The pace of workplace automation is expected to accelerate in the next three years. The automation of key segments of the production process is critical to boosting efficiency while maintaining competitiveness in the economy. Cutting edge technology such as artificial intelligence (AI) is also becoming increasingly popular among companies seeking IT solutions to meet their business needs. The surge in the adoption of AI solutions is spurred by the twin pressures of Covid-19 lockdowns, and the constant need for efficiency. When offices closed and remote work became the default arrangement, automation became a solution to labour shortages, causing a substantial spike in the demand for AI related technologies. For instance, AI can be used to automate both outbound and inbound calls for call centres or companies engaging in telemarketing. Imagine hyper-realistic Talkbots that are powered by natural language processing (NLP) and machine learning— tools that can be useful for meeting sudden surges in call volumes and increasing your customer outreach.

WIZ.AI talkbots are engineered to be able to understand the nuances in the human language (including complex ASEAN languages) while engaging customers in meaningful conversations. Far from being science fiction, our Talkbot technology has refined the art of humanized conversations to the extent that over 90 percent of users could not recognize that they were speaking to A.I. over the call. Instead of a monotone, robotic voice that one would commonly associate with voice-layered chatbots like Alexa and Siri, customers speaking to WIZ.AI's Talkbots are greeted with friendly, human-like voices. This experience is only possible because of the text to speech (TTS) speaker model that is meticulously developed and consistently refined by WIZ.AI's dialogue engineers to mirror the human voice.

So what are the business aspects regarding customer service and call centers that should be automated?

1. Repetitive Tasks
One of the biggest hassles in customer service and call centers are simple and repetitive tasks. They are important but sometimes take too much time and effort to do, and it is somehow wasteful to put a dedicated agent to deal with these tasks. Take the healthcare industry, for example. When it comes to managing appointments, it is not uncommon for people to forget their appointments or cancel them prior to a consultation. To ensure that appointments are managed in an orderly manner, staff in charge of administrative matters will have to spend hours calling patients who have made a booking, lest they miss their appointments entirely. Tasks such as appointment confirmation and reminder calls are rule-based and can be automated with Talkbots.

By carefully constructing a conversation flow that is user centric and intuitive, Talkbots can be easily utilised for this task. Crucially, the time spent confirming appointments is significantly reduced as the Talkbot can manage multiple callers at once. Additionally, the intention of the caller (whether they can make it) is automatically recorded in the system, significantly reducing administrative complexity. But what if someone does not pick up on the first call? Talkbots are able to identify missed calls and automatically schedule a later time to redial. 

With human error minimised, you can rest assured that every caller on the list will be contacted. In the event that the caller has a unique and complicated request that requires the assistance of a human staff member, the call can also be immediately transferred to relevant departments.

2. Telemarketing
According to Deloitte, voice-based communications are still preferred over emails or chats when it comes to complex conversations. Telemarketing or ‘cold calls’ can also be considered a repetitive task and is arguably straightforward. A user can have one of the following three intentions: (1) interested, (2) uninterested, or (3) on the fence. If it is the second or third option, the Talkbot can also be designed to be persuasive by mirroring some of the best practices of top performing call centre agents. At the very least, the Talkbot will leave some form of information that the user can easily recall, such as the name of your website. This piece of information can be disseminated either verbally at the end of the call or via a text message. If your potential customer decides to change their mind, they would at least know where to find more information.

Cold calling is both a tedious and time consuming process when done manually. Hence, it is also important to conduct audience segmentation to ensure that calls are targeted at the right people to maximise conversion rates. To this end, call logging or transcribing is necessary even though it is an onerous task. With conversational Talkbots and its speech-to-text capabilities, call logging is automated and the conversations can also be easily analysed. Not only does this generate valuable insights, it can also be used as a guide on how to further improve your script. Furthermore, as Talkbots are essentially computers, learning curves are no longer an issue. Any updates or changes are instantaneous and no time is lost while attempting to secure a customer. The Talkbot is able to provide timely calls and ‘strike while the iron is hot’— and that is the most ideal way of securing a deal.

