Conversational automation is crucial to great customer support. An effective customer service chatbot can communicate with customers and answer important questions, streamlining the customer support process.
How to Understand Your Metrics When Building a Customer Service Chatbot
Containment rate, or its alternative name, “deflection rate,” is the percentage of total conversations fully handled by a chatbot, and is a key metric to track when trying to figure out how well your chatbot is performing. Customer satisfaction is also important. Keep in mind how the introduction of a chatbot could alter existing performance indicators. For example, will the average handle time increase now that agents are only handling more complex inquiries? Ultimately, a well-defined customer service chatbot program will be able to communicate increased agent efficiency and customer satisfaction, which equals a reduction in the cost of care.
Learn how to build a chatbot that makes communication easy with these six chatbot tips, and watch customer satisfaction skyrocket! Now, let’s explore how to build an effective customer service chatbot program.
1. Start With Hello
Your first customer service chatbot does not need to be elaborate. In fact, we recommend against it. When you are first getting started, pick one or two simple (but useful) use cases to automate. Then, you can learn and iterate as you discover how your customers prefer to interact with a chatbot. No one gets it perfect right out of the gate, so avoid wasting time by trying to build something “perfect”.
2. Leverage the Agent
We have seen countless customer service chatbot programs fail to engage the existing front-line customer service team when designing an automated conversational experience. It’s great to learn from data and prevailing customer experience research, but your customer service agents are the ones who know how your customers are interacting with the chatbot. Treat the bot like another agent: when you need performance feedback, use its peers.
3. Templates, Rules, and Machine Learning
Not all customer service chatbots are “conversational AI”, because not all use cases require machine learning. Very effective bots can leverage rules and simple conditional logic — it all depends on the use case. Similarly, natural language processing is great when you have a customer service chatbot with many different skills and a large corpus of knowledge.
Why make your customers trudge through structured flows when they can ask the question directly? In both cases, we recommend leveraging buttons, quick replies, and other conversational templates that help the user move through the conversation quickly and efficiently.
4. Know When to Handover
A customer service chatbot is not a replacement for a human agent. Often, you need to give the user a way to bail out of tough conversations and difficult questions, and that’s alright. Chatbots are excellent at fully resolving low-level queries because they often suit the modern customer’s habits of utilizing mobile technology to solve simple issues. However, just because an issue is complicated does not mean a chatbot cannot be helpful. Consider how you can use the bot for information gathering and light triage before routing to the right agent. In these cases, the customer service chatbot helps reduce handle time and expedites the customer’s support request.
5. Automation Happens Elsewhere, Too
Customer service chatbots get a lot of attention when it comes to automation. Often it’s the mental model in our heads for intelligent customer service. Consider other ways you can streamline the customer support experience with a chatbot, and leverage additional intelligent services: automatic tagging, routing, and prioritization for the agent (just to name a few).
6. Be Customer-Centric
At the end of the day, the success of your customer service chatbot comes down to how well it fits into the customer support journey and cadence strategy you have outlined for your customers. Consider different segments of customers that might prefer automation to “direct human” connection. Perhaps automation can be more helpful at the end of a live chat interaction than at the beginning. Take a good look at your customers, and we’ll help you find out the right size that fits. In doing so, you will improve your customer experience and customer satisfaction metrics. Discover Kustomer’s intelligent chatbot solutions today.