Lead generation WIZ.AI

In this process, Prospective customers are also known as leads. In order to collect this leads companies need to engage in a process called lead generation. There are several ways companies could do lead generation. However, the most common and arguably the most effective way is through phone calls or a method called cold calling. A survey by Deloitte claimed that people still prefer voice communication over other methods of communication, especially regarding complicated matters. Cold calls also enable companies to reach their prospective customers faster, and in return allows companies to get faster and direct responses from the prospects. 

As effective as cold calls, however, it still comes with many disadvantages, such as the required resources and  somewhat unmeasurable return of investments. Not to mention when outbound calls didn’t get picked up, that lead might as well be considered lost, since it might not be called again in later time. Furthermore, counting human error as a factor, cold calls could be less reliable. Even the best call agents would have a bad day, and that day might be a good day for harvesting leads. Overall, using cold calls for lead generation is effective most of the time. However, it could be very unreliable and inefficient at times, more so if human errors are factored in. 

With the advancement of technologies, new tools started to emerge as solutions for better lead generation. Take chatbot as an example, with the existence of AI technology and several other supporting technologies, we can now build futuristic customer outreach tools that are entirely automated. Also, with such precise machineries the factor of human error could be minimized, thus ensuring the efficiency of the lead generation process. However, this futuristic technology is not free of disadvantages either. 

As good as chatbot technologies go, there are still limitations in the way they engage prospective customers. For starters, chatbot comes as a text based technology which means there is a high chance that the initial contacts they made with customers are completely ignored. Also, chatbots do not have the ability to classify the leads to single out the high value leads. Not to mention, the lack of originality and authenticity of chatbots when engaging the customers. In the end, chatbot could automate several simple tasks. However, the results are far from satisfactory. But what if there is a technology that combines the effectiveness of cold calling with agents and the efficiency of chatbots?

Effective and Efficient Lead Generation

To answer this problem, WIZ.AI comes with a technology called Talkbots, a conversational voice AI technology. Talkbots are highly specialized conversational voice AI assistants that can automate the many complex tasks needed to be achieved over a phone conversation, including lead generation. They are made up of a comprehensive AI system with the ability to engage multiple prospective consumers at once. Powered with ground breaking technologies such as Natural Language Processing, Text to Speech, Speech to Text, and other supporting technologies, Talkbots are able to interact with potential clients in a hyper-realistic way just like humans. This helps Talkbots to better identify high value leads. This means With WIZ.AI Talkbots, businesses could run a better lead generation process,  which in turn will generate better leads in terms of both quality and quantity

Talkbots also reduce the necessity for the company to put more resources into repetitive tasks. These resources instead could be put into more important tasks such as closing sales or customer engagements that require hands-on help. With Talkbots taking care of small repetitive tasks, the cost lead generation would be more efficient. Talkbots also consolidate all the best practice for lead generation, therefore there are no wasted efforts in every attempt to generate leads. 

Better than that, all of this could be done consistently since AI doesn’t get stressed by doing the same horrendous and repetitive task, which means the results would be consistently good. In addition to that, Talkbots also records every call with prospective customers. Every information of a successful call will be used to improve the Talkbots, making them better time after time, thus ensuring consistently better results in time. 

Ultimately, Talkbots are not only a piece of futuristic technology that is cool and convenient to have, Talkbots are the future of lead generation that could help companies to generate leads efficiently, effectively, and consistently gets better in the long run.

Remember how Google Duplex mesmerised 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 realise there has a been a cancellation that you were unaware of. Every client who cancels their appointment at the last minute is a lost business opportunity. 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. 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. As busy individuals, reminders for appointments are also extremely useful and closely related to customer service excellence. What if we told you that the process of managing your appointments could be fully automated?

Wiz. A.I specializes in hyper-realistic talkbots that can manage your appointment booking system. From rescheduling appointments to logging cancellations, the talkbot is 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 minimise 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 booking puts the customer at ease and leaves a positive impression of the company’s sincerity and proactiveness. This is standard of customer service excellence that many businesses would strive to achieve and maintain.

Appointment confirmation and its nuances — Can A.I handle it?

We’ve all 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 speaker and manage their appointments accordingly. Furthermore, it is also able to answer a whole bevy of frequently asked questions like the business’ opening hours and address.

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. Such hyper realistic, humanised experiences are a testament to the talkbot’s advanced text-to-speech system. Additionally, with highly customisable and user-centric scripts, conversations can be designed to be concise and efficient, reducing call and hold times.

While ASR and text-to-speech systems work hand-in-hand to provide the best customer service possible, the system’s continuous improvement further adds to its technological prowess. Machine learning ensures that the ASR system only increases in accuracy with every call and 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 your top customer service agents as the script would mirror their best practices and perhaps come in handy as an A.I. trainer for your newcomers as well. With machine learning, the peak performance of your best human call agents is now the baseline for the talkbot. Imagine the effect this would have on customer satisfaction.

