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industry: Collections and Payments

How Skit.ai Elevates CX in AI-powered Collection Calls

Posted on by Simone Somekh

Debt Collection and Positive CX: Is It an Oxymoron?

Discussing customer experience and debt collection in the same sentence might sound like an oxymoron: for most people, the experience of being reminded about an outstanding debt is not particularly thrilling. Yet, the fact that collection calls are not the most welcome calls a customer may receive does not mean their experience should be dry—even negative.

At Skit.ai, we offer an effective and easy-to-deploy conversational voice AI solution for the ARM industry. There are many ways to make the interaction between a user and a voice AI efficient, easy to navigate, and painless.

What is the role of Conversation User Experience (CUX) Design in fostering a positive customer experience (CX) in AI-powered debt collection calls? In this blog post, we’ll share the best practices we’ve adopted to enhance CX in our automated collection calls.

The Role of CUX Design in Improving the Customer Experience

When creating and configuring our conversational voice AI solution for collections, our designers prioritize three components, all of which are essential and will ultimately influence the customer experience when interacting with the voicebot: voice, verbiage, and interaction.

Voice is the audio component of the voicebot: Does it sound male or female? Young or old? What accent does it have? What’s the inflection of the voice? How does it sound—friendly, professional, clear, direct? How fast does it speak? Fast enough to keep the user engaged, but slow enough for the average user to understand? All these questions are taken into consideration when designing the voice AI solution. There are no correct answers, as different use cases and demographics require different characteristics.

Verbiage is the content of the voice AI’s communications during the call with the user. The aim is to make the voice AI solution speak in a natural language so that the interaction can flow smoothly and naturally. Designers take into account grammar, choices of terminology, and other utterances to ensure that the voicebot sounds natural.

Regarding terminology, designers usually seek to balance industry-specific jargon and simple terminology to accommodate users lacking the background and context around the call.

Voice and verbiage, paired together, contribute to creating the digital agent’s “Persona.” For example, that could be a 30-something-year-old female agent, with a confident yet empathetic voice, sounding efficient and eager to help the customer; she could have a midwestern accent and a friendly, yet professional attitude.

The interaction capability of the voice AI solution is the third key element that defines the user experience. This element is the voicebot’s ability to handle an effective back-and-forth with the user. Timing, here, is crucial: when does the AI pause, and for how long? The devil is in the details: missing a comma can change the meaning of a sentence and make it difficult for the user to understand.

How long does the AI wait to reply after the user has spoken?

How does the AI express its prompts? For example, at the beginning of the call, the voicebot will want to verify the user’s identity for authentication purposes; to do this, it will likely suggest the preferred format of the user’s response:

Example: Can you please verify your date of birth? For example, “July 1st, 1985.”

If the AI pauses between the question and the suggested response, the user might respond before the suggestion, leading to mistimings, disfluencies, interruptions, and a potentially failed interaction. To optimize the interaction, a CUX designer will configure the prompt so that the back-and-forth can take effect as smoothly as possible.

The success of the voice AI solution depends on these three pillars. But the customer experience goes well beyond that—let’s explore more aspects in the following sections.

Common CX Concerns: Quality of Speech Recognition and Agent Transfers

One common concern related to customer experience with conversational voice AI is the quality of the ASR, i.e., speech recognition. The fear is that the technology won’t understand the user’s responses and extract the correct “intents” and thus fail to deliver a smooth, natural-sounding interaction. The technology behind speech recognition and natural language understanding has dramatically evolved over the last few years. While this used to be a major problem a few years ago, today it’s less of a concern.

Of course, poor connection or background noise can still hinder the tech’s ability to understand what the user is saying. That’s where a repair strategy comes into play to take the conversation back on track and prevent misunderstandings. Whenever the AI fails to hear the user’s response, it can politely ask them to repeat or rephrase it. Similarly, when the user is uncertain about how to respond, it can offer to repeat it more clearly or rephrase it using different words.

Another common concern relates to agent transfers. Users often fear that the voice AI solution won’t let them easily transfer the call to a live agent if requested. That’s not the case with Skit.ai’s solution. Whenever the customer’s needs are too complex for the AI to handle, and whenever the customer requests it, the solution will always transfer the call to a live agent from the collection agency.

The Role of Personalization as an Effective CX Tool

To achieve a seamless customer experience, a company must know its customers. That is why, in addition to outlining the voice AI’s persona, we also consider the user persona, i.e., the user demographics. Incorporating personalization into the conversation with the voice AI solution helps make it more engaging and fosters trust. However, it’s important to maintain a balance—while personalization is great, you also don’t want to overdo it in order to protect the user’s privacy. This was recently highlighted in data showing that the majority of consumers expect personalization, as long as the data is handled responsibly.

One small touch is incorporating the user’s first name throughout the conversation. For example, after the user authentication is completed, the voicebot can say: “Thank you, Sarah,” to confirm that it’s verified the user’s identity.

Showing that the voice AI solution is aware of the context of the conversation can also improve CX. For example, during an inbound call, the voicebot may say: “I see that you have an outstanding balance of 241 dollars and 50 cents. Is this what you are calling about?”

After the user has made a payment, the voicebot can express enthusiasm like this: “Good news, Sarah! I received your payment of 241 dollars and 50 cents.”

Regional languages and dialects also ensure that the solution is tailored to specific markets. For example, Skit.ai’s voice AI solution speaks over half a dozen languages along with understanding several regional accents.

Incorporating Empathy in Automated Collection Calls

When it comes to sensitive use cases such as debt collection and medical-related calls, empathy is an important component of the voice AI solution’s capabilities. The choice of words, tone, and inflection used by the voicebot can greatly affect the voicebot’s ability to convey empathy, particularly when a user expresses their inability to pay off their debt.

For example, the user may say: “I just lost my job, I can’t deal with this right now.”

How should the voice AI solution respond? The role of empathy in AI is a complex matter: If the voicebot says, “I’m sorry to hear that,” it might irritate the user, given that a computer cannot truly grasp the emotions of someone who has lost their job. However, a common phrase like “I completely understand the situation” is a conventional expression to indicate that the AI solution has acknowledged the user’s challenge.

The voice AI solution is designed to offer options to reach a satisfactory resolution. If the user can’t pay off the debt right away, the solution can offer a few alternatives, such as a payment plan or the ability to connect again in the future.

When designing the voicebot to express empathy, we want to avoid the so-called “uncanny valley” effect. If the voicebot switches abruptly from an overly empathetic statement to a neutral tone, it can cause the user to experience unease and irritation. Therefore, there needs to be consistency in the voicebot’s naturalness and tone, avoiding excessive variation and unexpected changes in its behavior.

And Finally… Regular Quality Checks

While old systems were static and rigid, new-generation conversational voice AI solutions like Skit.ai are dynamic and adaptive. The solution is built to improve over time. Additionally, after the solution is implemented, CUX Designers regularly perform quality checks and listen to calls with customers to ensure that the voice AI functions correctly. This way, they’re able to regularly train the solution to add new capabilities, understand more user utterances and intents, and offer the most appropriate responses.

