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 LMMs 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 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:
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.
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.
Higher Resolution Rate, ~100%: Better accuracy and better conversation with higher engagement will help us achieve a conversational resolution rate of close to 100%.
Creating New Voicebots: The effort involved in creating a new voicebot will see a significant dip, as the complexity will be remarkably lower.
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.
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 intelligentconversations 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 is becoming mainstream in the ARM industry, and the days of chasing after customers for unrecovered debts in the most haphazard, manual fashion are nearly over. Additionally, thanks to the rising popularity of self-service channels and the ecosystem-led push involving regulatory changes like the Reg F that rewrite the expectations for debt recovery in the U.S. beyond simple automation.
Voice AI conveniently fits the bill for debt collection agencies by fixing the systemized inefficiencies with automation and analytics-driven voice communication outreach. In this article, we will explore why human-like voice interactions handled by AI-powered Digital Voice Agents help debt collection companies drive effective consumer interactions at better collection cost, performance, and efficiency ratio.
7 Ways Voice AI Helps Elevate Debt Collectors’ Productivity
At Skit.ai, we call it Augmented Voice Intelligence — the idea that Voice AI can augment, rather than substitute, the work of live agents and collectors. Let’s dive into the benefits of this strategy:
Human-like Conversations: Voice AI is purpose-built and modeled on human conversations. Digital Voice Agents can hold thousands of outbound customer outreach calls simultaneously, without the involvement of human collectors, helping collection agencies carry out human-like interactions at lesser cost and effort from their human resources.
Seamless Integrations: Voice AI’s integration features feed data from collection calls, such as right-party contact, call-back requests, no response, and more, into the collection management system to provide actionable insights for human collectors to be more proactive.
Higher Portfolio Coverage: Collection agencies can leverage Digital Voice Agents to scale collection outreach calls for different consumer accounts and across diverse portfolios with unique requests for payment alternatives, call-back options, or preferred time of contact.
Versatile and Accurate:Intelligent voice bots can be tailored according to the use case, offer profound insights for analytics on future actions, independently schedule automated triggers, auto call-back on request, and even make intelligent call transfers to human agents/live collectors for complex issues.
Better Compliance and Privacy: Voice AI’s algorithms can be trained to follow regulatory protocols on reaching customers, communication time, frequency or calls, and honoring their requests for discontinuing communication using APIs. It can be challenging to adhere to all the norms when done manually. Also, Voice AI’s strong encryption and consumers’ or cardholders’ data protection features comply with regulatory standards like HIPAA, PCI, FCRA, and more.
Lower Litigation:Voice AI lowers litigation risks compared to human agents, who are more likely to coerce consumers to pay with the hope of meeting targets and receiving higher commissions. Additionally, consumers are generally passive toward Voice AI and pin fewer expectations on the technology to understand their emotions or personal grief, reducing the odds of agencies ending up with lawsuits.
Better Insights and Analysis: Debt collection agencies can draw on the insights gathered by Digital Voice Agents to learn about consumers’ or callers’ experiences and conversations to design or augment debt collection processes for better collection campaigns, collectors’ experiences, and higher recovery rates.
How AI-powered Digital Collectors Can Outperform Live Collectors
While Voice AI embodies the promise of automation with a human touch, collection agencies don’t rely on anecdotal evidence. They look for value-creation and tenacity to transform traditional loan recovery practices with the technologies to a level that human resources alone cannot match. Skit.ai firmly believes in realizing the potential of voice communication in debt recovery by augmenting human support with AI for intelligent human-machine collaboration.
Here are the key differentiating features of Voice AI that match collection requirements and make processes more efficient in responding to various outbound debt collection use cases.
Collection Support Scalability: Voice AI can automate up to 70% of calls, helping curb hiring, recruitment, and training-related requirements in collection agencies. Additionally, Digital Voice Agents help leverage unlimited scalability by simultaneously handling multiple collection calls, which would otherwise be very time consuming and expensive when done manually.
24/7 Support: Digital Collectors can always be at the beck and call of consumers to offer 24/7 support. Delivering 24/7 support with human resources would be extremely costly and unrealistic.
Lower AHT: Voice AI guarantees better performance and can handle multi-turn conversations with prompt query resolution. It reduces average call handling time (AHT) by 40% and augments human agent teams’ efforts by transferring only complex queries and equipping them with real-time analytics and insights.
Higher Debt Collection and Recovery Rate: Skit.ai’sDigital Collectors have repeatedly demonstrated performance at par with average debt collectors while operating at less than 1/5th the cost of a human agent.
Better Account Classification: Unlike manual debt collection efforts, Voice AI’s ML classification models algorithms are trained to segregate consumers as per bankruptcy details, creditworthiness, outstanding loan amounts, blocked accounts, and do-not-call lists, to help collectors or accounts receivable managers respond appropriately.
Higher Accountability and Compliance: Digital Voice Agents are trained to comply with strict practices in debt collections (7/7/7 rule, TCPA, Mini-Miranda, etc.) and refrain from the usage of unsavory language or behavior that can later result in lawsuits to the agency, which would be challenging to regulate in manual collection use cases. Besides the analytics-driven insights on consumer responses and history, Digital Voice Agents guarantee higher accountability.
Complete Campaign Control: Digital Collectors can be turned on or off as per use case to match the call volume requirement or type of consumers’ requests and accounts, unlike calls by live collectors with efficiency issues and too much time, resources, and training.
Consistent Call Quality: Voice AI delivers consistent experiences at any scale and volume. It is humanly impossible to ensure the call experience remains the same and guarantees similar outcomes for all debtors’ conversations from manual collection campaigns.
