Topic: Customer Experience

Leveraging Cognitive Science to Improve CX with Voice AI

Posted on by Simone Somekh

How Human Cognition Impacts the Way Users Interact with Voice AI

When developing and configuring a conversational Voice AI solution, it’s imperative to take into account the experience that end-users will have when interacting with the solution. No matter what the use case is, users should be able to utilize the voicebot to reach a satisfactory resolution, while also having a pleasant experience.

CX is one of the elements that drive the work of Conversational User Experience (CUX) Designers, who ask themselves multiple questions when designing a Voice AI solution: Who is the client and what is its brand identity? What target persona will be interacting with the voicebot, and what use cases will the solution help them with?

To maximize the quality of the user experience and the consequent CX, conversation designers take into account cognitive science. The goal is to design intuitive, effective, and engaging interactions; cognitive science can provide insight into how users process information, make decisions, and interact with technology.In order to understand the role of cognitive science in CUX, we must first define the term “cognitive load.” According to the American Psychological Association, cognitive load (or mental load) is the “relative demand imposed by a particular task, in terms of mental resources required.” As humans, we can only hold so much information in our minds at any given time; our minds are limited, and we can’t overload them. That is why minimizing the cognitive load plays an important role in ensuring a positive user experience.

Let’s analyze these aspects one by one:

Natural language processing: CUX designers take into consideration the way users process language, including speech recognition and text-to-speech conversion, as well as the interplay between different elements of speech, such as prosody, pitch, emphasis, and the consequent tonality, which further contributes to perceptual and contextual semantics. NLP is essential for building effective conversational systems. This process also includes researching and implementing algorithms that accurately recognize and respond to human speech.

Memory and recall: The user’s ability to remember and recall information when necessary is essential to conversation design. The cognitive load is directly affected by the complexity and quantity of the information given to the user. Designers consider how the information is presented and stored, and ensure that users can easily and quickly retrieve it.

Attention and distraction: Understanding how people allocate their attention, what contributes to selectivity in attention in a given context, and how easily users can be distracted. Designers must structure the conversation to keep the user’s attention focused on the task at hand, resulting in better engagement and performance.

Emotion and motivation: Emotions play a significant role in shaping human behavior and decision-making. Designers consider how users may feel about the interaction and how to motivate them to engage with the voicebot. Secondary UX research about user demographics and socio-economic and geo-cultural backgrounds can provide valuable insights to improve CX.

Decision-making and problem-solving: Conversations often involve decision-making and problem-solving, and understanding how people process information and make decisions is crucial for effective conversation design. Factors include biases, heuristics, and cognitive load.

How Do You Reduce Cognitive Load in Conversation Design?

What are the best ways for conversation designers to reduce the users’ cognitive load in a conversation with a Voice AI solution, consequently improving the customer experience? Here are some guidelines you can follow:

Simplify prompts and confirmations: Using as few and simple prompts and confirmations as possible helps reduce the need for users to remember and respond to multiple options, ultimately leading to an optimal cognitive load and user experience. This is easier to accomplish with a well-designed conversational Voice AI than with legacy technologies such as IVR systems, in which users are forced to listen to long menus of mostly irrelevant options.

For example, a legacy IVR system will offer a lengthy menu of options, such as: “For your account balance, press 1; for information on your upcoming payment, press 2; to update your personal information, press 3 … To hear this options again, please press #.”

Instead, a Voice AI solution will simply ask: “How can I help you?”

Another example is the prompt for a user’s date of birth. A poorly-designed voicebot will say: “Please enter your date of birth in the following format—two digits for the month, two digits for the day, four digits for the year,” or a similarly lengthy and confusing prompt.

Instead, a well-designed voicebot will ask: “Could you please say or enter your date of birth?”

Use natural language: Use natural language and avoid complex sentence structures to reduce the cognitive effort required to understand the conversation.

See below an example that highlights the difference between a more robotic language choice and an alternative with more natural-sounding language.

Robotic language: Unfortunately, the payment amount that you have given is less than the acceptable minimum amount of $50. Can you please state an amount that is equal to or higher than $50?”

Natural-sounding language: “Sorry, but the minimum we can accept is $50. Can you please tell me how much above that amount you can afford to pay today?”

Provide clear cues: Open-ended questions can prompt a multitude of responses from the users; the voicebot might not understand many of the possible answers. Therefore, using clear cues to indicate when the user should speak, and using audio cues to confirm that the system has understood the user’s response should be adopted as a standard practice.

For example, here’s what the Voice AI solution will say to negotiate a payment plan: “We offer a choice of 2-month, 4-month, and 8-month payment plans. Which payment plan would you like?”

Another way to provide clear cues is the use of an audio signal informing the user that something is happening; in jargon, this is knows as an “earcon” (a brief, characteristic, harmonized and structured sound and its job is to communicate a specific message, event, status to a user or convey a task being performed).

This type of audio signal gives the user a cue that something is happening (e.g. a payment is being processed), instead of just having plain silence, which can lead to confusion. An earcon, for example, could be the sound of someone typing on a keyboard, which signals that the information is being processed.

Use progressive disclosure: Progressive disclosure is a strategy in interaction design to reveal information gradually and start only with the most essential information. Providing information to the user in a step-by-step manner, rather than overwhelming them with too much information at once, leads to increased engagement and enhanced experience.

