Chatbots, voicebots and conversation design for customer service
The better the technology, the better an organisation is able to achieve its goals and the greater the positive impact on both the customer and the employees. This also applies to chatbots and voicebots. These are ideally suited to contact centre applications, since they can deliver significant improvements in First Contact Resolution (FCR) – even outside of business hours – and because they facilitate self-service. In other words, they enable the customer to complete simple actions and processes themselves, allowing contact centre employees to focus on more interesting and complex cases.
“Sorry, I did not understand your question”
Despite the fact that they are of course computers, bots can help the customer in a personal way, and thus support the customer contact team. But that is not a given. How often does it happen that customers get stuck in a conversation with a bot, because it simply does not understand what is being said? That the customer – with a bit of luck – is still forwarded to a customer contact employee because the bot cannot help them further?
Human-like dialogue
Even though conversational AI and Natural Language Processing (NLP) are making bots increasingly capable of understanding human language and intentions, and of responding naturally, they are not one size fits all products that you can simply ‘switch on’. There is more to it. Bots must be programmed and trained so they are increasingly capable of speaking to the customer without a pre-written script. Designing these dialogues and flows – conversation design – is human work.
The basic principle is that a conversation between a customer and a bot flows as 'human-like' and as naturally as possible, so as a rule, customer questions for which the bot is designed are always resolved without the intervention of an employee. That is the power of conversation design.
Independent advice
DDM Consulting offers several solutions in which bots and conversation design are used for optimal customer contact, delivered by partners who are all specialists in their field. We give honest and independent advice about the possibilities of each solution, and we don’t hesitate to critically look at any limitations. This way we find the innovative technologies that best suit your organisation’s vision for the future.
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Frequently asked questions about chatbots, voicebots and conversation design
A customer service chatbot is a software application that automatically answers customer enquiries via chat, messaging apps or websites. Chatbots use predefined flows or artificial intelligence (AI) to simulate conversations and assist customers quickly.
In a contact centre, chatbots are typically used for:
- answering frequently asked questions
- supporting self-service
- handling simple customer requests
By using chatbots, organisations can reduce waiting times and ease the workload for agents. More complex enquiries are automatically transferred to a human agent, creating an efficient collaboration between technology and people.
The main difference between a chatbot and a voicebot lies in how customers interact with them.
A chatbot communicates via text, for example on websites, live chat or messaging apps. A voicebot uses speech and is typically deployed in telephone interactions or IVR systems.
Key differences include:
- chatbot = text-based
- voicebot = voice-driven
- chatbot = web and messaging channels
- voicebot = telephony and IVR
Both solutions often use AI to understand and respond to customer enquiries. Together, they form an essential part of an omnichannel customer contact strategy.
Conversation design is the process of designing effective and natural interactions between customers and chatbots or voicebots.
The goal is to create conversations that are intuitive, clear and user-friendly. This involves considering:
- customer intent
- conversation flow and structure
- tone of voice
- error handling and fallback scenarios
Well-designed conversations help customers quickly find the right answers without frustration. Conversation design is a critical success factor for AI-driven chatbots and has a direct impact on Customer Experience.
Chatbots are particularly effective at automating repetitive and straightforward customer enquiries.
Common use cases include:
- order status requests
- updating personal details
- opening hours and contact information
- frequently asked questions
- simple service requests
By automating these interactions, organisations reduce the workload for agents and allow them to focus on more complex enquiries. This improves both operational efficiency and customer satisfaction.
Chatbots improve Customer Experience by helping customers quickly and easily through digital channels.
Key benefits include:
- instant responses with no waiting time
- 24/7 availability
- consistent and accurate information
- support across multiple channels
Chatbots can also guide customers through their digital journey and help them find solutions independently. When combined with human support, they create a seamless and efficient experience across all touchpoints.
AI chatbots offer several benefits for contact centres by enabling automation and intelligent customer interactions.
Key advantages include:
- reduced operational costs
- shorter waiting times
- improved availability
- scalability during peak demand
- more efficient use of agents
AI chatbots can understand, analyse and respond to customer enquiries automatically. This allows organisations to handle higher volumes while enabling agents to focus on more complex and high-value interactions.
Chatbots are integrated with existing systems such as CRM platforms, knowledge bases and contact centre software to function effectively.
Key integrations include:
- CRM systems for customer data
- knowledge management systems for accurate answers
- ticketing systems for case handling
- contact centre platforms for routing
These integrations allow chatbots to provide personalised and up-to-date information. They also enable smooth handovers to human agents when needed, ensuring a seamless customer experience.
An effective AI chatbot implementation starts with analysing customer enquiries and defining clear use cases.
Key steps include:
- identifying repetitive questions
- designing conversations (conversation design)
- training AI models
- integrating with existing systems
- continuously testing and optimising
It is best to start small and expand gradually. By using data and analytics, organisations can continuously improve chatbot performance and ensure it aligns with customer needs.
Yes, chatbots often work alongside human agents in a hybrid model where technology and people complement each other.
Chatbots handle simple and repetitive enquiries, while complex or sensitive issues are transferred to human agents. This results in:
- more efficient processes
- shorter waiting times
- better use of agent capacity
This collaboration creates the right balance between automation and personal service, leading to an improved Customer Experience.
