- With the rising popularity of chatbots, it is no surprise that more businesses are flocking to get one of their own.
- Expectations of chatbots are endless, so, without an exact blueprint on how to go about it, steering technology to deliver results becomes problematic.
Like other conversational interfaces, chatbots are a powerful addition to an organization’s support suite. Even Since chatbots hit the market, they have received mixed responses —praised as they make customer service an easy process and critiqued for their lack of true intelligence.
Yet, businesses are gradually coming to recognize the importance of chatbots. This is evident by the fact that 80% of businesses are projected to integrate some form of chatbot system by this year. Additionally, more than 50% of customers expect businesses to be available 24/7, making chatbots a good tool to implement.
With the rising popularity of chatbots, it isn’t surprising that more businesses are flocking to get one of their own. To be true, expectations are endless. But without a clear roadmap, it will become difficult for this steering technology to deliver results. Organizations must plan carefully and strategize well to make the most of it.
This blog will a few best practices that must be followed during chatbot implementation to ensure it becomes a successful channel to engage with customers.
Start with what the users want
For a chatbot project to be a success, it is most important to consider what the users want. There is no point in building a chatbot just because it is in demand. It will only become a good investment only if it enhances customer experience.
Chatbots are a good solution if they can automate a human-powered process, can address user needs that are not currently addressed, and allow users to interact through their preferred channel.
For a chatbot implementation to succeed, the conversation must be designed around a user customer, not the outcome.
Chatbot scope should be well defined
It is difficult for modern chatbots to carry on an open conversation. Therefore, to create a satisfactory user experience, it is crucial to keep the scope of conversation well defined. For instance, a chatbot can very well reset a password for a user or book a table. Modern chatbots cannot converse on any open subject. But it can be frustrating if we have something that interacts just as a person does but fails to do the things a human can do. To avoid customer frustration and disappointment, it is best to define the tool’s limitations and be transparent that users are talking to a computer.
Users expect human-like behavior
Though it is advisable to make it clear to users that they are talking to a machine, enterprises should still strive to provide human-like behavior in a chatbot. This can be done by adding some charm and humor to the chatbot. This will certainly improve the customer experience.
Design chatbot’s tone of voice
A chatbot acts as a representative of your company. So, deciding the tone or personality of the chatbot is crucial. Whether a rule-based or AI-powered chatbot, every conversation must be human.
When building a chatbot, it’s good to sift through live chat or prior interactions from previous customer conversations to ascertain which type of tone will work the best. It’s critical to assess each discussion in rule-based chatbots to ensure customers recognize the brand voice.
Gaps can be easily detected and provide reasonable explanations since AI chatbots employ Natural Language Processing (NLP) to appear human while they converse.
Users like cohesion
Speaking about a chatbot, users would expect something exactly human-like. They would want to interact with a chatbot exactly as they would with a person. But most users expect it to behave like a search engine when they see the text input box. That’s alright. Do not ask your users to type numerous words when one is enough. The interface should be conversational, not a burden.
But the problem arises when users type just one word with no surrounding context. Here it becomes somewhat difficult for a conversation engine to interpret the intent correctly. Keep this aspect in mind when developing your training data.
Avoid going in circles
Chatbots often circle back to the same node in the conversation tree, which can be frustrating to users. To handle this, it is best to provide multiple responses for each node, detect repeat visits to a single node, and address this issue. If the conversation keeps going in circles, there ought to be something wrong. It would be beneficial to hand off to a person or specify the chatbot’s scope and limitations.
Handing off to human service provider
Some interactions are too complex for a chatbot to comprehend or so unusual that training a computer about how to handle them is not worthwhile. It is best in such cases to hand off the query to a human. This should not discourage the implementation of chatbots. Even if a chatbot only answers the most frequent inquiries or the first mechanical phase of a discussion, there can be significant efficiency advantages.
Real-time feedback collection
Chatbots, particularly those that use machine learning, gain knowledge from every contact. These insights are then used to make recommendations for informational gaps that need to be filled. The chatbot immediately improves itself for the forthcoming conversations.
Because of this capability, chatbots are touted as an easy-to-use tool for providing real-time feedback. Whether or not the chatbot uses machine learning, it is best practice to constantly gather input and adjust the flow of the conversations to increase the resolution rate.
The chatbot doesn’t have to collect feedback for every response it provides. Instead, it is best to implement a follow-up system that is automatically activated after the conversation to remind users to leave a rating.
There is a good reason why chatbots are attracting so much attention. They provide us with an alternative method of engaging with computers after years of using buttons on screens. From a business standpoint, they can automate repetitious communication and make voice transactions possible. They present an intriguing new challenge in user experience design as well as a fresh set of patterns for developers and designers to figure out.