See the example below:

Voicebot: “To set up a payment plan, can you tell me how much you are comfortable paying each month?”

User: “$60.”

Voiebot: “Thanks! Based on a $60 monthly payment, we can set up a payment plan with a duration of 4 months. Your payment plan will start on the next billing cycle. How does that sound?”

The reiteration of the monthly payment amount also serves as an implicit confirmation.

Contextual design: Using context to guide the conversation reduces the need for the users to provide additional information. For example, just as we do when we talk with a waiter at a restaurant, if the user has already provided their name, the system should use that name in subsequent interactions. As the conversation progresses, the voicebot will have more and more context and will be able to utilize the information it has collected to improve the user experience.

The voicebot shouldn’t just rely on context of the specific conversation taking place, but also on the context of previous interactions with the same user. Acknowledging previous interactions is a good idea.

Test and iterate: Testing the bot’s conversations with users and iterating the flows based on their feedback helps improve the user experience (UX) and reduce the cognitive load. The conversation flow can be optimized based on the different users’ needs. Additionally, different types of debt, different users, different demographics often require slightly different approaches.

There is no doubt that leveraging cognitive science in the design and development of conversational Voice AI solutions can significantly enhance the customer experience (CX).

By understanding how human cognition impacts user interactions, conversation designers can create intuitive and engaging interactions that reduce cognitive load, leading to more positive user experiences.

By applying these insights and best practices, business can rely on voicebots to meet their customers’ needs and optimize the use of their own resources. As the technology continues to advance, the potential for Voice AI continues to grow.

Want to learn how Voice AI can transform your business? Use the chat tool below to schedule a meeting with one of our experts!

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 voice 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 in capabilities of our Conversational Voice AI solution. The conversations are about to become more natural, and the capability to handle complex conversations significantly better leading to better CX and more collection for collection agencies.

At Skit.ai, we embrace the future and prepare to go beyond it.

The Giant Leap in Capabilities of Skit.ai’s Augmented Voice Intelligence Platform with Generative AI

With the application of LLMs, we are seeing a big jump in the conversational capabilities of our solution:

  • Higher Conversational Accuracy: Significantly high conversational accuracy as LLMs are capable of understating conversational complexities with a profoundly superior understanding of context, sentence parsing, and response accuracy.
  • Better Handling Complex Conversations: Superior understanding of complex conversations that were earlier escalated to human agents. This would cut down the percentage of calls passed over to live agents drastically.
  • Out-of-scope Calls: As LLM-powered voice AI solutions can handle a wide array of questions and issues, its ability to handle out-of-scope calls is thus much more.
  • Better and more natural bot utterances.
  • 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

Not resting with massive gains we are achieving with basic LLMs, we intent to take it a notch further up and outperform human collectors.

1. Going Beyond Human Agent Performance

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

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

2. 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 produces 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 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 better than human agents.

Business Outcomes of Incorporating Generative AI

Below are the major impact areas we will more the needle on:

  1. Higher Collection Rate, ~5%: It 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.
  2. Lower Agent Dependency, reduction by 50-80%: As the voicebot will be able to handle more complex queries we expect 50-80% reduction in agent touch points.
  3. Higher Resolution Rate, ~100%: Better accuracy and better conversation with higher engagement will help us achieve a conversational resolution rate of close to 100%.
  4. Creating New Voicebots: The effort involved in creating a new voicebot will see a significant dip, as the complexity will be remarkably lower.
  5. Entering New Markets with Ease, 15X faster: Entering into new markets, training for new use cases and applications needing less effort and resources. We are estimating the process to be 15X faster.

The Way Ahead

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 human resources and scale their collection efforts with call automation, schedule a call with one of our experts or use 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.

Voice AI Helps Auto Financers Reboot for Better Customer Loyalty and Retention

Posted on by Harshad Bajpai

Today, every CXO working in auto finance knows it takes just a few online searches and clicks to buy a vehicle. For an industry primarily focused on customer-centricity, auto finance companies are suddenly up against “seconds-to-minutes” worth of digital interactions to wow their customers for better engagement and retention.

Inflation in the U.S. is adding a new set of challenges, with rising interest rates, vehicle prices, loan delinquencies, and predatory competition, making the current landscape particularly complex.

Prospective car owners seek online financing options for the speed, convenience, and wealth of online information to make a decision. Their digital savviness intensifies the demand for fast-paced digital finance with seamless customer support. Auto finance companies must rethink every touchpoint and communication channel across the customer’s journey.

Ensuring customers stay satisfied throughout their auto lending journey is a complex task.

In this article, we’ll explain what Voice AI is and how it can add significant value to the customer experience (CX) in the auto finance industry. Skit.ai’s Voice AI solution can help auto finance companies automate various types of calls, starting with collection calls and payment reminders.

