Getting started with conversational AI for customer service

You have two callers on hold, a refund request in your inbox, and a team member asking if you can take a follow-up. It’s also 6:58 on a Friday night. You don’t want customers to wait, but you’re also, well, human.

That’s why many fast-growing customer service teams opt for conversational AI: to help keep up with support as call volumes grow. These always-on AI assistants help handle incoming customer requests 24/7. Plus, they help qualify leads and schedule appointments so your reps can spend more time on other tasks. 

In this guide, we’ll cover:

• What conversational AI tools are and how they work
• Types of conversational AI tools
• Benefits of using conversational AI for customer service
• How to get started with conversational AI for customer service

What is conversational AI for customer service?

Conversational AI refers to artificial intelligence tools that can engage in natural conversations with customers. Unlike traditional chatbots, it understands customer intent and asks follow-up questions.

For example, let’s say your customers want to learn more about your business. They can have a chat with a conversational AI tool to learn about your team’s certifications, your products and services, and more. They can ask follow-up questions and skip around the conversation as much as they want.  .  

Legacy AI chatbots, on the other hand, only provide a few preset menu options. If you don’t use specific words or phrases, they may not answer you accurately.

Now, let’s apply this in a customer service context.

You can use conversational AI for customer service to help people like a human rep would. But you don’t need any actual human involvement. AI assistants can “read” incoming messages, answer FAQs, and complete tasks like booking appointments in real time.

Most software that offers conversational AI for customer service can help by:

• Offering 24/7 support: Virtual AI agents can respond to calls, texts, and voicemails 24/7. They can also take messages so your team can call customers back after they’ve returned to the office.
• Handling basic support requests: AI tools can handle routine conversations. For example, it can answer questions related to your business hours or directions to your office. That frees up your team to focus on more complex needs, like building better relationships with your customers.
• Managing rising call volumes: Conversational AI can engage multiple customers at the same time. This prevents your team from getting overwhelmed by high call volumes.

How conversational AI works

Three things happen when customers chat with conversational AI:

1. Speech recognition and natural language processing, or NLP: AI tools analyze customer inquiries to understand their requests. This is sometimes called natural language understanding, or NLU. If a customer speaks to an AI voice agent instead of a chatbot, the agent uses speech-to-text software to analyze the speech more quickly.
2. Complex reasoning: AI systems use APIs, machine learning, and other similar functions to “think through” the request. It may search through a knowledge base to answer complex queries. Or it might sift through customer data to provide more personalized responses.
3. Generating a response: To respond to customer queries in a natural way, AI tools rely on large language models, or LLMs. If you’re using a voice agent, it’ll convert text into speech to talk to customers using text-to-speech software, or TTS.

The best part about conversational AI for customer service is that it can generate responses quickly. It has low latency, which means it can send responses quickly. Your customers don’t have to wait long to talk to a conversational AI agent.

6 conversational AI for customer service use cases

Here are six conversational AI use cases for customer service teams:

1. Answer basic support questions

You can train conversational AI tools to answer basic support questions autonomously. That way, routine questions like business hours and service options get resolved within minutes. Customers don’t have to wait for reps, and your team can deliver faster service.

One way to do this is with Sona, an AI voice agent by Quo, formerly OpenPhone. Sona can be trained on your company’s documentation. Simply share your website URL, upload your policies, or manually create knowledge pages to train it. You can then test how it answers questions about your business before assigning Sona to your calls. 

Another option is to use AI support chatbots. Quo, for example, uses a chatbot from Ada in our product to help customers quickly answer common product questions. We use Ada conversations to help us understand where customers need additional help in our Resource Center. If several customers run into the same issue, we create additional Resource Center content so they can get the answers they need quickly. 

2. Handle incoming calls after hours

Conversational AI agents can answer incoming calls, even when your team isn’t working. Case in point: businesses using Sona go from missing 70% of customer calls to less than 10% on average.

You can set up an after-hours call flow where Sona picks up the phone before customers go to voicemail. It can answer basic questions, take down customer details, or transfer urgent calls to a dedicated after-hours phone number

Having an AI receptionist answer the phone keeps your customers in the loop. It helps improve customer satisfaction and makes them feel valued. 

3. Automatically send relevant information

AI agents can text relevant information to customers so you don’t have to manually follow up later. They can send appointment booking links or website URLs with additional information. 

