by Maria Legaspi, on Jun 21, 2024 6:25:56 PM
Key takeaways from the blog
- Agent Assist is an Agent Copilot that assists enterprise functions, such as Customer Service.
- It extends enterprise databases, like CRMs, and offers quick responses to simple language queries.
- The resulting CXM empowerment brings immense benefits and drives up the brand reputation.
Customer Service Agents handle a humongous workload of calls daily. However, to solve customer queries instantaneously, the agents require access to real-time customer data. CRMs do store customer data. However, instantaneously retrieving the required data at the touch of a button from multiple pages of customer history in the CRM record and placing it in context with the business rules for answering the customer call can be tedious. To fulfill this business ask, the agent requires a solution that selectively picks the relevant customer information from the CRM in a contextual framework at a rapid pace. Technological advancements offer Agent Copilots or Agent Assist that use data from CRMs through SLM frameworks to offer quick answers to agent queries in simple language.
What are SLMs?
Small Language Models, or SLMs, are specialized and focused data models that are developed for a specific domain, such as Customer Service, by leveraging the organization’s live data from repositories, such as CRM systems. The focused data set and its model training make it a highly efficient vehicle for driving the cause, here customer service, within the organization as compared to the Large Language Model (LLM) performance. The SLMs provide apt answers to agents’ query prompts supported by summaries for solving customer queries in real-time. SLMs respond faster to queries as they require less computation power than LLMs. They are the best allies of customer service agents who field hundreds of service calls in a day. The SLMs get easily updated with ongoing CRM changes and serve best for focused interests such as supporting customer service agents. However, due to their limited focus, they have a limitation when they are queried for more exhaustive organization-level answers. The need may arise to have different SLMs for different organization sections, such as HR. However, SLMs run fast due to their limited scope of focused action.
How does Agent Assist improve the quality of conversation?
Agent Assist, powered by Small Language Models (SLMs), provides quick answers using live CRM data. This instant access helps agents respond to customer questions right away. It improves the rate of solving issues on the first try and allows agents to handle more queries accurately each day.
Agent Assist gives clear and concise answers, allowing agents to have meaningful conversations with customers, even within two minutes. This quick and correct response boosts customer satisfaction. Additionally, it has a live transcription feature to keep track of important points for quality checks later. Agent Assist can also show suggested answers from top-performing agents, helping all agents improve their responses.
What is the role of Agent Assist in CXM?
CXM demands quick issue resolution with zero wait time. Personalized services result in better customer mindshare. Accuracy and first-time rights are primarily important. Fulfilling these customer expectations through manual or semi-automation solutions is next to impossible.
Agent Assist is an Agent Copilot that supports the dynamic CXM environment. It reduces the turnaround time for query resolution. It taps into earlier customer interactions, similar historical queries and their answers, and fuzzy business rules to offer personalized and accurate answers in a contextual environment. Agent Assist or Agent Copilot serves as the quintessential support system of a dynamic CXM in modern enterprises.
What is the importance of FTR in CXM?
Customer-facing roles must be alert and proactive while resolving customer queries. They should provide accurate query resolution at the very first instance. First Time Rights also known as FTRs are important in customer service and have a direct impact on customer experience (CX). Customers accustomed to Amazon, Uber, and Ola like quick service, demand faster and better query resolution. Here FTRs resonate with the customer psychology and result in better customer satisfaction, increased customer loyalty, and better brand reputation.
Benefits of Agent Assist in CXM
- Access to live information: Agent Assist gives quick access to real-time customer information to resolve customer queries resulting in a higher FTR rate.
- Consistency in response: It helps in delivering consistent communication that directly influences brand reputation.
- Agent empowerment: Agents feel empowered while resolving complex customer issues with access to an up-to-date customer knowledge base through simple language querying.
- Enhanced CXM: Agent Assist has an in-built transcription facility that allows QA executives to analyze responses and improve overall CX.
- Higher productivity and efficiency: It improves the agents’ speed and response quality that allows them to resolve more queries with a high FTR rate.
- Personalized assistance: Agent Assist tracks customer details and earlier communication history based on the learning model and helps agents deliver personalized response.
Simply put
Agent Assist is like a helpful Copilot for customer service agents, sitting on top of enterprise data systems like CRMs. It uses specialized data models to provide quick and accurate answers to agents' questions. This helps improve the quality and speed of customer service, boosts agent confidence, and enhances the overall customer experience, ultimately improving the brand's reputation. By making agents' jobs easier, it also reduces stress, lowers attrition rates, and increases efficiency, further enhancing the customer experience.