7 Auto Finance Use Cases with Voice AI for Better Customer Experience

  1. Welcome Calling & Onboarding: Our Digital Voice Agents plug into contact centers to handle Tier-1 calls that are mundane and repetitive. These intelligent voice bots are tailored to send automated welcome messages, assist customer onboarding, and share loan-related information like interest rates, loan eligibility, loan approval, and payment details. 
  2. Payment Reminders: Auto loan providers can leverage Voice AI solution to set triggers for personalized, outbound payment reminder calls of any volume for loan payment, EMI dues, interest rate updates, and document submission.
  3. DPD 30-60 Collection: (DPD).Voice AI helps place thousands of automated, proactive, and timely calls concurrently without requiring human intervention or needing to scale human support teams. This is useful for auto finance collection cases involving consumers who have missed EMIs for 30 to 60 Days Past Due. The prime customer gets a grace period; late payment fees are waived, and credit scores will not be affected. These are the benefits that customers experiences which make ultimately result in better CX.
  4. Auto draft Signups:  Auto draft is like enache. Prime customer who is of the age of 50 and above still pays with a cheque or visits the bank. For them, auto-pay setup is essential to avoid penalties. In turn, it contributes to the convenience essential in enhancing CX and increasing customer loyalty.
  5. On-call Payment Assist: Digital Voice Agents can provide prompt on-call payment support to consumers by automating responses for Tier-1 calls and transferring only complex calls to human agents. The analytics and data on consumers’ loan accounts and payment histories also help collectors to have better insights for answering various consumer queries and providing on-call payment assistance.
  6. After-Hour Business Services: Voice AI helps auto finance companies provide 24/7 live customer support services to answer consumers’ queries about payments, loans, due dates, and more at any time of the day. Especially useful for calls made after business hours and for handling simplistic queries, while the other issues, such as disputes and other issues, are captured and updated with relevant CTA.

11 Ways Voice AI Drives Up Customer Loyalty and Retention 

The critical aspect of Voice AI in auto finance is to help companies against common operational pitfalls that can lead to potential and existing consumers slipping away to their competitors. Our Augmented Voice Intelligence platform allows auto finance companies’ contact centers to augment their support teams to unlock the best of its live collectors and Digital Voice Agents to serve many use cases, delivering superior CX. These further translate to customer retention and loyalty in the following ways:

  1. Higher Customer Engagement: Digital Voice Agents call automation; up to 70% of calls help reach the right consumers at the right time and frequency. This helps auto finance companies supercharge their engagement rate with current customers and onboard potential customers. 
  2. Better Brand Advocacy: As per the 2022 J.D. Power study report on Consumer Financing Satisfaction, existing customer relations are the low-hanging fruits for auto loan providers to leverage. Captive lenders reportedly outperform non-captive lenders with higher NPS. Voice AI helps engage with existing customers who are twice as likely to consider their current lender for their next vehicle purchase.
  3. Scalable Customer Support: Reminders at the right time and to the right person, with 1000s of concurrent calls, helps auto lending companies engage with thousands of callers across loan portfolios at a fraction of operational costs.
  4. 63% Faster Customer Query Resolution: Companies that implemented Voice AI in their contact centers were able to reduce 63 percent of the query processing time for better customer retention and satisfaction at 67 percent, as per a study by Ecosytm.
  5. Proactive & Diverse Support: Voice AI is customized for various functions and call automation capabilities to help the customer support teams to cater to diverse customer queries like payment collections, customer signups, document verification, loan approval, and purchases. 
  6. Augmented Human Support: By leveraging call automation and intelligent voice bots’ ability to provide prompt resolutions to tier-1 calls, auto finance companies can empower their contact center agent teams to save time and resources, be productive, and focus on high-value tasks that need actual voice conversations with customers in times of their need, translating to better CX. 
  7. Self-service Capabilities: Voice AI’s 24/7 availability with prompt response to queries gives customers control over debt repayment or auto finance process.
  8. Waitless Resolution: Digital Voice agents quickly disseminate information on products or loans, reducing wait time and elevating CX. 
  9. Personalized Responses: By delivering contextually accurate information specific to the use case, Voice AI ensures the responses are hyper-personalized with consistent call quality.
  10. Better Customer Intelligence: Auto finance companies can make the customers feel heard by unlocking a treasure trove of customer insights from data and robust analytics dashboards to improve the overall customer experience and call quality. 
  11. Higher Compliance: Collectors in the auto finance industry must be aware of core federal laws relating to auto loans and consumer communication, including HIPPA, FDCPA, FCRA, TCPA, and more. Voice AI’s algorithms are trained to adhere to consumers’ laws on privacy and compliance best practices which are critical for building a positive brand image.

Voice AI Represents a Breakthrough in Auto Finance 

The automotive industry is slowly evolving to build excellent customer journeys against the digital boom, rising consumer demands, and data ubiquity. A look into the future shows no signs of slow down in consumers’ expectations for digital and phygital experiences in auto retail and finance. Voice AI is poised to make contactless car buying a reality in the era of driverless cars!

To learn more about how Voice AI and Digital Voice Agents help reimagine customer support and collection in auto finance, schedule a call with one of our experts or use the chat tool below.

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.ai 

A Story of Transformation: How Skit.ai is Helping ICICI Lombard Reach New CX Milestones

Posted on by Harshad Bajpai

The age of hyper-personalization is here. For the digitized insurance sector, achieving communication-centricity along the way of personalization will be the mantra for superior customer experience (CX)!

Even though insurance policies are intangible, today’s customers look for tangible evidence in the customer service or product features that make their experience smooth and easy.

Insurance claims are moments of truth. They are sensitive moments following an ailment or an unfortunate event. Cost-effective and empathetic service holds the key!

