Conversational Customer Service: A Detailed Guide

What is conversational customer service?

Conversational customer service is a strategy focused on establishing customer connections through natural conversations. Technologies like artificial intelligence (AI) and machine learning (ML) are deployed to understand customer intent and provide responses that mimic human conversations.

You can use chatbots and voice-based technologies to have conversations with customers.  

As more and more customers expect brands to go beyond transactional relationships, conversational customer service helps improve customer engagement and retention.  

Let's find out how it can benefit the brands and customers and what brands can do to implement it.  

But before that, let's understand why moving away from traditional customer service is important.  

Traditional vs. conversational customer service

Traditional customer service is typically rigid. Agents follow pre-written scripts or workflows, which can limit their ability to respond to customer needs in a personalized or empathetic way. Conversational customer service uses technologies like artificial intelligence (AI) to create natural and engaging interactions between customers and businesses. Take a look at the following example.

Other aspects make conversational customer service more effective than the traditional one. 

Benefits of conversational customer service 

Customers expect prompt and efficient service. Conversational customer service can help you meet these expectations by providing customers with immediate access to information and support. It can automate repetitive tasks and aid customer service agents in being responsive and delivering a smooth experience to customers. 

Conversational customer service can also help you in: 

1. Improved customer service

Conversational customer service is a more convenient and engaging way of delivering customer service.

It allows customers to engage with your agents using their preferred customer service channels, such as chat, messaging, or social media. They can interact with your agents or chatbots on their own time without having to wait on hold or navigate complex phone menus.

More importantly, technologies like AI and ML-based solutions conversational customer service solutions can help your agents understand customer preferences and provide tailored support experiences. For example, it can remember a customer's past interactions and provide relevant information or recommendations.

2. Reduced costs

Gartner predicts that tools like conversational AI can reduce labor costs by 80%.

Conversational customer service can reduce costs for brands in a number of ways:

• Reduced labor costs: Conversational customer service can be used to automate many of the tasks that are currently performed by human agents. This can reduce the overall cost of labor.

• Reduced training costs: Tools like conversational AI can be trained to handle a wide range of customer queries, thus saving the cost of training new agents. 

• Increased customer satisfaction: In addition to these direct cost savings, conversational customer service can also lead to indirect cost savings by improving customer satisfaction and reducing the dependency on customer support. 

 Also Read: How to Use Conversational AI for Customer Service  

3. Shorter response time 

75% of customers demand instant service within five minutes of online contact. This is where conversational customer service helps. Conversational customer service tools, such as chatbots and virtual assistants, can be used to provide customers with immediate support. These tools are available 24/7 and can answer a wide range of questions, sometimes without the need for human intervention. 

Learn more: Tips on Improving Customer Response Time with AI 

4. Improved agent efficiency 

Customer service agents often get boggled by the sheer volume of customer queries. It leaves them with little time to focus on high-value tasks, such as building relationships with customers and providing personalized support. It also takes a toll on their efficiency. 

Conversational customer service can automate the customer service process through options like self-service. For example, you can give customers access to a knowledge base and other resources. This can reduce service interactions by 40-50% and reduce the cost-to-serve by 20%. 

Options like customer service automation and self-service can reduce the volume of queries and help agents manage their tasks more efficiently. 

5. Reduced customer churn 

Customer churn is a major concern for brands, regardless of their size.  

• Customers may choose to switch to a competitor if they are dissatisfied with your service. This can significantly impact your business's revenue. 

• Several factors can contribute to customer churn, including poor customer service, lack of personalization, and lack of engagement.  

• Poor customer service is a major factor that drives customers away. Long wait times, unhelpful or rude agents, and unresolved issues can make customers feel undervalued and dissatisfied.  

Conversational customer service can solve this problem. It can help your agents provide personalized responses to customer queries by using customer data to tailor responses to their individual needs. For instance, an agent could use a customer's purchase history to recommend products or services they are likely interested in. 

It can also help agents have more interactive conversations with customers using solutions like chatbots and virtual assistants and improve the experience.  

Leverage conversational service to your advantage to stop customers from leaving. 

Also Read: 7 Proven Ways to Reduce Customer Churn Rate  

Tips to improve conversational customer service

Mere implementation of conversational customer service is not enough. You need to improve it continuously to ensure it delivers the expected results. This could include tracking metrics, using tools to deliver stellar customer service, analyzing customer sentiments and improving conversations.  

Here's how you can improve the quality of conversational customer service.  

Use AI tools to be more responsive

Conversational tools are AI and ML-powered. They automate repetitive tasks like scheduling callbacks and messaging that improve customer response time. They also personalize interactions to enhance customer experience. 

Use these tools to understand the customer's needs, analyze customer patterns and identify opportunities to cross-sell and upsell new products and services.  

Take the example of Aramex. This Dubai-based logistics and transportation solutions provider uses AI chatbots to automate chat conversations and serve customers quickly and efficiently.  

Tools like these simplify your agents' work and transform the customer experience.  

