15 Feb
How can AI and chatbots improve support agent experience & productivity
According to a survey, post-covid, 59% of customers will care even more about customer experience than they did in the “before times” when deciding which companies to support or buy from.
With the increased expectation for a speedy resolution and more interactive engagement, customer service representatives (CSR) alone cannot handle the rapidly evolving needs of customer support. An American Express survey found that 78% of consumers have bailed on a transaction because of a lousy service interaction.
As the pressure to scale up processes and deliver quality customer engagements mounts, contact centers witness higher attrition and agent turnover. Hence, to be truly successful in providing exceptional customer experiences, an organization needs to view agent experience, meaning how efficient, empowered, and effective its agents are, as an integral part of its overall customer support strategy.
To augment agent effort, chatbots and other AI-driven technologies are making their way into contact centers. Let’s discuss how a hybrid, co-existential human and AI model improves support agent experience and productivity.
The Different Ways AI improves Agent Experience and Productivity
1. Cognitive Search
As agents routinely deal with tons of product information, they may have to put customers on hold while they skim through heaps of FAQs, blogs, documents, spreadsheets, and other internal sources of information in search of the right answers.
Moreover, traditional keyword-based searches lack context and often generate less relevant results that are not in sync with what the customer actually wants. This leads to a longer average handle time (AHT), a key performance metric for any support agent.
In such a scenario, AI-powered tools that understand the context and deliver highly meaningful search results come in handy. Such tools lead agents to the most relevant content within the vast array of structured and unstructured data that the organization holds.
Mesh 3.0 – A Modern SharePoint Intranet solution for enterprises, connects all your external and internal apps and offers a unified, AI-enabled cognitive search engine that reduces the time you spend locating the relevant information.
2. Smart AI Advisor
Today’s customers demand instant answers and expect the agent at the other end of the line to provide the best resolutions. However, on encountering a new query, agents may need time to review the customer’s account and evaluate potential solutions.
Advanced AI tools, including chatbots, can look into a customer’s history, including transactions, usage, preferences, and other information, and quickly provide a list of customized resolutions to assist the agents.
So, armed with contextual information and the right recommendations, agents can deliver more focussed, engaging, and meaningful interactions.
3. Reduce agent effort by understanding customer intent
Another critical metric involved in evaluating a support agent’s performance is the number of tickets closed.
Every time a customer emails an agent, even thanking them for their support, the service ticket gets reopened. Consequently, the support agent must manually update and close the ticket, leading to duplication of effort and an adverse impact on his KPIs.
With the help of AI, systems can detect the intent behind customer responses before deciding whether or not to reopen a ticket.
Read More: How Agent Assist Bots Help Improve Customer Service Productivity
4. Act as an AI assistant
Traditionally, customer-facing chatbots and virtual assistants were used for simple FAQs. However, a chatbot’s applications need not be limited to just customer-facing interactions.
Today’s sophisticated agents can handle more complex work – understand where to look for the right information, recommend verbiage that agents can use with customers, and automate routine queries to free up the agent for more complex tasks.
Moreover, bots can assist agents in delivering superior and more efficient customer service –
- Supporting agents during live calls or chats by providing the needed information and immediate contextual suggestions
- Connecting to backend knowledge bases and CRM systems and extracting relevant articles and documents to help with the customer’s query
- Escalating customer interactions to a live agent, when needed, and providing the entire chat history, including sentiment analysis scores and other contextual information, to the CSR
- Automating time-consuming and tedious tasks, such as recording customer information, post-interaction form filling, surveys, etc.
- Mining audio calls and textual conversations to capture significant details and insights
- Act as a chat AI co-pilot by studying customer profile, mining prior conversations with higher CSAT scores, and recommending responses
Read more: How Chatbots Can Boost The Customer Retention Rate
5. Assist in quality control through active listening
For training and quality assurance purposes, call center managers listen in to agent conversations, but they are limited to only one agent at a time. With the advent of text-to-speech technologies and machine learning, AI systems can listen in on thousands of live conversations, understand customer intent and context, and present insights on the agent’s screen in real-time.
Additionally, by conducting sentiment analysis on every customer utterance and agent response, systems can alert managers about conversations that require a handover to or assistance from a supervisor.
Get Started
Businesses are built on the experiences they provide to their customers. And agent experience is fundamental to delivering an excellent customer experience. AI-powered solutions enhance support agent productivity and deliver next-generation, synergistic customer experiences.
The best results occur when AI and humans work shoulder-to-shoulder. By acting as smart virtual assistants for agents, handling mundane tasks, and providing scalable, 24X7 service, AI tools are paving the way for seamless outcomes for both support agents and customers.
At Acuvate, we help clients build and deploy smart, AI-enabled chatbots with our enterprise no-code, bot-building platform called BotCore.
Functioning as a handy source of on-demand information, providing intuitive and proactive assistance to agents, and handling routine queries, BotCore’s AI bots help improve support agent experience and productivity and reduce agent turnover.
To know more about BotCore, please feel free to schedule a personalized consultation with our experts.
Abhishek is the AI & Automation Practice Head at Acuvate and brings with him 17+ years of strong expertise across the Microsoft stack. He has consulted with clients globally to provide solutions on technologies such as Cognitive Services, Azure, RPA, SharePoint & Office 365. He has worked with clients across multiple industry domains including Retail & FMCG, Government, BFSI, Manufacturing and Telecom.
Abhishek Shanbhag