Consumers have become more accustomed to interacting with chatbots and virtual assistants. AI chatbots are a great solution to customer support. Scaling your business means the ability to provide support to different regions without compromising on quality. An AI chatbot builder platform can help you do just that. However, there’s a catch – if the conversation doesn’t flow naturally, people quickly lose interest and move on to something else. In this blog post, we’ll discuss how to design chatbot conversation flows for engaging chats that keep customers interested and result in successful outcomes.
What is Chatbot Conversation Design?
Designing chatbot conversations is crucial for making AI assistants more natural and helpful. Chatbot conversation design aims to address the challenges users face when interacting with AI bots, such as misunderstandings, failure to confirm issues, or the inability to personalize responses.
Chatbot conversation design involves setting up basic conversational structures like acknowledgment, confirmation, and prompts. It can be used in various areas such as customer service, marketing, sales, human resources, and online coaching.
When an AI chatbot truly understands what the user is trying to achieve, it can proactively solve their problems. AI chatbots integrated with LLMs like ChatGPT (from OpenAI) remove the need to train chatbots on conversations. These GPT chatbots are advanced enough to comprehend user responses and maintain the conversation flow.
How to Design a Chatbot Conversation Flow
A good conversation flow should enable the AI bot to understand the task at hand, be trained on users’ preferences, build trust to keep users engaged and help users overcome any obstacles in the chat. Salesforce gives the conversation design elements of a chatbot:
- Welcome message: first interaction that introduces the bot.
- Agent transfer: message before the human handoff.
- Conversation loopback: a confirmation before ending the chat.
- Closing message: a message with a clear call to action for the user.
- Error handling: a planned response to bot failure scenarios.
Let’s dive into some strategies to train your bot on a great conversation that is specific to your business needs.
1. Understand Your Customer to Foster Meaningful Relationships
Before you start designing chatbot conversation flows, spend some time studying your target audience.
- What are their preferences?
- What are their pain points?
- What kind of questions are recurring and can be easily automated?
Answering these questions will give you valuable insights that you can use to frame your conversation around their needs.
You can get more insights into user preferences by using this guide:
- Software Subscribers: Understand the plan they are on, or if they are new to your website.
- Online Retailers: Find out their purchase history or preferences based on their interactions.
- E-commerce: Identify big spenders and active users based on their time on your store.
- App Users: Select them based on their subscription start date and trial expiration date.
Multiple AI bots for effective customer support
By creating multiple AI chatbots, you can address various customer demands throughout their journey while also cutting down on operational expenses.
Active users want advanced support: Identify active users who frequently engage with your product and provide them with prompt assistance. Additionally, offer them personalized recommendations and exclusive discounts as incentives.
Introduce new products meaningfully to existing users: Capture the attention of users by showcasing new additions to your product lineup through engaging chatbot conversations.
Cater to company size and requirements: Customize chatbot conversations based on the specific needs and preferences of different organizations, adapting the experience accordingly.
Prioritize VIP customer issues: Quickly escalate and attend to any issues your VIP customers may encounter, ensuring their satisfaction and loyalty.
2. Don’t sell. Be natural.
Conversation flows should sound human and should not be forced. It’s essential to keep your chatbot’s tone according to your brand’s voice. As far as possible use simple direct language, and be concise. Avoid the use of jargons or complicated terminologies that might confuse your customers further. Moreover, when designing your conversation flows, simulate a real conversation between two people.
Confirm and empathize to gain trust
When chatting with AI bots, it’s totally normal to wonder if they “get” what we’re saying. It can feel awkward if we’re not sure they understand, right? That’s why it’s super important for AI chatbots to use warm and friendly confirmation techniques to show empathy and keep the conversation flowing. This technique, called mirroring, can help keep conversations flowing.
Chatbots should aim to be understanding and empathetic by summarizing or putting things in their own words. This lets users know their thoughts are being heard and makes it easier to keep the chat going.
Customer: I want to cancel my subscription, but your website keeps giving me errors.
AI without mirroring:
To cancel your subscription, please follow these steps…AI with mirroring:
I understand you’re trying to cancel your subscription and encountering errors on our website. That must be frustrating. Let’s resolve this together. Can you tell me which specific page you’re having trouble with, so I can guide you through the cancellation process?