3. Calls that require large amounts of emotional labour
Have you ever heard of Emotional Labour? Emotional labour is the process of managing your emotion while doing a task. One example would be having to perk yourself up every single time you pick up a call from another customer, regardless of whether you have been picking up calls for the past 3 hours, or if your previous call was an extremely unpleasant one. This takes an emotional toll on call centre agents which in turn, inevitably affects their performance in the long run. As employees either make or break the business, especially in customer-facing roles, it is in the company’s interests to protect their emotional needs. Adopting Talkbots to handle difficult calls allows employees to  monitor calls from a distance and intervene at the right time. Additionally, because the Talkbot is able to keep its tone consistent at all times, customers may be more satisfied with the call as it is highly unlikely that they will be speaking to a tired call agent who may come off as insincere – a disastrous setup if customers are already frustrated on their end.

All in all, A.I.-driven automation might be your best bet at increasing cost efficiency and optimising your work processes. Seize the opportunity to leverage A.I. technologies to elevate your business for success.

Remember how Google Duplex mesmerized the audience when it successfully booked an appointment with a hairstylist in a live demonstration? It was not only an introvert’s dream but also a sign of technological breakthrough in our times. Now that we have witnessed what A.I. can do for the consumer’s side, what about the business side of things?

Automation of appointment booking systems
Nothing is more exasperating than waiting for a patient to turn up at their appointment, only to realize there has been a cancellation that you were unaware of. Every client who cancels their appointment at the last minute is a lost business opportunity. Not only because they cancel the appointment, but also because of the time and effort that is wasted to prepare our best service to a client who is not going to turn up. Someone could have replaced them if they logged in their cancellation or arranged for a reschedule at an earlier time. While an appointment booking system can partially automate this process, it still requires someone to man the computer or system. However, the case of last minute cancelation will still be a problem that needs to be solved. Ultimately, the most efficient way to mitigate cancellations would be to call every single client ahead of time to confirm their appointment booking status; but this is only possible with sufficient manpower which many small enterprises do not have. Reminders for appointments are extremely useful in ensuring that the client will fulfil their appointment and is an important factor in providing customer service excellence. So, wouldn’t it be nice if the process of managing your appointments could be fully automated?

To fully automate appointment management there are several systems that can be deployed. One of them is WIZ.AI’s hyper-realistic Talkbots backed by robust Voice AI technologies such as Natural Language Understanding, Text to Speech, and Interactive Voice Response. From rescheduling appointments to logging cancellations, Talkbots are designed to call a large volume of your clients before their appointments to check their booking status and reduce last minute backouts. This would significantly increase the attendance rate, and help minimize the administrative nightmare of last-minute cancellations.

One might argue that creating an appointment booking system on an app is another way to manage the high volume of appointments. However, it is always better to initiate first contact, which is why talkbots are perfect for this job. By calling customers at an ideal time, your business would be able to have enough time to make the necessary schedule adjustments which increases work efficiency by leaps and bounds. Additionally, being called by a company to confirm an appointment puts the customer at ease and feel more appreciated, which will leave a positive impression of the company’s sincerity and proactiveness. This is a standard of customer service excellence that many businesses should strive to achieve and maintain.

Appointment confirmation and its nuances — Can A.I handle it?
We have seen how appointment confirmation processes can become complicated; with both the customer service personnel and customer flipping through their respective calendars to find overlaps. This back and forth exchange of “is this day okay” or “I can’t make it” can also contain a lot of nuances. Driven by A.I., machine learning, automatic speech recognition (ASR), and natural language understanding (NLU), the Talkbot is able to accurately identify the intentions of the customer and manage their appointments accordingly. Furthermore, it is also able to answer a whole bevy of frequently asked questions like the business’ opening hours, business’ address, and products or services that the business has to offer.

