Chatbot 101
A powerful communication and engagement tool, chatbots are becoming an integral part of many companies’ digital strategies. In fact, Gartner predicts that chatbots will handle over 85% of a business’s interactions with a customer by 2020.
Our team has helped a number of clients build and deploy chatbots this year, delivering an enriched customer experience that offers immediate responses, personalization, and convenience. Drawing from our recent work, we’ve put together a list of key features and technical tools that ensure optimal functionality and return on investment.
Key Chatbot Capabilities
There is no universal “right” way to build a chatbot, but several key choices during the development process will determine whether or not users adopt or abandon your new digital product.
Make Your Bot Easily Accessible.
A chatbot is only effective if it is able to reach and engage with your target audience. Develop your bot on a platform that maximizes your social reach.
Keep the UX Simple.
Chatbots are built to streamline communication and create convenience. Choose a minimal design with easy controls and organized navigation, giving the user quick access to information, troubleshooting, and task scheduling.
Create an Intelligent Experience.
Intelligent conversation is key for user engagement. Leverage cognitive technologies to predict user needs and interests and engage in responsive and empathetic dialogue.The most effective chatbots will be capable of recognizing and reacting to human emotion to make the user feel connected and comfortable.
Enable timely transitions.
Chatbots should be able to monitor the conversation to detect issue complexity and a user’s emotional state and seamlessly transfer conversation to a human agent when necessary.
Technical Capabilities
Consumers are becoming used to chatbots, and can easily spot those that will be truly helpful and those that are simply glorified forms. To provide real value to your customers, chatbots should be capable of the following;
Natural Language Processing
Natural Language Processing (NLP) allows chatbots to understand language and authentically interact with customers. Using sentence structure evaluation and linguistic pattern recognition, NLP can develop conversation that’s personalized and targeted to address users’ specific needs and intent.
Active Learning
Active learning improves bot conversation with minimal human effort. By using a cognitive model based on collected data, conversation is modified and improvised to build greater understanding to answer queries. Active learning helps chatbots learn progressively by improving conversation with time.
Visual Recognition
Visual capabilities can increase chatbot security and contextual understanding. Chatbots can use visual technology to verify identity through facial recognition or gauge a user’s emotions to increase empathy in conversation.
Voice Recognition
As with visual recognition, chatbots can use voice recognition capabilities to enhance security and determine a user’s cognitive and emotional state. Voice can be used to authenticate or authorize user identity, accounts, and passwords. It may also be used to determine the state of the user, i.e. labored breathing may indicate the user is stressed or scared.
Sentiments Analysis
Identifying the sentiment of text, whether positive, negative, or neutral, helps a chatbot adjust conversation according to a user’s feelings. Should a user become too frustrated, sentiment analysis enables a bot to recognize the user’s emotional state and make the decision to transfer conversation to a human agent. Over time, sentiment analysis can be used to collect valuable data about a user’s likes, dislikes, and frustrations.
Challenges
Whether you’re a tech giant or a startup, your business may encounter challenges that can reduce or limit your chatbot’s success.
Maintaining Context
Human conversation is non-linear. Chatbots should be able to adapt to changing conversation flows while staying in context. If necessary, the chatbot should have the ability to drive the conversation back to relevant topics.
Avoiding “Bot Speak”
Rigid language and generic responses lead to frustrated users and decreased engagement. Chatbots should be able to diversify responses and use cognitive technologies to build upon user data.
Chatbot Persona
Making users feel comfortable talking to a screen can be difficult. To counter this, build in a persona that takes on human characteristics and names, like Amazon has done with Alexa.
Chatbots are set to become the new standard of communication between a business and its customers. With much of a chatbot’s success dependent on development and implementation, consider partnering with a developer with AI/ML expertise to help you leverage this disruptive technology.
