Conversational AI platforms — chatbots, voice assistants, and AI-driven virtual assistants, have become the go-to medium of interaction within enterprises — be it, customers or employees. Automating conversations through chatbots not only brings increased customer satisfaction, reduced attrition, and enhanced employee engagement, it helps organizations reduce costs, scale operations, and build a favourable brand image.
Typically used in customer service, chatbots have now assumed a variety of roles within enterprises, automating workflows that enhance business efficiencies and improve overall experiences.
According to research by Technavio, the chatbot market share is expected to increase by USD 1.10 billion from 2019 to 2024, and the market’s growth momentum will accelerate at a CAGR of 28.51%. Several factors have fueled this growth, including the advancements in cognitive technologies like AI, a wider acceptance of conversational AI interfaces, and the need for quick and speedy resolutions.
What facilitates a good chatbot interaction is the level of maturity it has attained, which is defined by a host of features and functionalities. When chatbot engagements are non-conversational, mechanical, and inferior to what a human agent may offer, businesses may have a challenging time getting to increase conversational AI adoption.
Regardless of where you currently stand in your chatbot journey, you need to assess your chatbot’s maturity and devise ways to deliver more complex and powerful experiences for your customers and employees.
Below, we present a quick guide to assessing your chatbot’s maturity.
To assess a chatbot’s maturity, also known as conversational AI maturity, organizations leverage what’s known as a chatbot maturity model.
A chatbot maturity model uses performance benchmarking to help in-house chatbot experts evaluate their bot and take measures to achieve more mature futuristic levels.
A chatbot maturity model defines the different stages of chatbot readiness, the characteristics in each of these stages, and potential deployment opportunities to exploit to achieve early success with your digital assistants.
|Maturity Level||Defining Features||Deployment Potential|
|Immature||No NLP (Natural Language Processing), Predefined keywords, No learning||Simplest Q&A|
|Infant||Simple NLP, Chatbot cannot learn from user conversations||Simplest Q&A+tasks|
|Mature||Advanced NLP + Supervised learning mechanisms||Moderately intelligent|
|Advanced||Powerful NLP + context and sentiment management + self-learning||Meaningful, intelligent AI virtual assistant , and contextually aware conversations|
Delivering exceptional customer and employee engagement through chatbots is not every chatbot developer’s cup of tea. It requires a consistent, multidisciplinary approach to developing an extensive strategy around the six pillars of chatbot strategy. Benchmarking features that help assess how advanced your chatbot is, include the following:
|Pillar||Questions to benchmark your chatbot|
|Omnichannel and Multilingual capabilities||
At Acuvate, we help clients build and deploy mature, intelligent chat and voice bots using our enterprise bot-building platform called BotCore.
As a Microsoft Gold Partner, we leverage core Microsoft Azure and AI technologies that arm bots with advanced, future-ready functionalities like Knowledge Graphs, context management, voice commands, dialog builders, machine learning, and a superior NLP engine, BotCore is used by over 150 customers across industries for a range of customer and employee use cases.
What’s more, you can offer customers and employees humanizing conversations and the convenience of interacting in the language of their choice with 90+ languages.
BotCore is a low-code platform that can be deployed both on-cloud and on-premise and offers integrations with 100+ enterprise systems, including Office365, PowerBI, Oracle, SAP, and many more.
To know more about BotCore, please feel free to schedule a personalized consultation with our experts.