Are you curious to watch Skit.ai’s Conversational AI solution for collection calls in action? Contact us using the chat tool below and schedule an appointment with one of our collection experts!

Skit.ai’s Augmented Voice Intelligence Platform Takes a Giant Leap with Generative AI

Posted on by Harshad Bajpai

Skit.ai’s Augmented Voice AI Platform is now powered by Generative AI. With the incorporation of Generative AI, we are taking a giant step forward and boosting the capabilities of our Conversational Voice AI solution. The interactions with consumers are about to become more natural-sounding and complex, leading to an improvement in customer experience (CX) and better results for collection agencies using Voice AI.

At Skit.ai, we embrace the future and go beyond industry standards and expectations.

How Generative AI Impacts the Capabilities of Skit.ai’s Augmented Voice Intelligence Platform

With the ongoing application of large language models (LLMs), we are seeing a big jump in the conversational capabilities of our solution:

Higher Conversational Accuracy: LLMs are capable of understanding consumer interactions through an improved understanding of context, sentence parsing, and response accuracy, leading to significantly higher conversational accuracy.

Better Handling of Complex Conversations: Generative AI enables our voicebots to better handle more complex interactions that were earlier escalated to human agents. This improvement can reduce the percentage of call transfers from the Voice AI solution to the company’s human agents.

Out-of-scope Calls: The LLM’s ability to grasp a wide range of questions and topics enables our voicebots to better handle out-of-scope utterances and calls.

Natural Utterances: The Voice AI solution is able to express a wide variety of natural-sounding utterances that improve the quality of the interaction.

Faster Voicebot Creation: Incorporating Generative AI give a big boost to the speed at which new voicebots can be created as the inherent complexity and effort involved in the design, and creation is a fraction of earlier effort.

Massive Performance Gains with Generative AI Springboard

In addition to the massive gains we are seeing thanks to LLMs, we intend to take this exercise even further and enable our voicebots to outperform human agents and collectors.

Going Beyond Human Agent Performance

An agent’s performance rests on two things: the ability to communicate and technical skills. At Skit.ai, we’ve seen that, with current LLMs, we can achieve superlative communication skills, and by training extensively with end-user data, we can achieve a high degree of technical skills. Hence our solution can excel on both fronts.

To share a rough estimate: the best-performing agent finds success on 5% of the calls (out of all connected calls), while low performers convert about 2% of the calls.

With Generative AI, we take a big jump. From the current voicebot conversion capability of around 1-2%, we expect the performance to jump 3-4 folds. Beyond this, our Reinforcement Learning platform learns from outcomes to personalize the conversation to figure out the ideal strategies, learning from thousands of daily conversations.

Better and More Natural Spoken Conversations

Generative AI, with its unparalleled conversational capabilities, needs to be complemented with equally capable speech synthesis and understanding systems that produce the right speech given the output from LLMs. And that is one of the major areas from the many below:

  • A more natural-sounding TTS (text-to-speech) voice
  • Conversational context handling prosody of generated audio
  • Full duplex and backchannels in speech conversations

Ultimately, we will be able to deliver the most engaging conversations that delight consumers by solving their problems faster and better than human agents.

The Business Outcomes of Incorporating Generative AI

Below are five major impact areas we will move the needle on:

Higher Collection Rate, ~5%: This is a difficult number to quantify, but as the incorporation of Generative AI matures, we expect its collection capability to move beyond 5%, surpassing even the best of human agents.

Lower Agent Dependency, reduction by 50-80%: As the voicebot will be able to handle more complex queries, we expect a 50-80% reduction in agent touch points.

Higher Resolution Rate, ~100%: Better accuracy and conversations with higher engagement will help us achieve a conversational resolution rate close to 100%.

Creating New Voicebots: The effort to create new voicebots will see a significant dip, as the complexity will be remarkably lower.

Entering New Markets with Ease, 15X faster: Entering new markets and training for new use cases and applications will require less effort and resources. We are estimating the process to be 15X faster.

What’s Next

Though the improvements in our Augmented Voice Intelligent Platform are visible and clear, we will further our efforts to achieve greater performance gains and stay ahead of the curve.

To learn more about how Voice AI can help support your collection efforts through call automation, schedule a call with one of our experts using the chat tool below.

An Unbiased Look into the Positive Side of Voice AI

Posted on by Harshad Bajpai

Artificial intelligence is experiencing exponential innovation. Generative AI, ChatGPT, DALL-E, Stable Diffusion, and other AI models have captured popular attention, but they have also raised serious questions about the issue of ethics in machine learning (ML).

AI can make several micro-decisions that impact such real-world macro-decisions as authorization for a bank loan or be accepted as a potential rental applicant. Because the consequences of AI can be far-reaching, its implementers must ensure that it works responsibly. While algorithmic models do not think like humans, humans can easily and even unintentionally introduce preferences (biases) into AI during development and updates.

Ethics and Bias in Voice AI

Voice AI shares the same core ethical concerns as AI in general, but because voice closely mimics human speech and experience, there is a higher potential for manipulation and misrepresentation. Also, people tend to trust things with a voice, including friendly interfaces like Alexa and Siri. 

Call automation for call centers and businesses is not a new concept. Unlike computerized auto dealers (pre-recorded voice messages) like Robocall, Skit.ai’s Voice AI solution is capable of intelligent conversations with a real consumer in real-time. In other words, Voice AIs are your company representatives. And just like your human representatives, you want to ensure your AI is trained in and acts in line with company values and displays a professional code of conduct. 

Human agents and AI systems at any given point should not treat consumers differently for reasons unrelated to their service. But depending on the dataset, the system might not provide a consistent experience. For example, more males calling a call center might result in a gender classifier biased against female speakers. And what happens when biases, including those against regional speech and slang, sneak into voice AI interactions? 

In contrast to human agents, who might sometimes unintentionally display biases, Voice AI follows a predetermined, inclusive script while strictly adhering to guidelines that prioritize consumer satisfaction and compliance. This level of professionalism eliminates the potential for misbehavior and creates a positive consumer experience. 

Our team is always potentially looking out for any potential bias that accidentally seeps in, as ‘biases’ as constantly evolving. One thing can be acceptable today, but may bee seen as a bias tomorrow. At Skit.ai our skilled team of dedicated designers meticulously construct the dialogue patterns to guarantee balanced responses. Following these predefined scripts allows our Voice AI solution to offer consistent, unbiased interactions, thus establishing an inclusive user experience. This emphasis on conversation design aids us in overcoming potential biases that may surface in human interactions, thus securing a more balanced and impartial user experience.

Consumer Convenience and the Growing Preference for Voice AI

Consumers increasingly prefer interacting with Voice AI rather than human agents due to the convenience it offers. Voice AI allows users to communicate naturally through voice commands, eliminating the need to type or navigate complex menus. This convenience aligns with the preferences of many individuals who find it easier and more natural to speak rather than type. Furthermore, Voice AI is available 24/7, providing round-the-clock support without the need to wait for human agents. 

This instant access to information and assistance enhances consumer satisfaction and can lead to faster issue resolution. Additionally, voice interactions can be personalized and tailored to individual preferences, creating a more personalized and engaging consumer experience. The convenience and preference for voice-based interactions make Voice AI a valuable tool for meeting consumer expectations.

