6 Min
Chatbots have taken over the digital communication channels because of its wide adoption and growing movement towards customer-centric strategies. Businesses are using it for competitive advantage. They are everywhere, and every bot claims to be backed by artificial intelligence (AI).
So, what are the importance of artificial intelligence(AI), natural language processing(NLP), and machine learning(ML) in the world of chatbots? How can we figure out which chatbot is intelligent, and how does knowledge management fit into the picture?
Table of contents
How do chatbots function?
A customer service chatbot typically initiates a conversation by asking a question or series of questions regarding basic context in order to narrow down the user’s intent. To do so effectively, the chatbot uses natural language processing(NLP) to convert the customer’s query, information it uses to make its own query to a standalone knowledge management solution for the right content, answer, or solution.
On the front end, this user experience ought to be seamless and hassle-free. Chatbots backed by structured knowledge management is efficient and intelligent enough to pose as humans, allow customers to get the right aid at the right time while freeing up your support front liners for more complex tasks.
Why do companies implement customer service chatbot?
First of all, the goal is to offer a convenient, self-help way for customers to find information for basic queries. Doing so can help organizations in scaling contact center operations simultaneously. Let’s take a look at few benefits that chatbot brings for the businesses:Ability to Respond Immediately
1. Reduce support tickets
2. Minimize operational costs
3. Seamless digital customer interactions
4. No more call wait, hold, and transfers
5. 24 hours availability
6. Consistent response
7. Personalized customer service
Additionally, Chatbots Can Save Up To 30% In Customer Support Services
Source
This seems to be great news but only if bots are fed with the right information.
In contrast, according to Gartner, 99% of artificial intelligence (AI) initiatives in IT service management will fail, due to the lack of an established knowledge management (KM) foundation.
Knowledge management and operation of chatbots are co-dependent. Both require each other to pull and deliver meaningful insights for your organization and together it can help make overall remarkable customer experience.
Knowledge management for efficient chatbot
To be effective in the capacity, chatbots need to be fed with the right and actionable information. This makes an organization’s knowledge management strategy, foundational to the efficacy of its customer service chatbots. Hence, if the knowledge base lacks the right content, the chatbot fails to do any of the functions effectively. Thus, knowledge management (KM) is considered to be the foundation of any AI initiative, and it provides strength for your AI chatbot to manage and make better customer support with each passing day.
Without good KM in place, an organization’s chatbots are at risk and can be considered just an app. At the end of the day, an organization can have all the knowledge contained in the world; but without a robust KM system, it’s not possible for bots to find it.
KM unifies information neatly
If you have enough time, and you are aware about the location of a file, you can arrange those through the hierarchy and find any information you need. However, this method is ineffective when you are dealing with a huge amount of information and ocean of knowledge. It takes time to collect information manually and find the intended information.
Knowledge management’s capability to support all formats of information, ensure all organizational knowledge is structured and in a centralized platform. Files ranging from PDF, word documents, PPTs, and excel spreadsheets; enable easy access to your library by allotting permissions and rights to users, employees, and front liners. A semantic search capabilities to fetch a piece of information is an add-on for easy findability. Further, with NLP in action, the bot can understand a query well, and employ deep learning to analyze the entire information, just in a blink and provide a direct response.
Eliminate hassles by direct delivery of responses
Without a proper KM tool, if somehow you manage to retrieve information manually from a dataset, you can’t be sure whether the information is up to date and precise, that will eventually reflect on your customer support quality.
In contrast to this, the knowledge management will handle the back-end processing for you, while your bot enjoys delivering direct response and agents is making customer relationship better through service calls. Moreover, you can be assured about the correctness of the information.
Conclusion
To be precise, organizations need a structured knowledge base groundwork to create, curate and maintain the useful content for their chatbots and make them effective and intelligent to handle customer services and enjoy saving on OPEX.
Considering the complexity of content (PDFS, FAQs, Text, Web, Tables, etc.) where the intended information might reside, only KM has the information processing power to come up with organized workflows. Chatbots are revolutionizing the business sphere, but for that to happen with your business too, you need to think about Knowledge management first as at the end of the day, you can have all the information contained on the planet; however, without an effective KM tool; chatbots probably won’t have the option to deliver it for you.