The start of the pandemic was characterized by panic and a surge of calls for many healthcare organisations. 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 centres 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 centre 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 normalised 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 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 digitise, 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.

Imagine a future where you can have phone conversations with robots. And no, we’re not talking about monotonous sounding robots but hyper realistic ones that bear an uncanny resemblance to humans. Once 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 (NLU), automatic speech recognition (ASR) and several other mechanisms that makes the hyper realism possible. These technologies translate to improved cost efficiencies through lower labour costs and increased sales volume. With that said, what are the benefits of incorporating talkbots into your call centre?

A disruptive technology in the world of business

It is in every business’ interest to reduce their costs in order to maximise their earnings. In a time of economic disruption, it is essential for businesses to ensure that their resources are optimised. When it comes to call centres, time consuming tasks include those that are repetitive in nature, such as calling customers to check in on their interest in a product or to confirm an appointment, for instance. When a call centre 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 underutilisation 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)  has equipped talkbots with the ability to identity 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.

As Wiz.A.I creates highly customisable talkbots for your business needs, these talkbots will 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. Not only is implementing a new sales tactic now a seamless process, 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 he/she is 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. It is however, tricky to know when that window of opportunity will open. This is where customer analytics becomes crucial. Using the Conversational A.I Talkbot, 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 talkbot would be able to identity who are the customers who have expressed great interest, before shifting their attention to persuading them.

Using A.I. for customer service calls can also allow for greater customer outreach and loyalty. Being able 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. Small gestures like congratulating customers or letting them in on an exclusive deal will also build brand loyalty, leading to higher returns in the long run.

Furthermore, machine learning which is an integral part of these talkbots 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 system upgrades and hence, 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. Engineering a talkbot and scripting to accurately reflect your company image to deliver the right information to the audience makes a world of difference. Building a talkbot for your company allows your business to regain control of your brand image, while maintaining its consistency through A.I. delivered service standards.

Every call centre 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 may hence be in a better position to handle such tricky situations as its tone of speech is maintained. When necessary, the call can be also be transferred to relevant departments. Such arrangements prevent unwelcome scenarios such as when an exasperated customer meets a tired call centre agent who is misunderstood to be insincere.

Companies may also sometimes experience a surge in call volumes where increasing the number of call centre agents in such short notice would be impossible. Once again, 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 returns. This is a golden opportunity to supercharge your call centre services and elevate your business to the next level.

Covid-19 not only pushed the world to intensify digital transformation efforts, it also made companies aware of the necessity of automating some business processes to meet their immediate needs in times of crises. Numerous call centres screeched to an abrupt halt during the lockdown as many companies were unprepared for remote work. More often than not, call centre agents are outsourced and not within the premises of the company’s office. Moving the phones and its accompanying infrastructure was a logistical nightmare especially in such short notice. While Covid-19 forced the majority of the world to adopt remote work arrangements, it drove companies to realise the potential of Artificial Intelligence (A.I.) and how automation could revolutionise call centres.

A.I and the changing landscape

The call centre is typically in charge of handling outbound and inbound marketing calls or other relevant customer enquiries. A large team of call agents is often sufficient in handling large call volumes, but when lockdowns are imposed and everyone is forced to stay at home, the workforce immediately gets thinned out, and the usually manageable call volume becomes a formidable task. Enter, Conversational A.I. talkbots. These intelligent talkbots are powered by A.I. and are able to engage in human-like conversations with caller. This is possible because the talkbot is driven by systems like Natural Language Understanding (NLU), Automatic Speech Recognition (ASR) and Machine Learning; to name a few. Equipped with the capability to engage a customer, high call volumes are easily handled and when confronted with complex enquiries, the talkbot is smart enough to transfer the call to a human agent who can promptly provide a solution.

As mentioned previously, most companies outsource their call centre agents to other countries where labour costs are lower. As a result, these call centre agents may not have a deep understanding of the company they are working for. By contrast, the talkbot is curated, scripted, and customised according to the company’s needs. The process of building a conversational talkbot is centred on the company’s messaging, the image they would like to portray to the public, or a sales tactic they would like to employ on customer calls. All in all, this allows the company to have better control over their content, messaging, and image – elements which are easily lost when telemarketing calls are outsourced to external labour.

Businesses that were forced to look into automating some processes would also have realised how A.I. is able to reduce the cost of production significantly. Furthermore, the quality of the service is not only maintained but arguably, has become better than before. How does this happen?

While constructing the talkbot, Wiz.A.I looks at the best practices of your top-performing call agents. We then incorporate these practices into the structure of the talkbot’s conversation to ensure that inbound and outbound marketing calls are not only intuitive, but also engaging and convincing. The talkbot is engineered to be strategic in the information that is provided to the caller to maximise the efficiency and effectiveness of the conversation; two qualities which have become increasingly important in a society where time is precious and attention spans are shorter than ever.

