Generative AI for Customer Support
Let’s face it. Customers demand quick, prompt, and effective solutions to their problems. They hate to wait. They hate to search for answers. They hate to face the same problems over and over again. And no customer should ever find themselves in these situations. Customer Support (CS) teams have a very crucial role in keeping customers happy. However, CS teams often find themselves crying out for help, leaving us wondering: "Who Supports Customer Support?”
The Power of Generative AI
Customer Support teams are overburdened with a high volume of requests and constrained by the limitations of the software they use - leading to slower response times and decreased customer satisfaction. Enter Generative AI to the rescue.
AI chatbots provide instant responses to common queries and provide a personalized, conversational experience for each customer. These GPT-powered bots can handle a significant volume of customer inquiries on their own, freeing up Customer Support teams from repetitive tasks and letting them focus on bigger issues.
AI can help Customer Support agents analyze past customer interactions and identify patterns. Agents can proactively identify and resolve common issues, improving customer satisfaction and reducing the number of inquiries they receive. Additionally, AI can automate routine tasks for Customer Support agents. For example, AI can help agents categorize and prioritize support tickets based on their frequency and urgency with the click of a button, enabling teams to focus on the most critical issues first and resolve them quickly.
Using AI-powered Customer Support software can help businesses both improve customer satisfaction and increase the productivity of the support agents. Here are some ways in which AI can be the copilot to your Customer Support as they keep making customers happy.
AI copilot to your L1 Customer Support
Knowledge Base (KB)
Core to every AI-powered Customer Support software is a knowledge base management in place. A knowledge base (KB) is a collection of information that can be easily logged, accessed, and searched.
Once all the information is sorted and stored, the AI can scrape the information for a response most relevant to the query raised by a customer. The response provided by the chatbot is conversational in nature as the GPT-powered chatbot uses Natural Language Processing techniques. As the chatbot interacts with more customers and learns from their interactions, it can continuously improve the accuracy and relevance of its responses.
Deflection
Deflection refers to the ability of AI chatbots to automatically provide first line of responses to common customer queries. Using natural language processing (NLP) techniques, the chatbot can understand the customer's query and provide a response that is personalized, contextual, and conversational. The chatbot does not simply direct the customer to a website or PDF where they have to search for the answer. Instead, it provides a simple, direct, and easy-to-comprehend answer to their question.
Through deflection, AI-chatbots can provide initial response to customer queries automatically. As the chatbot performs this operation repeatedly, it learns in the process and constantly improves the accuracy and relevance of its response with every answer that it generates. An AI-powered chatbot that is self-learning is more capable than a traditional chatbot trained by a decision tree or built using flow-builders.
DevRev’s PLuG widget can be deployed in minutes and are unrestricted by the limitations of the number of steps in a flow builders. It is powered by DevRev Turing AI. Deploying PLuG is as easy as point, click, and deploy. There is zero decision tree management involved in the process.
Routing
AI-chatbots, as a first line of response, can handle a significant volume of incoming queries as most of them can be resolved using information available in the knowledge bases. But when a customer raises a query that is beyond the scope of what’s available in the knowledge repositories, the AI-chatbot must promptly and seamlessly escalate the conversation to a human agent who can quickly resolve the issue that the customer is facing.
But how does an AI chatbot handle this process given that there are numerous steps involved in making the escalation seamless for a customer, who may be feeling agitated? Firstly, the AI-chatbot creates a ticket on its own once it understands that the customer's query requires human intervention and can only be resolved by a human agent. Next, it goes above and beyond by choosing which agent to transfer the ticket to.
Using Product Assist, DevRev Turing AI can identify the right customer support agent or product manager to fix the problem and automatically assigns the ticket to the right person.
Summarize
In customer support, the time taken to resolve a query is critical. It directly affects customer satisfaction scores and the number of queries that an agent can resolve in a day. Although AI-powered chatbots can reduce the burden on customer support agents by providing initial responses to commonly asked questions, once the query is escalated for human intervention it may be challenging to understand the context and background entirely. While the assigned customer support agent is on a race against time, they have no choice but to scroll through several pages of chat to understand the exact details of the customer's problem.
With DevRev Turing AI, Customer Support agents can use a simple “/summarize” command to get the gist of the conversation without losing the context or the finer details. The assigned Customer Support agent can then quickly get on to resolving the problem, drastically reducing the customer wait time and queueing time. No more asking the customer to repeat their ordeal. No more scrolling through endless chat to understand why a customer needs help. AI does it best so that you can do what you do best - keeping customers happy.
