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  1. Home
  2. Blog
  3. Enterprise Chatbots
  4. A Quick Guide to Assess your Chatbot’s Maturity
June 20, 2022   |    By Satheesh Kothakapu

20 Jun

Chatbot Maturity

A Quick Guide to Assess your Chatbot’s Maturity

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.

A 101 on 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 LevelDefining FeaturesDeployment Potential
ImmatureNo NLP (Natural Language Processing), Predefined keywords, No learningSimplest Q&A
InfantSimple NLP, Chatbot cannot learn from user conversationsSimplest Q&A+tasks
MatureAdvanced NLP + Supervised learning mechanismsModerately intelligent
AdvancedPowerful NLP + context and sentiment management + self-learningMeaningful, 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:

The Six Pillars of Chatbot Maturity

­Pillar Questions to benchmark your chatbot
Functionality
  • Is your chatbot able to answer both simple and complex questions?
  • Can it automate mundane, repetitive tasks?
  • Can it pull information for the user?
  • How good are the existing alternatives to achieve the same tasks?
Conversational intelligence
  • Is the chatbot able to comprehend the context of the conversation? Is the bot able to successfully extract the intent from the interaction?
  • Is it able to understand the nuances of the language, including grammar and slang?
  • Is the bot able to handle dialog changes? Can the chatbot retain context and pick up conversations from where they were left without the user having to repeat himself?
  • Can the chatbot learn from past conversations and hold personalized, context-rich user interactions?
Emotional Intelligence
  • Is the chatbot able to comprehend the tone and emotion (sad, joyful, angry, frustrated, etc.) of a user’s utterance?
  • Consequently, is the bot able to alter its own style of interaction or handover the conversation to a human agent?
Omnichannel and Multilingual capabilities
  • Is the bot able to provide consistent engagement across all channels (social, web, messaging, voice) and devices (desktop, mobile, smart speakers)?
  • Can the bot converse in multiple languages, and understand the nitty-gritty of each, including canonical word forms?
Flexible Integrations
  • Can the bot integrate with legacy and backend systems, including ERP, CRM, etc., and enterprise databases, and draw the right information to perform various tasks?
User Experience
  • Encompasses the bot’s accessibility, usability, and the pleasure of interacting with it.
  • Can the user easily access the bot to initiate a conversation? Can the virtual digital assistant provide maximum support by asking the bare minimum number of questions?

How can Acuvate help?

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. 

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Satheesh Kothakapu
Satheesh Kothakapu

Satheesh Kothakapu

Satheesh Kothakapu is Technical Architect at Acuvate and brings in 10+ year of strong expertise across Microsoft stack. He has consulted with clients globally to provide solutions on technologies such as Cognitive Services, Azure, DevOps, Virtual Agents. Currently he manages key customer engagement, involves in architecting the solutions and leading the team of Azure services.