Building Ethical Voice AI 

Empathetic conversational design eliminates bias. At Skit.ai, we’re dedicated to developing leading-edge Voice AI technology. Our mission is to facilitate communication that is equitable and devoid of bias. Through conversational design, biases are eliminated, ensuring fair and inclusive interactions. A significant part of our strategy involves refining the conversational capabilities of our systems, striving for a natural, seamless exchange of speech that ensures equal treatment for all and eradicates discriminatory tendencies. As we navigate the future of work, Voice AI stands as a valuable tool, empowering enhanced communication, fostering seamless consumer conversations, and further elevating customer satisfaction.

To learn more about how Voice AI can help support your human resources and scale their collection efforts with call automation, schedule a call with one of our experts or use the chat tool below.

Are You Still Using an IVR Menu for Debt Collections?

Posted on by Simone Somekh

What is an IVR System for Debt Collections?

IVR stands for “Interactive Voice Response,” and it’s a legacy technology that enables companies to automate both inbound and outbound calls by using a pre-recorded voice that interacts with consumers and guides them through a pre-set menu, which can be navigated by inputting DTMF (dual-tone multi-frequency) from the phone keyboard.

Virtually everyone has interacted with an IVR system at some point. Whether you’ve called a business, a bank, a pharmacy, a doctor’s office, or a phone service provider, you are certainly familiar with prompts like: “For hours of operations, press 1.”

Call automation for call centers and businesses is not a new concept. IVR became popular in the 1980s when it emerged as an essential customer service technology. Debt collection agencies have been using IVR for over a decade, for both outbound calls (such as payment reminders) and inbound calls (such as consumer inquiries).

However, the fact that IVR is so common does not mean that it’s an optimal solution. In this blog post, we’ll go over the limitations of IVR and explain why adopting a conversational Voice AI solution is a far better option for collection agencies.

Why IVR Is Overwhelmingly Unpopular

IVR reduces wait time for consumers, but it does not eliminate it, as it forces users to listen to lengthy menus that are for the most part irrelevant. At least 61% of consumers think that IVR systems make for a poor customer experience (CX).

A survey conducted by Vonage with Opinion Matters in 2019 revealed that having to listen to seemingly endless, irrelevant menu options is the primary factor that contributes to the consumers’ negative experience. Additionally, the respondents complained that IVR menus are usually too long, that the reason for their call is sometimes not even listed, and the system prevents them from speaking directly to a live customer representative.

Building the right IVR for your company can be tricky. When the system is not designed well, users will get frustrated and abandon the call. IVR is notoriously difficult to navigate, especially when a business offers different services or targets various sets of consumers.

In one sentence: consumers don’t like IVR. So what’s the alternative?

Voice AI Is the Best Alternative to IVR

Conversational Voice AI is the cutting-edge technology behind what is commonly referred to as a “voicebot.” It enables companies to automate both inbound and outbound calls with customers without the involvement of a human being. In recent years, SaaS platforms offering Voice AI solutions have become more affordable and easier to deploy.

In the ARM industry, Voice AI can transform the operations of collection agencies for the better; these solutions are infinitely scalable and can handle the vast majority of calls with consumers. The AI can handle the most repetitive and mundane calls, empowering live agents to focus on the most important and revenue-generating calls.

Skit.ai’s solution can handle intelligent, personalized, and effective conversations with consumers, eliminating wait times and significantly cutting costs for the company adopting it. The AI is aware of the context and will tailor the service it offers based on the specific needs of the user. The technology not only understands what the user says but also the semantics of the conversation.

Voice AI for Outbound Collection Calls

Collectors are usually expected to go through thousands of files per month; a large number of those files remain untouched since it’s impossible for a human collector to contact and speak with so many consumers. This process leads to substantial losses in potential revenue for the agency.

When fed with large quantities of files, a Voice AI platform can initiate and handle an extraordinarily high number of calls. These are some of the solution’s capabilities:

The solution can easily transfer the more complex calls to a live agent when it cannot reach a satisfactory resolution. When agents see that a call is being transferred from the Voice AI, they know the customer is usually inclined to make a payment or reach a settlement.

Why You Should Not Use IVR for Outbound Collection Calls

Using IVR for debt collection calls is limiting and is unlikely to lead to a successful debt recovery on a consistent basis. The system can’t capture meaningful dispositions and is capable of handling a limited number of actions. Let’s say the consumer refuses to pay or disputes the debt—can your IVR capture the reason? Let’s say the consumer is willing to pay but can only pay off part of the debt at this time; can your IVR handle a negotiation? If the consumer is busy right now, is your IVR able to capture call-back dates and times? Probably not.

Voice AI for Inbound Queries

When a customer calls the collection agency, rather than having to deal with an annoying IVR menu, they get to interact with the Voice AI solution.

The AI picks up the call right away, eliminating the wait time of a regular call; additionally, the user does not have to patiently listen to a long list of options. The AI typically authenticates the caller’s identity and, if relevant, informs them of their due balance. Here the customer gets to have an intelligent, effective, multi-turn conversation with the Voice AI solution.

In revenue-generating inbound calls, the Voice AI can easily help the customer make a payment. In non-revenue-generating inbound calls, the solution will answer the customer’s questions based on the information it has on file, and will transfer the call to an agent when needed.

Why You Should Not Use IVR for Inbound Queries

Whenever a consumer is interested in making a payment and resolving their debt, they might be turned off by the poor customer experience offered by the IVR. In non-revenue generating inbound calls, the IVR system is often incapable of resolving the query, and therefore will likely transfer the call to a live agent.

U.S. debt collection agencies report that their agents spend about 20% of their time answering inbound calls! Many of these calls are not revenue-generating, so they consume time and resources that could be easily allocated to collection calls.

The Benefits of Adopting Voice AI for Debt Collection Agencies

Here are some of the benefits reported by collections agencies that have adopted Skit.ai’s Voice AI platform:

Interested in learning more about how Conversational AI can help you streamline your collection strategy and reach your full potential? Schedule a call with one of our experts using the chat tool below!

Tips for an Agile, Digital-first Debt Collection Agency

Posted on by Simone Somekh

The State of the U.S. Debt Collections Industry in 2023 

Let’s start from the data. The U.S. debt collections industry is worth $20 billion in 2023, according to IBIS World research. Given that the industry was estimated to be worth only $11.5 billion in 2018, the growth has been remarkable—approximately 73.9% in just five years.

About half of the market share is dominated by the 50 largest ARM companies, over a total of almost 7,000 businesses.

As the industry continues to grow, it has become challenging for executives to keep up with the times. While recovery rates are a key factor influencing competitiveness, technological innovation is the other element defining a company’s success. Digital transformation is no longer a “plus” for agencies, but rather a “must,” and while many ARM companies have embraced change, there is still a long way to go.

In this article, we’ll discuss what it means for a debt collection agency to be agile and adopt a digital-first approach and we’ll go over a few examples of types of technology that agencies are adopting.

What Does It Mean for a Debt Collection Agency to Be Agile?

