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Description
An analysis of 1 million heavily loaded trucks that passed through weigh-in-motion scales indicated that 92% of these vehicles were far from their full capacity. AutoO2 addresses this issue by transforming shipping requirements—such as the movement of goods from a manufacturing facility to a distribution center—into optimized, cost-effective truckloads that utilize nearly every available pound or cubic inch of space. The resulting loads are not only compliant with regulations but also free from damage and fully maximized. Manufacturers often ship products using slip-sheets or bundles, which facilitates the creation of loads that can occupy more floor positions compared to traditional palletized methods. For instance, when stacks measuring 1.02 meters by 1.2 meters are loaded with their wider dimension aligned along the trailer's length, a 16-meter trailer can accommodate only 15 rows, leading to a 0.7-meter gap at the rear. Conversely, if the stacks measure 1.0 meter by 1.2 meters, the same trailer can fit 16 rows, eliminating any waste. However, a challenge arises due to the diverse range of product footprint sizes in the shipping process, complicating load optimization further.
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.
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
AutoO2
Founded
1990
Country
United States
Website
t-wo.com/software/
Vendor Details
Company Name
Bidgely
Founded
2011
Country
United States
Website
www.bidgely.com
Product Features
Warehouse Management
3PL Management
Barcoding / RFID
Category Customization
Channel Management
Demand Planning
Inventory Management
Location Control
Order Management
Purchasing
Quality Control
Receiving / Putaway Management
Returns Management
Shipping Management
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