Tag: 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!

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.

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! 

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