mnubo makes Internet-of-Things smarter.
mnubo's SmartObjects service transforms ‘connected things’ into ‘smart objects’. Our focus is to help extract true value from sensor data by delivering advanced real-time analytics, strategic insights and enabling richer applications.
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key benefits of IoT analytics

Analytics have generally been defined as “the discovery and communication of meaningful patterns and insights in data”. For years, analytics have been empowering the web, mobile applications and social spaces with data-driven decision making. Most websites, mobile applications and social engines have analytics as an integral part of their product and business strategy.

Their primary motive for adopting analytics is real-time, valuable insights for:

  1. Usage feedback to drive better and more-focused development
  2. Improvement & optimization of value-added services to spur potentially new monetization avenues

IoT is no different.

Product manufacturers are embracing analytics as the cornerstone of their connected product experience and aftermarket service offering. When applied to the IoT, analytics focus on providing competitive differentiation and strategic insights to IoT product manufacturers and IoT service providers on the usage and behaviour of connected products.

mnubo’s SmartObjects platform is designed to analyze various aspects of IoT data from an ingestion, modeling, storage and analysis perspective. SmartObjects focuses on delivering business outcomes (ROI) that answer key business questions (KPIs) for IoT product manufacturers and IoT service providers.

IoT analytics can be grouped into 5 key benefits:

  1. Product & service feedback – manufacturers use product usage feedback to assess product quality and monitor behaviour thereby focusing their R&D spend
  2. Usage behaviour tracking – understand how customers are interacting with the connected product and enhancing the experience to match the customer’s behaviour
  3. Operational analysis – optimize service offerings based on usage segmentation analysis and reduce the costs associated with providing that service
  4. Contextual analysis – enrich the sensor data with external data (weather, geolocation, etc) to provide greater context on how the physical objects are behaving in relation to their surroundings
  5. Predictive analysis & maintenance – use previous patterns and the knowledge of the current usage to predict future trends and behaviour

Find out how mnubo’s SmartObject IoT Analytics platform allows businesses to create data-driven differentiation and deliver richer applications. Download the whitepaper “Analyzing the world’s data”

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