Exploring the Need for Call Automation with Voice AI and Leapfrogging CX 

The high volume of calls in the insurance industry makes call automation imperative. For instance, insurance claims status follow-up typically involves sharing policy information and reference numbers over IVR, keying in their details in self-service dashboards, and calling customer support for status confirmation and validation. Shortening reach to that information most quickly is a definite way of improving CX.

From the providers’ standpoint, dispensing the correct information at the right time without impacting cost, productivity, and customer satisfaction could be a grandiose ambition, especially with the rising cost of human-agent interactions. Besides, the bar for CX is raised too high by thriving CX-centric companies from other industries. Nearly 86% of buyers are willing to pay more for great CX.

Here’s a snippet of industry research that we think can help insurance providers chart a realistic customer support roadmap in claims status management: 

  • People and technology combinations are the most sought-after options for insurance interactions, according to a study by Gartner.
  • Digital channels are great for securing sales but lack personalized advice capabilities, according to the Capgemini World Insurance Report 2021. 

To sum up, an ‘Always-on’, real-time and intuitive customer service is the need of the hour. Insurers need a balanced combo of human representatives and AI-powered automation for frictionless customer support.

We will discuss further in the article how Skit.ai’s Voice AI aces in enhancing both human-machine combinations for personalized claims status support for ICICI Lombard, one of India’s leading private sector general and motor insurance companies. 

Skit.ai and ICICI Lombard Partnership Upholds the Promise of Customer-centricity

ICICI Lombard has held a strong focus on being digital-led and agile. It has successfully launched an array of tech-driven initiatives that are tailored to customers’ expectations. Throughout their legacy of over two decades, ICICI Lombard is committed to customer-centricity with their brand philosophy, ‘Nibhaye Vaade’. As of March 2022, the company has issued over 23.9 million policies, settled 2.3 million claims, and has 283 branches with 11,085 employees. 

The insurer wanted to implement a revolutionary approach to help customers with ‘claims status’ updates for–better CX, contact center performance, and lower cost. The answer was Skit.ai’s Augmented Voice Intelligence platform, which helped the insurer usher in call automation in their contact centers and empowered human agents to drive better CX.

Skit.ai’s purpose-built AI-enabled Digital Voice Agents can handle tier 1 customer service calls, which are around 70% of total call volumes, and make intelligent handovers to human agents for more complex calls. It takes time and post-implementation pursuits to reach such high levels of automation, training the voicebot for all use cases and situations. 

We will discuss the positive business outcomes that Skit.ai’s Augmented Voice Intelligence platform helped ICICI Lombard achieve by automating and modernizing its legacy, checklist-driven claim status processes. Additionally, we will also be detailing the existing challenges in claims status management that prevents insurers from demonstrating speed, value, and efficiency. 

Dive deeper: What are Digital Voice Agents? 

How Skit.ai’s Digital Voice Agents are Accelerating ICICI Lombard Claims Status Support with Call Automation

Digital Voice Agents plug into contact centers and augment human agents by automating cognitively routine work. With the deployment of Skit.ai’s solution, ICICI Lombard could augment its performance in the below-mentioned areas. Other insurance companies can also transform on similar lines:

  1.  Personalization and Empathetic CX: Digital Voice Agent answered customer calls and automatically checked their history based on their registered mobile number. This knowledge helped ICICI Lombard personalize interactions with the customers. Upon request, the voice agents confirmed claim details and updated them on the claim status in less than a minute. ICICI Lombard could also leverage voice automation and personalized caller’s journey without making them wade through the IVR menus or wait to speak to an agent. No wonder they experienced a rise in CX. 
  2. Shorter Conversations: Obviating IVRs, the voice agent helped the insurer shorten the conversations by capturing all the details and transferring them to a human agent who picked up from where the voicebot concluded. This helped in improving the quality and average handling time for human agents. 
  3. Lower Contact Center Opex: Digital Voice Agents can contain a significant volume of claim status calls without needing intervention by the insurer’s customer support teams. This efficiently manages their contact center operations to handle a large number of customer queries (containing up to 30% of claims status calls), and also curbs additional expenses on training and hiring human agents to handle zero-value, repetitive tasks.
  4. Agent Productivity: The automation capabilities of Digital Voice Agents can help contact centers to use their human resources more judiciously by allowing them to only handle complex claims-related cases and escalations.
  5. Always On Support: Running contact centers 24/7 is not feasible from a cost and agent availability standpoint. An insurance policyholder can approach customer support for claim status information at any time of the day. Digital Voice Agents are capable of carrying out human-like conversations and can understand intent, sentiment, and voice tone to cater to their needs even post the working hours.

Discover the Biggest Contact Center Automation Trends of 2022

Business Outcomes of Call Automation at ICICI Lombard

With the help of Skit.ai’s Augmented Voice AI platform, ICICI Lombard achieved impressive outcomes: 

  • Contact center operational cost reduction by 28%
  • End-to-end automation for 30% of calls; no need for a human agent
  • Time to Value of fewer than 100 days 

These results represent just the beginning of possibilities for ICICI Lombard with voice automation.  Additional improvements will emerge as more use cases are added. Also, the learning curve advantages that come with time, will give the insurer a decisive competitive edge.

