Voice AI Technology

18
Apr
Voice AI Technology
Your questions on ChatGPT and generative AI

ChatGPT, DALL-E and other generative AI solutions are taking the internet by storm. These developments can redefine how we work and create – but for someone who is unfamiliar with AI technology, taking a step into the world of artificial intelligence may seem overwhelming, if not confusing. In this article, we’ll cover some of the questions raised during our recent webinar with Yusi Chen of GGV Capital, Zhen Wang of Advance Intelligence Group, Leslie Teo of AI Singapore, and WIZ.AI’s very own Jianfeng Lu.

 

What’s the first step for a company to introduce AI, particularly ChatGPT, into its processes?

Our webinar panelists generally suggested integrating AI into your day-to-day work. While the suggestion might seem simple, it can be overwhelming to consider for someone who has never worked with AI before. Fortunately, the market has AI solutions that are more accessible to the average office worker. Microsoft, an investor in OpenAI, has launched AI-powered assistants called Copilot. It works like ChatGPT, creating content with simple prompts like “summarize this document into three bullet points”.

For those who are still unfamiliar, we suggest trying out ChatGPT and asking it to generate some text for you. Start by giving the context of your request (e.g. I need to draft a professional recommendation) and then put in your requirements (e.g. How can I integrate AI into my daily work?). Do note, though, that the information ChatGPT provides may not be accurate, so remember to cross-check information yourself. Bing chat search works in a similar way, and can also help you get used to working with AI.

 

How would Italy’s decision to ban ChatGPT impact the industry?

As GGV Capital’s Yusi Chen pointed out, the issue behind Italy’s ban is data security. By using ChatGPT, a user’s interactions with the chatbot will be sent to OpenAI as training data. Italy’s data security regulator sees the use of ChatGPT as a breach of Europes strict privacy laws.

“It’s true, using ChatGPT means sending data,” AI Singapore’s Leslie Teo quips. “But look at it this way. Companies can ban the use of software or apps or block websites, but what do employees do? They use it on their iPhones. Is that safer?”

Teo suggests taking a different approach. “It’s much better to educate people on how to use these solutions,” he explains. “You can go and ask ChatGPT questions, but don’t use real data or information. Instead of giving a name, you say “A” and instead of saying 150, you say 1.5 to obscure the data.” 

And for WIZ.AI’s Jianfeng Lu, the data security gap is an opportunity for entrepreneurs. “Previously, we needed to exchange public keys to build trust. Then later someone invented zero-knowledge authentication systems. So this is an opportunity to develop solutions for another kind of data security in AI models.”

 

Which employees would feel most threatened by Generative AI?

According to Teo, roles like analysts, risk managers, economist will be greatly affected. “Anyone who does explanations of trends,” he explains. “I also think coding will change dramatically, and so will data science. That’s aside from marketing and communications professions.”

Chen then goes into GPT-4’s performance on standard tests. “On GRE, GMAT, SAT, APE… ChatGPT comes out in the top five percent of test takers,” he begins. “Even on a college professor’s exam, ChatGPT can get an A or A+. I think it’s quite possible that in five years, maybe a college student cannot compete with GPT. So that’s one group that will face lots of challenges with GPT, but also lots of opportunities.”

Teo continues on that thought and mentions a paper on GPT and productivity, which states that a knowledge worker’s productivity can improve by 30% with AI tools and solutions. “For example, if I use Copilot for coding, and I’m confident in my skills, I feel like I’m getting more out of the tool than when I am completely oblivious about coding,” he begins. “So with ChatGPT doing better on exams, maybe the problem is the test and not the human.”

 

AI as an enabler and not a threat

At WIZ.AI, we encourage businesses to embrace the possibilities that AI technology has to offer. While adopting AI may seem daunting to some, understanding what solutions can or cannot do – and how they can help you do better work – is key to building a successful AI strategy.

Want to try an easy-to-deploy generative AI solution? Try our latest product, TalkGPT, which is powered by ChatGPT. Craft and deploy customer communications in five clicks.
Explore TalkGPT

10
Apr
Voice AI Technology
Large language models and the power of generative AI
Last 05 April 2023, WIZ.AI hosted a live webinar with four thought leaders in the artificial intelligence space. Moderated by Yusi Chen, Vice-President of GGV Capital, the hour-long session gathered insights from AI Singapore‘s Senior Director Leslie Teo, Advance Intelligence Group‘s Chief Technology Officer Zhen Wang, and WIZ.AI’s Chairman and co-founder Jianfeng Lu. Below are highlights of the engaging discussion.
 

Trends in the finance industry and artificial intelligence

Global financial markets have seen a lot of ups and downs in recent weeks, but there are longstanding trends that affect the industry. For fintech companies, specifically, the challenge is how to remain relevant in the face of rapidly developing and newly emerging technology. Teo notes that fintech companies disrupted traditional banking, but a new breed of solutions may later unseat fintechs from their current position.
 
For Wang, regulatory compliance is the key thing financial institutions need to keep an eye on. Stricter and stricter policies are being formed around data privacy, data security, and data jurisdiction. These guardrails also affects the use of AI and language models. Private companies and financial institutions will likely develop and use their on language models instead of relying on those provided by big tech like Google Bard of OpenAI ChatGPT. Wang also sees a greater use of open-sourced models like Meta’s LLaMa and Stanford’s Alpaca in the future. The development of proprietary models Bloomberg GPT will only accelerate.
 
