Alex RaineyAlex is an experienced CTO and founder who largely focuses on all the technical areas of My AskAI, from AI Engineering, Technical Product Management and overall Platform Development.
Table of Contents
- Steps to Create a Conversational AI
- Step 1: Learn What Conversational AI is
- Step 2: Understand How Conversational AI Works
- Step 3: Determine How Conversational AI Can Help Your Business
- Step 4: Select a Platform To Build the Conversational AI
- Step 5: Implement a Prototype
- Step 6: Launch the Conversational AI model and Evaluate its Performance
- Tips for Implementing Conversational AI in Your Business
- Leverage The Power of Conversational AI Today
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In the 19th century, Babbage and Lovelace invented the first mechanical computer capable of calculations and data storage. Fast-forwardd 200 years,, and today’s computers can “talk” with humans. They can understand context, determine intent, and create personalized messages.
And all of these are thanks to conversational AI.
Conversational AI is one of the recent cutting-edge tech solutions businesses have adopted to elevate their services, such as customer support. Around 87% of business contact centers across the United States, Canada, and the United Kingdom claimed that conversational AI in the form of chatbots boosts their productivity and around 97% are eyeing to adopt AI for customer self-service automation.
Want to learn how to create a conversational AI for customer support? Read on our step-by-step process for creating conversational AI for business.
Steps to Create a Conversational AI
Creating a conversational AI starts by understanding this astounding technology, and then gradually employing it according to your business needs and goals.
Step 1: Learn What Conversational AI is
Conversational AI is a general term that refers to AI-powered technologies that can understand human inputs and respond using human-like speech. Simply put, conversational AI is an “intelligent” software or program that can converse with humans.
Developers use machine learning algorithms to train conversational AI. Tons of datasets are fed to the algorithms so the model can learn conversation patterns and generate responses. Meanwhile, natural language processing (NLP) allows the conversational AI to decipher the meaning of the user’s input and recognize its intent.
Let’s take a look at AI chatbots—a common application of conversational AI in customer support. Before, chatbots worked by using predefined responses “triggered” by some keywords present in the user’s input. They cannot engage in a nuanced discussion or write personalized messages since their responses are pre-programmed or scripted.
In contrast, AI chatbots are “intelligent” - they can handle complex discussions because of their ability to understand context. Their responses are not pre-programmed but are based on their analysis of the training data provided. Hence, AI chatbots can generate personalized responses, provide relevant suggestions, and improve performance over time. For this reason, many of the best customer support chatbots are now AI-powered.
Other examples of conversational AI include an Interactive Voice Response (IVR) system that routes customer calls to live agents, voice assistants, and AI email assistants.
Step 2: Understand How Conversational AI Works
Now that you’ve understood what conversational AI is, it’s time to get a glimpse of how it works. This technology’s mechanism is quite simple - a person will input text into the program, NLP will analyze the input’s intent, and then the model will predict and generate the best response based on its training data.
The process repeats every time the user inputs a query or prompt to the application until the conversation ends.
To further understand, let’s see how chatbots actually work. Suppose that a customer wants information about a feature of a SaaS product. They type their question into the AI chatbot’s widget. Once the user enters his query, the model will immediately analyze the words to determine the user’s intent (which is to ask a question about a product feature). Using the bot’s training data, the bot will write a response that satisfies the customer’s question.
If the customer enters a follow-up question, NLP allows the bot to understand that the second input is not a separate question but a follow-up to the previous one. This enables the bot to generate a contextual response, making the conversation more personalized and helpful.
Another example can be seen with AI voice assistants. Instead of typing, a customer can state his query using the app’s Automatic Speech Recognition (ASR) interface, which will translate the verbal prompt into text. After that, the app will analyze the input to generate a response that is based on the model’s training data.
Step 3: Determine How Conversational AI Can Help Your Business
Specify the potential use cases of conversational AI in your business. To do this, you can
Start by knowing the challenges that conversational AI might solve for your business.
Say that your support team receives hundreds of customer queries and tickets daily and you’re struggling to address them promptly. You can deploy AI chatbots to respond to basic queries to give your team ample time to solve the remaining tickets. With this solution, your support team becomes faster and more efficient, while maintaining personalized connection with your customers.
Step 4: Select a Platform To Build the Conversational AI
In previous years, building a conversational AI like a chatbot took time and effort. Businesses need to hire developers to create a model from scratch. Without knowing some of the programming nitty-gritty, it’s almost impossible to build one.
Fortunately, many third-party platforms offer ready-made, customizable models that can help you create conversational AI easily.
The easiest approach currently available is offered by AI chatbot builders. They offer accessible, no-code bot building where you’ll simply provide your training data, tweak some settings, and customize the bot’s appearance. For instance, My AskAI lets you create AI customer support chatbots by providing data sources like your business files (like DOC, PDF, XSLX, CSV, etc.), webpages, or cloud storage (e.g., Google Drive, Dropbox).
Step 5: Implement a Prototype
The first conversational AI application you’ll come up with serves as your prototype - a preliminary program that needs monitoring and refinement to ensure that it meets your business’s needs.
You can launch first your conversational AI internally. For instance, you can ask your employees to test the accuracy of your AI chatbot’s responses or put it to actual work as an AI internal assistant about business-specific knowledge and information.
Step 6: Launch the Conversational AI model and Evaluate its Performance
When your prototype is deemed successful, you can now deploy the conversational AI system on your website and other digital platforms. It’s crucial to constantly track its performance to identify points of improvement, so collect user feedback and track its performance regularly.
Tips for Implementing Conversational AI in Your Business
Here are some tips to successfully utilize conversational AI for customer support.
- Pick an appropriate tone for your conversational AI: Your bot must sound like a human agent, speaking in simple and casual language. Avoid making it overly formal and verbose.
- Ensure the accuracy of your training data: Your conversational AI might harm your business if it provides false information. To ensure that it will only provide accurate responses, make sure that its training data are on point, correct, and precise.
- Provide “Fallbacks”: There are some queries that your conversational AI cannot address. But instead of defaulting its response as “I don’t know” when it lacks the knowledge to answer a query, you can provide “fallback” options (e.g. sample questions) instead that will show the user what your conversational AI can accommodate.
- Add seamless agent routing: Your conversational AI should provide a quick and easy option to escalate customer concerns. Ensure that the bot can also inform the agent about the concern’s context for quick resolution.
Leverage The Power of Conversational AI Today
With My AskAI, you can create conversational AI chatbots for your customer support even if you have zero programming knowledge. Simply upload your business files or add your webpages, and you’re good to go. Deflect up to 75% of customer queries by signing up today.
Written by
Alex Rainey
Alex is an experienced CTO and founder who largely focuses on all the technical areas of My AskAI, from AI Engineering, Technical Product Management and overall Platform Development.
