Floatchat: Agent Assist Chatbots Enhance Customer Support

8 min read
06 September 2023

Introduction

In recent years, chatbots have become an increasingly popular technology for businesses looking to improve customer service and streamline operations. One type of chatbot that has seen rapid growth and adoption is the agent assist chatbot. Agent assist chatbots are AI-powered conversational agents designed to work alongside human agents in customer service roles.

What are Agent Assist Chatbots?

Agent assist chatbots are a specific class of chatbot that are designed to collaborate with human agents in customer service environments. They are AI-powered programs that can understand customer questions and requests, provide quick answers to common inquiries, and assist human agents in more complex conversations.

The key capabilities of agent assist chatbots include:

  • Natural language processing to understand and interpret customer questions and requests
  • Access to knowledge bases and FAQs to provide instant answers to common questions
  • Integration with CRM and helpdesk systems to access customer data and history
  • Conversation hand-off to seamlessly transition chats to human agents when needed
  • Sentiment analysis to gauge customer satisfaction and escalate unhappy customers
  • Chat transcript review to assist agents in understanding customer issues

Compared to standalone chatbots designed to fully automate conversations, agent assist chatbots are intended to work symbiotically with human agents to enhance the customer experience. They handle routine inquiries, while allowing human agents to focus their time on higher-value interactions.

Floatchat: Agent Assist Chatbots Enhance Customer Support

Benefits of Agent Assist Chatbots

There are several key benefits that make agent assist chatbots valuable assets for customer service teams:

  1. Reduced Customer Effort
    By providing instant responses to common questions and requests, agent assist chatbots reduce the effort required for customers to get answers. This improves customer satisfaction and loyalty.
  2. Faster Resolution Times
    With an agent assist bot handling simple, repetitive inquiries, human agents can devote their time to resolving more complex issues. This speeds up resolution times and improves service levels.
  3. More Efficient Operations
    Agent assist bots allow human agents to focus on high-value interactions. This increases agent productivity and efficiency in the contact center.
  4. 24/7 Availability
    Chatbots can engage with customers anytime, day or night. This provides companies with around-the-clock support capabilities.
  5. Valuable Insights
    The conversational data from chatbot interactions can be analyzed to gain insights into FAQs, customer sentiment, and opportunities for self-service.
  6. Omnichannel Engagement
    Chatbots can provide consistent customer experiences across different channels like web, mobile apps, messaging platforms.
  7. Lower Costs
    Chatbots require less overhead compared to hiring more human agents. The automation of routine inquiries reduces operating costs.

Use Cases for Agent Assist Chatbots

There are several customer service scenarios where agent assist chatbots can have high impact:

  • Handling simple FAQs - Chatbots excel at providing consistent answers to frequently asked questions. Offloading these repetitive inquiries from human agents saves substantial time.
  • Addressing account and order status requests - Customers often need information on order status, account balances, transaction history etc. Chatbots with access to the necessary systems can instantly fetch and provide this information.
  • Supporting customer onboarding - Many customer onboarding processes include repetitive data collection and confirmation steps that chatbots can handle automatically.
  • Managing payment or billing issues - Chatbots can answer common payment and billing questions and also access account information to assist human agents in resolving more complex issues.
  • Facilitating appointment scheduling - Chatbots can go through the steps of determining appointment requirements, checking availability, and scheduling appointments based on customer preferences.
  • Product recommendations - Chatbots can provide tailored product recommendations by analyzing customer data and purchase history information.
  • Addressing churn risks - By detecting signs of customer dissatisfaction through sentiment analysis, chatbots can flag at-risk accounts for proactive outreach.

Key Capabilities of Effective Agent Assist Chatbots

For agent assist chatbots to provide maximum value, they need to have certain key capabilities:

  • Natural language processing - To accurately interpret and respond to customer questions, chatbots need advanced NLP capabilities like intent recognition, entity extraction and sentiment analysis.
  • Integration with business systems - Seamless integration with CRM, helpdesk, ERP and other systems allows chatbots access to customer data and enterprise information critical for providing good responses.
  • Customer context tracking - Maintaining context on customer issues and history during conversations allows chatbots to provide personalized and relevant responses.
  • Conversation hand-off to agents - Chatbots need to smoothly transition chats to a live agent when conversations exceed their capabilities and avoid frustrating customers.
  • Self-learning abilities - Over time, chatbots should continue expanding their knowledge by learning from conversations with customers and human agents.
  • Omnichannel deployment - Companies need the ability to deploy chatbots across their website, mobile app, messaging apps and other channels for consistent experiences.
  • Analytics integration - By integrating with analytics tools, chatbot data can be used to derive insights on optimal customer journeys, pain points and opportunities for self-service.

Key Considerations in Chatbot Implementation

Companies looking to implement agent assist chatbots need to keep certain best practices in mind:

  • Start with a limited use case - Take an incremental approach by piloting chatbots for high-impact but narrow use cases first before expanding to broader applications.
  • Involve agents and users - Get input from customer service agents on common inquiries and pain points. Talk to customers to understand their expectations.
  • Plan for integration - Architect the chatbot solution with integration to necessary systems like CRM, billing and knowledge bases in mind from the start.
  • Focus on conversation design - Well-designed conversation flows that anticipate customer questions and needs are critical to driving good chatbot experiences.
  • Analyze chatbot conversations - Leverage tools to analyze chatbot dialogues and feedback surveys to continually refine chatbot performance.
  • Have human review - Initially have agents review a sample of chatbot conversations to check responses and identify areas for improvement.
  • Enable seamless handoffs - Make moving from chatbot to live agent smooth and context-aware to avoid disrupting customer experience.
  • Monitor KPIs - Establish key metrics like containment rate, customer satisfaction, resolution time and monitor impact on these KPIs.

The Future of Agent Assist Chatbots

Agent assist chatbots are still a relatively new technology, but one that is likely to see massive growth and adoption moving forward due to the clear benefits for customer service. Gartner predicts that by 2022, 70% of white-collar workers will interact with conversational platforms on a daily basis. As chatbots get smarter, they will take on more complex conversations and deliver an increasingly human-like conversational experience.

For chatbots and human agents to work synergistically, there needs to be deeper integration between AI and contact center infrastructure. Vendors are already working on tighter integration for things like screen pop-ups, recording chatbot interactions, and unified agent desktops encompassing both chatbot and human conversations. This will allow a seamless omni-channel experience across different interaction modalities.

Exciting innovation is also happening around emotional intelligence, allowing chatbots to detect subtle customer cues like frustration or doubt and adapt their responses accordingly. More natural-sounding speech and an understanding of customer intent rather than just literal word meaning will greatly enhance chatbots’ conversational capabilities.

While chatbots will become more advanced at handling customer service independently, the need for synergistic human-chatbot collaboration isn’t going away. Intelligently combining AI capabilities with human skills and emotional intelligence will remain essential for providing delightful customer experiences. Agent assist chatbots that augment and enhance human agents are poised to become a critical element of the customer service stack.

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