In the Words of ICICI Lombard Leadership 

Reflecting on their successful journey with Voice AI, the leadership team at ICICI Lombard also expressed their thoughts: 

“At ICICI Lombard, we believe that insurance is a promise that a customer pays for upfront, and the claim is the moment of truth. With our digital transformation strategy, we have set out to deliver on this promise with an intelligent digital voice agent that cuts down on customer wait time and holds empathetic conversations. It is an unconventional, modern solution that simplifies a legacy process that is quite complex,” said Girish Nayak, Chief of Service, Operations and Technology, ICICI Lombard.

“This is a watershed moment for the industry—for an insurance company to employ Voice AI to transact with customers and provide them with their claim status. One of the big CX wins is that customers don’t have to suffer DTMF anymore—no more,” ICICI Lombard mentioned in the case study.

Commenting on this revolutionary move, Vasundhara Bhonsle, Head of Customer Support at ICICI Lombard, said, “At ICICI Lombard, our digital transformation strategy focuses on deploying innovations that provide the best service and experience to our customers. Through our partnership with Skit.ai, we are creating a milestone for the Indian insurance industry. By implementing a digital voice agent to manage inbound queries for claim status, we are modernizing a legacy, complex process to make customer interaction a lot more personalized and empathetic. We look forward to bringing the benefits of the digital voice agent to millions of customers in India.”

Reimagining Insurance Customer Support with Voice AI 

ICICI Lombard began the deployment of Skit.ai’s Digital Voice Agents with one of the most challenging use cases i.e. Claim Status Support. Generally, dispensing claims status information on the go requires a good deal of time and resources. Sometimes, insurers are also dependent on other external stakeholders like hospitals and care providers using time-consuming, manual procedures for patient data and claims status-related updates. To ensure these hurdles do not affect customer support, insurance companies need to remain a step ahead leveraging Digital Voice Agents in the claims status area. 

Below are 6 reasons why insurance companies should up their game with intelligent Voice AI-led workflows in customer support to lead customers in their insurance and claims-related decision-making:

  • Much Newer and Tech-savvier Competition: With the arrival of smarter and innovative entrants in the market, it gets tough for insurers practicing legacy approaches in the claims process to remain relevant and win over customers. CX is crucial for survival and customer loyalty. So, it makes sense to integrate novel CX enhancing technologies and contact center automation to make claims status processing quick.  
  • Delays Cause Frustrations: Delays and long wait times for updates on the status of the claim frustrate customers. The claims process typically has limited human touch points. The absence of timely updates can gravely lower CX and customer satisfaction. 
  • Mounting Opex of Contact Centers: The time and cost factor for outbound efforts, confirmatory calls, and resources used as per policy with the available support team makes it difficult to reach all policyholders on time. This is yet  another driving factor to consider innovation in claims status and leverage Digital Voice Agents for 24/7 service.  
  • Automation Must Follow Digitization:  If approached in layman’s terms, there is too much information like claims reference number, policy number, name, address, and more that a policyholder must manually read out to a contact center agent along with call authentication conversations. This is not only time-consuming but also would be best if the information can be input and confirmed on self-service dashboards rather than over phone calls. 
  • No Room for Errors. Follow-up, changes, and corrections with the human agents when a slew of information (mostly when they are numbers and characters) is exchanged and input manually, has high scope for errors. Inaccuracies and mistakes can be costly for the insurer’s brand reputation and bring down customers’ confidence.  Automation with Voice AI allows for perfection by taking over repetitive, mundane processes. 
  • Self-service and DIY Option Comes with Privacy Factor: Offering intuitive self-service options and Digital Voice Agents that hold human-like conversations with customers can guide them through the claims process and can allow them a degree of autonomy. Since customers are independently accessing the claims process and status, it creates a strong sense of privacy which is integral for customer satisfaction and CX. 

How Voice AI Helps Insurance Companies Streamline Inbound Support

Looking Ahead: 

The future of customer support is voice. Rising costs and human agent attrition make delivering quality support prohibitive. But with evidence abound, Voice AI is fast emerging as a technology to leverage, and leapfrog CX. Voice AI was an option, but it is fast becoming an imperative, watch out!

The journey of transformation has just begun. As we constantly evolve and experiment with our technology across use cases in the insurance domain, there’s clear certainty for better numbers and more success stories in our pipeline.  

Are you interested in exploring automation possibilities with Digital Voice Agent to elevate your customer experience with better customer support? Use the chat tool below to book a demo with one of our experts! 

Move Beyond IVRs: Transform CX with Digital Voice Agents!

Posted on by Harshad Bajpai

For contact centers, Interactive Voice Response (IVR) systems were a turning point a few decades ago, but now have become a customer experience turn-off. IVR systems have helped companies manage call volumes as well as create value with self-service options, information gathering, and call routing.  But a recent study found that, on average, IVRs cost businesses $256 per customer each year! Additionally, a whopping 61% of these customers are unhappy with IVR systems and believe they contribute to a poor customer experience.

“About 83% of the customers abandon the call and company after their IVRs encounters.”- Vonage report.

Why IVR Systems a Customer Service Turn off 

Historically, IVRs have failed to delight callers due to the poorly designed phone menu and the inability to dispense an answer or connect an agent on the go. Companies and businesses receive a lot of flak due to the general notion of associating IVRs as cost-effective replacements for contact center agents. It is paradoxical that customers warmly accept other forms of automated, self-service options for an instant response like ATMs and a variety of mobile applications but not IVRs!

