Confluent > Case Studies > SunPower's Modern Customer Engagement Strategy with Confluent

SunPower's Modern Customer Engagement Strategy with Confluent

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 SunPower's Modern Customer Engagement Strategy with Confluent - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Real Time Analytics
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Cement
  • Renewable Energy
Use Cases
  • Fleet Management
  • Real-Time Location System (RTLS)
Services
  • System Integration
The Customer
About The Customer
SunPower is a leading renewable energy company that provides residential and commercial services. The company monitors over 286,000 systems and 6 million devices in the United States. SunPower is known for its innovative approach to energy solutions, offering products like the SunPower Equinox® solar and SunVault™ storage systems. The company aims to provide its customers with rich access to their own energy usage data and control over their energy systems. SunPower is committed to optimizing its service and offerings based on real-time data and customer feedback.
The Challenge
SunPower, a leading residential and commercial renewable energy company, monitors over 286,000 systems and 6 million devices in the United States. The company aimed to differentiate itself by creating a software offering for consumers that pairs with their SunPower Equinox® solar and SunVault™ storage systems. This software would provide consumers with rich access to their own energy usage data, control over their SunVault™ system, and allow SunPower to optimize its service and offerings. However, this required SunPower to collect, aggregate, and provide access to real-time data from 6 million devices, a task that was beyond the capabilities of its legacy system. SunPower wanted to utilize the vast amount of data it generated on energy usage across its existing fleet to build more efficient products, make data more accessible and actionable by different parts of the business, and offer customers a more instantaneous energy management experience.
The Solution
SunPower chose Confluent as the backbone of its data platform, unlocking a new set of architectural capabilities and use cases. With Confluent, SunPower was able to build a real-time monitoring platform that allows homeowners and commercial customers to understand and control their energy usage. Confluent enabled SunPower’s engineers to ingest all the energy data flowing from its solar and storage solutions. This helped customers understand and track their power usage, rate of energy consumption, and state of their various batteries in real-time, enabling them to optimize their behavior, save energy and use SunPower’s products more efficiently. Additionally, SunPower could improve fleet management by better measuring and predicting the performance of its fleet to catch potential issues before they occur. For instance, engineers could understand how a weather event may affect SunPower’s fleet in a specific region, and subsequently alert its homeowners to modify their behavior based on this real-time data.
Operational Impact
  • With Confluent, SunPower experienced a significant improvement in data processing speed. Previously, engineers were constantly in a “tug-of-war” with other disparate systems on SunPower’s platform. Data was siloed separately across multiple systems, each department required lead times to make their data accessible for other teams to use. By serving as the central nervous system of the monitoring platform, Confluent enables engineers to process and make actionable insights from their data quickly and reduce the time it takes to bring new features to market. Moreover, SunPower can receive and respond to data in real-time, allowing them to build customer-facing features that were not possible in the legacy system. In the case of SunVault™, they can notify customers of outages and other relevant events without delay.
Quantitative Benefit
  • Real-time data collection and aggregation from over 6 million devices
  • Improved efficiency in energy usage and product utilization
  • Enhanced predictive capabilities for fleet performance

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