Conversational AI for customer service: Redefine how you support customers
Revolutionize customer service with conversational AI. Enhance efficiency, personalize interactions, and provide 24/7 support seamlessly.
Introduction to conversational AI for customer service
Conversational AI is a type of artificial intelligence that enables machines to understand written or spoken language from humans and respond naturally. Powered by natural language processing and machine learning, conversational AI machines are built to grow smarter and mimic human dialogue better with each interaction.
Because of this, conversational AI chatbots, voicebots, and smart assistants have become the go-to customer service solutions for modern businesses. Brands that build their conversational AI assistants on customers’ favorite channels, including messaging apps and smart home devices, are the golden example of meeting customers where they are with fast, personalized service.
And giving customers the option to receive support at any time of day and on any channel or device has proven to be a key advantage in higher customer satisfaction and brand loyalty.
Benefits of conversational AI in customer service
Conversational AI has sprung customer service forward, with machine technology that mimics human behavior – bringing many benefits for businesses and customers.
And when coupled with a powerful communications platform, the horizons only grow wider.
24/7 availability
Set up always-on support and be ready to assist customers at any time of day, increasing satisfaction.
Automated routine tasks
Offload tedious, repetitive queries from agents to give them more time to focus on complex customer needs.
Multilingual support
Connect with a global audience in an efficient and respectful manner.
Cost savings
Reduce staffing, training, and turnover costs with automation.
Data analysis
Tailor responses and future recommendations, while giving agents better insight when resolving a complex case.
Free agents
A chatbot or voicebot can sort and prioritize requests to route customers to the appropriate agent for their request.
How conversational AI is enhancing the customer service industry
Conversational AI is reshaping customer service by making it more efficient, responsive, and personalized.
When used with an omnichannel communications platform, businesses can empower their smart assistants even further through:
Omnichannel support
Adding conversational AI to the various channels your customers use enables you to provide a connected experience that doesn’t end after the first chat or call. Customers can contact your smart assistant on one channel and continue the conversation with them or an agent on another that is more convenient for them.
Intelligent routing
The data collected through conversational AI is stored and sorted to help your chatbot or voicebot route customers to an agent that is best fit to resolve their query. For example, if a customer contacts you to return a shirt and then contacts you again to ask for an update on the return, your assistant will know to try to redirect them to the same agent that helped them initiate the return.
Predictive analytics
The more your smart assistant interacts with your customers, the more it learns about their changing interests and needs. The data it collects and sorts from these conversations helps your smart assistant consistently create tailored responses and recommendations. It also helps your marketing and sales teams fine-tune campaigns and messaging to better resonate with each customer segment based on their previous interactions.
Agent takeover
Connecting your conversational AI to your contact center enables your agents to seamlessly takeover the conversation when necessary. For example, if a customer tries to renew their subscription but they also want to discuss their last bill with an agent, your smart assistant can complete the renewal and transfer them to an agent, all within the same conversation.
Key features and capabilities of conversational AI platforms
Setting up conversational AI solutions through a platform like Infobip enables human-like interactions to connect to every other part of your business – including your customer service, marketing, and sales teams. Seamless transfers between machines and agents become a reality, and words like “scalable”, “economical”, and “personalized” start to stand behind your brand.
Although conversational AI platforms have a lot to offer, there are a handful of key features and capabilities it should contain to be able to build a successful customer service experience, including:
Implementing conversational AI in customer service strategy
There’s more to implementing conversational AI in customer service than meets the eye. That’s why it’s important to map out a detailed strategy to ensure you see the results you hoped for. Here’s an example of what your conversational AI implementation strategy might look like.
step 1
Define your business objectives and align with customer needs
The first step in any strategy is to determine what you want to achieve. Is it to reduce response times, improve customer satisfaction, or increase efficiency? Maybe it’s all of the above. Regardless of what your specific goals are, it’s important to understand your customers’ expectations and pain points so you can tailor your AI solution accordingly.
step 2
Identify use cases that will help you reach your goals
Most brands already have the data they need to fuel their AI. A good place to start is to review historical customer service interactions to identify frequently asked questions and common issues.
Then, group them into categories, such as account inquiries, technical support, and billing questions. From there, you can rank your use cases based on factors like frequency, complexity, and impact on customer experience.
step 3
Choose the right technology
We already mentioned the key features and capabilities you should look for in your conversational AI platform. Being clear on what you want to implement, whether it’s a chatbot or voice assistant, is a good first step when looking for which platform fits your business needs. Other factors to consider include its ability to integrate with existing systems and the extent to which you can customize its content and functionalities to fit your brand.
Having a responsive support team can also ensure you use the platform to its utmost advantage.
step 4
Design your conversational flow
Developing customer segments and profiles will help your conversational AI personalize interactions from the start. It’s also helpful to consider multiple user inputs and potential responses for each use case, and plan for scenarios where your AI cannot resolve an issue, so they escalate to a human agent.
step 5
Develop and train your AI
Now it’s time to collect historical data, FAQs, and relevant content to train the AI model. A well-structured knowledge base ensures that the AI provides consistent and accurate responses. As the volume of customer interactions grows, a knowledge base allows the AI to scale effectively and handle more queries without compromising quality.