Synthesize
AI-chatbots serve many more functions even after a customer query has been passed on to a Customer Support agent for intervention and resolution. Agents can put the natural language processing capabilities of AI to use synthesize a tailored response that takes information from knowledge bases and past customer interactions. Agents can use Generative AI to create a personalized and conversational response that directly addresses the customer's question, instead of having to type it out themselves and spend time on wording it properly.
With Recommended Replies on DevRev Turing AI, agents and support engineers can resolve customer queries faster.
Rephrase
While conversing with customers, there is no room for miscommunication in order to ensure a faster resolution time. The responses to a customer, who is already upset or frustrated, must be simple and comprehensive. And many times, Generative AI can be used to rephrase technical or complex language into simpler terms that are easier for customers to understand. In other cases, Generative AI can be used to change the tone of a response as well to sound more empathetic and understanding while conversing with a customer who sounds very concerned.
Using DevRev Turing AI, Customer Support agents have Rephrase and Change tone features at a click of a button to ensure that their customers are not confused and find a solution to their problems as soon as possible.
AI copilot to your L2 Customer Support
Summarize
Often times, a customer query cannot be fully resolved by a chatbot or a Level 1 Customer Support agent. This typically occurs when a customer's issue is more complex and beyond the scope of what's available in the knowledge base. The Level 1 agent may also escalate the conversation when a customer has already tried multiple solutions, but the problem persists. In such cases, the query gets escalated to a Level 2 Support agent or engineer.
Using DevRev Turing AI, Level 2 Support teams can quickly get a summary of the customer conversation without losing any context or details. With a simple "/summarize" command, the AI generates a summary of the entire conversation that the customer had with the chatbot and the Level 1 agent. The feature makes it easier for the assigned agent to understand the problem and quickly start working on a resolution. The generated summary includes all the important details such as the customer's problem, previous interactions, and any actions that have already been taken. This drastically reduces the time taken to resolve a query and helps improve customer satisfaction scores.
AI copilot to your L3 Customer Support
At times, a customer's issue may be complex and beyond the expertise of Level 2 Customer Support agents. Such issues are escalated to Level 3 Support teams. These issues often require attention from those with specialized knowledge or feature enhancements that fall outside the scope of the product's current functionalities. In such cases, having the right insights plays a significant role in paving the way forward for enhancements.
Cluster
Level 3 Support agents have visibility of all the tickets that come into the ticket management software. Large volumes of tickets with details of the issues that customers are facing is a goldmine of information on customer painpoints and aspirations. However, deriving insights from vast amounts of data is virtually impossible without the support of an AI powered system that can identify emerging issues which require significant attention.
DevRev Turing AI can cluster similar tickets, allowing support engineers and product teams to gather insights from tickets. By analyzing incoming support tickets, Turing AI groups similar tickets together, giving support and product teams added visibility and clarity in making decisions around feature enhancements and innovation, reducing the time and effort needed to resolve them. Additionally, with clustering, teams can identify patterns in ticket inflow and ensure that they are addressed before they become widespread.
Deduplicate
With DevRev Turing AI, similar tickets are clustered together, allowing us to identify and remove redundant tickets. This reduces the total number of support tickets that a team has to handle. Once tickets are clustered, duplicates can be removed, saving valuable time for the support and product teams.
By removing redundant tickets, the support team can focus on solving unique issues, while the product team can prioritize feature enhancements based on the most common customer pain points.
Converge
Identifying patterns in customer issue tickets not only provides visibility on major problems faced by customers but also enables decision-making for future product enhancements. With this information, product development and management teams can confidently prioritize features that require immediate attention and fast resolution. Generative AI not only elevates Customer Support in any organization but also speeds up the pace of Software Development.
Generative AI is the answer
Organizations like 100ms uses DevRev for their Customer Support. Here’s what changed for them as a result
- 120%+ Net Customer Retention
- 5X+ Faster Resolution
- 50%+ Cost Savings
“We tried everything… literally everything: Zendesk, Freshdesk, Intercom, every software out there. The problem is just so unique to the new age, API first companies and none of the existing tools are built for it. It felt like all the existing tools were built for supporting a B2C product.”
Kshitij Gupta, Co-founder and CEO, 100ms