The best part about the Talkbot: most people are unaware of their existence. Over 90% of users thought they were conversing with a human customer service agent. When in reality they are talking to Talkbot. Such hyper realistic, humanized experiences are a testament to the Talkbot’s advanced text-to-speech system. The text-to-speech system also works hand-in-hand with ASR systems to provide the best customer service possible. In addition to that, the system’s continuous improvement further adds to its technological prowess.

The other main technology that supports Talkbots is Machine learning, which ensures that the ASR system will always increase it’s accuracy with every call and ensure that the text-to-speech engine is further refined to provide an even more realistic caller experience. The Talkbot is also an amalgamation of all the skills and abilities of your top customer service agents as the script would mirror their best practices that would also come in handy as an A.I. trainer for newcomer agents. With machine learning, the peak performance of your best human call agents is now the baseline for the Talkbot and it would definitely have a significant positive effect on customer satisfaction.

The need of Robust AI systems in Crisis
The start of the pandemic was characterized by panic and a surge of calls for many healthcare organizations. If anything, Covid-19 has shown us how high call volumes can come at unexpected times. In the life & death urgency of a contagious pandemic, call centers need to be able to handle these volume surges to put their patients at ease. With such a short notice, it is impossible to hire a large number of call center agents and administrative assistants, let alone train them to be able to answer business-related questions. In such cases, the Talkbot is the perfect solution as it is able to handle the sudden increase in call volume with no time required to overcome a learning curve.

Now that Covid-19 has normalized the need to book appointments in advance, the demand for IT solutions that handle such bookings is also growing rapidly. When it comes to places like clinics and hospitals where overcrowding is detrimental to safety, having a robust system for managing appointments is all the more crucial to maintaining public health.

Talkbots are more than a stop-gap measure for appointment bookings during a pandemic. It is also a viable and permanent solution that many companies can turn to. At a time where most business processes are being forced to digitize, many enterprises are already exploring IT solutions to increase work efficiency and reduce costs. Little wonder that A.I. solutions have increased in popularity in recent months, especially when many of these solutions have proven to be effective and can be implemented for the long term. There is no better time to venture into Talkbots than now.

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Hopefully we get to experience that too. I am really curious about that. you know maybe we can actually have a sentient virtual pet in the future

Imagine a future where you can have phone conversations with robots. And no, we are not talking about monotonous sounding robots, but hyper realistic ones that bear an uncanny resemblance to humans. Once only existing in the realm of science fiction, this scenario has become reality today. Conversational Talkbots are artificial intelligence (A.I.) machines powered by natural language processing (NLP), automatic speech recognition (ASR) and several other mechanisms that allow them to sound hyper-realistic . As a result of this technology allows companies to improve cost efficiencies through lower labor costs and increased sales volume. With that said, what are the benefits of incorporating Talkbots into your call center?

A disruptive technology in the world of business
It is in every business’ interest to reduce their costs in order to maximize their earnings. In a time of economic disruption, it is essential for businesses to ensure that their resources are optimized. When it comes to call centers, time consuming tasks usually waste a company’s resources inefficiently. Repetitive tasks, such as calling customers to check in on their interest in a product, or to confirm an appointment should not be the tasks where companies spent most of their resources on. When a call center agent that is known to have a knack for securing sales is tasked to only confirm appointments, we would consider this to be a misallocation and underutilization of talent. This is where Conversational A.I. Talkbots can come in handy.

Riding on the worldwide push for task automation, Conversational A.I. Talkbots can augment your existing workforce by automating repetitive calls such as sending appointment reminders or other relatively straightforward tasks. Improvements in Natural Language Understanding (NLU), Natural Language Processing (NLP) and Automatic Speech Recognition (ASR) have equipped Talkbots with the ability to identify the caller’s intent as well as nuances in their speech. By automating such repetitive calls, businesses are then able to divert their best agents to handle more complex call tasks, thereby ensuring cost efficiency when running a business.