Further in the AI front, Lu believes that AI transformation and digitalization accelerate as businesses become better positioned to adopt new solutions. The key hurdles to overcome in AI development are model accuracy, data security, and response times.
 

The development of AI-human collaboration

Lu continues to say that AI, ideally, should support human work. Currently, though, humans are still needed to support or guide AI. For instance, if a voice bot is not responding the way it should, human agents can jump in and take over the reigns. Humans also oversee AI work, checking the output and annotating or updating the models as needed. WIZ.AI, specifically, uses a corrections or annotation system that enables its CX designers to quickly update its bots and fine-tune data accuracy.
 
Looking beyond today, Teo sees AI solutions becoming a teammate, not just a tool or enabler. The larger vision is for AI to become a real collaborator at work – contributing input much like a human colleague. As it stands, though, AI is still prone to errors, which limits its applications. Solutions like ChatGPT can impress users, but it’s also known to give the wrong information while sounding believable. For now, the reliability of AI is still in question.
 
Where AI Singapore comes into the picture is enabling an ecosystem that develops AI technology. AI Singapore invests in research and builds research capability in the AI space. A lot of its work involves collaboration between research and industries such as healthcare. AI Singapore also invests in apprenticeship programs by training AI engineers then deploying them into companies that provide 6-month internships. Finally, the organization also looks into AI governance and ethics. AI Singapore is largely a capacity-building entity for govtech, healthcare, and defense industries.
 
One of the biggest projects AI Singapore invests in is the development of Southeast Asian large language models (LLM). AI Singapore wants to be the voice of Southeast Asia, ensuring that people in the region are properly respresented in AI models. It works together with companies like WIZ.AI in developing these models to fill the gap that GPT-4 has left. (GPT-4 is mainly trained on data from western countries like the United States and the European Union countries).
 

The future of AI and large language models

Looking into the future, Chen is bullish on vertical industry applications such as having healthcare-specific or banking-specific language models. Where previously it was nearly impossible to build industry-specific LLMs, the availability of open-sourced LLMs has made this attainable. A key example is Bloomberg, which built BloombergGPT specifically for the investment industry.
 
For all four panelists, the future of AI looks bright. Teo notes how GPT-4 shows sparks of Artificial General Intelligence (AGI), which is the holy grail of AI developers. This has led to many industry leaders like Elon Musk declaring a need to pause the development of AI, Wang notes. However, Wang sees this call to pause as futile and counter-productive, because the technology will inevitably move forward. What is needed is for government and regulators need to speed up the development of guardrails to modulate or manage the risks of AI. Teo agrees, and emphasizes that the risks with AI largely lie with how humans use it.
 
Lu closes the session with seeing the accelerating pace with which new developments come out. Previously, new versions come out every month, then maybe every two weeks. Now it is common to hear of updates happening weekly. This may seem like a threat to startup founders, who need to keep pace with everything that’s happening. But ultimately, entrepreneurs need to keep their eye on the big picture – businesses exist to help humans live better, more productive lives. The role of the AI solutions provider is to help everyday people learn how to use AI and new technologies well.
Launch customer engagement campaigns in just a few clicks with TalkGPT, ASEAN’s first generative AI-enabled omnichannel solution.
Explore TalkGPT

29
Mar
Talkbot Basics  ·  Voice AI Technology
How to choose the right conversational AI solution for your business
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

As businesses strive to improve customer experiences and streamline their operations, many are looking towards artificial intelligence (AI), specifically conversational AI solutions. Because conversational AI leverages natural language processing (NLP), machine learning (ML), and voice recognition technologies, it’s especially powerful for companies that want to adopt proactive customer service. But even for typical customer service calls, advanced voice AI technology can be a gamechanger. Voice AI bots can provide human-like interactions, helping businesses scale operations exponentially.

But not all conversational AI solutions are created equal. Different features and factors can define the success of your AI adoption. Let’s look at these in two parts – information processing and workflow integration.

Start with language understanding and dialogue

The fundamental features that can make or break a voice AI solution is how the machine processes and responds to information, which in this case, is spoken language. There are multiple factors to look into here, which are listed below.

Natural Language Understanding

Natural Language Understanding (NLU) enables machines to process and comprehend human language and respond appropriately. Without NLU, machine-powered conversations would be limited to predefined answers, almost like recordings made for interactive voice response (IVR). NLU enables conversational AI solutions to accurately interpret the intent behind customer requests, regardless of how they are phrased. NLU capabilities also enable machines to gather insights into customer needs and preferences by analyzing conversations, helping businesses understand their customers better.

Dialogue Management

Dialogue Management enables the smooth and natural flow of conversation between callers and the automated system. This involves keeping track of the conversation’s context and guiding the dialogue towards a resolution. Without effective Dialogue Management, a voice conversation with an AI engine may become disjointed or repetitive; the machine may end up providing unrelated comments or repeating itself unnecessarily.

A well-designed dialogue management enables AI to provide a natural, human-like experience for customers. For example, a customer may start a conversation with a chatbot to report an issue with a product. The bot then guides the customer through a series of questions to determine the root cause of the problem. Once in a while, the customer might interrupt with a seemingly related detail. The bot, if designed with good Dialogue Management like WIZ Talkbots, will be able to determine if this is something to explore further or if it needs to redirect the conversation to the previous point. As the conversation progresses, the bot may suggest a solution or escalate the issue to a human agent for further assistance.

