Talking to machines is no longer limited to science fiction novels and movies. Instead, it is evident in real life; we can now talk to our cars, smartphones, and appliances without too much effort. The implications of this are not just for individual consumers, but they are also for businesses across industries.
While artificial intelligence (AI) helps to develop systems that can perform intelligent actions, natural language processing (NLP)—a subset of AI—enables systems that can understand language. The combination of AI and NLP is what produces advanced speech recognition technology and intelligent machines that can process and communicate language.
Many organizations today are already taking measures to take the lead in and benefit from conversational human interaction with machines. Perhaps, this is the reason that the chatbot market is expected to reach $1.25 billion by 2020. It is not just the private corporations that are stepping up their efforts in conversational AI; many governments around the world are also doing their bit.
An example of this is the American AI initiative, which aims to improve the quality of life of Americans by increasing government-level investments in AI. In pursuit of this goal, the U.S government has already implemented automated voice systems and chatbots; the idea behind this is to allow Americans to perform self-serve transactions so that digital citizen services can better meet the needs of citizens.
One of the best examples of this is Emma, a chatbot developed by the U.S. Citizenship and Immigration Services. As of October 2019, the AI chatbot had processed over ten million requests (made in both Spanish and English) from more than three million unique visitors.
Another example of AI and NLP enabling intelligent business assistants is the virtual newsreader developed by China’s state news agency Xinhua News. According to the news agency, its virtual newsreader can read text just like a professional news anchor. The virtual newsreader comes in both a Chinese-speaking version and an English-Speaking version, and it is modeled on human presenters of the Xinhua News agency. There are many more AI and NLP-enabled intelligent business assistants to cover. However, before we get to them, it is important to fully understand the following top AI assistant technologies for businesses available today.
One of the most common applications of conversational AI in the real world is chatbots. These are conversational assistants that use text to interact with users. You’ve probably already had an interaction with these conversational assistants on chat windows that automatically pop up after you navigate to a website. They are also used to respond to comments on social media. Recognize chatbots now? You probably do.
If we were to explain chatbots in a single sentence, then we would have to define them as cognitive applications that allow humans to converse with machines and vice versa. Recently, chatbots have become increasingly popular, with many technologists predicting them to replace 99% of the applications today. However, others see chatbots as an ‘over-hyped’ technology that is not living up to expectations. So, what is the reality?
The reality gives both parties some benefit of the doubt. For example, the overall savings in customer support that chatbots are expected to bring to businesses by 2022 exceed $8 billion. This is a prediction made by Juniper Research. The research company also predicts that, by 2022, 90% of customer queries will be handled by chatbots, and only 10% will be directed to human customer service representatives.
On the flip side, we are some way off from seeing autonomous robots that can converse with shoppers in retail stores or can greet guests entering a hotel.
According to a study, more than half of all searches will be voice-based by 2020. In such circumstances, it is imperative to understand the importance of voice in business and prepare for it as early as possible. Many people today use voice search to find something they need. They do this by either speaking to a voice assistant such as Alexa or by giving a command to the voice function of a search engine like Google voice search.
While Google voice search can only provide you with search results, voice assistants can go the extra mile to place online orders for customers. Alexa and Google voice search are not the only voice search technologies out there; there’s also Apple’s Siri and Microsoft’s Cortana. For a lot of people in the U.S, voice search is a daily habit, as 41% of adults in the country use voice search at least once per day.
The remaining 59% have only started using the technology within the past year, and it is expected that, as these people get more used to voice search, the number of people in the U.S using voice search on a daily basis would increase. This means that most of the search engine queries in the future will be made using devices without screens. As voice search will make search more conversational, expect to see a shift in search terms in the coming years.
Also known as emotion AI, sentiment analysis is an AI-enabled automated process that identifies the nature of opinion and emotion from textual information. Sentiment analysis identifies the emotion/opinion as negative, positive, or neutral.
Today, an increasing number of businesses are using emotion AI to derive insights from customer reviews, survey responses, and social media comments in order to make data-driven and informed decisions. In short, sentiment analysis has become critical to make sense of data in a world where 2.5 quintillion bytes of data are generated each day. But, how does sentiment analysis work?
There are two different ways to perform sentiment analysis:
Rule-based approaches refer to systems that use a set of rules that are crafted manually to perform sentiment analysis. Inputs used by these approaches include classic NLP techniques like tokenization and stemming, and lists of words and expression generally referred to as lexicons.
On the other hand, automatic approaches involve automatic systems that learn from data using different machine learning techniques. The task of sentiment analysis is typically modeled as a classification problem. Here, the text is fed into a classifier in order to get the following sentiment analysis: positive, negative, or neutral.
There are many reasons for businesses to employ intelligent AI assistants in customer support and other areas; these intelligent assistants can help businesses to overcome many challenges while allowing them to meet customers’ demands. Below are some major advantages of employing intelligent AI assistants for businesses.