Talkbots mirror your best service agents and their best practices to ensure customer service excellence. When it comes to human agents, any changes to their script or sales tactics requires training, and this in turn consumes precious time with an indefinite outcome as to whether the new skill is effectively learnt and applied. With a Talkbot, any updates to the information disseminated to your callers can be implemented almost instantaneously, bypassing steep learning curves. Implementation of a new sales tactic is now a seamless and easy process. In addition to that. feedback is also available almost immediately through data insights and analytics that track the reception of customers.

Driving Sales with A.I.
Closing a sale is also a time consuming and time sensitive process. When a company is able to call a customer when they are in the midst of deliberating, there is a higher likelihood of successful conversion. Like the proverbial striking of the iron while it is hot, getting the time right is already half the sales battle won. However, it is tricky to know when that window of opportunity will open. This is where customer analytics becomes crucial. Using the Conversational A.I. Talkbots, companies would be able to conduct some form of customer segmentation after identifying their intentions. After retrieving this valuable information, businesses can then devise a better strategy to tackle each customer persona. For example, the Talkbots would be able to identify customers that express great interest in the product that is offered, before shifting their attention to persuade them to actually do the purchase.
Using A.I. for customer service calls can also allow for greater customer outreach and loyalty. The ability of Talkbots to reach out to numerous people at one time while checking in on their interests not only allows for companies to have a higher chance of sealing the deal, it also makes for a memorable customer and brand experience. In addition to that, Small gestures such as calling the customers to congratulate them or letting them in on an exclusive deal will also build brand loyalty, leading to higher returns of investments in the long run.

In the AI field there is a term called machine learning which is an integral part of these Talkbots that allows these intelligent systems to become progressively better at picking up the intentions of the callers. The more data and exposure to different conversations, the better it is and the faster the progress. The rapid rate of technology development in A.I. also allows for continuous Conversational A.I. Talkbotssystem upgrades, which leads to customer service excellence.

Most customer service calls are often outsourced to countries where labour costs are more affordable. As such, these agents who are not working directly under the company may not be able to understand the image that the company is trying to present to the general public. Therefore, engineering Talkbots and scripting to accurately reflect your company image and deliver the right information to the audience is an important measure. Building a Talkbot for your company allows your business to regain control of your brand image, while maintaining its consistency in the quality of service standard that could only be delivered by an AI system.

Every call center agent has their fair share of nasty calls, making it increasingly difficult to maintain a positive and professional tone during a long day at work. Talkbots could be a better alternative to handle such tricky situations as its tone of speech is perfectly maintained. When necessary, the call can also be transferred to relevant departments. Such arrangements prevent unwelcome scenarios such as when an exasperated customer meets a tired call center agent who is misunderstood to be insincere.

Companies may also sometimes experience a surge in call volumes where increasing the number of call center agents in such short notice would be impossible. For this situation, Talkbots are well equipped to rise to the challenge, handling sudden fluctuations with ease.
All in all, adopting A.I for higher levels of automation is becoming a business strategy proven to have significant beneficial impacts. This is a golden opportunity to supercharge your call center services and elevate your business to the next level.

Despite its recent rise to the limelight, Conversational Voice AI has only just started to gain recognition. However, many are still unfamiliar with the terms that are used. Here is a quick guide on the terms and acronyms and the explanation of their functions.

What is Conversational Voice Artificial Intelligence?
Conversational Voice Artificial Intelligence comprises what we termed as voice activated machines, with notable examples including Apple’s Siri, Google’s Home Assistant, Alexa by Amazon and Talkbots from WIZ.AI. Under its broad umbrella, Conversational Voice Artificial Intelligence also includes other intelligent assistants such as the chatbots that appear at the side of your screen when you visit a website.

In Conversational Voice Artificial Intelligence, humans would not only use their voice to provide these machines with commands or to ask questions; it is also possible for the AI to have hyper-realistic conversations with users. The AI’s unique capability of understanding nuances in the user’s responses and context of the conversation are made possible with machine learning, text to speech engines, natural language processing and natural language understanding, thereby creating a lifelike experience for whoever voice AI interacts with. The terms that have just been mention would be explained in the following sections.