For example, a restaurant’s AI agent can text a link to a seasonal menu when a customer asks about holiday catering. Or a home service company’s AI agent can text a link to an updated list of products and services. If you manage an insurance agency and use conversational AI for insurance, you could text a link for policy renewals.

Sona’s Send SMS action makes this easy by triggering helpful texts based on your caller’s requests. You can add the action to your custom jobs in Sona’s settings. Just be sure to collect your caller’s consent to text them. 

Watch a quick demo of the Send SMS action: 

4. Take down messages for callbacks

Conversational AI tools can collect customer details when your team is busy or unavailable. Team members can call back with full context about the customer’s issue. This saves time and ensures customers won’t have to repeat themselves.

If a customer wants to report an issue, Sona can use a checklist to gather the necessary information. You can instruct it to ask, “How have you tried to fix the issue so far?” or “How urgent is your request?” That way, your support team can prioritize callbacks and assign the right people to the right requests.

5. Escalate calls to the relevant department

Conversational AI can’t answer every question and fulfill every customer request. That’s where it can escalate calls to your team.  In Quo, Sona uses intelligent call routing to transfer calls to a specific team member or shared number.Sona can determine when to transfer a call based on the caller’s request. Use the Transfer call action in your Sona jobs to inform it when an escalation is required, like a billing issue. Sona will automatically transfer calls to the right team member or department.

6. Identify call trends to improve team performance

Conversational AI can help you learn from your past calls. With Quo’s AI call tags, you can automatically organize calls by their content. Create custom tags to track recurring issues or opportunities for your business.  That way, teams can quickly spot call drivers without having to manually listen to hours of calls.

Managers can use call tags to provide more targeted coaching to teams. Filter your calls by team member and identify which calls impact their performance. You can then refine scripts, run call review sessions, and monitor results over time. 

That’s how Brandon Ingram, Sales & Operations Manager at Environment Control, uses AI call tags:

“Call tags have been a game-changer for efficiency! They’ve made it super easy to sort through calls and quickly identify important conversations, which has significantly sped up my workflow. I also appreciate how they improve communication with my team by providing a clear context for each call.”

Benefits of conversational AI for customer service

Conversational AI tools offer several benefits for customer service teams:

1. Improve customer experience

Better customer experiences start with faster response times. But 24/7 coverage and consistent performance certainly don’t hurt. With customer service AI, customers don’t have to stay on the phone or wait for your callback service. They can get help right away, with accurate answers every time.

A great real-life example is Loop Earplugs, which was growing so fast that reps couldn’t keep up. It took five or six days for most customers to receive a reply. So Loop turned to Aura, an AI chatbot managed by Ada, to help manage chat, email, and social media messages.

Aura handles the workload of 25 full-time employees, reducing customer wait times to a max of two hours. Loop quickly saw other benefits as well, including:

• 194.52% faster response times
• 357% return on investment
• 80% customer satisfaction score

Conversational AI made it possible for Loop to reduce the number of customer support tickets assigned to human reps by 33%. What’s even more impressive:they did it while sales increased by 400% over two years.

2. Increase team efficiency

With conversational AI bots, your existing team can serve more customers in less time. You also don’t have to increase your headcount to grow your business. 

That’s what JetBlue did when it created an AI chat tool for customers. The US airline’s contact center saved 73,000+ hours of rep time in three months, averaging about 4.5 minutes per chat. This freed up its team to focus on other tasks. 

3. Designed for scalability

Conversational AI optimizes your operations for scalability. As your support volumes grow, you can respond to new customer requests without missing a beat.

It also doesn’t require training or a ramp-up period to perform consistently. With Sona, you can train your AI in minutes. You can easily add, update, or change information whenever the need arises.

If you only have a team of live virtual receptionists or you outsource customer support to a call center, you’ll need time to train and ramp up each rep. This process can take weeks, or even months. Conversational AI offers a more scalable support solution for fast-growing businesses. 

4. Grow customer retention

Higher customer service, or CSAT, scores usually mean customers want to stay with your business. 

As you’ve likely seen, some of the biggest drivers of high CSAT scores include:

• Easy interactions
• Fast responses
• Accurate information

With 24/7 call coverage and quick response times, conversational AI tools can keep your customers engaged every time they reach out. They help reduce wait times and callbacks and increase your customer satisfaction.  

5. Reduce operational costs

Conversational AI tools are a fraction of the cost compared to hiring reps as your support volume grows.

For example, AI virtual receptionists cost between $0 and $200 per month. Live virtual assistants, on the other hand, can cost between $300 and $2,000+ per month.