The reasons for it are pretty simple. Since their introduction into the contact center market, IVR systems have undergone few iterations, and their main features haven’t changed much. The hold time, lengthy pre-recorded menus, and the need to repeat query information, especially during an emergency, continue to be a liability for businesses.  More importantly, customers have a strong affinity for resolving queries with a human representative than with restrictive, pre-recorded systems that only leave them with unsavory emotions towards the brand.

Nearly 47% of callers reportedly experience frustrations with IVRs. A significant number of them admitted feeling angered and stressed, according to the Vonage report.  

The same report also revealed that instead of IVRs, if the customers were able to get a hold of a live agent, they experienced relief (27%), less frustration (26%), and less anger (24%).  However, call center agents often end up at the receiving end of customer frustrations from navigating a labyrinth of IVR menus. Therefore the onus is on brands to elevate customer experiences without negatively impacting agents’ morale and productivity.

In this article, we share our insights on overcoming common contact center and customer experience challenges associated with traditional IVRs by diving into the capabilities of Voice AI. We will explore how brands can elevate their customer support with intelligent voice automation of nearly 70% of calls and human-like conversations.

Explore Now: AI-powered Digital Voice Agents vs Outbound IVRs 

Understanding Digital Voice Agents: DVA vs. IVRs 

Imagine a scenario—a customer calls a banking company’s contact center to block their stolen debit card. In lieu of pre-recorded messages and caller authentication protocols, the call is handled by a voice agent that is capable of contextually comprehending the caller’s urgency and making appropriate suggestions. The overall call experience is different! Why?

  • Zero waiting time
  • The instant response instead of punching numbers, a refreshing change from the lengthy IVRs menu options, annoying IVR theme music, and even from the exasperating experience of going down the rabbit hole of the menu by accidentally pressing a wrong button. 
  • For simple queries, no need for human agents

That’s our Digital Voice Agent (DVA) at work. Skit.ai’s DVA, for instance, is an AI-enabled virtual agent built from the ground up to understand human conversations. It can be plugged into contact centers to resolve tier 1 customer problems and automate cognitively routine work.

Digital Voice Agents vs. IVRs

  1. Built for Voice: Unlike conventional IVRs and chatbots that are capable of understanding only transcriptions, Digital Voice Agents are crafted specifically for voice conversations. Whenever a customer calls the contact center, they can interact with the voice agents in the same way as they converse with human agents.  
  2. Built for Personalization: With DVAs, there wouldn’t be any psychological barriers that callers experience when they are forced to interact with IVRs or chatbots. Besides, an intelligent voice agent that can sound like a human, picks up on the immediacy of the issue, giving callers a sense of relief and comfort in their critical moments, adding a more personal touch to customer service. Besides, they can even interact in the caller’s preferred choice of language.
  3. Built for Accuracy: Another issue when dealing with IVRs is that they work well only when there are no external disturbances like background noise or music. They can sometimes not recognize text inputs and end up redirecting the caller to the undesired part of the IVR menu. But DVAs can take in both voice and text inputs, and even filter out the ambient noise to capture the accurate voice response by the customer. 
  4. Built for Capturing Intent: Voice agents are based on powerful spoken language understanding (SLU) algorithms and can identify the semantics of the conversation. They can accurately capture the caller’s sentiment, tone of voice, and speed of the conversation to identify intent. 
  5. Built for Resolution: In emergency situations that require a quick response from customer support, a call hold would reflect poorly on the company’s services. It can even make them lose customers to their competitors. Most IVRs cannot pick up on non-linguistic cues like pauses, gasps, and utterances in between sentences. It is purely designed for text inputs. DVAs are capable of having contextually accurate interactions without relying on a limited stack of keywords, enabling quick query resolution. 
  6. Built for Intelligent Human and Machine Collaboration: IVRs are automated and function independent of human agents. DVAs are capable of end-to-end automation of simplistic calls and pass on complex ones to human agents, involving them only in complex use cases.

 A Deep Dive: AI-powered Digital Voice Agents vs IVRs

Now, let’s look into 7 specific angles where Skit.ai’s purpose-built, industry-specific voice-first technology, Voice AI, makes a tremendous difference to contact centers.  Skit.ai’s voice agents are a better fit than traditional IVRs in enhancing the quality of customer service.