Business agility is defined as the ability to make changes and decisions quickly. Usually, companies become agile by prioritizing data-driven decision-making, efficiency, flexibility, and innovation. In other words, agility is the exact opposite of stagnation.

According to Entrepreneur, agile decision-making can be related to a variety of issues, such as responding to new competitors or market changes; solving problems as they emerge; launching new products and services; and minimizing time spent internally.

Why is it important to be agile? McKinsey has found that companies that undergo a successful agile transformation gain a 30% increase in operational performance, efficiency, and customer satisfaction.

Digital transformation is a key process influencing agility.

“Some ARM companies have been slow to adopt new technologies and, as a consequence, they are now at a competitive and operational disadvantage,” explained Scott Carroll, industry veteran. “Some didn’t know they needed technology, or they didn’t know exactly where to look and where to start. But now the industry is quickly catching up.”

Carroll explained that tight regulations, concerns over compliance, and widespread litigation are some of the reasons why the industry has been lagging behind in innovation. “Businesses have been naturally more cautious. But now, as they get a better understanding of the regulations, they’re finally looking toward technology to improve their operational efficiency,” he said.

One strength the collections industry has is that it’s usually prepared to pivot: “Because of fast-changing regulations and client needs, the industry needs to be prepared to respond to change.”

How the Industry Is Catching Up by Becoming Digital-first and Tech-savvy

A growing interest in innovation is driving the push toward agility in the ARM industry. Staying updated on new technologies, monitoring emerging tech companies and solutions, and investigating how leading technologies like artificial intelligence can be applied to debt collection are the key tips to implement an agile transformation.

In January 2023, the industry held its first-ever conference entirely dedicated to technology. ARMTech, which took place in Nashville, was a four-day event aimed at helping executives understand the technology that is revolutionizing how debts are collected. The event was organized by Mike Gibb, industry leader and editor of the website AccountsRecovery.net.

The industry is moving toward a digital-first model, as it’s evident that consumers prefer to deal with companies offering omnichannel services and interact through digital channels. Omnichannel includes a wide range of channels, such as website, mobile app, social media, telephony, chatbot, voicebot, SMS, and email.

Telephony systems and dialing platforms are essential for any contact center, including a collection agency, whose business largely depends on outbound and inbound calling. These platforms include TCN, Twilio, Genesys, LiveVox, RingCentral, 8×8, Five9, and more.

Collection management software is the other most common type of software adopted by collection agencies. These systems of record enable agencies to manage their portfolios in one easy-to-use, centralized platform updated regularly by the agents.

Conversational Voice AI, the technology behind voicebots, is gaining ground as a widely popular technology in the ARM industry. Skit.ai has developed an AI-powered Digital Collection Agent, which handles human-like outbound calls to collect payments from consumers. The voicebot intelligently interacts with the consumer, handling payment reminders, negotiation, and processing. The Digital Collection Agent does not substitute the human agents but rather augments their work by handling the most repetitive and tedious tasks. This solution can be easily integrated with the other tools in use.

Voice AI should not be confused with IVR (interactive voice response) systems, a legacy technology that requires consumers to navigate lengthy menus through DTMF inputs or basic voice-enabled inputs.

Key players in the industry are also adopting business intelligence and analytics solutions that support agents during and after their calls with consumers. Prodigal’s solution offers real-time agent assistance, auto-writes call summaries, and analyzes collection calls on dozens of parameters to monitor and boost performance and compliance.

What’s Next?

It looks like 2023 will be a defining year for the collections industry in regard to digital transformation and agility.

“Agility is a key operating factor for success,” advised Scott Carroll. “My tip is to stay current on technology, investigate new tools, stay on top of the latest trends, and keep your eyes open for anything that helps you increase your margins and reduce your exposure. This will ultimately lead to increased collections.”

Entering a New Era of Debt Collections with Conversational Voice AI

Posted on by Harshad Bajpai

Debt collection companies have been automating various parts of their operations, much like companies in other industries. However, one of their core problems—the inability to automate complex conversations with consumers—has impacted their ability to solve their core challenges.

Connecting with consumers to recover payments is at the core of what a debt collection company does. According to a new survey by TransUnion and Datos, communicating with consumers is a top priority for collection agencies. A growing number of agencies are exploring new methods of communication for debt collection, focusing primarily on AI-powered chatbots and voicebots, as well as text messaging.

Conversational Voice AI, with its capability to automate collection calls, solves all significant challenges and ushers in a new era of debt collections. In this blog post, we’ll learn how this technology is dramatically changing the landscape of collections.

How is Voice AI Changing Debt Collections Forever?

100% Account Penetration: A Voice AI solution can initiate and handle millions of calls within minutes, covering an agency’s entire debt portfolio in an impressively short amount of time. This level of automation has never been possible until recently; it’s important to note that over a third of an agency’s files often remain untouched.

Less Dependence on Human Agents: It is hard to recruit a skilled collector, and having a consistent team that can scale up when needed has been extremely challenging for agencies, especially the smaller ones. AI provides the benefit of instant and infinite scalability, making the issue of staffing less concerning. Thanks to end-to-end automation of consumer calls, agencies can scale up and down as needed.

Augmenting Agent Productivity: Voice AI enables live agents to focus on more complex and revenue-generating tasks. Without call automation with Conversational AI, this would be impossible, as live agents would have to spend a lot of time establishing right-party contacts (RPC) and handling time-consuming, repetitive tasks that should be automated.

File Segmentation for Better Recovery: For the first time, collectors can now see the entire picture of their portfolio. As the Voice AI solution goes through the entire portfolio, collectors can see the set of right-party contacts (RPCs), the propensity to pay, and other crucial data that can inform a more strategic and data-driven recovery strategy, ultimately improving collections.

Remarkably Lower Collection Costs: Calls handled by Voice AI cost approximately one-third of a traditional collection call handled by a human agent.

Voice AI Comes with Other Remarkable Benefits. Here Are a Few: 

Lower Compliance and Legal Risk: Voice AI has the potential to improve compliance and reduce the risk of legal issues for agencies. The debt collection space is heavily regulated, and collectors must follow strict compliance rules. With our Augmented Voice Intelligence platform, compliance rules and guidelines such as call frequency, the Mini-Miranda, and other important regulations — both at the federal and state levels — are built into the technology to ensure the Voice AI solution follows them. Voice AI never goes off-script and never has a bad day, protecting both the consumers and the agencies.

Better Decision-making with Data Analytics: Artificial intelligence can analyze consumer data and make informed decisions on the best course of action. For example, Voice AI can use data on a consumer’s payment history, income, and expenses to determine the best payment plan for them. This data-driven approach can lead to more efficient and practical debt resolution outcomes and a better customer experience (CX).

Unprecedented Automation: One of the main benefits of Conversational Voice AI in debt collections is that it automates much of the manual work involved in the recovery process. Debt collectors can use Voice AI to automate tasks such as calling consumers, sending out payment reminders, and recording consumer interactions. This saves time and allows collectors to focus on more complex tasks, such as negotiating payment plans and resolving disputes.