To ensure the AI can understand and process natural language inputs effectively, it’s best to test it in controlled environments, gather feedback, and refine its responses.
step 6
Launch and promote your AI assistant
Before launching your AI assistant to your global audience, first test it with a small audience to monitor performance and gather insights. Use this customer feedback and analytics to make improvements. It’s also important to train your customer service agents on how to collaborate with your AI tools to handle escalations.
Once your customer service AI assistant is up and running, it’s time to promote it through digital marketing campaigns. Try pop-up messages or banners within your app or website or implement interactive guides that walk users through using the chatbot.
step 7
Monitor performance and scale as needed
After your customer service AI assistant has been active for some time, it’s time to monitor its interactions and performance. Continuous optimization enables the AI to learn individual customer behaviors and preferences – leading to more personalized interactions.
Interaction data can also reveal gaps in the knowledge base or areas where the AI struggles, which allows you to update the knowledge base or refine the AI’s capabilities to handle specific queries more effectively.
Best practices for deploying conversational AI in customer support
Focusing on user-friendly interactions, data privacy, clear escalation paths, and continuous improvement will create a robust support system that enhances customer satisfaction and fosters long-term loyalty.
Choosing the right conversational AI platform
Choosing the right conversational AI platform involves careful consideration of scalability, integration, customization, and overall value. By investing in a robust platform, you can ensure your conversational AI meets your current needs and adapts to future growth, meeting your customer and business needs.
Scalability
As your business grows, so will your customer interactions. Choose a platform that can scale with your needs. Look for platforms that can handle increased volumes without compromising performance, and that can accommodate a growing user base.
Integrations
Seamless integration with existing systems is vital for a smooth customer experience. Choose a platform with well-documented APIs that can easily connect with your CRM, helpdesk software, and other tools – preferably one that enables quick set up without extensive development.
Customization
Look for platforms that allow the customization of conversation flows, branding, and responses to create a personalized experience for your customers. A platform that supports adaptable natural language processing can be fine-tuned to understand your specific industry terms and customer preferences.
Retrieval-augmented generation (RAG)
Retrieval-augmented generation (RAG) enhances the capabilities of conversational AI by incorporating current information from external sources. This ensures that responses are not only current but also tailored to the user’s specific needs, ultimately enhancing the reliability and effectiveness of the AI.
Analytics
Having access to powerful analytics tools that help you track performance, gather insights, and make data-driven decisions will ensure you can optimize your AI to continuously meet customer and business needs.
Support
Setting up conversational AI for customer service can come with its challenges. Look for a platform that offers comprehensive support including onboarding, training, and ongoing assistance to help you succeed.
Multilingual support
Your conversational AI platform should offer extensive language options, allowing you to engage with customers in their preferred language – minimizing barriers and enhancing user experience.
Case studies: Successful implementations of conversational AI
How to overcome challenges in implementing conversational AI
Implementing conversational AI can bring significant benefits, but it’s not without its challenges. Here are a few common barriers and how you can overcome them:
Challenge
Solution
Challenge:
Language barriers: Many organizations struggle to cater to diverse customer bases with varying language preferences and dialects.
Solution:
Implement regional dialect support and multilingual capabilities in your AI. This allows the system to understand and respond in the language and style preferred by different user groups.
Challenge:
Privacy concerns: Customers are increasingly wary of how their data is handled, making privacy a significant concern.
Solution:
Establish strong data protection measures that comply with regulations like GDPR or CCPA, and clearly communicate your data handling practices to customers.
Challenge:
System integration: Integrating conversational AI with existing systems can be complex and time-consuming.
Solution:
Collaborate with expert IT teams to ensure smooth integration with your CRM, helpdesk, and other critical systems – and use well-documented APIs to simplify the process.
The future of conversational AI in customer service
The landscape of conversational AI in customer service is rapidly evolving. As technology advances, we can expect to see innovations that enhance user experiences and redefine customer service, including:
Multimodal interactions
We will see a shift towards multimodal interactions, allowing customers to communicate through various channels—text, voice, video, and even chatbots within augmented reality (AR) or virtual reality (VR) environments. This flexibility will create richer, more engaging customer experiences.
Emotional intelligence
As AI becomes more sophisticated, the integration of emotional intelligence will allow systems to recognize and respond to human emotions. By understanding customer sentiments, AI can tailor interactions in a way that feels more empathetic and supportive.
Personalization and context
The importance of personalization will only grow. AI will leverage data to provide context-aware responses, creating highly tailored experiences based on individual customer histories and preferences. This level of customization will deepen customer loyalty and satisfaction.
Find out how to create exceptional conversational experiences
TrueBusiness: Empowering Thai businesses with omni-conversational experiences
Discover how businesses can meet customer expectations with conversational experiences by leveraging the partnership between TrueBusiness and Infobip.
Conversational AI for sales: The future of selling
Transform your sales and enhance customer experiences with Conversational AI. Boost efficiency and embrace the future of selling with Infobip.
Chatbots vs. conversational AI: Exploring the differences
Discover the differences, benefits, and uses of chatbots and conversational AI to transform your business and enhance customer engagement.
How Carrefour is transforming the shopping experience with conversational retail
Carrefour is leveraging conversational retail to transform the way we shop. Dive into the new era of customer service and personalized interactions.
What is conversational AI? Examples and how it works
Get a grasp on what Conversational AI actually is, with examples how it improves customer engagement and streamlines business operations.
Integrate conversational AI chatbots: A how-to guide
Learn how to integrate conversational AI chatbots seamlessly with your platform to elevate your customer engagement and automate support.
