Customer support 2024-06-17
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Growparabolic

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AI Support Agent to accelerate your ticket resolution.
Generated by ChatGPT

ChatGPT for Customer Support, known as Parabolic, is an AI tool designed to enhance customer support services. This AI assistant is aimed at improving the efficiency and accuracy of ticket resolutions, eliminating repetitive queries, and providing specialized responses.

Integrated within existing ticketing softwares like Intercom, Zendesk, or Helpscout, it uses a 'human-in-the-loop' model where responses are verified by agents before they're sent, allowing it to learn and improve over time.

With just one match in past conversations or knowledge base, Parabolic can suggest responses, even addressing rarely asked queries. It's capable of navigating multiple back-and-forths as conversations progress.

Another distinct feature is its ability to append relevant upsells or cross-sells based on the customer's issue, turning customer support into a potential sales channel.

The 'Auto-Categorize' feature is designed to automatically tag and direct incoming questions to the appropriate category like payments, memberships, etc.

It's also designed to detect a user's intent, independent of specific keywords, and draft two types of responses: generalizable and customer-specific.

Generalizable responses can be used for common queries, while customer-specific responses utilize information from your internal database for more personalized assistance.

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Growparabolic was manually vetted by our editorial team and was first featured on February 22nd 2023.
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Pros and Cons

Pros

Accelerates ticket resolution
Embedded within existing software
Trained on user's data
Detects user's intent
Auto-drafts responses
Handles multiple exchanges
Adds upsells/cross-sells
Auto-categorizes incoming questions
Auto-indexes sent responses
Answers rarely asked questions
Uses human-in-the-loop model
Improves over time
Integrated with Intercom
Integrated with Zendesk
Integrated with HelpScout
Converts support to sales
Auto-tags incoming questions
Drafts two response types
Handles generalizable/customer-specific responses
Uses internal database data
Privacy policy available

Cons

Limited to existing ticketing software
Agent verification slows responses
Dependent on past conversation data
Possibility of inappropriate upsell/cross-sell
Automated categorization errors
Limited to specific databases integration
Demands extensive user-specific data
Potential privacy issues
Pricing not specified

Q&A

What is Parabolic?
How does Parabolic integrate with existing ticketing software?
How does Parabolic learn from support data?
What does it mean that Parabolic can detect a user's intent?
How does Parabolic auto-draft responses?
Can Parabolic handle multiple back-and-forths in a conversation?
How does Parabolic utilize upselling and cross-selling?
What is Parabolic's auto-categorize feature?
What is a 'human-in-the-loop' model in the context of Parabolic?
How does Parabolic index responses?
Can Parabolic answer rarely asked questions?
What's the difference between generalizable and customer-specific responses in Parabolic?
How is my company's internal database used by Parabolic?
How does Parabolic handle privacy and data protection?
What are Parabolic's terms of service?
How is Parabolic's pricing structured?
How can Parabolic increase response efficiency?
Can Parabolic be used with Intercom, Zendesk, or Helpscout?
Is Parabolic backed by Y-Combinator?
How does Parabolic handle different categories of customer queries like payments and memberships?

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