An Explanation on Natural Language Processing (NLP)
Natural Language Processing focuses on the interaction between computers and human language and allows the machine to comprehend the content of the language, be it speech or written text. Natural Language Processing also gives the computer the ability to understand the context of the conversation as well as the nuances in the user’s response, a process also known as intent recognition. Used not only in speech recognition but also in machine translation and predictive typing, Natural Language Processing is a foundational building block of artificial intelligence that gives the computer the capacity to understand the human language, process it and generate useful information for humans in an efficient manner.

The Difference Between NLP and Natural Language Understanding (NLU)?
This is where it gets a little more complicated (but not to fear! We’ll explain it). Natural Language Understanding is a subtopic of Natural Language Processing and utilizes syntax (or arrangement of the words) and grammatical rules in the language to understand the user’s responses and its context. It involves processes like sentiment analysis where lines are interpreted to decipher the sentiment attached to it (whether positive, negative or neutral). Commonly used on survey responses or customer reviews, NLU processes data with speed and efficiency, while rendering value-added insights which fit the context and sentiment in the situation it is used. On call centers, NLU has the capability to categorize natural language into topics to ensure that the user is transferred to the right agent for each nuanced customer service need.

Text to Speech (TTS)
Text to speech involves the use of a human voice to produce a realistic recitation of any written text into spoken words. An example of how it is used in a customer service A.I would be when the customer’s phone number (which is specific to the caller and different for everyone) has to be read in the call for a personalized experience. As it is impossible to hire a voice actor to record every single combination of numbers to form an identification number, text to speech speeds up the process with its ability to immediately convert a written text into a verbal recording. An immense amount of work is required to make a robotic voice sound realistic given the unique intonations and emotions that are often embedded in our day-to-day speech.

Speech to Text (STT)
On the contrary, the Speech to Text feature is demonstrated when callers’ voice is transformed into text. This feature is also known as Automatic Speech Recognition (ASR), which basically means to “log” or “transcribe” the call. With the contents of the call automatically transcribed into text, it is much easier for the company to analyse and conduct audience segmentation, which is essential for creating targeted marketing strategies to boost business results. As transcribing calls can be a tedious process that requires good listening skills and lighting-speed typing for any human agent, it is not surprising that this process is automated for higher efficiency and cost-savings.

Dialogue Management
In the process of creating a computer which can communicate with customers, it is important to build the structure of how the conversation could naturally flow in order to ensure that the call experience is as intuitive and realistic as possible. This involves analyzing real life phone calls, and feeding the system data and information of the customers to understand their needs and thought process. Dialogue management generally involves two main processes: The first one is called Dialogue Modeling which involves tracking the state of the dialogue. The second one is called Dialogue Control where dialogue managers determine how the flow of the conversation with the A.I would be like.

Interactive Voice Response (IVR)
More often than not, the chirpy jingle of the customer service hotline is followed with an instructional speech that says something like, “For inquiries related to ­­­___, press one” and then you would proceed to input the right number into your keypad. This input then transfers you to the agent that specializes in handling your calls. The process of keying in a number into your keypad signals to the IVR; which is a basic feature used to manage your call and divert it accordingly to the appropriate handling agent.

Overall, the aforementioned components work together to create an intelligent robot. It will not only be able to increase your cost efficiencies, but also help drive your sales as it is able to encompass all the best practices of your agents. When coupled with machine and deep learning technologies, the innovation Conversational Technology improves every time with each customer interaction and call. With every customer conversation transcribed and documented, they would be easy to analyze. By doing so, companies are able to derive useful customer insights with no effort at all. These insights go a long way in creating more personalized customer experiences, which in return will ensure brand loyalty.

Though Conversational Voice AI is definitely an innovative technology which is constantly evolving, there is still a need for a human touch in the world of customer engagement. The best solution would be a combination of the two, Conversational Voice AI to help handle the rule-based, self-serve option, together with a Human Agent who can take care of the high value customer engagements.