How to Choose the Right Conversational Voice AI Solution Provider for Your Company

The most important thing to remember about a Voice AI solution is that it either works and satisfies the consumer, leading to positive outcomes and recovery, or it will lead to consumer frustration and significantly adverse outcomes. Hence the choice of vendor is highly vital. Here are a few things to consider:

Proven Track Record: To ensure a successful implementation, working with a Voice AI provider with a proven track record in the accounts receivables industry and who can provide a comprehensive and integrated solution is essential. Collection executives prefer to adopt solutions that have been in business in the accounts receivables industry for at least six months.

Ease of Integration: Another priority when implementing Voice AI in debt collections is ensuring the technology is integrated with existing systems and processes. The provider’s capability to integrate with existing systems and other vendors—such as payment gateways—is one of the significant factors that must be considered while selecting a Voice AI vendor.

Ease of Deployment and Use: One of the critical challenges in implementing Voice AI in debt collections is ensuring that the technology is user-friendly for debt collectors and consumers. Make sure that your vendor’s solution is easy to deploy and to use.

Speed of Deployment: The solution must be ready. No promise of building a solution in a few months should be considered, because no viable, working product is ready. Select a vendor who is ready to go live immediately after a series of well-defined tasks required on your end.

Positive Business Outcomes: Look at the results the AI vendors have been about to achieve in the recent past with companies similar to yours. See if these business outcomes and success metrics align with the outcomes you’re hoping to achieve.

Make the Right Choice 

Conversational AI technology is remarkable and has proved its worth in our industry and beyond. The only thing left for debt collectors is the selection of the right Voice AI vendor. Select the right vendor, and it will help you gain a competitive edge and show your tangible positive outcomes in a matter of weeks.

Voice AI technology is about to change debt collections forever; don’t miss out!

To learn more about how Voice AI can help solve your staffing challenges and improve your recovery strategy, use the chat tool below to schedule a call with one of our experts.

Human Collectors vs. AI-powered Digital Collectors: An In-depth Comparison

Posted on by Harshad Bajpai

Voice AI is becoming mainstream in the ARM industry, and the days of chasing after customers for unrecovered debts in the most haphazard, manual fashion are nearly over. Additionally, thanks to the rising popularity of self-service channels and the ecosystem-led push involving regulatory changes like the Reg F that rewrite the expectations for debt recovery in the U.S. beyond simple automation.

Voice AI conveniently fits the bill for debt collection agencies by fixing the systemized inefficiencies with automation and analytics-driven voice communication outreach. In this article, we will explore why human-like voice interactions handled by AI-powered Digital Voice Agents help debt collection companies drive effective consumer interactions at better collection cost, performance, and efficiency ratio.

7 Ways Voice AI Helps Elevate Debt Collectors’ Productivity

At Skit.ai, we call it Augmented Voice Intelligence — the idea that Voice AI can augment, rather than substitute, the work of live agents and collectors. Let’s dive into the benefits of this strategy:

Human-like Conversations: Voice AI is purpose-built and modeled on human conversations. Digital Voice Agents can hold thousands of outbound customer outreach calls simultaneously, without the involvement of human collectors, helping collection agencies carry out human-like interactions at lesser cost and effort from their human resources.

Seamless Integrations: Voice AI’s integration features feed data from collection calls, such as right-party contact, call-back requests, no response, and more, into the collection management system to provide actionable insights for human collectors to be more proactive.

Higher Portfolio Coverage: Collection agencies can leverage Digital Voice Agents to scale collection outreach calls for different consumer accounts and across diverse portfolios with unique requests for payment alternatives, call-back options, or preferred time of contact.

Versatile and Accurate: Intelligent voice bots can be tailored according to the use case, offer profound insights for analytics on future actions, independently schedule automated triggers, auto call-back on request, and even make intelligent call transfers to human agents/live collectors for complex issues. 

Better Compliance and Privacy: Voice AI’s algorithms can be trained to follow regulatory protocols on reaching customers, communication time, frequency or calls, and honoring their requests for discontinuing communication using APIs. It can be challenging to adhere to all the norms when done manually. Also, Voice AI’s strong encryption and consumers’ or cardholders’ data protection features comply with regulatory standards like HIPAA, PCI, FCRA, and more.

Lower Litigation: Voice AI lowers litigation risks compared to human agents, who are more likely to coerce consumers to pay with the hope of meeting targets and receiving higher commissions. Additionally, consumers are generally passive toward Voice AI and pin fewer expectations on the technology to understand their emotions or personal grief, reducing the odds of agencies ending up with lawsuits.

Better Insights and Analysis: Debt collection agencies can draw on the insights gathered by Digital Voice Agents to learn about consumers’ or callers’ experiences and conversations to design or augment debt collection processes for better collection campaigns, collectors’ experiences, and higher recovery rates. 

How AI-powered Digital Collectors Can Outperform Live Collectors 

While Voice AI embodies the promise of automation with a human touch, collection agencies don’t rely on anecdotal evidence. They look for value-creation and tenacity to transform traditional loan recovery practices with the technologies to a level that human resources alone cannot match. Skit.ai firmly believes in realizing the potential of voice communication in debt recovery by augmenting human support with AI for intelligent human-machine collaboration.

Here are the key differentiating features of Voice AI that match collection requirements and make processes more efficient in responding to various outbound debt collection use cases.

Collection Support Scalability: Voice AI can automate up to 70% of calls, helping curb hiring, recruitment, and training-related requirements in collection agencies. Additionally, Digital Voice Agents help leverage unlimited scalability by simultaneously handling multiple collection calls, which would otherwise be very time consuming and expensive when done manually.

Higher Cost Savings: Voice AI processes non-revenue generating calls at 1/5th of the cost of manual calls. Also, they are capable of decreasing operational costs by 50%.

24/7 Support: Digital Collectors can always be at the beck and call of consumers to offer 24/7 support. Delivering 24/7 support with human resources would be extremely costly and unrealistic.

Lower AHT: Voice AI guarantees better performance and can handle multi-turn conversations with prompt query resolution. It reduces average call handling time (AHT) by 40% and augments human agent teams’ efforts by transferring only complex queries and equipping them with real-time analytics and insights.

Higher Debt Collection and Recovery Rate: Skit.ai’s Digital Collectors have repeatedly demonstrated performance at par with average debt collectors while operating at less than 1/5th the cost of a human agent.

Better Account Classification: Unlike manual debt collection efforts, Voice AI’s ML classification models algorithms are trained to segregate consumers as per bankruptcy details, creditworthiness, outstanding loan amounts, blocked accounts, and do-not-call lists, to help collectors or accounts receivable managers respond appropriately.

Higher Accountability and Compliance: Digital Voice Agents are trained to comply with strict practices in debt collections (7/7/7 rule, TCPA, Mini-Miranda, etc.) and refrain from the usage of unsavory language or behavior that can later result in lawsuits to the agency, which would be challenging to regulate in manual collection use cases. Besides the analytics-driven insights on consumer responses and history, Digital Voice Agents guarantee higher accountability.