Voice Capabilities

Voice Capabilities refer to a conversational AI system’s ability to accurately recognize and interpret voice input and respond through natural-sounding speech. Well-developed technical features like automatic speech recognition (ASR) and text-to-speech (TTS) language capabilities are critical in this area. High-level voice capabilities are needed to provide a natural and human-like customer experience.

 

Talk about integration and escalation

The next set of factors to consider affect operations – how well the solution integrates with your existing technology stack, and how it works with humans. Below are some of the operational considerations for selecting a voice AI solution.

Channel Integration

Channel Integration determines where and how your AI solution will be used – the touchpoints that customers will encounter it. In today’s digital age, customers expect to communicate with businesses through a variety of channels, including web, mobile, messaging apps, and voice assistants. A conversational AI solution that is not integrated with one or more of these channels may be challenged to deliver a seamless customer experience. Customers may If handoffs are not easy, customers may abandon interactions instead of completing a transaction. A conversational AI solution that offers a wide range of channel integrations provides customers choice – enabling end-users to go through their preferred channels. Because of these factors, the fewer channels a voice AI solution can accommodate, the potentially less powerful the solution can be.

Back-end Integration

Back-end Integration ensures that the system can seamlessly interact with a company’s exisiting business systems and processes. New solutions are taken up because they promise to make things better – either improve efficiency, save costs, or other optimizations. When a solution can’t mesh well with what’s already there, then the experience becomes more frustrating and troublesome than the original setup.

One of the systems that conversational voice AI may need to integrate with is a customer relationship management (CRM) solution. The new AI solution may need to access the CRM database to initiate customer outreach. Without effective back-end integration, the conversational AI solution may not be able to do what it was designed to do. Robust back-end integration ensures effective and efficient interactions with other business systems and processes, helping things move along smoothly.

Agent Escalation

Agent Escalation is what enables the AI bot to seamlessly transfer a conversation to a human agent when necessary. Conversational AI solutions can handle a wide range of customer requests and inquiries, but there may still be situations where human intervention is required. If the customer’s request is too complex for the system to handle, or if the customer is expressing frustration or dissatisfaction, it may be appropriate to transfer the conversation to a human agent. Effective agent escalation systems ensure that the customer does not have to repeat their request or context to the agent once the call is handed off. A robust hand-off system ensures that the agent taking over has access to all relevant information from the conversation so far. This helps reduce frustration and improve the overall customer experience.

So which conversational AI features are most important?

There are other factors or features that determine the performance of a conversational voice AI solution. The list of features provided here is not exhaustive, but can serve as a quick checklist to see if a product meets your requirements.

To come up with a more structured way of evaluating your options, we suggest taking the above factors and assigning a weightage to them. Then rate the voice AI solution against each factor from a scale of one to four. Multiply each rating against the weightage then add the scores together to get the final rating of the solution being considered. Do this for every option you are considering. Below is our suggested weightage for each of the features or factors discussed, based on how easy it is to get right.

Feature
Weightage
Natural Language Understanding
20%
Dialogue Management
25%
Voice Capabilities
25%
Channel Integration
15%
Back-end Integration
10%
Agent Escalation
5%

Bear in mind that each business will have specific priorities when it comes to choosing a voice AI solution. You may want to adjust the weightage according to what you believe to be important in your operations. If you need a solution that can work across all your customer communication channels, then Channel Integration must have a higher weight in your evaluation. If all six factors seem to be equally important, then divide the scoring equally.

By carefully assessing factors that are critical to your business success, you can select a conversational AI solution that offers the right mix of capabilities to meet your requirements. The right conversational AI solution will help you transform your call operations and differentiate your brand from competitors in today’s increasingly digital and customer-focused marketplace.

Conversational voice AI may be the solution you need to optimize your call operations. Speak with one of our business executives to find a tailor-fit solution.
Contact us

22
Mar
Talkbot Basics  ·  Voice AI Technology
Transform your operations with voice AI technology
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

Events in recent years have accelerated digital transformation across the globe. More than ever, businesses see the importance of leveraging digital technologies to stay competitive in today’s rapidly evolving landscape. These same businesses are embracing new digital tools to improve operational efficiency, enhance customer experiences, and drive growth.

One of the key technologies driving digital transformation is artificial intelligence (AI). With this technology, tasks that traditionally require human intelligence, such as recognizing speech, understanding natural language, and making decisions based on data, can now be – to some degree – outsourced to machines. From automating repetitive tasks to delivering personalized customer experiences, AI is transforming the way businesses operate and engage with their customers. In particular, voice AI has emerged as a powerful tool for improving customer experiences and optimizing business processes.

Here are some of the benefits of voice AI in three specific business areas – sales and marketing, customer service and support, and personalization and user experience.

Voice AI for sales and marketing

Adopting voice AI solutions can have significant impact in sales and marketing. Conversational AI can be used to power voice bots that can engage with customers through voice calls. In the case of WIZ Talkbots, these conversations can even be initiated in the user’s local language.

Voice AI-powered bots are especially useful in handling large volumes of outbound lead generation calls. Through automation, Talkbots can handle up to 10 million calls in an hour, exponentially growing a brand’s reach through telemarketing.

