Bidgely Enterprise Analytics Succeeds in Transforming Smart Meter Data into Customer Analytics and Grid Edge Intelligence, and Utility Partners into Data-Driven Enterprises

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Artificial intelligence and personalization drives intelligent demand side management program planning and customer targeting, reduces churn, improves call center operations and more

Bidgely has successfully equipped its global utility and energy retailer partners with new tools to create value from untapped customer data through its artificial intelligence-powered Enterprise Analytics Solution. Bidgely has partnered closely with global customers like TEPCO, NV Energy, Duke Energy, VSE and others to extract data insights from smart meters, or the advanced metering infrastructure (AMI); to create personalized customer energy profiles; and to better help them understand both customer needs and grid loads in new, data-driven ways. Enterprise analytics has demonstrated value for use cases across the organization, such as targeted demand side management (DSM) planning, personalized program recommendations, call center intelligence, electric vehicle (EV) and solar PV detection, propensity modeling, and grid edge load shaping and shifting.

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Navigant’s Global AMI Tracker 4Q19 recently highlighted the trend of accelerated deployment of smart meters, noting particularly the North American and European markets’ pursuit of advanced analytics as a long-term technology transformation to create a more intelligent grid. Bidgely’s first-of-its-kind partnership with Itron, recognized by Navigant as a North American AMI leader, fast-tracks the industry toward the “next frontier of smart meters,” delivering a scalable integrated solution of Bidgely enterprise analytics plus Itron’s meters for electric and dual-fuel utilities to propel their transformation into data-driven enterprises.

“We are committed to our mission of being the trusted artificial intelligence partner for utilities and energy retailers around the world – delivering on the wide-ranging value that a 360-degree view of customers brings to the entire organization as well as to AMI investments overall,” said Abhay Gupta, CEO of Bidgely. “With personalized customer data insights at its core, utilities can create an integrated ecosystem that effectively disseminates actionable intelligence throughout the organization to drive more strategic decision making while at the same time boost customer engagement, satisfaction and brand loyalty.”

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Insight into individual energy consumption enhances demand side management planning and grid forecasting, for instance, as utilities now understand which home appliances are being used during peak times, and they can more accurately execute grid upgrades or load shifts. Utilities can also better target customers for greater marketing ROI, for example, by correctly identifying homes with inefficient appliances and targeting them for rebate programs in highly personalized ways. Data-driven analytics can be applied for numerous use cases, including:

  • DSM: to improve demand side management program planning and estimation by tracking energy at meter level and perform personalized home audits.
  • CSAT: to measure satisfaction using multiple customer touch points and educating customers on energy programs specific to their usage.
  • Revenue: to increase customer acquisition, reduce customer churn through greater satisfaction and brand loyalty, and generate interest from third-party partners.
  • OpEx Reduction: to reduce both the number of high bill calls coming into the call center and time spent per call, as well as detect gaps in user data in real-time.
  • Electrification: to deploy AMI-based EV detection and load estimation that enables utilities to target EV and solar owners for better engagement and TOU rates.
  • DER: to analyze the effect of PV on the grid and identify how much energy is being fed back into the grid.
  • Grid Mapping: to identify savings potential among customers in specific locations and load-constrained geographies with load shifting opportunities.

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