Complete Campaign Control: Digital Collectors can be turned on or off as per use case to match the call volume requirement or type of consumers’ requests and accounts, unlike calls by live collectors with efficiency issues and too much time, resources, and training. 

Consistent Call Quality: Voice AI delivers consistent experiences at any scale and volume. It is humanly impossible to ensure the call experience remains the same and guarantees similar outcomes for all debtors’ conversations from manual collection campaigns.

The Bottom Line: Voice AI  is the Key to Supercharge Debt Collections 

It is time to embrace the reality that neither automation nor pure human intelligence can help debt collection agencies to master complex collection campaigns. Skit.ai’s Augmented Voice Intelligence platforms like Skit.ai enable the collaboration between humans and AI-powered machines to respond to the mounting operational stresses in debt collection agencies. These solutions empower live collectors to perform consistently throughout the debt collection process at a better cost, productivity, and recovery rate.

To learn more about how Voice AI can help reimagine debt collection efforts with call automation, schedule a call with one of our experts or use the chat tool below.

Tackle Agent Productivity in Debt Collection Agencies Using Voice AI

Posted on by Harshad Bajpai

For debt collection agencies, debt recovery is a labor-intensive effort that typically relies more on human effort than capital investments. Even with the adoption of newer digital communication tools that promise to scale manual efforts, the ARM industry invariably struggles with one major issue — human resource turnover.

Across all industries, average attrition rates in contact centers vary between 30 to 40%.

It’s hard to know the exact attrition rate in the ARM industry. Agencies reported a monthly quit rate of 2.9% in 2021. Before the pandemic, in 2016, large collection agencies reported experiencing an average turnover rate of 75% to 100%, according to the Consumer Financial Protection Bureau.

The high attrition that characterizes the collections space makes third-party debt collection agencies vulnerable to several challenges, like loss of domain expertise, risk of non-compliance, lawsuits, and increased cost of hiring and training new talent. In the United States, with nearly one in four citizens having at least one debt in collections, recovery has become an increasingly costly endeavor.

Most Common Reasons for Collection Agent Attrition in the Debt Collection Industry 

Here are some of the most common challenges that make it so difficult for agencies to retain collectors:

  • Too Many Accounts, Too Much Work: Given the growing debt delinquency in the U.S., one can only imagine the amount of verification and debt-related communication work that can drive collectors to overwork.
  • Collectors’ Commission is Dependent on Recovery: Third-party debt collection agencies are involved when credit card issuers or creditors’ collection representatives cannot recover overdue balances. Collection agencies face thinning profit margins, and human agents’ commissions for debt recovery further burn holes in their pockets. There is no set rule or guarantee on the time the human agents need to recover outstanding loans successfully.
  • The Great Resignation: While all contact centers face high attrition rates, many people have been rethinking their careers and seeking opportunities in new fields over the last two years. This also applies to the ARM industry, where collection agents face acute stress from chasing after customers over the phone while adhering to a wide array of regulations, making attrition an even bigger challenge.
  • Empty Promises to Pay: It is common to find consumers dodging debt-related interactions. When confronted directly, they are likely to make promises to pay that may only sometimes be honored, which is another detractor for collectors to stick to their roles.
  • Debt Shame: Debt collection calls are direct and can sometimes make the debtors uncomfortable delving into the details of their unpaid loans. According to a study by Webio, people can be much more honest when communicating via text messages than in voice interactions for difficult scenarios. In the case of debt collections, textual conversations can reduce stress for both debtor and collector.
  • Efforts Often Don’t Justify Conversion Rates: When it comes to debt, the devil is in the details. To invest too much attention and time in each customer who needs a detailed overview of their loans and debts is unrealistic. It is extremely costly and leads to operational overkill, another reason for collectors’ resignation.
  • Debt Collection is Not for Everyone: Employee turnover in any field results from the nature of the job/employer and the employee’s capabilities. Working conditions, perks, quality of work, and benefits will fix the collector’s morale. But employees’ capabilities for the job determine how much they are willing to stick to it. 
  • Rapid Changes in Regulatory Framework: Many regulatory agencies like FTC and rules like Fair Debt Collection Practices Act dictate how collection agencies can approach consumers without violating consumer protection laws. It requires constant staff training and procedural approaches like obtaining debt verification requests, debt validation, forbearance, and foreclosures that rely on unique expertise. When agencies adopt a manual route or use restrictive debtor communication methods, errors and inaccuracies are expected.

 The Rising Role of Voice AI in the Debt Collections Industry

These challenges highlight the urgency for digital transformation in collection agencies; in particular, agencies are looking at automation as the primary solution to their attrition crisis.

In our previous articles, we discussed the unique capabilities of Voice AI technology in reducing contact center agent labor costs via call automation. Concurrently, Gartner’s estimates from their survey also suggest that labor expenses represent 95% of contact center costs, and adopting Conversational AI helps cut expenses by $80 billion. The customer-facing side of ARM, particularly the debt collection agencies, can capitalize on this trend to reduce staff shortages, curb labor expenses and make human resources more efficient and effective. 

Skit.ai’s Voice AI platform is at the forefront of transforming the ARM industry with its Digital Voice Agents and augmenting collection agencies’ workforce to focus on resolving complex use cases. 

Voice AI’s value-adds are in areas that impact collectors’ productivity and bandwidth which further determine talent retention in this space. Here’s the rundown of its merits that help address agent attrition challenge in the debt collections industry:

  1. End-to-end Call Automation: Voice AI helps automate 70% of calls (inbound and outbound), allowing prompt query resolution. Also, agencies can leverage automation to identify consumers, policy numbers, and other debt-related information. This reduces the effort and time it would take to call and follow up with each debtor manually. 
  2. Reduce High Cost of Collection by 1/5th: Digital Voice Agents that plug into contact centers and take over calls by holding human-like conversations can execute calls at less than 1/5th of the actual cost of manual calls. Collection agencies can lower operation costs with intelligent voice agents in lieu of collectors by concurrently calling over thousands of defaulters.
  3. High Scalability: Agencies can scale their debt collection efforts and consumer outreach by leveraging call automation and Digital Voice Agents that can handle and answer tier-1 caller queries by automating up to 70% of calls, reducing dependency on human agents. 
  4. Higher Portfolio Coverage Intensity: Collectors can cover many more debt files when they leverage Voice AI’s ability to handle multiple calls simultaneously. With minimal effort, cost and time, agencies expand their scale of reach of debt collection practices with minimal human intervention.
  5. Strict Adherence to Compliance: Fear of lawsuits or going off track by the debt collectors will be alleviated by the Voice AI platform, which is purpose-built and specific to the domain and use case. Digital Voice Agents can be tailored to hold and attend calls as per the laws governing consumers’ preference for call frequency, tone, language, and time to receive debt collection calls.
  6. Solve Diverse Use Cases: The recovery process in the collection agencies involves rigorous reviews, checking outstanding balances, sending demand and acknowledgment letters, and arranging for telephone contact. It is humanly impossible to keep track of all details, numbers, and sensitive information about different types of debt and cases at their fingertips. Digital Voice Agents can be optimized to address various debt-related queries and use cases without time, cost, and human effort constraints, reducing work stress and dissatisfaction for debt collectors. 
  7. Enhance Human Agent Productivity: Debt collectors can experience higher and faster conversion levels by leveraging Voice AI’s analytics and caller data insights. The pre-call verification, call automation (inbound and outbound), and routing features enable real-time agent augmentation, boosting productivity and performance. Also, the Digital Voice Agents are capable of intelligent call transfers to human agents only for complex cases, allowing the human workforce to focus on efforts that help retrieve debts faster. 
  8. Voice AI Calls are Free of Human Biases: Holding debt recovery conversations is a sticky collection practice that most consumers tend to avoid out of pressure, discomfort, shame, and fear of judgment. Voice AI’s call automation capability eliminates direct voice interaction between defaulters and collection agents, making collection calls free of human biases. Also, Digital Voice Agents can hold persuasive, contextually accurate, and proactive conversations and keep interactions direct and objective. This way, collection agents can experience higher work quality without job stress, dissatisfaction, and the chances of misdemeanors while talking to consumers. 

