5 ways to improve customer response time with AI

Modern customers expect instant responses, and businesses must act with velocity to resolve complaints and retain customers.

And, the room for error has reduced. Customer service teams must constantly be on their toes because a late resolution is seen as a 'no resolution'. Every moment matters, and customers expect an instant update on any query or problem they face.

What does this mean for customer service teams, and how can they keep up with this new wave of customer expectations?

Let’s find out.

How customer service response time impacts revenue

There is a direct correlation between customer service response time and customer retention. But first, let’s understand what customer service response time means when we talk about customer issue resolution.

What is customer service response time?

Customer service response time is the time between the customer registering a complaint and the first response from the brand on the complaint. The response can be provided by a human agent, or it can be done by a chatbot.

Reducing response times and responding to your customers with helpful and relevant information is the key to a good customer experience. Happier customer come back and buy more from the brand.

According to customer service executives, the biggest customer service challenge they face is slow response times. When contact centers address issues on the first call, only 1% of customers say they will likely go to another business. But most of the brands fail to meet this expectation due to conventional systems which do not give the right data and tools to agents to respond faster and accurately. Poor customer service costs businesses up to $75 billion in the United States alone.

AI capability checklist to reduce customer service response time

Before adopting AI to reduce your customer response time, you must first understand how well your contact center is equipped. A good starting point would be to ask yourself a few questions.

How AI helps in improving customer service response time

The reality of contact centers is that you need to look at each customer, understand their individual experience, and identify precisely where you can deliver efficiencies and add intelligence. But this isn’t easy, given the enormous amounts of data.

This is where AI comes into the picture. AI can help drastically improve response times by providing near real-time feedback to customer queries and working side by side with agents to understand the intent and sentiment of the customers. Let’s understand how.

1. Intelligent self-service

The best way to reduce the response time is to enable your customers to solve their own problems. Customers prefer taking a first stab at their issues before contacting a contact center.

Chatbots and voicebots may be the most visible use of artificial intelligence (AI) in the customer service process. When customers choose to chat online with a business, chatbots greet them, collect some background information, and try to solve the customer's issue.

With chatbots and voice bots, organizations are able to provide personalization at scale, 24/7 instant replies, asynchronous communication, and mobility across channels — serving them anywhere and at any time. With agent-to-bot and bot-to-agent routing within a customer conversation, there can be self-service moments within human agent conversations as well for use cases like performing customer authentication, accessing billing information, and performing first level triaging.

2. Agent assist (Human + AI)

A unified agent desktop, powered by AI enhancements gives superpowers to human agents. It ensures that the agent has the relevant customer history and previous case summaries, preventing the agent from asking for information multiple times, especially when the call is transferred or escalated.

AI also provides the agents an intent summary on why the customer is calling along with customer sentiment to ensure the agents tune their responses accordingly. Moreover, AI offers suggestions from knowledge bases, similar cases, and auto-suggests responses tailored and personalized to a specific conversation, reducing the time the agent spends in researching and typing out a response.

It offers integrations with other systems like CRMs via APIs to automatically complete the customer request (eg. renewing/canceling a plan) by recommending the correct workflow based on the conversation.

3. Conversational analytics

A contact center’s speed of response depends on millions of variables. You can’t manage the variables with a spreadsheet—the data set is too big for humans to keep track of, and the data changes by the second.

AI can reveal relevant patterns in contact center conversations so you can confidently make adjustments. These adjustments would help you solve future cases faster and smarter.

AI-based tagging of emotions, sentiments, entities, intent, topics, and outcomes gives rich insights to improve customer experience in an omnichannel setting.

Apart from these use cases, AI can predict customer issues and suggest to customers that the contact center can proactively reach out to them at a time they are comfortable with based on experience.

4. AI-based smart routing

Matching the personality of agents and customers can reduce repeat calls by 40%. Smart routing allows businesses to route calls based on the caller’s online activity, their history with your company, their demographic information, or based on custom fields you create in the software.

For example, calls from people who have visited certain pages of a business website could be routed to a certain group of agents with expertise in that area. Customers short on time can be paired with efficient agents, while others who like to talk can be paired with agents who are extroverted.

Routing helps agents handle cases concurrently by ensuring the cases involving different levels of intensity are grouped to not overwhelm the agent, helping customers get a faster response.

5 Ways to Improve Customer Response Times — and Your Bottom Line

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5. AI-driven coaching

Large-sized contact centers face attrition. This, combined with increased call volumes, means that there is very little time to train new agents before they are needed to solve customer issues.

A contact center must ensure adequate agents with the right skill sets are present at the right time to handle customer issues without asking the customers to wait to ensure a good response time. All customer interactions are evaluated and scored automatically for quality, compliance, and behavior. AI automatically identifies areas of improvement for agents and recommends articles from the knowledge base, and courses for the supervisor to assign as a part of the agent’s coaching plan.

Insights from AI can be used to train agents in skills that are seen to be in demand, providing effective customer service without making the customers wait.

Real-time coaching of agents with prompts on response and behavior allows agents to get immediate feedback on customer interactions and shortens the training period before they can interact with customers.

To meet customer expectations in the modern age, you need smarter contact centers where agents and AI work hand in hand.

You can build leaner and more effective customer service operations fit for the digital age with Sprinklr Service. Start care earlier with AI-enabled listening, scale wider with self-service and automation, and use AI to supercharge your call center.

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