Download Free Report: 3 Steps to Transform Your Customer Experience with AI-Driven Insights 

Identify the metrics to measure

Every successful brand monitors a set of Key Performance Indicators (KPIs) to measure customer satisfaction. For example, metrics like customer satisfaction score (CSAT), net promoter score (NPS), and average handling time (AHT) help measure customer service efficiency. 

• Identify the key customer service metrics that can help you improve customer service and measure them regularly. 

Not sure what metrics to measure? Start with these 21 customer service metrics 

Analyze conversations and make improvements 

Tools like conversation analytics use natural language processing (NLP) and ML to analyze customer interactions across email, chats, voice and social media.  

Use these tools to understand customer sentiments and preferences and personalize support. This will help your agents improve customer service and increase customer success scores.  

You can also use the insights gained to improve agent training and enhance the quality of customer service.

Brands like Cdiscount use analytics to review conversations. It helps them understand customer sentiments and measure the quality of interactions to train agents accordingly. It has helped Cdiscount improve its CSAT score by 15%.

Read the full story here. 

Train customer service agents to be more effective 

While you rely on AI and ML to enhance customer interaction, don't give up on the customer service agents.  

Train them on these new tools, introduce them to the new workflows and help them adapt to conversational customer service. This is especially important for tenured employees. Bridging the skills gap is crucial to improve their skills and performance. 

Monitor their progress and provide them with feedback and resources to improve their efficiency. 

Also Read: Using AI Scoring in Contact Centers to Tailor Agent Training Programs

Keep the interaction humanized 

Remember that the purpose of conversational customer service is to augment the role of human agents and not replace them.  

Keep the interaction human. Even customers don't prefer talking to chatbots.  

Encourage the customer service agents to keep the interaction conversational and free. Nudge them to use workflows to automate interactions but avoid using scripts while interacting with customers. This will help them understand the customer's problems better and solve them more efficiently. 

How to implement conversational customer service

We now know how conversational customer service can reduce churn, improve agents' efficiency, and save costs. Let's learn how to implement it in your company to boost customer engagement and retention. 

🤝Step 1: Align all key stakeholders 

Conversational customer service is a new concept. Hence, you must align all key stakeholders and reach a consensus before implementing it. Speak to the operations and product teams, subject matter experts and customer service agents to identify customer query scenarios. Discuss the best ways to manage such scenarios and train the agents and chatbots. This will help your agents to deliver superior customer experience. 

🔧Step 2: Choose the right tech stack 

You cannot have conversations with customers without the help of the right tools and platforms. Choose the ones that are: 

• Easy-to-use 

• Armed with emotional intelligence to detect customer sentiments and respond with empathy 

• Allow consistent cross-channel collaborations 

• Improve response speed 

 🔖Step 3: Structure and label your data 

If you use AI and ML in conversational customer service, you must structure the unstructured and semi-structured data. This will allow you to categorize the data, label it and train the AI model. By structuring and labeling the data, you are helping the machines understand it. This will help the AI model to respond to customer queries efficiently. Once the model is ready, integrate it with the workflow and get started. 

Also Read: Customer Service Analytics – A Comprehensive Guide

📍Step 4: Map your customer journeys 

According to McKinsey's research, more than half of surveyed customers use three to five channels to purchase or raise queries during each journey. For example, a customer will switch nearly six times between a mobile app and a website before booking an accommodation.  

A customer journey map will help you identify the possible touchpoints a customer could use to interact with the brand. This will help the agents understand the customer's journey and give them the context to serve the customers efficiently.  

📣Step 5: Personalize customer communications 

Customers get frustrated when the responses are not contextually relevant. It's important to understand the context and tailor the interactions accordingly.  Use tools that help you understand the customer's profile, view previous transactions and analyze the customer's sentiments. It will help you personalize the responses.  

🤖Step 6: Keep training your AI models 

Machines, like humans, need continuous training to improve efficiency. AI models can become redundant if they are not fine-tuned and maintained up to date. Hence, monitor the AI models regularly. This will help you identify biases, integration issues and security risks. You can also label new data and retrain models to improve accuracy and customer experiences.  

Final thoughts 

Brands are realizing the significance of conversational customer service in retaining customers, reducing agent costs and improving profits. If you are planning to transition from traditional to conversational customer service, remember to: 

• Bring all stakeholders together to shortlist various customer service scenarios and train agents and AI models 

• Choose the right tools like conversational AI and conversational IVR to automate customer service and make it more conversational 

• Train agents to use these tools and adjust to new processes 

• Structure and label data to train the machines 

• Define and monitor KPIs regularly to improve customer satisfaction 

• Train the AI models to ensure they are compliant and updated 

All these steps will help you get started on the journey of adopting conversational customer service.  

If you are looking for tools to implement conversational customer service, sign up for our 30-day free trial. We set up your conversational customer service from the ground up within minutes so you can start conversing with your customers across 15+ channels.

Alternatively, you can request a demo to experience Sprinklr's solutions first-hand.