Businesses can also improve customer satisfaction and loyalty through voice AI adoption, thanks to the rich data which AI engines can extract from recorded calls. Analytics from voice data can help brands identify customer preferences and tailor product recommendations and marketing messages accordingly. This can, in turn, help businesses increase their conversion rates and generate more revenue.

Voice AI for customer service and support

AI-powered Talkbots can also be used to answer and triage inbound calls, providing customers with instant assistance and support. With voice AI, businesses can provide their customers with 24/7 support without the need for human intervention. Voice AI can handle a range of customer service tasks, from answering simple queries to helping customers troubleshoot technical issues. This can significantly reduce the response time for customer queries and complaints, leading to improved customer satisfaction. Furthermore, voice AI can handle a high volume of queries simultaneously, reducing the need for human agents to handle simple and repetitive queries.

Voice AI in customer service can also provide more personalized support. By analyzing customer data and behavior, voice AI can identify individual customer needs and preferences, and provide customized solutions. This level of personalization can help to build a strong relationship between the customer and the business, leading to improved customer loyalty and retention.

By providing round-the-clock support, personalized assistance, and quick response times, voice AI can help businesses to meet the evolving needs and expectations of their customers.

Voice AI for personalisation and user experience

The previous use cases have shown how voice AI technology can drive hyper-personalization. But there are other instances where personalization can come into play. Voice AI has the ability to adapt to different contexts and situations, providing more appropriate responses based on the user’s location, time of day, and other contextual factors. This helps build a more seamless and intuitive experience and a stronger connection between users and brands, leading to improved customer loyalty and retention.

In general, leveraging analytics from voice data can help businesses to create more engaging and intuitive interactions, leading to improved customer satisfaction and loyalty.

Voice AI for general operations

Voice AI is not limited to the above scenarios, and can be used to optimize a lot of internal business processes. For example, it can be used to automate repetitive tasks such as call transcription, tagging, and data entry, freeing up employees to focus on more complex tasks. In almost all use cases, voice AI can help businesses to increase their revenue, improve customer satisfaction, and optimize their internal processes. By leveraging the power of voice AI to deliver personalized experiences and engaging interactions, businesses can stay ahead of the competition and meet the evolving needs and expectations of their customers.

Voice AI can be a key step in the digital transformation of your call operations. If you need more guidance, speak with one of our business executives today.
Contact us

16
Mar
Customer Stories  ·  Voice AI Technology
Link Net doubles its customer outreach with WIZ Talkbots

 

Link Net has been providing Indonesians with internet connectivity and home entertainment for over 20 years under the First Media, i-solution, and Link Net brands. It currently serves 2.8 million homes across 23 cities in Indonesia. Keeping track of all those accounts – especially when they fall past due – is a whole operation in itself.

“Previously, we used SMS for billing, which then was supplemented with outbound calls,” begins Pak Ikhsan Kurniawan, Head of Printing and Collection Department at Link Net. “We gradually moved to email and now, we also use WhatsApp. We also tried smart IVR but it turned out not to be suitable for overdue payments. So we stopped using IVR because it did not bring results.”

Link Net also struggled with capacity planning for its outbound calls for collections. When the telephone collections team is experiencing a manpower shortage, the company would temporarily reassign people from other departments to help manage the load. This disrupted day-to-day work and workload management. Link Net realized it needed a more effective way to follow-up with overdue accounts, and started exploring options.

Going beyond one-way conversations

“We liked WIZ’s solution because it was a two-way interaction, not like IVR which is very limited,” shares Pak Ikhsan. “It also helped us with workload balancing. If someone from telecollections takes maternity leave, we can immediately add more bots to fill the gap.” 

The solution brought tangible results. “When we tried the WIZ solution, our results improved, especially in the connection rate,” shares Pak Herri Dwi Prasetyo, MIS Leader of Collection & Recovery Department at Link Net. “The connection rate for human agents was 25 percent but with the Talkbot, it increased to almost 50 percent.” The use of Talkbots also freed up human agents from many of the easy, repetitive tasks. It also reduced the call load for human agents by half. “This gave our agents more time to focus on retaining customers and handling more complex complaints. The use of the bot made the role of human agents more strategic,” Pak Herri adds. 

“Talkbots are the best collection strategy we have implemented so far,” confirms Pak Ikhsan.

"We stopped using IVR because it did not bring results. Talkbots are the best collection strategy we have implemented so far."

– Pak Ikhsan Kurniawan, Head of Printing and Collection Department at Link Net

An exceptional user experience

When talking about their experience with WIZ, Pak Herri has good things to say. “The application itself is very user-friendly and has a good validation system,” he begins. “For example, if someone tries to upload the same number twice, the system will immediately eliminate one of them.”

Working with the WIZ team has also been positive. “All the WIZ team members are so supportive and helpful,” Pak Herri continues. “Whatever we need, the escalation process is so fast. As an end-user, it is very helpful to know that everything is processed quickly and all team members are contactable.”

For Link Net’s customers, the change in strategy was barely noticeable. “99% of customers do not realize that they are contacted by a robot,” says Pak Ikhsan. “Out of 20,000 contacted, only 10 complained about being called by a bot. When that happens, we exclude the specific customers from the next Talkbot call database.”

"All the WIZ team members are so supportive and helpful. Whatever we need, the escalation process is so fast. As an end-user, it is very helpful to know that everything is processed quickly and all team members are contactable."

