Driven by AI, automated rules, natural-language processing (NLP), and machine learning (ML), chatbots process data to deliver responses to requests of all kinds.
There are two main types of chatbots.
Keeping Up with the Trends: Being Present on Messaging Platforms
Improved Customer Service
Increased Customer Engagement
Monitoring Consumer Data & Gaining Insights
Better Lead Generation, Qualification and Nurturing
Easier Approach to Global Markets
Harness the power of AI-powered chatbots to increase sales, provide multi-channel support, and improve organizational efficiency
Always on duty 24x7, 365 days a year. No holidays or off-days
Use artificial intelligence to understand and reply to a query
Easy to adjust or update the parameters
Complete flexibility according to the specific requirements of a business
Free up your personnel for other important tasks
Reminders about important tasks to be completed
Customize chatbot by adding visual elements to reflect your brand identity
Recommend products and push offers to the right person at the right time
Turn visitors into customers with human-like multi-turn conversations
Chatbots are essentially a form of automated service that customers can communicate with via text or voice on different channels, e.g. website, Facebook Messenger, phone, other applications or via voice assistants such as Amazon Alexa, Google Assistant.
Chatbots that are able to semi-automatically learn can understand natural language and therefore do not need as specific commands. That means bots based on Machine Learning get smarter with every interaction. The effort behind these automated systems is of course much greater.
With a rule-based chatbot, possible user queries and potential answers are defined in advance. If a question is asked that has not been previously defined, the chatbot will not be able to assist in answering the question.
In contrast to rule-based bots, chatbots based on Artificial Intelligence are able to process natural language. This is done with the help of Natural Language Understanding (NLU). AI-based chatbots are able to learn semi-automatically.
Chatbots are suitable for many industries and use cases. They are well-known to be able to provide excellent customer service, but there are also some great examples of chatbots in marketing & sales.
Two very important factors for the overall performance of a chatbot are the structure and quality of the data that are available for answering questions. This is where Knowledge Graphs come in.
Knowledge Graph is a synonym for a special kind of knowledge representation. It stores facts in the form of edges between nodes in a graph. In addition, most knowledge graphs also store the schema of the data. Knowledge Graphs develop their full potential, especially with large and complex data structures.
The investment that you put into a chatbot depends on various factors. Things such as the complexity of the bot, its AI capabilities, how it is built, technical integrations, infrastructure, launch & post-launch support and more have to be considered when you calculate or compare the cost of a chatbot.
Again this depends on the type of chatbot and bot builder or service provider that you chose for your technical implementation.
At Shadow infosystem, we define and implement individual content together with customers as well as any necessary interfaces to data sources. Moreover, preconfigured modules s are available through our Conversational AI platform. After the technical setup is done, thorough tests and optimizations are done before the chatbot is set live. Customers can then manage any chatbot content, analytics and more through our SaaS platform.