This comparison demonstrates:
- Acknowledging the customer’s intent and difficulty
- Recognizing the emotional aspect of the situation
- Offering personalized assistance for a financial transaction
- Seeking clarification for accurate help
Expert Tip: To design prompts that naturally answer queries, it’s essential to have a clear idea of the user’s journey on your website. By documenting chat history and identifying common pain points, you can make conversations that help users. This approach enables you to provide personalized support, creating a frictionless user experience.
You can also use pre-built forms for lead generation and qualification that can be later used for personalized marketing and sales efforts.
3. Use a Logical Chat Sequence for a Consistent Customer Experience
For an AI chatbot, it’s important to provide logical guidance to customers. Your conversation should lead users step-by-step towards their desired outcome. To achieve this, you can create a roadmap that outlines the conversation you want to have. This roadmap should include various prompts and responses that are dependent on the user’s previous answers. By doing this, you can predict the user’s journey and help them reach their goal more efficiently. It’s crucial to keep this in mind so that customers feel guided and supported throughout their interaction with the chatbot.
Framing conversation to guide users
Every now and then, your AI bot might come across a question it can’t answer. When this happens, your chatbot politely responds with: “Sorry, I’m not trained to answer that.” Remember, your chatbot is here to handle all inquiries related to your business. That’s why it’s important to frame the conversation in a way that guides users. For instance, starting with “Hello, how can I help you today with product and pricing?” is more effective than “How can I help you today?” when it comes to customer support. This approach helps narrow down the range of possible questions and guides the users in a friendly and effective manner.
AI without framing:
How can I help you today?
…
Sorry, I’m not trained to answer that.AI with framing:
Hello, how can I help you today with product and pricing?
or
Hi, I’m Sam. I can help you with our catalogue, bulk orders, and delivery options. What would you like to know?
By framing the conversation around your business’s expertise, you reduce the chances of your bot encountering queries it can’t answer – providing a more satisfying user experience.
4. Personalization and Turn Taking in Conversation Design
Personalization is a key factor in designing conversation flows. You can collect data from your customers and use it to provide personalized questions and responses. For instance, if a user has visited your site before, you can start by asking them questions based on the last conversation. Personalization is crucial in designing effective conversation flows. For example:
AI: Welcome back! Last time, we discussed social media marketing tools. Would you like to continue exploring that topic?
For new customers or when the AI’s confidence is low, turn-taking with simple binary questions is an effective strategy to maintain conversation flow:
- Start with an empathetic response to build trust.
- Follow up with easy-to-answer binary questions.
- End each message with a question to prompt user response.
Example:
AI: Welcome to TechSolutions Inc. I’m here to help you find the right enterprise software. Are you looking for information on our products?
User: Yes, I am.
AI: Great! Are you interested in our cloud-based solutions or on-premise software?
User: Cloud-based, please.
AI: Excellent choice. We offer cloud solutions for various business needs. Is your primary interest in CRM, ERP, or data analytics?
User: CRM.
AI: Perfect. For our CRM, would you prefer to see a product demo or discuss pricing options first?
This example shows:
- A clear introduction of the bot’s purpose
- Use of binary questions to guide the conversation
- Progressive narrowing of the user’s interests
- Offering specific next steps based on the user’s responses
- Each message ends with a question to maintain engagement
This approach guides the conversation, collects valuable information, and ensures the user feels understood and supported. By combining personalization for returning users and clear turn-taking for new or uncertain situations, you can create more engaging and effective AI interactions.
It’s also important to personalize your AI chatbots according to different channels – whether it’s website, dashboard, or social media channels. This helps you to draw customers with high intent into your conversation.
5. Optimize With a Unified View of Chat Volume and Engagements
Conversation flows should be tested and optimized regularly to improve their effectiveness. Run tests and analyze chat data to see where the bottlenecks occur and then refine and optimize your conversation flow accordingly.
Unified processes, and insights into metrics like user engagement, time spent on your website, and conversion rates help you improve the chatbot conversation design.
Conclusion
AI chatbots are a great new tool for providing customer support. A chatbot conversation design that has a great flow for engaging chats can be challenging, but it’s worth the effort. A good conversation flow can help retain customers better allowing you to scale your business to new regions. The tips we’ve shared in this blog provide a solid foundation for designing conversation flows. Remember, understanding your customer, keeping it natural, using a logical sequence, personalizing the conversation, and testing and optimization are the keys to designing effective conversation flows. Keep these principles in mind, stay curious, and never stop experimenting.