– Pak Herri Dwi Prasetyo, MIS Leader of Collection & Recovery Department at Link Net

A new way to retain old customers

With the success of the new collection strategy, Link Net was keen to try the Talkbot in other scenarios. The company decided to try automating customer retention or recontracting. Together with the WIZ team, Link Net created a new script for contacting customers who were recently lost, like those who have not paid for their subscriptions in three months. “The contact rate for this category of customers is lower,” explains Pak Ikhsan. “We hope that with the new retention script, we can win back customers by offering promotions.” 

It’s still early days in the customer retention campaign and results are still to be seen. The team is currently refining the script based on feedback, in order to get the right message across.

Pushing the limits of automation and analytics

Link Net wants to set more stringent standards for their debt collection processes in the future. “We are heading towards digitization, everything must be automated,” begins Pak Ikhsan. “If someone defaults or misses a payment, they should be called automatically. Everything should already be automated, including redials. Then the results can be updated in real-time on the Link Net system.”

For Pak Herri, data is the secret ingredient to ongoing and future success. “We expect in the future we can download the transcript of the conversation directly from the system,” he says. “With this feature, we can use all information to gain feedback and complaints from customers. So when a human agent conducts a follow-up call to a certain customer, they will immediately know what the customer complained about. We will have the customer history and can give a seamless experience.” 

The collections team was so satisfied with the WIZ Talkbot that it recommended the solution to Link Net’s sales team, for customer onboarding. “We never contacted these type of customers before,” confesses Pak Ikhsan. “This is something we will explore and discuss further with the WIZ Team.”

Wondering how voice AI automation can improve your business results? Speak to one of our specialists today.
Contact us

10
Mar
Talkbot Basics  ·  Voice AI Technology
Voice AI: The future of proactive customer service
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

In recent years, proactive customer service has emerged as a game-changer in the world of customer experience (CX). Instead of waiting for customers to report issues or complaints, businesses are taking a more proactive approach by reaching out to customers with relevant information, personalized recommendations, and real-time support. This shift towards proactive customer service is driven by changing customer expectations and the growing availability of AI-powered tools and technologies.

Benefits of proactive service

There are several benefits to adopting a proactive customer service approach. According to Statista, 70% of consumers have a more favorable view of brands that contact them with proactive customer service. This translates to a 5% increase in customer retention over a 12-month period, according to a report by Enkata. And it’s not just brand perception that gets a boost; companies that engage in proactive customer service have reported a reduction in customer service call volumes by up to 30 percent, which contributes to a 25 percent reduction in operating costs. Let’s look at these benefits one by one.

  1. Improved customer experience. Proactive customer service anticipates and addresses customer needs before they become problems. By providing relevant information, personalized recommendations, and real-time support, businesses can demonstrate their commitment to customer satisfaction and build stronger relationships with their customers.
  2. Reduced operational cost. Businesses save time and resources with proactive customer service by reducing the need for reactive support. Because issues are identified and resolved before they get escalated, businesses can minimize the number of support tickets or calls they receive, freeing up staff time for more high-value tasks. This leads to increased efficiency and productivity, as well as cost savings.
  3. Increased customer loyalty and retention. When customers feel that a business is proactively looking out for their best interests, they are more likely to stay loyal and recommend the business to others. Reports indicate that proactive service increases customer retention by up to 5% per year. This can lead to repeat purchases, and ultimately, business growth.
  4. More customer insights. Proactive customer service is a great opportunity to solicit feedback on products and services. It also presents opportunities to dig deeper into user motivations and preferences. Businesses can gain a deeper understanding of their customers and use that knowledge to deliver even more personalized and effective customer experiences.

Using AI to power proactive service

To reap maximum benefits from proactive customer service, businesses need a way to scale its outbound call operations. This is where voice artificial intelligence (AI) comes in. Businesses can leverage voice AI technology to provide automated, personalized, and context-aware customer interactions. Voice AI systems can also identify opportunities for proactive engagement and deliver targeted messages or offers, thanks to advanced analytics. Fed with rich data, businesses can proactively serve customers with relevant and timely information that improves user experience.

Call-based voice assistants could remind a customer about an upcoming appointment, suggest a new product based on their previous purchases, or offer personalized discounts. This not only improves customer experience but also increases the chances of repeat purchases and customer loyalty.

Personalizing interactions with analytics

In addition to automating customer outreach, voice AI technology can also use predictive analytics to anticipate customer needs and deliver proactive solutions. For example, if a customer frequently asks about a specific product feature, a voice assistant could proactively offer additional information or training on that feature. This not only improves customer experience but also reduces the need for reactive support, saving time and resources for both the customer and the business. 

Voice AI technology can also provide insights into customer sentiment and satisfaction. By analyzing tone, language, and other factors, voice AI systems can identify when a customer is experiencing frustration or dissatisfaction and take proactive steps to resolve the issue. For example, if a customer expresses frustration with a product or service, a voice assistant could offer to connect them with a customer support representative or escalate the issue to a higher priority. 

Voice AI technology can enable businesses to deliver proactive customer service at scale, tailored to individual needs and preferences. As voice AI technology continues to evolve, it is likely that we will see even more innovative and effective applications for proactive customer service.