Collection agencies rely entirely on outstanding loan payments to survive. Voice AI helps collection agencies strike a balance between meeting their recovery targets and making debt collection efforts more intuitive in a way that doesn’t come at the cost of operational burnouts and resignations. Voice AI eliminates bottlenecks in debt recovery and improves the overall customer experience.

To learn more about how Voice AI can help you solve attrition challenges, schedule a call with one of our experts or use the chat tool below.

How Voice AI Helps Debt Collections Companies Improve Top and Bottom Lines

Posted on by Harshad Bajpai

Many debt collection companies are evaluating emerging technologies and looking into digital transformation. You can’t blame them: due to a faltering economy, rising costs, and high agent attrition, new processes and solutions are needed.

As a result, within the next three years, one in every ten interactions with call center agents will be voice bots driven, according to the new Gartner report. These findings are directly attributable to the spectacular rise to the advances in conversational artificial intelligence (AI), along with the mounting challenges we detailed above.

The report also estimates that by 2026, Conversational AI could save about $80 billion in labor costs! That is a significant number, indicative of the merits that early adopters will have in terms of cost, CX, and expansion of top and bottom lines. But, starting early is key to competitive advantage.

It is an open secret that high human agent churn is due to the fact that most calls are low-value and tediously repetitive. By handling these calls, Conversational AI will make the agents’ jobs more exciting and fulfilling, allowing them to focus on high-value and complex calls.

Globally, there are approximately 17 million contact center agents, and their cost makes up 95% of contact center costs. By intelligent call automation led by voice-intelligent technology, Voice AI, a big part of unproductive calls can be taken over by Digital Voice Agents, yielding high cost and CX advantages.

The Direct Cost and Efficiency Benefits of Voice AI for Debt Collection Agencies:

The most significant takeaway for the debt collection agency is that the benefits of Voice AI implementation are tangible and quickly realizable. But before we go into stats, here is a simple explanation of what essentially happens in a debt collection agency when they deploy a voicebot.

Voicebot Functioning

A voicebot is a conversational Voice AI application that can understand what the customer is saying as it is trained for a specific customer problem. It can strike a meaningful conversation with the customer. This happens because the entire conversation design has been done keeping in mind all the possible difficulties a customer can encounter.

So for every customer query, the voicebot has a ready answer as it pulls out relevant information from the client system and informs the customer, cutting the duration of the conversation remarkably.

Digital Voice Agents (DVA) Vs. IVRs: It is worth mentioning here that DVAs are remarkably different from IVRs; in fact, there is no comparison between the two. DVAs are at the cutting edge of the technological spectrum, while IVRs are legacy technology.

IVR can not converse. It is an unintelligent technology that runs a tedious exchange of inputs and outputs. For something as sensitive as debt collections, it is remarkably unsuitable.

Digital Voice Agent is AI-powered, built on Spoken Language Understanding (SLU) and context-rich conversational designs.

Dive deeper: The difference between Digital Voice Agents and Outbound Robocallers 

For a debt collections company, the two main categories of calls are Inbound and Outbound. Here is the process of value creation:

Inbound Calls: Many agencies cannot process a significant portion of customer calls. From them, a tiny fraction of customers have called to pay and perhaps need guidance.

Answering Non-revenue Generating Calls 

The data from various sources is precise: A majority of calls are so simple that answering them by a human agent does not add any value to the company.

We’ve discussed the value of adopting a Digital Voice Agent for call automation. If you want to learn more, take a look at our Resources page, in which we regularly explore current topics related to the ARM industry.

Understanding the Top and Bottom Line Impact of a Voice AI Solution on a Debt Collection Company

The Final Word

Voice AI has proved its capability in bringing about a transformation of contact centers either with a small team or a big one. As its adoption increases, it will become a technology that can deliver sustainable cost advantages as well as a competitive advantage.

Refer to our Voice AI page for more information about its transformative potential.

Book a demo with one of our experts-www.skit.wpenginepowered.com

Rethinking Self-service in the Age of Voice AI 

Posted on by Harshad Bajpai

What’s common among interactive voice response (IVR) systems, ATMs, knowledge base, mobile applications, virtual assistants or chatbots? They are all self-service options that can help dispense answers and resolve queries at lightning speed! Self-service or self-help tools and options make for an empowered customer support team and a loyal customer base. 

Self-service equals simplified customer journeys! 

In a mobile-driven digital economy, a brand’s relevance and value is measured in terms of the speed, convenience and the level of autonomy offered to their customers. Digital self-service is the central objective of today’s automated customer support, but tailored for better CX and performance. Since the COVID-19 pandemic, the usage of digitized self-service by customers across demographics accelerated with sudden digital transformation (DX). With newer entrants into the market— more digital native brands, always-on, smartphone users and Gen Z customers, numerous possibilities await businesses using digital self-service in their customer support. As per the recent OnePoll study involving over 10,000 respondents from 11 countries to explore humanity’s shifting relationship with digital tech and experiences:

  • Nearly 58% percent of participants said they will continue their digital brand interactions more than their pre-pandemic levels. 
  • Most study respondents felt that the digital experience was fast and convenient, making it better or on par with the real-world, face-to-face customer service interactions. 
  • Almost 66% reportedly had a ‘good’ or ‘excellent’ experience using online customer service options. 

Diving a little deeper, the research summed up the exact reasons for positive reactions:

  • Instant issue/query resolution (48%).
  • Convenience (46%).
  • Speed (45%).

These findings form the crux of self-service. In this blog we will begin our exploration on why self-service tools are truly adept in capturing customers’ interest, and meeting productivity and performance goals of brands’ customer support. 

Psychology behind Self-service

Self-service is not the same as automation. Sure, digital self-service gives automated responses to repetitive queries in blazing speed. It is not only about allowing customers to resolve things on their own but also empowering them to address them faster. The overall value of the self-service strategy is measured in terms of its impact on CX. The faster, more convenient and more cutting-edge the self-service options, the better would be the CX scores. Moreover, the intuitiveness and simplicity of self-service helps reduce customer effort while solving problems on their own. This lowers the customer effort score (CES), another key metric for frictionless CX!

