Blog
Delve into research, how-tos, trends, and tips on all things messaging.
Agent-Facing AI Tools
Take your customer
service to the next level
with AI response tools
for agents.
Supercharge your support with Quiq’s AI agent assistance.
Quiq’s Conversational CX Platform features a first-in-market set of LLM-powered response tools that are designed for your customer service agents. Each one helps agents move faster, accomplish more and provide a better customer experience.
Quiq Compose.
With Compose, an agent can respond to a customer inquiry with typo-laden, informal language, and Compose will generate a well-written response that has good grammar, uses empathy, and is clearer.
Compose leverages Large Language Models (LLMs) to ingest an outline of an agent response and generate a well-written alternative. Then, the agent can review the rewritten message and hit send. This feature keeps a ‘human in the loop’ to secure brand quality and safety.
The result? Improved agent response quality and customer experience.
Why your team needs Quiq Compose:
Improves agent satisfaction.
Compose makes agents’ jobs easier by lowering the language skills required to craft the perfect response.
Reduces agent costs.
Quiq Compose improves agent efficiency by lowering the cost to serve, allowing you to serve more customers.
Improves agent response time.
Since agents only need to type terse notes, they can handle inquiries faster.
Response Obligations.
Response Obligations monitors conversations with AI to understand which party (agent or customer) is expected to respond next.
By accurately knowing when it is the agent’s turn to respond, Quiq can coach the agent on how to respond or re-route the conversation if they fail to answer.
Response Obligations will improve your:
- Customer experience
- Agent efficiency
- Agent performance
…all while ensuring no customer is ignored and helping you meet SLAs.
Talk to us about agent AI for your team.
Quiq Suggest.
Quiq Suggest learns how top agents responded to similar conversations in the past and then uses that knowledge to suggest responses in real time for agents to send, or edit.
Quiq uses Generative AI to build an Edge Language Model that’s specifically trained on your company’s data. It’s like a Large Language Model, but smaller, so that it can run very fast for auto-complete.
Why Quiq Suggest is a contact center must-have:
Save agent work time.
Suggest saves up to 30% of typing time, allowing agents to resolve inquiries faster.
Lower average handle time.
Agent handle time (AHT) is the total amount of time it takes an agent to have a conversation with a customer. Reducing AHT makes customers happier and agents more efficient.
Increase response quality.
Agents often send the same, repetitive messages. Now you can ensure they are accurate, fast, and consistent across the business without literally repeating the same words.
Improve customer and agent experience.
Give every customer the experience of working with a top agent, and make it easier for agents to know what to say.
Reduce new agent ramp time.
Suggest helps new agents learn what top agents say in similar situations, giving them shorter ramp times to productivity.
Conversation Summarization.
Improve quality, agent coaching, and conversation analytics while reducing average handle time with strategic Conversation Summarization. Quiq leverages LLMs to summarize conversations in two critical situations.
1- Summary upon transfer
Whenever a conversation is transferred to a human from an AI assistant or another agent, a summary is delivered to the receiving agent in Quiq’s UI. This way, the agent can quickly read it before taking over the conversation.
2- Summary upon close
When the conversation is closed, a summary is stored along with the conversation. You can choose to sync it to your CRM platform, analytics tool, or other system of record for analysis.
Unimportant Message Filtering.
Unimportant Message Filtering uses AI to filter out unimportant messages that are received after a conversation is closed, such as “Thank you” or “Have a good day”. If a message is determined to be unimportant, Quiq adds it to the end of the transcript.
Without Unimportant Message Filtering, agents would need to leave conversations open to wait for any customer messages received in closing.
Or if the agent did close the conversation immediately, unnecessary follow-up conversations would be created, wasting agent time and cluttering your contact center metrics.
Ready to start with Quiq’s agent AI tools?
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