Want to ramp up your proactive customer service? Book a call with one of our business executives.
Contact us

02
Mar
Talkbot Basics  ·  Voice AI Technology
Build richer customer profiles by unlocking hidden preferences with AI
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

The surge of interest in artificial intelligence (AI) brought about by the launch of GPT-3 – the engine behind OpenAI’s ChatGPT bot – has gotten more businesses exploring possibilites in AI technology. One of the more obvious benefits of AI technology is its ability to analyze large amounts of data quickly and accurately. Voice AI pushes this boundary even further by converting unstructured voice data into structured datasets.

Voice AI can capture a wide range of data points, including the customer’s tone of voice, sentiment, and the specific words or phrases they use. This data can provide businesses with insights into customer preferences, needs, and behaviors, depending on how deep and well you dig into the information. One key ingredient in unlocking and enhancing customer interactions is what the AI training world calls intents.

Voicing out customer intents

Intents play a crucial role in AI technology, particularly in voice AI systems. Intents are essentially the goals or purposes of a user’s spoken or written input. They can be signalled by specific words or picked up contextually, and are used by AI engines to determine what action should be taken in response. In other words, intents help AI systems understand what a user wants or needs, allowing them to respond appropriately.

For example, if a user asks a voice assistant to play a song, the intent of their input is to request music playback. The voice assistant’s AI technology recognizes this intent and responds by playing the song that was mentioned. Similarly, if a user asks a bot for recommendations on a particular category of product, the intent of their input is to seek advice on product choices. The bot’s AI technology recognizes this intent and, taking cues from previous interactions, responds with personalized product recommendations.

Intents are typically defined using natural language understanding (NLU) models, which are trained on large datasets of human language to identify and classify intents accurately. NLU models use a combination of techniques, such as machine learning algorithms and semantic analysis, to interpret the meaning behind a user’s input and identify the intent accurately.

Getting intents right enables businesses to provide more accurate and personalized interactions between users and machines. By understanding users’ intentions, AI systems can provide more effective responses, improving the overall user experience and increasing user engagement.

Discovering what customers like

Voice AI can discover hidden customer preferences by picking nuances and taking note of them into customer profiles. These extra data points can help paint a more complete picture of customers, enabling businesses to better personalize customer journeys. Here are some ways voice AI engines can pick up hidden cues from call data.

  1. Tone of voice analysis – Just as human agents can sense a customer’s emotional state through their tone of voice, voice AI engines can also be trained to pick up these signals through changes in pitch or speed of talking. When a bot detects that a customer is agitated, it can switch to a more soothing or calming tone to reassure customers. If the customer shows a persistent pattern of getting agitated, this can signal a preference to speak with a human agent. Talkbots can use mellow speaking tones during initial interactions, then hand off the interaction to a human agent who has high empathy and emotional intelligence.
  2. Sentiment analysis – Voice AI technology can analyze the sentiment of customer interactions, categorizing them as positive and negative experiences based on how the customers respond. This information can provide businesses insights into areas where they need to improve, as well as how, when, and in which channels customers prefer to be spoken to.
  3. Natural language processing – By leveraging natural language processing, AI can attribute meaning to customer statements, even when they use colloquial language or non-standard grammar. As bots engage with customers, the AI engine begins to develop its understanding of certain expressions and can classify specific words or phrases as having positive or negative connotations. As the patterns are strengthened through various interactions with different customers, the bot can then refine its future interactions.
 

Building better customer profiles with data

All these tools enable AI assistants to collect data from every interaction. While humans may struggle to record, analyze, and interpret vast amounts of data from call recordings, voice AI engines can transcribe, process and analyze customer interactions in a matter of minutes. This analytic capacity enables businesses to identify patterns and trends in customer behavior that may not be picked up in a timely manner, or even altogether missed.

The ability of voice AI engines to collect data on customer interactions is proving to be more and more useful in building up robust customer profiles. helping build more robust customer profiles. This, in turn, helps create more personalized customer experiences and tailored marketing, which ideally improve customer satisfaction.

We are just starting to build our capabilities in AI technology. As large language models continue to become more sophisticated and AI neural engines more accurate, intent recognition will continue to improve. Ultimately, this will lead to even more seamless and personalized interactions between users and machines, creating experiences that customers will not just enjoy, but also remember.

Capture even more information from customer engagements with WIZ.AI Talkbots. To learn how our data analytics can help you understand your customers better, schedule a call with one of our consultants.
Contact us

22
Feb
Talkbot Basics  ·  Voice AI Technology
How AI technology can help call centers up their game
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

Call centers play a critical role in shaping customer experiences – many, if not most, of customer queries get routed to a contact center. These business units are also often the ones who do a lot of customer outreach, promoting new offers or enlisting new customers. With so much customer interface, it makes sense to focus on amping up contact center operations.

Relieving call center pain points with AI

Unfortunately, these centers face a range of challenges that can impact customer experience, agent performance, and overall business outcomes. Many of these pain points are operational and demand more flexible, intelligent solutions. Here are some problems call centers encounter, and how solutions powered by artificial intelligence (AI) can help reduce or solve them.