This can add up to significant cost savings over the years. For instance, a Gartner survey found AI agents can save up to 30% of your operational costs. 

Types of conversational AI tools

There are five main types of conversational AI tools available to customer service teams:

1. Traditional chatbots: Legacy chatbot systems that respond to keywords with pre-programmed responses. You may hear them referred to as static chatbots since they can’t dynamically respond to customer input. They can only handle a few types of customer interactions. For example, they can send links to refund policies or auto-submit tickets.
2. Generative AI chatbots: Modern AI-powered chatbots that use LLMs to respond to customers. This includes tools like ChatGPT and Claude. They’re best used to help your teams synthesize data and spot trends in calls.
3. AI-powered voice agents: Advanced AI voice agents that handle customer support calls  on their own. One example of this is Sona, Quo’s AI voice agent. Sona can answer questions, take messages, and transfer calls to your customer support reps.
4. Voice assistants: Basic voice assistants that respond to voice commands. These can complete simple tasks like setting reminders or searching for emails. Some of the most popular examples of voice assistants are Alexa, Siri, and Google Assistant.
5. Interactive voice response, or IVR, systems: Intelligent IVRs that use voice AI to understand customer needs. Customers dial or speak their menu option, and are then routed to the appropriate team or team member.

How to get started with conversational AI for customer service

Now that you know how conversational AI works, here’s how you can implement it in your business.

1. Create goals based on customer needs

Instead of starting with what you think customers need, work backward from their perspective. Figure out the problems automation solves for them rather than for you. That way, your team can deliver a five-star customer service experience.

Start by analyzing your customer support tickets. Connect your business phone with Claude or ChatGPT. With Sona, this can be done via Quo’s Model Context Protocol, or MCP.

Now you can ask the AI tools what your most common support requests are. This can give you more data on how to train your conversational AI agent to have the most impact. 

Let’s say the majority of your support tickets are callers wanting to book a consultation with your team. This is one use case you’ll want to prioritize for your AI agent. Here’s an example from our co-founder Daryna:

2. Identify the right conversational AI tool for your business

Choose the right conversational AI tool, depending on where your support team does most of its work. 

If you primarily offer phone support, an AI voice agent is a better fit. But if you offer web-based chat, an AI chatbot is a better option.

What if you offer omnichannel customer service? The solution is to set up a chatbot and an AI virtual receptionist. You can connect both systems to your CRM and keep track of your customer interactions. 

3. Run a pilot with a subset of customers

Before you flip the switch on your conversational virtual agent, test it with a subset of your customers. We recommend starting with around 5% of your customer base. Then, scale up as you become more confident in the tool’s performance.

One way to test the performance of your conversational VoIP AI tool is to let it tackle after-hours calls first. Once you’re satisfied with how it performs, you can start testing it on calls during business hours. 

4. Measure success with customer-centric KPIs

First, decide on the outcomes you want for your support team. This might be faster response times or higher resolution rates. Then decide which customer-focused metrics to track. Customer satisfaction scores and customer engagement metrics are usually a good place to start.

Run a pilot of your conversational AI, then review the data to see how it went.

For quantitative info, you can review your call analytics. For example, in Quo’s call views, you can see how many calls were handled by Sona vs your team.. For qualitative data, gather feedback from customers and your team. Is conversational AI helping your team or causing challenges?

Rinse and repeat to work out the kinks.

5. Test your conversational AI tools as you scale

As your business grows, so will your AI use cases. That means you’ll want to make sure it keeps responding correctly to various customer scenarios.

You’ll want to make sure that:

• The tool’s tone matches your business
• Its messaging and actions are still accurate
• It follows your rules for specific situations

With Quo, you can easily test Sona inside our call flow builder. That lets you make some demo calls before going live. When you’re happy with your changes, just click Publish. You can keep monitoring its performance with our call recordings and AI call transcriptions.

Move faster using AI with Quo

Conversational AI makes it easy to scale customer support without losing your human touch. With Quo, you can answer simple questions and automate routine tasks with our AI agent, Sona, available with every plan.

Small and growing businesses rely on Quo to communicate with customers and build better relationships. But you get a lot more than Sona to help with customer service:

• Review past calls faster with AI call summaries and transcripts.
• Catch ongoing call drivers consistently with AI call tags. 
• Add new contacts to your address book automatically with AI-suggested contacts.

See why 90,000+ businesses trust Quo as the conversational AI platform for customer service teams.

Try Quo and Sona free for seven days.

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