithms and models and then delivers automated, real-time actions or decisions. Medio inGenius is a predictive analytics platform, in the cloud, with a set of automated tools to deliver deep customer understanding and improve customer engagement. The core platform is a Hadoop-based cloud solution that supports predictive analytics, machine learning and business rules to drive better decisions. Medio is very focused on end to end solution development and delivering Decisions as a Service with a rich set of developer tools, APIs and an SDK.

Key benefits of this approach include:

  • Fast time to benefit:
    Simple to use SDKs, standardized data collection, cloud-based easily accessible data storage
  • Individualized customer understanding:
    Based on past experience, user segmentation, active dashboards
  • Automated engagement:
    Personalized recommendations, multi-channel optimization, multi-content optimization.

The platform collects large amounts of data in real-time.  It then aggregates this data and stores the results in a Hadoop-based environment. The system can also ingest data from internal or external sources such as billing or purchase information, 3rd party demographics, or other event streams. Aggregated data is used to build predictive analytic models that drive business actions.  These models are constantly tuned to optimize business results.  All the predictive analytic models are used in real-time. A simple API allows access to real-time recommendations from any application. The data processing infrastructure, analytics and various management tools (like reporting) are all hosted in the cloud and sold through application modules.

Medio uses a standard and proven methodology. Data is collected in real-time from multiple platforms and then cleansed and integrated. A core set of predictive analytics are created by data scientists along with what Medio calls “Clustomers” or dynamic clusters of customers with similar behavior. Finally the platform supports iteration and multi-variant testing. Ongoing analytic routines adapt and improve these models once they are deployed. The results of these analytics drive dashboards and reporting but primarily are used to deliver decisions recommendations, custom content or offers.

You can get more information on Medio and its products here. While Medio offers a number of pre-configured solutions built on their platform, they also support customers developing unique custom solutions. As such Medio is one of the vendors in our Decision Management Systems Platform Technology Report.


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