  1. Speed and  Simplicity: Simple and easy-to-understand customer support is a formula for delighting a captive audience. There’s a good chance that the majority of callers may not get past the common obstacles in IVR menus, complex navigation, and confusing terminologies. IVRs can best offer five top-level and three sub-level menu options whereas DVAs immediately attend to calls, keeping it short and simple. 
  2. Quick Resolution with Cost Efficiency:  Apart from resolving customers’ problems, customer service organizations look at cost and call time spent as success metrics. Instead of wasting time, waiting for the right menu option on IVRs, customers’ queries with DVAs are addressed instantly and at a fraction of the cost while also engaging with the callers over voice conversations at scale. 
  3. For Intelligent Customer Service: Today’s customer service is expected to be built intuitively to absolve current issues and anticipate the next course of action. DVAs help make the most of the voice conversations with customers by mimicking human-like conversations and leveraging customer data to make appropriate recommendations, suggest steps or make intelligent call transfers to human agents.
  1. Quick Agent Reach during Emergency: Even the most loyal customers lose patience and abandon calls midway when forced to repeatedly go over the IVR system. For critical use cases that require timely resolution, DVAs work best. They not only hold an immediate voice interaction with the callers but also identify short, conversational utterances, pick up on callers’ intent, and capture customer details for quick call transfers to human agents. 
  1. Making Query Resolution Interactive: Speaking to a live agent immediately is not the magic bullet for customer support success. Augmenting IVR systems or replacing them with Voice AI-driven automation for call back features at customers’ preferred time helps personalize and enhance the call experience making the conversations more empathetic. The rapid scalability and robust integrations of the DVAs help include options to reach customers with interactive emails and voicemails along with call-back options. 
  1. Easy Integration with Customer Experience Systems: Customer service calls can be more proactive and intuitive when integrated with customer relationship management (CRM) platforms and automated call distribution (ACD)  systems. Voice agents have access to caller history, previous purchases, and other customer data based on the caller ID number. It provides enough pre-context to authenticate calls before call handovers to human representatives.

Read in Detail About–Digital Voice Agents: What, Why, and How 

  1. Timely, Useful Insights for Enhanced CX:  DVAs help brands adopt advanced analytics-driven approaches to unlock a treasure trove of insights on call performance as well as define relevant KPIs and areas for improvements in the customer’s journey for cost savings and better CX. IVRs need optimizations to deliver this capability. While DVAs work as productivity enhancers with timely insights that help add incremental value to the brand or business’ customer experience. 

Despite several detractors that customers unanimously agree on, IVR systems remain a staple in customer support. The worldwide growth rate of the IVR market is expected to reach $6.7 billion by 2026.  This growth trajectory can be a blessing to CTOs who chose IVRs for long-term customer service investments, but certainly a nightmare for CMOs against the backdrop of increasing customer calls. Technological innovation and AI-driven upgrades are needed to drive the progression of IVR systems. Until then, Voice AI helps empower businesses to elevate inbound and outbound initiatives for better CX in ways that IVR systems fail to live up to. 

Are you interested in contact center automation with our Digital Voice Agent to elevate customer experience?  Book a demo with one of our experts: www.skit.ai   

Transforming Customer Experience with Optichannel Support and Augmented Voice Intelligence

Posted on by Harshad Bajpai

We have all been in dire straits and dealt with frozen bank accounts and medical or travel emergencies. We can vividly recall the palpitation and frustration felt during those moments, waiting for customer support, navigating IVRs, or a chatbot.

Companies have long wanted to change it, but challenges such as high attrition rates, unscalable teams, inconsistent CX, and cost pressures have curtailed their capability to serve customers.

Consequently, customer frustration is on the rise. A 2019 report said that customers are annoyed by the irrelevant options presented by the IVR. In fact, two out of three Americans (66 percent) say they would choose AI-powered voice-over chat if it were effective at answering their questions.

Riding the wave of recent advancements in NLP and AI, we are graduating from machines automating crude, low-value tasks to a new era where AI-enabled voice customer support would help companies create enormous value, conversing in their preferred language with semantic understanding to resolve their problems.

Explore How to Improve Customer Experience With Voice AI

For Exceptional CX – Technology and Channel Strategy Matters

A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as critical to the overall business performance of their company.

Companies now realize that multi-channel or omnichannel strategy has failed to live up to the expectations of improving CX, primarily because different customer segments prefer specific channels to connect. Thus, an optichannel or optimal channel strategy is more prudent as it focuses on the capability to support a customer journey via a channel/modality optimal for that problem.

Even today, after years of decline in customers’ preference for voice support to troubleshoot, voice is still over 50% in contact volume. Though companies may pursue an omnichannel strategy, if they are not good at voice support, they must be cognizant of its impact on CX. Optichannel is thus a more prudent strategy as being good at different modalities such as emails and chat will not compensate for the damage done by poor voice support. Companies have to choose wisely, there is no one-size-fits-all solution.

Text and Voice: Don’t Mix and Serve

Acing CX means that the company must be good at serving customers with their preferred channels. Voice is complex, subtle, and requires semantic understanding. Nuances of a voice conversation such as a change in the rate of speech, voice modulations, and more that convey a customer’s feelings are lost if your solution is not built from scratch for voice. Bundling a chatbot with a readily available Automated Speech Recognition (ASR) to add voice capability just kills the beauty of spoken conversations because it can transcribe but not converse.

Shortcuts like these fulfill notionally the goal of being present in every channel but defeat the goal of being good at the relevant channel. 

Moving Beyond the Complexity of Digital Transformation with Voice AI

In the last few decades, the world moved from voice to text to chatbots. But as customers still prefer voice over other communication channels, even brands are taking notice. WhatsApp, a chat messaging platform, is building voice-led solutions for businesses. A Deloitte study reveals that by 2030 there will be a proliferation of voice-led technology across the globe and that 30% of sales will be via voice by then.

As companies hustle to achieve digital transformation, the low success rates, and disturbingly lower rates of sustainable DX success are proof of the precarious journey. 

Fortunately, there is one way to not only automate contact centers with the most cutting-edge technology but also ensure that it succeeds without a big resource commitment from the organization. Yes, Voice AI is one such solution with stand-alone deployment and stunning success rates. 

