Chatbot vs Virtual Assistant: What’s the Right Choice for Your Business?

Innovative technologies allow companies to automate routine processes, minimize expenses, and achieve sustainability. The deployment of chatbots and virtual assistants helps businesses generate timely replies to queries, serve customers 24/7, fix shipping and payment issues, collect invaluable insights about buyers’ behavior, and improve strategies. Designed to assist people with solving a variety of issues, AI-powered tools can be taught to send notifications, answer voice calls, track shipping, analyze transactions, collect information about consumers’ preferences, and perform other tasks. In this guide, we will consider the differences between both types of tools and explore how they shape the future of various industries that can benefit from workflow automation.

What are Chatbots?

The term refers to programs developed to offer customer support (CS) services. Such bots analyze questions and produce detailed responses. Their usage allows companies to minimize delays, eliminate bottlenecks, and serve consumers 24/7. They perform such tasks:

• Fix technical issues;
• Answer queries;
• Expedite search.

The implementation of such solutions allows companies to automate repetitive tasks. By streamlining routine operations, chatbots enable employees to prioritize convoluted queries. Here are the main types of such programs:

1. Rule-based: These traditional solutions utilize specific rules and scripts, which enables them to handle simple user queries. They analyze input using specific words and search through the integrated knowledge bases to provide a suitable response. Even though they allow CS teams to handle increased volumes of requests, they are less suitable for handling complex issues. A brief chatbot vs virtual assistant comparison shows that the former might provide irrelevant responses if it faces an unusual situation, which may cause customer dissatisfaction. The main advantage of such solutions is their affordability. Besides, firms do not need to hire specialists with advanced technical skills to integrate chatbots with web-based platforms.
2. AI-driven: The deployment of Large Language Models (LLMs) has transformed CS workflows. Trained to analyze huge datasets, they can fix challenging issues and maintain engaging conversations. Even though building and deploying custom LLMs requires significant investments, it’s a cost-effective solution in the long term. The usage of natural language processing (NLP) technology lets such chatbots improve customer experience (CX). They are trained on extensive datasets, which allows them to handle all sorts of queries without escalating tickets to human agents.

While AI-driven chatbots masterfully adapt to changing contexts and generate replies in a natural-sounding voice, they are susceptible to biases and may occasionally provide inaccurate responses if the quality of datasets is low. Despite these shortcomings, they are considered a better option for ventures that want to increase the scope of their operations and offer multi-language support.

Both rule-based and AI-driven chatbots enable firms to streamline the processes within CS teams, increase sales, and improve the quality of their marketing efforts. However, the latter have more advanced functionality due to the usage of AI algorithms.

What are AI Virtual Assistants?

The development of AI technology contributed to the emergence of powerful systems with a significant degree of autonomy. They rely on NLP to interpret queries written in various languages, recognize intent, detect early signs of dissatisfaction, and provide helpful recommendations.

The usage of ML and deep learning algorithms allows LLMs to process large datasets and extract valuable data, helping companies grow. AI helpers are trained to cope with the following tasks:

• Schedule meetings;
• Send notifications;
• Expedite order finalization;
• Configure smart device settings.

If you compare a chatbot vs virtual agent, you will see that the latter has more impressive functionality. Known for their advanced capacity to interpret user inputs in various formats, virtual assistants utilize LLMs to improve the quality of generated responses. They discover trends and patterns, which allows them to handle complex situations even if they weren’t trained to solve specific issues. Users can engage AI helpers in a conversation via text messages or audio calls.

Chatbots vs AI Virtual Assistants: Notable Differences

When considering the main features of both solutions, it becomes noticeable that basic bots are suited for repetitive tasks that can be automated easily. LLM-based digital helpers leverage edgy technologies to produce elaborate replies and solve convoluted issues. Below, we have rounded up the main factors that make them distinct.

Summing up, a virtual assistant bot is more suitable for companies with convoluted workflows that want to save valuable resources by optimizing their operations. Even though such systems typically require significant investments, they allow businesses to achieve sustainable growth.

Top Reasons to Implement Chatbots and Virtual Assistants

Even though these solutions are suitable for different situations, companies typically integrate them with legacy support systems to achieve specific goals. Most ventures rely on automated solutions to reach the following objectives:

• Reduce average response time: Chatbots and digital assistants answer queries even outside business hours, which eliminates the need for bloating staff to serve clients from different time zones.
• Analyze customer preferences: While chatbots collect only basic information about customers, including their names, contact data, and location, generative AI technology solutions can be used to make marketing efforts more targeted.
• Improve the quality of support services: The deployment of virtual helpers facilitates providing personalized experiences and serving people better. As most people expect to get instant replies when contacting brands, automated software allows businesses to solve their queries in real time.
• Increase a satisfaction rate: The usage of self-service platforms saves a firm’s resources and makes clients happier. AI tools remember user preferences and use information about buyer’s habits to make helpful suggestions or provide appealing offerings.

Companies on a tight budget leverage chatbots to save money. Even though many businesses consider building LLMs and deploying full-fledged virtual assistants too expensive, using the services offered by a reliable provider allows them to access edgy technologies at a fraction of the cost.

MetaDialog builds powerful LLM-based solutions that increase customer satisfaction by up to 28% and allow businesses to increase the productivity of their teams by 5 times. When interacting with virtual assistants, users do not need to worry about misunderstandings. Their issues are solved swiftly and efficiently.

Main Uses of AI-Driven Virtual Assistants and Chatbots

Both solutions have an advanced capacity to analyze client input in different formats, but their approaches are slightly different. Traditional chatbots operate within pre-defined frameworks and use pre-programmed scripts to interpret conversations and generate a response. Algorithm-powered assistants rely on the power of NLP to analyze client questions and generate context-relevant replies.

Chatbots are utilized in situations when companies use basic decision trees to categorize queries and produce replies. They have a more narrow scope of applications. AI assistants deploy advanced machine learning (ML) algorithms to come up with the most relevant response in a specific situation. They utilize LLMs to process new data and engage a client in a conversation.

While chatbots demonstrate high efficiency when it comes to answering simple queries, virtual assistants use conversational AI to solve more complex issues. They utilize voice recognition, ML, and other technologies to satisfy clients’ needs. MetaDialog develops custom LLMs to help firms reduce the average resolution time to 20 seconds and automate up to 81% of replies.

Below, we have outlined the main use cases of chatbots and AI helpers across various industries:

• eCommerce: The deployment of AI chatbots allows retailers to optimize client journeys, provide 24/7 assistance, facilitate access to knowledge bases, and manage an inventory efficiently;
• Healthcare: AI tools integrated with CRM and ERP systems schedule patient appointments, provide treatment recommendations, analyze large volumes of data, and improve the accessibility of the services provided by medical professionals.
• Hospitality industry: Both chatbots and virtual assistants help clients book hotel rooms, cars, and flights. They share helpful tips that enable people to choose the most suitable destination depending on their budget and needs.
• Finance: AI solutions analyze market trends and assist investors with making weighted investment decisions.

AI virtual assistants also integrate with smart home applications, which further demonstrates their wide scope of applications.

Which Option to Choose?

A company that wants to automate routine tasks and optimize workflows to process client queries quickly even during peak times can benefit from building a basic chatbot designed to answer simple questions. Expanding the scope of their operations requires enterprises to deploy advanced LLM-based systems. Let’s describe the main things businesses should consider to make the right choice:

• Features: AI virtual assistants are built to perform various tasks, including handling challenging queries, scheduling appointments, and controlling smart home devices. Chatbots retrieve information from knowledge bases, track orders, and solve other issues.
• Industry: Depending on the sector, a company should choose an option that suits its particular needs. Virtual assistants can be trained to find solutions to convoluted problems, while chatbots facilitate finding information in self service automation systems, getting shipping updates, and handling basic requests.
• UX: AI assistants utilize conversational UI and contribute to more enhanced UX. A chatbot has a streamlined interface designed for simple tasks.

AI-powered tools offer dynamic interpretations of client inputs and rely on NLP technology to produce appropriate responses depending on the context.

Future Developments

The deployment of AI systems allows ventures to increase their efficiency and achieve strategic goals. MetaDialog builds powerful applications that boost CS teams’ productivity by up to 5 times. Here are the most likely developments that will transform how AI is used across industries:

• Omnichannel support: Top-grade AI bots will enhance their ability to communicate with consumers across various social media, messengers, and online platforms.
• Advanced natural language understanding (NLU): This technology will further enhance the ability of chatbots and AI tools to interpret conversations and produce meaningful replies.
• Deeper collaboration between robots and humans: Agents can benefit from using LLMs to discover insights, fix challenging problems, and streamline processes. By augmenting their ability to serve customers, virtual assistants become an integral part of their workflows.
• Voice technology support: AI tools understand voice commands and interpret phone calls, which allows them to provide top-level support.

By becoming early AI technology adopters, enterprises get an edge over competitors, improve resource allocation, and expedite repetitive tasks. After comparing chatbots and virtual assistants, it becomes obvious that the former utilize simple algorithms, while the latter have a wider scope of applications.

Integrating LLM-based systems with legacy tools requires extensive experience in AI technology. MetaDialog has a team of experts with strong technical backgrounds who help clients leverage the power of AI in their processes. Get in touch with our professionals and discover how to handle increased volumes of queries and perform other complex tasks without significant investments.