For businesses, customer experience is the new frontline. In fact, more than 85% of businesses are already competing on customer experience (CX). Superior CX is enabled by two key factors in the customer journey: customer care and customer support. Unfortunately, not many businesses are finding success in these areas in today’s world of constantly increasing customer expectations.
However, times are changing, and now businesses of all sizes have highly sophisticated AI chatbots and virtual assistants available to them; these bots and assistants are helping businesses to take their customer experience to a whole new level; this is a level of CX where customers’ expectations are not just met, but they are also exceeded.
Unlike the conversational AI bots of previous years that could handle only a few frequently asked queries, the current generation of these robots can help businesses to accomplish a lot more. An example of this is the AI chatbot of KLM, one of the world’s premier airlines. The airline’s chatbot integrates with Google and is available on several social platforms, including Twitter, Facebook, and WhatsApp.
The chatbot provides customer support round the clock and is trained on historical data for many years. This data includes CRM data, routing history, chat logs, and metadata history. Since the implementation of the AI chatbot, KLM has experienced many positive results, such as a 50% increase in response to customer queries and an improved over time.
For businesses, a completely new sales channel is enabled by chatbots and AI voice assistants. Using just these AI assistants, businesses can now manage the entire customer journey from awareness to after-sales experience management. Leveraging a social media platform or a mobile app, the AI assistants can provide the complete shopping experience within a single conversation.
An application area of conversational commerce is voice marketing. Voice could be the next major disruptor in advertising. Not only can voice emulate how we already communicate as humans, but it can go a step further to help marketers establish a genuine connection with customers
An example of this is the voice-activated coupon that Google and Target launched a few months back. This was the first-ever marketing campaign that uses Google Assistant. People who activated the offer through Google Assistant were given $15 off their next Target order on Google Express. However, the offer was valid for a limited time only.
Similarly, Tide—a laundry detergent owned and produced by American multinational Procter & Gamble, offers a voice-powered app that helps users remove stains. So, we can say that voice assistants have now become everyday resources for customers that help strengthen your brand connection.
If businesses want to have less churn in the future, then they need to improve the onboarding experience for new customers. Additionally, bottom lines are directly impacted by improved mechanisms for customer engagement and retention.
According to Customer.io, businesses can increase their revenues by more than three percent by slightly improving their customer acquisition; they can also experience a 7% improvement to their bottom line with a minor improvement in customer engagement. This makes it critical for businesses to increasingly focus on streamlining their onboarding process and improving retention rates.
One company that is doing just that is Expensify—a software company that builds expense management systems for both businesses and individual users. Recently, the company implemented an AI assistant in its customer onboarding process to make it easier for new users to learn about and get used to the product. Currently, the AI is available on the company’s website and mobile application and will soon be offered on Slack.
Since implementing the AI assistant, Expensify has experienced considerable growth in the demand for the free trials of its products.
Enabling co-automated workflows is another major advantage of employing intelligent AI assistants for businesses. Today, business teams everywhere are often required to deal with repetitive and mundane tasks. The good news is that these low-value processes can be streamlined to minimize the loss of productivity by incorporating AI-enabled chatbots and virtual assistants into daily work routines.
Some of the areas where these chatbots and assistants can be set up and customized to assist businesses team and make their job easier are several common administration tasks, follow-ups, collection of data, and lead scoring. In fact, recent advances in machine learning and natural language processing (NLP) have enabled the development of intelligent assistants that can streamline the hiring process by assisting business teams in more complex tasks than those mentioned above.
An example of this is Mya—a new tool that assists in job recruiting and application. Using the conversational platform of Mya, HR teams can prescreen a large pool of candidates through various channels, including chat, SMS, Facebook, Skype, and email.
Candidates are asked a bunch of predefined questions by the AI assistant, and their responses are captured. The assistant also answers any questions the candidates may have and provides them with tips and progress updates.
For businesses, the benefit of this is that they get a list of candidates that are ranked according to their suitability for the vacant position; this suitability is based on several different metrics. According to the developers of Mya, its AI tool can automate more than 70 percent of the qualifying and engagement process, which can significantly increase efficiency and candidate engagement.
AI chatbots, voice assistants, and sentiment analysis technology have evolved over the years to raise the bar of intelligence and create a larger impact for stakeholders. The technology behind chatbots has progressed over time to become a virtual assistant capable of performing multiple tasks on its own such as scheduling meetings, booking cabs, and ordering items based on voice and text commands.
While great headway has already been made in the conversational AI space, we are at least a decade or two away from intelligent machines that can process and communicate language like or better than humans in every scenario.
Achievion team helped improve customer experience to a number of companies by designing, developing and training intelligent AI-powered chatbots. Reach out to us if your organization wants to leverage this technology as well.
In the next article in this series, we will look at how AI-enabled computer Vision technology is helping businesses to solve complex business problems through face recognition, body measurement, and object recognition.
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