Take the following scenario: A call centre agent is tasked to call 200 customers by the end of the day to confirm their appointments. It is not surprising that by the time the agent calls the 50^th customer of the day, his enthusiasm would have dampened and his tone, noticeably fatigued and exasperated, especially if he/she has endured difficult calls. Talkbots by contrast, are able to maintain a consistent tone throughout all 200 calls, which in turn translates to higher quality calls and consistent service standards. Frustrated customers are more likely to be put at ease when the call agent is patient and sincere.

With one talkbot to handle a large volume of customers at once, your call centre agents can be put on standby to handle more complex tasks instead of repetitive ones. It’s better to let your talkbot do the mundane task of recording the caller’s intentions like whether they are able to make it for the appointment or need to reschedule, while the valuable skills and emotional capacity of your call centre agents can be fully utilised in more productive areas.

This new work environment sounds too good to be true?

A.I. technology is no longer in the realm of science fiction or just another pipe dream, it is being applied to several aspects of daily life. Take smart home devices, for example. With A.I., our personal lives are much easier and it is a given that companies would try to leverage technological advancements to improve their businesses.

Wondering if callers might realise they are speaking to talkbots? Wiz’s A.I. technology has refined the art of human-like conversations to the extent that 90% of our callers thought they were speaking to a human! This is possible because of the text-to-speech technology which generates talkbot voices that sound as human as possible. Additionally, talkbots also recreate the various nuances of human conversations – pausing when interrupted, clarifying questions when confused, and adapting the conversation flow according to new questions. This all makes for a hyper-realistic customer service experience. Additionally, machine learning allow the talkbot to be continually refined in its accuracy in understanding nuances in the human language; a tricky task that is second nature to humans but not so to computers. Trained on large amounts of data, the talkbot only gets better with time. Instead of lengthy learning curves, any updates to the information disseminated or the incorporation of a new sales tactic in outbound marketing can be incorporated into the calls instantaneously, saving the company precious time and money.

In spite of the economic challenges of the past year, there is a golden opportunity to ride the wave of A.I. adoption. Rather than a dystopian narrative of a “robot takeover”, A.I. technology constitutes a handy tool that compliments your workforce, positioning your business for elevated growth, and revolutionising the call centre industry as we know it.

The  pace of workplace automation is expected 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 (A.I.) is also becoming increasingly popular among companies seeking IT solutions to meet their business needs. The surge in the adoption of A.I. 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 A.I. related technologies. For instance, A.I. can be used to automate both outbound and inbound calls for call centres or companies engaging in telemarketing. Wiz. A.I. specialises in creating 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’s talkbots are engineered to be able to understand the nuances in the human language (and yes, this includes complex ASEAN languages) while engaging customers in meaningful conversations. Far from being science fiction, our talkbot technology has refined the art of humanised conversations to the extent that over 90 percent of users could not recognise 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’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’s dialogue engineers to mirror the human voice.

Which types of calls can be handled by talkbots? 

1. Repetitive 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 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 identity 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 but onerous. 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

Emotional labour is defined as the arduous task of 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 allow 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.

Talkbots are the future

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.

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

What is Conversational Voice Artificial Intelligence?

Conversational Voice Artificial Intelligence comprises of what we termed as voice activated machines, with notable examples including Apple’s Siri, Google’s Home Assistant, Alexa by Amazon and including WIZ.AI’s Talkbot. Under its broad umbrella, it 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 use 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 its 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, hereby creating a lifelike experience for whoever it interacts with. The above terms 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.

What about 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 it 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 their emotions (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 emotions in the situation it is used. Lastly, NLU is also capable of categorizing 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)

If we follow the train of thought from the above section, logically, the Speech to Text feature is demonstratedwhen the caller’s voice is transformed into text. Also known as Automatic Speech Recognition (ASR), it 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 a 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 processes of creating a computer which can communicate with customers, it is important to build thestructure of how the conversational flow is like to ensure that the call experience is as intuitive and realistic as possible. This involves analyzing real life phone calls, putting yourself into the shoes of the customer to understand their needs and thought process. Dialogue management can involve two main processes: First, Dialogue Modeling which involves tracking the state of the dialogue, and Dialogue Control, where dialogue managers determines 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 a 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 that is not only able to increase your cost efficiencies but also drive your sales as it is able to encompass all the best practices of your agents. Coupled with machine and deep learning technologies, the innovation Conversational AItechnology improves every time with each customer interaction and call. With every customer conversationtranscribed and documented for easy analysis, companies are able to derive useful customer insights with no effort at all, which goes a long way in creating more personalized customer experiences and hence ensuringbrand loyalty.

In Conclusion

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.

Register for a quick demo to see how your business can benefit from WIZ.AI Talkbot automations.