Understanding Agent Assist technologies for customer support

Customer support teams interact with customers via a variety of systems to assist them in answering customer queries. The most popular systems used are popular CRMs such as Salesforce, Zendesk, MS-Dynamics, ServiceNow, and Freshworks to name a few. They also use Contact Center Technologies that help Agents interact via voice or digital channels. 

Alongside CRMs and traditional contact center technologies, customer support leaders often invest in technologies that drive process improvements – process enhancers or productivity boosters. Gartner refers to these technologies as “spend to save” tools.

Agent assist is one such productivity booster. It aggregates several value-add technologies that sit at critical junctures of the agent experience. These tools offer a critical helping hand, helping agents with access to relevant information, personnel (Subject Matter Experts) or process flows that make agents more productive.  Productive agents drive better customer experiences – increasingly a key differentiator for companies. This article explains what agent assist is, the technologies involved, and why it is important for customer support.

Contents

What is Agent Assist

How does Agent Assist work

Importance of Agent Assist for Customer Support

Frequently asked questions

What is Agent Assist

Agent-assist technologies can be classified as applications or solutions that complement CRMs and Contact Center platforms. They focus on delivering relevant information, guidance, and support to agents in real-time, so they can navigate customer queries.

Typically triggered by keywords and phrases, Agent Assist tools provide real-time suggestions, guidance, and information to human agents as they handle customer inquiries and issues. Agent Assist technologies now increasingly also leverage artificial intelligence (AI) and natural language processing (NLP) capabilities to improve the accuracy of real-time suggestions, guidance, and information retrieval. 

How does Agent Assist work?

Following are typical ways in which Agent Assist works,

●     Team Collaboration – Enable Agents to collaborate with each other or connect with non-support personnel, and subject matter experts to get immediate peer-to-peer help.

●     Real-time Information Retrieval: When a customer contacts a company through various channels like phone, chat, or email, Agent Assist quickly pulls all relevant customer-related information.

●     Knowledge Base Access: When a customer contacts a company through various channels like phone, chat, or email, Agent Assist analyzes the customer’s query or message. Agent Assist tools can quickly access knowledge bases and retrieve relevant information to answer customer questions accurately.

●     Suggestion Responses: Based on the customer’s query and historical data, Agent Assist generates suggestions for the human agent. These suggestions can include relevant knowledge articles, responses to common customer queries, and troubleshooting steps.

●     Agent Guidance: Provide real-time guidance during an interaction based on dialog happening between customer and agent.  These are often referred to as agent scripting. AI technologies have improved this further with intent-based guidance.

●     Automated Responses: In some cases, Agent Assist can automatically draft responses or provide canned responses to common customer inquiries. The human agent can review and customize these responses before sending them to the customer.

●     Performance Management: Agent Assist can also provide real-time analytics and insights to supervisors and managers, allowing them to monitor agent performance, track customer sentiment, and identify areas for improvement in customer service operations. These also involve elements of gamification to drive agent behavior.

Importance of Agent Assist for Customer Support

Agent Assist can significantly improve the efficiency and effectiveness of customer service teams. Key benefits include

●     Reducing response times: Agents can quickly access information and responses, leading to faster issue resolution.

●     Ensuring consistency: Agent Assist helps maintain a consistent and standardized approach to customer interactions.

●     Driving Agent productivity: Makes agents perform tasks faster and better.

●     Improving agent training: New or less-experienced agents can benefit from real-time guidance and support.

●     Enhancing customer satisfaction: Faster, more accurate responses lead to happier customers.

Thus, Agent Assist is a valuable tool for businesses looking to enhance their customer service operations by combining the strengths of human agents with the capabilities of AI and NLP technologies.  With CSAT being a key driver and differentiator, Agent Assist technologies are becoming more and more important.

Support Automation platforms are making the deployment of Agent Assist technologies that much more easy. With seamless CRM integrations, the GenAI platform empowers support Agents with easy access to aggregated knowledge bases, delivers suggested responses, and thereby helps agents resolve tickets faster. GenAI platform has helped customers drive a 45% reduction in response times.

Frequently asked questions

What is Agent Assist?

Agent-assist is a process enhancer that offers a critical helping hand to support agents with access to relevant information, personnel (Subject Matter Experts) or process flows that make agents more productive.

What are the key technologies used in Agent Assist?

Key technologies that come together include collaborative tools such as team messaging. search technology for information retrieval from knowledge bases, scripting/low code/no-code tools for guided conversations, Natural Language Processing (NLP) and Natural Language Understanding (NLU), and generative AI for suggested responses.  Analytics and gamification techniques to drive Agent behavior.

What are the benefits of Agent Assist technologies?

Agent Assist is a valuable tool for businesses looking to enhance their customer service operations, drive agent productivity, and improve CSAT.