  1. High Call Volumes – Call centers don’t handle the same volume of calls day-in and day-out. Many contact centers experience high call volumes during periodic moments, or even unexpectedly – such as during a service outage. The problem comes when contact centers are not equipped or designed to handle these peak loads. Many call centers are resourced by humans, which have a finite capacity and can only answer a fixed number of calls a day. Because of this lack of resource elasticity, customers end up having long wait times during peak seasons. This degrades the customer experience and builds frustration instead of loyalty.
    To help with peak loads, AI-powered chatbots and voice assistants can handle basic customer queries. This frees up live agents, giving these agents the time and capacity to focus on the more complex calls. Customers, in turn, gain the attention and level of service that they need for their queries.
  2. Inconsistent Customer Service – One of the hardest things to get right in call centers is consistency in service quality. The goal is to provide excellent service to all customers all the time, but even your best agent will have bad days. And your workforce is made of different individuals with varying capacities, so the way these individuals provide customer service will vary, too. One way to overcome this inconsistency is to rely on machines. Voice AI can respond to customer queries in a standardized way, ensuring that every customer receives the same level of service. And the interactions don’t need to sound robotic – WIZ.AI can design voice AI bots that speak in your local language, putting your customers at ease.
  3. Agent Burnout – Call center agents often face the brunt of customer frustrations, fielding a large number of complaints or trying to help anxious customers address issues. They may also be fielding a high volume of repetitive calls that drain them, making them feel like they’re stuck in a negative loop. Human agents can be freed of tedious and repetitive tasks or queries through the help of AI-powered chatbots and voice bots. These machine-enabled agents can take care of routine customer queries, easing the workload and pressure off human agents. Using AI-powered bots also enables agents to focus on more complex issues and deliver higher-quality service to customers.
 

Getting further ahead with efficiency gains

Outside of the handling of calls, AI technology provides other benefits, too. Using AI bots reduces the time and resources needed for agent training and onboarding. Because AI agents are already programmed, adding one is just a matter of allocating additional computing resources – which can be done as quickly as one hour. What’s more, companies can leverage AI’s consistent delivery to train new human agents. AI engines can identify trainee errors and provide coaching to improve delivery. This system can even be extended into regular quality control checks to ensure consistency in service across teams.

Then there are the savings incurred. AI-powered agents are more cost-effective because these can handle more calls per hour compared to human agents. Redialling of uncontacted numbers is done automatically, and transcription is practically real-time. This saves businesses time and money, enabling contact centers to reassign human agents to higher-value tasks such as closing sales or providing VIP assistance.

Reaping the benefits of human-bot collaboration

Contrary to some fears, AI will not replace humans – no matter how well-programmed they are. Well-designed voice AI agents can actually help boost contact center performance, bringing the service of human agents to the next level. Voice AI solutions like WIZ Talkbots can help create better customer experiences and more efficient operations. Used in the right way, AI technology can help alleviate many of the pain points that contact centers face, thereby improving customer experience, reducing costs, and increasing efficiency.

WIZ.AI Talkbots can bring your contact center from good to great. Schedule a call with one of our consultants to see how your operations can benefit from voice AI technology.
Contact us

15
Feb
Talkbot Basics  ·  Voice AI Technology
Compete – and win – by delivering amazing customer experiences
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

In today’s competitive landscape, customer experience has become a key differentiator for businesses. Customers now have access to more options than they had in all of history – and they’re mostly available at their fingertips. Companies must now work harder than ever to stand out, and part of that differentiation is through crafting a memorable customer experience.

Customer experience (CX) encompasses all interactions a customer has with a business, from researching products to post-purchase support. By providing a positive customer experience, businesses can increase customer loyalty and retention, improve their brand reputation, and drive revenue growth. On the other hand, a negative customer experience can lead to a loss of business and harm to a company’s reputation. In a PwC report, we read that 59% of consumers in the United States will walk away after several bad experiences, 17% after just one bad experience.

In addition, customer experience has become a key factor in purchasing decisions. The same PwC report indicates that 73% of consumers consider experience as the third most important factor in purchasing decisions, after price and quality. Multiple surveys in the past ten years have also shown that customers are willing to pay more for a better customer experience. That trend is unlikely to change course; in fact, it will only accelerate. Businesses that invest in creating a seamless, personalized, and consistent experience across all touchpoints are more likely to delight customers and keep them loyal. With customer experience becoming increasingly important, businesses need to focus on delivering exceptional customer experiences in order to stay ahead of the competition.

Creating better experiences with AI technology

One way to compete – and gain advantage – in the CX space is through the smart use of technology. AI-powered solutions have the potential to significantly improve customer experience in a number of different ways. Here are some of them.

  1. 24/7 support: Voice AI solutions can provide 24/7 support to customers, without the need for human intervention. This can help improve the customer experience by providing instant and efficient support, reducing wait times and improving response times. According to a report by Salesforce, 64% of customers expect companies to respond in real-time.
  2. Improved customer insights: AI-powered voice solutions can help businesses gather valuable customer insights, by analyzing voice interactions and identifying patterns and trends in customer behavior. This can help businesses improve their products and services, and tailor their marketing strategies to better meet customer needs.
  3. Personalized interactions: With deeper customer insights, brands can better provide personalized interactions based on unique customer preferences and behavior. A more tailored and relevant experience to each individual customer creates a sense of being valued, and increases appreciation for the brand.

As AI technology continues to advance, businesses that prioritize the use of AI in their customer experience strategies are likely to see increased customer satisfaction, loyalty, and revenue growth.