Companies must consider deploying Augmented Voice Intelligence for contact center automation as a good starting point toward digital transformation. But before that, brands must ponder over the most significant question – What does the shift towards voice entail as we cross the voice automation rubicon? What is its impact on the market and competitive landscape? 

Look before you leap!

Only if you feel that your human agents are doing zero-value repetitive tasks, and there could be enhancement of their productivity. Your company is continuously facing resource, cost, and compliance challenges. Perhaps it’s time to contemplate and change.

For more information and free consultation, let’s connect over a quick call; Book Now!

Also, for more information: How We Can Transform Customer Experience

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Voice AI for Insurance: Streamline Inbound Support

Posted on by Harshad Bajpai

Today, the expectations of insurance customers are heavily influenced by the tech first disruptors. In order for traditional insurance companies to continue with their market domination, they will need to take a comprehensive and structural approach to transform their business models to compete with the nimbler tech-savvy entrants- Insurtechs, which are redefining product offerings and customer experience (CX).

The insurance industry is going through a tectonic shift, as more consumers are buying insurance policies online rather than taking the help of agents/brokers, in order to minimize contact – a behavioural change that has accelerated due to the recent Covid-19 pandemic. The online insurance market in India is expected to grow to INR 220 billion by 2024 (Mordor Intelligence report). However, most insurance companies are overwhelmed with the increased surge and face a hard time in resolving queries of leads and customers. 

Since the trend is only going to increase in the future, it’s critical for insurance companies to reimagine their inbound support strategy. With limited resources and increasing support queries, insurance companies need to leverage the right technology and automation to see results.

AI Voice bots, for example, are becoming increasingly popular among insurance companies and are being leveraged by many insurance companies to answer mundane support requests and streamline the claims process. In this blog, we dive deeper and understand exactly how AI Voice bots are driving value for insurance companies when it comes to inbound support –

Role of Voice AI 

Voice AI is a combination of technologies that enables interaction between computers and customers through voice. AI Voice bots that are powered by Voice AI are built using sophisticated and advanced Artificial Intelligence (AI) algorithms. 

With the ability to understand the context and intent and hold human-like conversations they can engage with customers and assist them without any human intervention. 

By connecting with the customer at different stages in the customer journey, be it to remind them about upcoming renewals, lead qualification, answer FAQs or inform about claim submission status, AI voice bots delight the customer while freeing up additional agent bandwidth to take up complex tasks. 

While the solution is equally effective in increasing renewals and for proactive customer engagement, in this blog, we’ll just focus on how it can streamline inbound support – 

Answering FAQs around policy quickly

Insurance companies receive a lot of inbound queries daily around premium payment terms, maturity date, lock-in period and more. A huge chunk of these queries are mundane in nature and don’t need human assistance. However, most insurance companies still resolve these questions manually. 

With limited bandwidth, companies struggle in reducing response times. Also, this negatively impacts the productivity of the agents as they waste their time answering repeated queries each day. 

A great way to fix this is by leveraging AI voice bots to answer these questions. They can easily understand the customer’s query and resolve it instantly 24/7. Customers no longer need to wait in a queue or go through complicated IVR systems. With the right integrations, AI voice bots can easily fetch customer past data to provide a personalized support experience. 

By freeing up agent bandwidth, human agents get more time in resolving complex support queries. Customers on the other hand get immediate answers to their queries which could have otherwise easily taken a few minutes. 

Additionally, AI voice bots are extremely helpful in tackling surges in the number of support queries during certain events such as a flood, earthquake etc. 

Enhancing the claims experience 

The claims process is a defining moment in a policy holder’s life. They expect it to be frictionless. However, most of the time they’re left disappointed. Traditionally, the insurance claims process has been slow and challenging. Getting a claim processed in a few days or weeks with minimal effort is nothing less than a miracle. 

With time, insurance companies have understood this. They know it’s critical for customer retention, sustainable growth and differentiating themselves from the competition. Hence, they constantly employ different strategies and technology solutions to streamline their claims process and make it more efficient. 

But, oftentimes, the reason for dissatisfaction among customers has to do with the lack of information around the status of the claim (especially during life-changing events) than the overall processing time. To fix this, insurance companies can leverage AI voice bots.

AI voice bots can intelligently assist customers throughout the claims process and even proactively inform them about the status of their claims. They can answer common questions around how to raise a claim, claim forms and more. If required they can also seamlessly do handoff calls to agents. 

By engaging with customers at every stage and keeping them in the loop, they prevent any information gap and remove the need for them to reach support. This significantly enhances the customers’ claims experience, thus increasing satisfaction and customer loyalty. 

The road ahead for Insurers

By focusing on convenience, personalization, friction less customer service and building loyalty insurers can stay ahead of the competition and attract loyal customers. But the road ahead for them is not easy. Insurers need to invest in customer-centricity to build and maintain a competitive edge.

About Skit

Skit is an Augmented Voice Intelligence Platform, helping businesses modernize their contact centers and customer experience by automating and improving voice communications at scale. By enabling preemptive, intelligent problem solving and seamless live interactions, we have automated over 15 million calls for global enterprises across industries. We help our customers streamline their contact center operations, reduce costs, and also enhance customer experience and engagement.

Connect with us if you’re interested in learning more about the platform and how it can streamline your contact center strategy.

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