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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
Automated routine tasks
Multilingual support
Cost savings
Data analysis
Free agents
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
Intelligent routing
Predictive analytics
Agent takeover
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.
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.
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.
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.
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.
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.
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.
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
Integrations
Customization
Retrieval-augmented generation (RAG)
Analytics
Support
Multilingual support
Case studies: Successful implementations of conversational AI
Podravka: Empowering users to make healthy choices with an engaging AI-assistant
-
18%
conversion rate to engaged user -
343k
messages exchanged in the first 90 days
LAQO Insurance elevates support with Infobip’s Gen-AI and Azure OpenAI partnership
-
30%
of queries are handled by the AI digital assistant -
90%
of queries are handled within 3-5 exchanged messages
Mediclinic: Boosting digital transformation with Microsoft and Infobip
-
30%
patients using chatbot for screening
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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
Language barriers: Many organizations struggle to cater to diverse customer bases with varying language preferences and dialects.
Privacy concerns: Customers are increasingly wary of how their data is handled, making privacy a significant concern.
System integration: Integrating conversational AI with existing systems can be complex and time-consuming.
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
Emotional intelligence
Personalization and context
Find out how to create exceptional conversational experiences
TrueBusiness: Empowering Thai businesses with omni-conversational experiences
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Chatbots vs. conversational AI: Exploring the differences
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How Carrefour is transforming the shopping experience with conversational retail
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What is conversational AI? Examples and how it works
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Integrate conversational AI chatbots: A how-to guide
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Set up your conversational AI assistant for customer service
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