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Description
A 50% decrease in high bill inquiries has led to improved customer satisfaction. By proactively identifying cases that may lead to customer support needs, companies can preemptively address concerns. Implementing straightforward, timely, and actionable notifications offers a sophisticated method to engage with customers proactively, which helps lower the number of incoming calls. Providing tailored, proactive explanations for those who experience unexpectedly high bills prepares customers for potential changes in their energy usage patterns. Additionally, notifying customers about upcoming seasonal transitions and offering energy-saving suggestions can further enhance their experience. Integration with Google Home and Amazon Echo allows for personalized insights, enabling customers to inquire about billing, outages, itemization of appliances, bill forecasts, utility programs, and much more. Call center representatives often face challenges when addressing bill-related inquiries, which can lead to expensive escalations and unnecessary truck rolls. The Bidgely Bill Analyzer, an AI-driven tool for customer service representatives, equips agents with detailed appliance-level usage data for each customer, enhancing their ability to resolve issues effectively. In doing so, it not only streamlines the support process but also fosters a more informed and satisfied customer base.
Description
The MAISY databases for both commercial and residential utility energy consumption were first launched in 1995, encompassing details on 10,000 utility clients across the United States. Since then, these databases have undergone extensive annual updates, culminating in the 2020 MAISY databases, which now feature up-to-date energy consumption and hourly load profiles for over 7 million individual utility customers in the US. Each record within the databases contains comprehensive information regarding the building, equipment, operational details, occupant profiles, and energy usage of the respective utility customers. The development of these hourly load profile databases has been informed by a wide range of data sources, including utility companies, industry associations, governmental data, as well as proprietary surveys conducted by Jackson Associates and in-depth engineering assessments of appliances. Importantly, these databases represent a statistically valid cross-section of both residential and commercial utility customers nationwide, ensuring their reliability and usefulness for energy analysis and planning. Their extensive scope allows for a more informed understanding of energy usage trends across diverse sectors.
API Access
Has API
API Access
Has API
Integrations
Databricks
Itron Enterprise Meter Data Management
Salesforce
Snowflake
Integrations
Databricks
Itron Enterprise Meter Data Management
Salesforce
Snowflake
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Bidgely
Founded
2011
Country
United States
Website
www.bidgely.com
Vendor Details
Company Name
Jackson Associates
Founded
1995
Country
United States
Website
www.maisy.com/maisydatabases.htm
Product Features
Utility Management Systems
Billing & Invoicing
Cable
Customer Management
Demand Planning
Electricity
Natural Gas
Plant Management
Service Call Management
Trash
Water
Work Order Management
Workforce Management
Product Features
Database
Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization
