AI virtual assistants vs. chatbots

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AI virtual assistants vs. chatbots

Learn what a chatbot is, how it improves the customer experience and the best practices for building them.

A virtual assistant is an application that uses artificial intelligence (AI) and natural language processing (NLP) to understand customer questions and automate responses to them, simulating human conversation. Virtual assistants can make it easy for users to find the information they need by responding to their questions and requests—through text input, audio input or both—without the need for human intervention.

You may know virtual assistants that use audio input, such as Apple's Siri, Google Assistant and Amazon Alexa. Some virtual assistants are embedded in websites and interact through text chat. Either way, the key to recognizing a virtual assistant is that you can ask questions about what you need in a conversational way, and the virtual assistant can help refine your search through responses and follow-up questions.

You may hear virtual assistants called “intelligent virtual assistants” or “virtual agents.” But while they are also sometimes called “chatbots,” these two terms should not be used interchangeably; there are key differences between their technologies.

Virtual assistants and chatbots: the primary difference

Historically, chatbots were text-based, and programmed to reply to a limited set of simple queries with answers that had been pre-written by the chatbot’s developers. They operated like an interactive FAQ, and while they worked well for those specific questions and answers on which they had been trained, they failed when presented with a complex question or one that hadn’t been predicted by the developers.

In short, the primary difference between a chatbot and a virtual assistant is the chatbot’s inability to learn.

Virtual assistants, on the other hand, use natural language recognition capabilities to discern the user’s need. Then they use advanced AI tools to determine what the user is trying to accomplish. These technologies rely on machine learning and deep learning— elements of AI, with some nuanced differences—to develop an increasingly granular knowledge base of questions and responses that are based on user interactions, which improves their ability to predict user needs accurately and respond correctly over time.

For example, if a user asks about tomorrow's weather, a simple chatbot can respond plainly whether it will rain. A virtual assistant, however, might determine that what the user really needs is to know is whether or not they should wear a raincoat and bring an umbrella.

Aren’t chatbots becoming smarter, though?

You may notice the terms chatbot and virtual assistant being used interchangeably at times. And it’s true that some chatbots are now using complex algorithms to provide more detailed responses.

However, it is worth noting that the deep learning capabilities of virtual assistants allow interactions to become more accurate over time, building a web of responses via their interactions with humans. The longer a virtual assistant has been in operation, the stronger its responses. So a virtual assistant using deep learning may provide a more detailed and accurate response to a query, and especially to the intentions behind the query, than a chatbot with recently integrated algorithm-based knowledge.

How virtual assistants are used

Consumers use virtual assistants for many kinds of tasks, from engaging with mobile apps to using purpose-built devices such as intelligent thermostats and smart kitchen appliances. Conversational interfaces can vary, too. They can be used in social media messaging apps, stand-alone messaging platforms or applications on websites. Some typical use cases include:

  • Finding local restaurants and providing directions
  • Defining fields within forms and financial applications
  • Getting the latest score for a sports game
  • Receiving general customer service help from a favorite brand
  • Setting a reminder to do a task based on time or location
  • Displaying real-time weather conditions and relevant clothing recommendations

Why use virtual assistants?

Improve customer engagement and brand loyalty

Before the mature e-commerce era, customers with questions, concerns or complaints had to email or call a business for a response from a human. But staffing customer service departments to meet unpredictable demand and retraining staff to provide consistent replies to similar or repetitive queries, day or night, is a constant and costly  struggle for many businesses.

Today, virtual assistants can consistently manage customer interactions 24x7 while continuously improving the quality of the responses and keeping costs down. A virtual assistant can also eliminate long wait times for phone-based customer support, or even longer wait times for email, chat and webform-based support, because they are available immediately to any number of users at once. That’s a great user experience—and happy users mean increased brand satisfaction and loyalty.

Reduce costs

Staffing a customer support center day and night is expensive. And for some departments, such as human resources, it might not be possible. Industries have been created to address the outsourcing of this function, but that carries significant cost and limits your company’s control over your brand’s interaction with your customers.

A virtual assistant, however, can answer questions 24 hours a day, seven days a week. It can provide a new first line of support, supplement support during peak periods, or offer an additional support option. At the very least, using a virtual assistant can help reduce the number of users who need to speak with a human, which can help businesses avoid scaling up staff due to increased demand or implementing a 24-hour support staff.

Generate and nurture leads

Virtual assistants can help with sales and improve conversion rates, providing guidance and key information to shoppers. For example, a customer browsing a website for a product or service may have questions about different features, attributes or plans. A virtual assistant can provide these answers, helping the customer decide which product or service to buy or take the next logical step toward that final purchase. And for more complex purchases with a multistep sales funnel, the virtual assistant can qualify the lead before connecting the customer with a trained sales agent.

Best practices and tips for selecting virtual assistants

Selecting a virtual assistant can be straightforward and the payoff can be significant for companies and users. Providing customers with a responsive, conversational channel can help your business meet expectations for immediate and always-available interactions while keeping costs down.

For example, a digital strategist for an eCommerce company could select and deploy a virtual sales assistant to provide browsing customers more detailed information about the products, highlight differences between models, and offer additional user guides and how-to videos. Likewise, the HR department in an enterprise organization may ask a developer to find a virtual assistant that can give employees 24x7 access to information about benefits and facilitate navigating that information—all without having to speak with someone in person.

Whatever the case or project, here are five best practices and tips for selecting a virtual assistant.

  1. Pick solution that can accomplish your immediate goals but won’t limit future expansion. What does the group requesting the virtual assistant want to accomplish in the short-term? How is this goal currently addressed, and what are the challenges that are driving the need for a virtual assistant? How could other groups in your organization also use this technology for their needs, including agent assistance, internal IT or HR support, and even health benefits enrollment?
  2. Understand the impact AI has on the virtual assistant and customer experience. Like many buzzwords, AI gets thrown around, so figure out where and how AI is used. It should be helping understand what customers are trying to do and making sense of the various ways that can be expressed as well as helping manage conversations in a natural, non-robotic way. The goal is the get the customer to the information they need without running into any dead ends. Without this, it’s just another chatbot.
  3. Ask what it takes to build, train and improve your assistant over time. Despite the hype, AI doesn’t come knowing everything you need it to do, so get a clear sense of what intents (goals) or prebuilt content comes out-of-the-box and what you need to create yourself. Some virtual assistants offer the ability to use historical chatlogs and transcripts to create these intents, saving time. Those using machine learning can also automatically adjust and improve responses over time.
  4. Look for ways to connect to, not replace, existing investments. Often, emerging channels or technologies seem like they will replace established ones. But instead, they become just another medium for an organization to manage. A virtual assistant that connects to these channels and customer case systems can provide the best of both worlds; modernizing the customer experience while more accurately routing users to the information and individuals that can solve their problems.
  5. Determine if the virtual assistant meets your deployment, scalability and security requirements. Every organization and industry has its own unique compliance requirements and needs, so it’s important to have those criteria clearly defined. Many virtual assistants are delivered via the cloud to draw on the learnings and outcomes from other customer conversations, so if you require an on-premises solution or a single tenant environment, the list of available providers is much shorter. It’s also important to understand if and how your data is used, as it can have major impacts in highly regulated industries. IBM Watson® Assistant, for example, provides various deployment options including SaaS, on-premises and public cloud via IBM Cloud Pak® for Data, as well as optional data isolation for more stringent data privacy.

Virtual assistants and IBM

Tap into Watson

IBM Watson Assistant is a cloud-based AI assistant that can help solve customer problems the first time. It provides fast, consistent and accurate answers across applications, devices and channels. Using AI, Watson Assistant learns from customer conversations, improving its ability to resolve issues the first time while alleviating long wait times, tedious searches and unhelpful chatbots. Coupled with IBM Watson Discovery, you can enhance user interaction with information from documents and websites using AI-powered search.

Watson Assistant optimizes interactions by asking customers for context around their statements. This reduces the frustration of having to rephrase questions, providing a more positive customer experience. In addition, Watson Assistant provides customers with an array of options in response to their questions. If it’s unable to resolve a particularly complex customer issue, it can seamlessly pass the customer to a human agent, right in the same channel.

Watson Assistant is designed to plug into your customer service ecosystem, integrating with your platforms and tools, making the entire customer experience smarter and simpler from start to finish. This makes your customers’ interactions with your business feel more like a meaningful relationship with someone who genuinely cares, and less like a series of random, fragmented conversations with strangers.

IBM also understands that a customer experience isn’t just about the conversation—it’s about protecting sensitive data, too. That’s why we bring world-class security, reliability, and compliance expertise to the design of all Watson products. In addition, IBM helps you protect your investment by giving you the flexibility to deploy Watson Assistant on-premise, in the IBM Cloud or with another cloud provider of your choice via IBM Cloud Pak for Data.

The bottom line

Chatbots and virtual assistants may be distinct solutions, but they both play a role in the cost reduction, resource optimization and interaction automation needs of today. It is important to understand your organization’s needs and evaluate your options to ensure you select the AI solution that will help you achieve your goals and realize the greatest benefit.

Take this 5-minute assessment to find out where you can optimize your customer service interactions with AI to increase customer satisfaction, reduce costs and drive revenue.

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