Investing in customer experience creates win-win scenarios

Focusing on CX can increase brand loyalty and customer retention. Customers who have a positive experience with a company are more likely to return and do business with that company again. By making the effort to provide a consistently positive experience at every touchpoint, businesses can build trust with their customers and foster long-term relationships that are crucial for sustained success.

Prioritizing customer experience can also improve a company’s brand reputation and generate customer advocacy. Happy customers are more likely to recommend a company to their friends and family, leading to an increase in word-of-mouth referrals and organic growth. A strong brand reputation and positive customer reviews help attract new customers and build trust in the marketplace.

The benefits of focusing on customer experience are clear. By prioritizing customer satisfaction and delivering a consistently positive experience at every touchpoint, businesses can build customer loyalty and retention, improve their brand reputation, and drive revenue growth. The investment in delivering a high-quality customer experience can pay dividends in the form of increased customer lifetime value and a stronger competitive position in the marketplace.

AI Talkbots can empower your enterprise to execute and reap the benefits of exceptional CX. Find out how we can help you achieve CX excellence by scheduling a call with one of our consultants
Contact us

09
Feb
Talkbot Basics  ·  Voice AI Technology
Elevate customer experience through smart design, not just technology

Last 08 February 2023, we concluded our successful webinar “Customer Engagement Strategies for APAC Leaders in 2023 and Beyond” – done in partnership with Microsoft and Whispir. Speakers Shuh Hun Tan (Commercial Business Lead at Microsoft) and Andrew Fry (Global Vice-President for Strategic Partnerships at Whispir) shared their insights on customer experience (CX) within the region, alongside our very own Allan Ong (Head of Business Development and Partnerships). Below is a summary of key points discussed during the event, as well as some additional insights around the topic of customer engagement.

The CX landscape is changing rapidly. While companies are benefitting from the growth of their customer base, the ratio of service agents to customers subsequently gets stretched. This means customers may not get the kind of service or attention that they need, when they need it. There’s also a growing mismatch between how customers want to be served and the channels that are available to these customers. This further adds to the frustration that customers feel when they are trying to resolve an issue.

Smarter use of technology for enhanced CX

The answers to these issues lie not simply in technology, but the smart application of relevant solutions at the right stages. The foundation of any CX strategy should be the customer journey map. A well-thought out map includes customer touchpoints and the channels that can best serve customers at those points. Only then should brands start thinking about how they can craft messages that are relevant and meaningful – interactions that will build brand strength and recall.

Critical to informing the design of customer conversations and interactions are the data collected from past interactions. Voice data is often difficult to leverage because in its raw form, it is unstructured and disparate. But voice AI technology can bridge that gap, enabling companies to draw insights from a wealth of data that was previously untapped. The new challenge is making sure that the right people get access to this data in a secure manner, so that customer communications can be refined and personalized.

Forces of Customer Experience (CX)

Status – make customers feel valued, respected, and worthy of special treatment
Certainty – design communication to be clear, transparent, and working as expected
Control – prompt response, help customers feel in control of the situation and feel they are in the driver’s seat
Localization – speak or communicate in the customers’ language; create a sense of familiarity through language and tone

The need for seamless, omni-channel communication

One key issue plaguing CX professionals these days is the fragmentation of customer journeys. This is often the result of siloed activities and a hard separation between channels. FAQs might be answered on the website or through chat or messaging apps; service or technical issues might be handled by a hotline or voice channel. A customer might come to your help site looking for assistance, only to be told that they need to call a helpline to address their issue.

What if, from the automated chat, the bot recognizes the need for a live agent and automatically connects the customer to a live agent via voice call? How delighted would that customer be? And yet customers today don’t expect that kind of seamless handoff and omni-channel communication, because companies have yet to offer that level of service. We need to be able to deliver connected conversations across channels and this starts from making sure our customer journeys are no longer fragmented. We need to join things up better with the help of smart tools.

Rising customer expectations

Fry also mentioned how expectations of customers are now higher than ever. Post-pandemic, after a boom in digital transactions, expectations of immediacy, personalization, first-time resolution, and respecting consent have risen to all-time highs.

Against this backdrop, customer engagement is now even trickier. There is so much more pressure for organizations to get things right – to respond in time, through the right channels, with targeted messaging and quick resolution while respecting the customers’ preferences in terms of being contacted.

This is where technology comes in. Technology can help businesses better understand their customers, empower their employees, and optimize their operations. Solutions like voice AI-powered automation can help enterprises reach individual customers with targeted, personalized messages at scale. AI technology can empower brands to answer specific needs more efficiently or offer relevant services in a way that is secure, respectful of consent, and regulatory-compliant.

Future-proofing your CX operations

Even as new solutions are introduced into the CX toolkit, the fundamentals remain the same. Brands need to develop content that resonates with their audience, independent of specific channels or touchpoints. Doing this enables companies to continue delivering personalized experiences to customers regardless of how devices or channels evolve.

Understanding how technological solutions interface with human workers is key to long-term success. As Ong points out, companies need to leverage human-machine collaboration to increase overall productivity. Identify what machines are good at, and what people can do better – creating a customer experience that is both efficient and human.

Whether you’re a cutting-edge fintech or a well-established traditional, AI solutions should be in your future-proofing arsenal. And adopting a pre-built solution is one of the easiest ways to get started on your AI journey.

Looking to optimise your CX operations using voice AI technology? Speak to one of our consultants today.
Contact us

Page 2 of 4