An intuitive, anytime self-service strategy across the platforms or channels also helps evade a laundry list of options for customer service-related interactions and unnecessary contact with human agents.  This is integral for curbing additional contact center operations costs and allocating resources and human efforts in areas that build proactive and customer-centric impressions.  No wonder, in the U.S. 88% of customers prefer self-service for dealing with their everyday problems. The number is equal to the global average of customers that expect brands and businesses to include a self-service support portal. 

The Most Common Types of Self-service Options

Now, let’s have a look at this run-down of the widely adopted self-service support options.

  1. Knowledge Base and FAQs: Internet-savvy customers leverage business/brands’ digital presence to find their way from the search engine platform to access information in a variety of forms (videos, landing pages, texts, infographics, illustrations, audiobooks, guides, and icons) for problem-solving.   Dedicated FAQ pages that are brief and true-to-context is another form of self-service option that guides customers through specific customer service-related scenarios on the company’s website. 
  1. Integrated Contact Centers: Customer data is created across multiple channels. Integrated contact centers bind sales, contact center agents or other representatives with unified data sharing, collaboration and improved access to customer data across customer journeys and omni-channels for customer service. The intention is to boost CX and reduce the need to repeat information as customers navigate different customer service departments to solve issues on their own. 
  1.  Interactive Voice Response (IVR) Systems: IVRs have existed for more than five decades. They are customer-facing phone systems that offer (inbound and outbound) support with pre-recorded messages and self-service menu responses to customers’ text inputs. They are cost-effective, scalable, and automated alternatives to human agents. 

Move Beyond IVRs: Transform CX with Digital Voice Agents 

  1. Chatbots: Chatbots use text-based or voice interfaces that are integrated to websites or mobile apps’ chat/message window  to interact with customers. They are AI-driven and created based on the planned interaction flow chart to respond to customers in a matter of seconds. 
  1. Mobile Applications: Mobile apps with intuitive and interactive UX and UI give information to customers via dashboards, push notifications and updates in their moments of need, on their mobile devices. 

Voice AI: A Quantum Leap in Self-service 

The common forms of self-service options are the building blocks of the new age customer support. But there’s always the expectation for solutions that drive up the cost savings and operational efficiency while also helping brands’ contact centers meet their CX objectives. Imagine, if brands were able to achieve that while also offering self-service support that was voice-led, personalized, empathetic and proactively responds in real-time! For today’s automation and customer-first era, Skit.ai’s purpose-built Voice AI platform redefines self-service for optimizing customer support not only for better CX but for enhanced employee and business experience. 

Built to enable conversations that are modeled on human interactions for prompt query resolution and personalized caller experiences, Voice AI is a next level of innovation in self-service. It delivers the best of voice experiences for brands through their contact centers that go beyond the capabilities of generic voice bots. 

Voice AI is built to be domain-specific unlike generic voice-first platforms by Amazon and Google. The  spoken language understanding (SLU) layer of Voice AI helps capture short, conversational utterances and is capable of deciphering semantic details that helps identify the right intent.  

Why Every Company Must Have a Voice: Read Now 

How Voice AI Lays the Framework for Self-service 

Voice conversations are the most natural forms of human communication and still remain one of the most sought after brand-customer interactions. Live voice conversations are critical to delivering high-quality customer experience. Customers interacting with self service options such as IVRS and messaging chatbots think before inputting a text command and hit send. Voice AI is a technology built to understand the intricacies of spoken language and not limited to text. It can quickly grasp customers’ voice interactions and filter through pauses and repetitions.

The  Digital Voice Agents plug into the contact centers for automating cognitively routine work and independently resolving tier 1 customer problems. This would aid the human workforce to focus on more complex customer queries and contact centers to adopt intelligent human-machine collaboration. This way customers can stay in control and brands also get to pick the best self-service strategy for delightful CX. 

Now, let’s dig into various features of Voice AI that makes it a better alternative to conventional self-service support:

  • Natural human-like Interaction: Digital voice agents that can mimic human-like conversations and comprehend interactions at a semantic level. It doesn’t feel like interacting with IVRs. It feels like holding conversations with the brands’ contact center agent.
  • Problem Recognition: Customers navigating through the self-service option can feel like they are lost in translation because of the complex IVR loops, limited menus or options that do not cater to their requirements. Sometimes chatbots are built with an ASR layer on top of NLP. They are great for transcriptions, not conversations. They deliver the same experience as going through a rigid IVR system. Digital Voice Agents can understand the right sentiment and nuances of human conversations, allowing the customer support to accurately identify and solve customers’ problems.
  • Always-on, Human Agent-free experience: One of the core value propositions of implementing a digital voice agent is its ability to function 24/7 for the ‘always-on’ customers without the dependency on human agents. This translates to cost savings by automating high-volume, zero-value and repetitive customer queries.
  • Quick Resolution: Self-service platforms optimized by powerful AI-capabilities and strong data sets based on customers data can be used for competitive advantage. It allows fast resolution, impacting customer satisfaction and CX. 
  • Diversify Customer Service at a Lesser Cost: When more problems that are unique in nature can be handled by voice agents and automated, it helps brands’ customer service be a one-stop-shop for addressing customer queries at a fraction of a cost.
  • Smarter Human Resource Allocation: Self service options in contact centers make it easier to address trivial problems or anything that is repetitive in nature using Digital Voice Agents. Human agents can be allocated only for complex customer service issues, allowing for better resource planning and empowered customer support teams.
  • Make Self-service More human: Digital voice agents add a human touch to the overall experience without involving a human. The datasets are designed for SLU and built for domain-specific words which makes it easier to hold contextual conversation with the customers even via self-service options.
  • Hyper-personalize Customer Support: Brands can guarantee hyper personalization leveraging Voice AI’s extensive language support. It helps break spoken language barriers for enhanced query resolution and overall caller experience.

If you still have questions, refer to the infographic below for a brief comparative analysis between Voice AI and three most popular self-service tools.

FeaturesVoice AIIVR Systems Chatbots Mobile Apps 
Primarily Built for Voice Input YesNoNoNo
Analytics and insights CapabilitiesVery HighLowHighLow
Elasticity of Customer Service  HighLowModerateLow
Hyper-personalized and Contextual dialog CapabilityHighLowHighHigh
Handling time Lowest Very HighModerateLow
Quick Query Resolution Quickest Slowest Quick Quick

Our Titbits

Envisioning customer service in the age of self-service is all about setting the right priorities. With the hope of keeping up with the trends for relevancy, brands and businesses need not steer away from their cost, profits and resource management goals. That’s the core objective of reimagining customer self-service using Voice AI. Brands across industries can supercharge their CX with befitting self-service strategies to be more result-oriented and insight-driven to add a competitive edge. 

Our reflections for the future—customers never settle and self-service alone is not enough! Therefore, we believe Voice AI is the most robust and well-rounded technology to improve customer support capabilities that go beyond conventional contact centers, adding a desired level of autonomy and self-sufficiency in customer service. 

Refer to our Voice AI page for more information on actively engaging with your customers and unlocking the power of self-service.  Book a demo with one of our experts–www.skit.wpenginepowered.com 

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