Overview

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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February 13, 2023

Initial release of Growparabolic.

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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

View 16 more pros

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

View 4 more cons

Q&A

What is Parabolic?

Parabolic is an AI-powered customer support assistant. It is optimized to speed up ticket resolution and is designed to be integrated into existing ticketing software. Parabolic can identify user intent and auto-generate replies, along with managing multiple rounds of conversations, attaching upsells and cross-sells based on customer's issues, and automatically categorize and index responses.

How does Parabolic integrate with existing ticketing software?

Parabolic integrates with existing ticketing software such as Intercom, Zendesk, and Helpscout. This integration enables it to embed within these platforms, providing seamless support without any need to switch to different tools or platforms.

How does Parabolic learn from support data?

Parabolic adopts a 'human-in-the-loop' model, allowing responses to be verified by agents before they are sent out. Every time an agent rejects a draft, Parabolic learns from these interactions and enhances its capability to improve with time, developing more accurate and sophisticated responses.

What does it mean that Parabolic can detect a user's intent?

Parabolic's ability to detect a user's intent means it is designed to understand the underlying purpose or goal of a user's communication, regardless of the specific keywords used. This allows it to generate accurate responses that effectively address a user’s specific needs or concerns.

How does Parabolic auto-draft responses?

Parabolic auto-drafts responses by detecting user intent and then generating two kinds of replies: generalizable and customer-specific. Generalizable responses can be used for commonly occurring queries, while customer-specific responses make use of details from the internal database for a more tailored approach.

Can Parabolic handle multiple back-and-forths in a conversation?

Yes, Parabolic is capable of managing multiple back-and-forths in a conversation. It can progressively navigate through ongoing dialogues and adjust its responses as the conversation evolves.

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How does Parabolic utilize upselling and cross-selling?

Parabolic uses upselling and cross-selling by detecting customer's issues and appending relevant upsells or cross-sells. This converts the customer support channel into a potential sales opportunity.

What is Parabolic's auto-categorize feature?

Parabolic's auto-categorize feature is designed to automatically tag and direct incoming questions into appropriate categories. For instance, the feature can classify questions related to payments, memberships, etc., making it easier to manage and respond to the queries.

What is a 'human-in-the-loop' model in the context of Parabolic?

The 'human-in-the-loop' model in Parabolic means that the response generated by the AI is verified by human agents before it is sent out. The model allows Parabolic to learn from the actions of human agents and continually improve its capacity to draft applicable responses.

How does Parabolic index responses?

Parabolic indexes responses by auto-indexing any response that you've ever messaged to a customer. Through this, it creates an extensive, reusable database for response management which enhances its capability to provide accurate replies swiftly.

Can Parabolic answer rarely asked questions?

Yes, Parabolic is capable of answering rarely asked questions. It only needs one match in past conversations or the knowledge base to suggest an answer to a question, no matter how infrequent it is.

What's the difference between generalizable and customer-specific responses in Parabolic?

Generalizable responses in Parabolic are those that can be used for common questions, while customer-specific responses are personalized responses that use data from the internal database to provide a more custom-tailored assistance.

How is my company's internal database used by Parabolic?

Parabolic uses your company's internal database to draft customer-specific responses. This can include information like order details, account status, or any other client-specific data that can be used to personalize the responses.

How does Parabolic handle privacy and data protection?

Parabolic is committed to privacy and data protection, adopting a stringent privacy policy to ensure that all data is handled responsibly and securely.

What are Parabolic's terms of service?

Parabolic's terms of service highlight the rules and guidelines that users must agree to follow to use the service. It provides a detailed explanation of legal rights and responsibilities, ensuring usage transparency and accountability.

How is Parabolic's pricing structured?

Parabolic's pricing structure is provided on their website and it's designed to deliver optimal value and affordability.

How can Parabolic increase response efficiency?

Parabolic increases response efficiency by integrating seamlessly with existing ticketing software, learning from previous interactions to improve response accuracy, auto-generating generalizable and customer-specific responses, and navigating through multiple rounds of conversation with the user.

Can Parabolic be used with Intercom, Zendesk, or Helpscout?

Yes, Parabolic can be integrated with Intercom, Zendesk, and Helpscout. This ensures that the AI-powered customer support is available right within the platforms that companies are already using.

Is Parabolic backed by Y-Combinator?

Yes, Parabolic is backed by Y-Combinator, a renowned startup accelerator known for nourishing innovative tech startups.

How does Parabolic handle different categories of customer queries like payments and memberships?

Parabolic handles different categories of customer queries, such as payments or memberships, by using its auto-categorize feature. It automatically tags and directs incoming questions to appropriate categories.

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