The Bottom Line: Voice AI is the Key to Supercharge Debt Collections
It is time to embrace the reality that neither automation nor pure human intelligence can help debt collection agencies to master complex collection campaigns. Skit.ai’s Augmented Voice Intelligence platforms like Skit.ai enable the collaboration between humans and AI-powered machines to respond to the mounting operational stresses in debt collection agencies. These solutions empower live collectors to perform consistently throughout the debt collection process at a better cost, productivity, and recovery rate.
To learn more about how Voice AI can help reimagine debt collection efforts with call automation, schedule a call with one of our experts or use the chat tool below.
We are at the initial stages of Voice AI’s evolution, in an epoch where well-functioning vertical Voice AI solutions will be instrumental in helping companies transform customer support and gain customer loyalty. But to a significant faction of CXOs, the understanding of Voice AI technology, its capabilities, and nuances remain obscure. Our earlier articles have tried to elucidate voice technology and how it can prove instrumental in transforming contact centers. In this article, we further that conversation and move on from discussing the Voice AI ‘product’ to the ‘platform’ and why companies looking to automate their contact centers must consider platform capabilities as a factor that will impact their long-term success.
The platform question holds greater gravitas when the top priorities are ROI, time-to-live, control over performance, and market leadership. In this blog, we deep dive into the core questions: what does a Voice AI platform look like, why does having a capable platform matter, and what are its far-reaching implications?
Today, voice technology has advanced sufficiently to deliver intelligent voice conversations. The wait is finally over, and companies can transform their CX with voice-first Augmented Voice Intelligence platforms.
Even coming to the correct conclusion about a Voice AI vendor capabilities is not easy. But let’s assume the product is good, but before signing up, look into the vendor’s platform capability. It is the next big and most important task because, in the long run, the performance will depend mainly on the platform’s capabilities.
Before we go deep into the topic, let us, distinguish a product from a platform.
A product is essentially an application that solves a specific use case.
The Platform is the underlying structure that provides the core building blocks and the infrastructure for the functioning of one or many products.
In other words, a platform is an enabling environment over which many products run. The architecture of a chat-first voice-capable platform will be very different from that of a voice-first platform because the latter is built and optimized for voice, giving it a distinct performance edge. Here is a glimpse of a purpose-built Augmented Voice Intelligence Platform:
The Platform View of a Vertical Voice AI Company
From the above diagram one thing comes out clearly: that for smooth functioning of a Voice AI solution, its various constituent parts must work in perfect synchronicity. Hence, beyond the product, i.e., the voicebot, various other platform features are needed for an ideal Voice AI solution.
Let’s deep dive to answer the questions: why should companies look for platform capabilities in their potential Voice AI vendor?
At the core of this issue is the increasing realization that voice as a medium of customer support will see an irreversible rise in the coming years, led by Voice AI technology. In the long run, any company that wants a firm hold on its market share or leadership must look into the Platform capability of its Voice AI vendor to enhance the probability of sustainable success and competitive advantage. Here are the five core advantages of a robust Voice AI platform:
Long-Term Success: The performance, strength, and sophistication of the Platform, not the product, determines the success of the company in the long run. Choosing the right Platform will help contact centers mitigate the risk of changing the vendor and starting from scratch mid-course.
Replicating Platform Technology is Challenging: Platforms can not be built overnight. Creating a state-of-the-art platform technology takes vision, resources, capability, and time. Over time the benefits multiply due to network effect and learning curve advantages associated with AI models. This initial advantage creates a remarkable difference as years add on.
Leveraging Modularity: A robust platform always aces modularity as it provides diverse and latest technology options for contact centers to create their solution the way they want. It allows for ease and diversity of integrations. This gives the company flexibility in cherrypicking integrations.
Multiplier Effect: In the extended run, contact centers, Voice AI providers, and other application providers benefit from a robust platform as it harnesses the multiplier effect by leveraging the presence of dozens, hundreds, or even thousands of third-party vendors. So, any company using the platform to deploy a voicebot will have not only a multitude of choices, but they will also benefit from the innovation they bring in, as it can be easily incorporated into their voicebot.
Faster and Agile: A strong Voice AI platform will make it easy for companies to create and upgrade their voicebots. Reduction in time-to-go-live and ease of creating, maintaining, and enhancing the voicebot makes it easy to change and maximize its effectiveness.
Here are some of the capabilities of an evolving Voice AI platform:
A Unified View: It should give a unified view of the entire voicebot, from stats on conversational design to integration to ASR.
Voicebot Creation: It must allow companies to create conversational flows and test and deploy them with minimal help from the Voice AI vendor.
Collaboration: It must allow the users to collaborate and comment at any point of voicebot creation.
Enhancements and Testing: Changes in policy, customer preferences, or offers must reflect changes in conversational design. The users must be able to easily do these upgrades and modifications and test them before deployment.
Campaign Management: The effectiveness of the voicebot depends on the capability of the user to run campaigns with complete control. It must allow them to upload data, run campaigns, and modify them real-time.
A Wide Range of Tools and Integrations: Creating a voicebot with autonomy requires giving a choice of a wide range of tools. A robust platform would provide that to its users along with a great variety of integrations.
A Voice AI vendor can have a great product and a short time to market. But if it is missing a great platform, then, in the long run, its clients will lose their competitive advantages. A CXO can indirectly identify the signs of a weak platform. Here are a few major red flags of a weak platform:
Opaque: The creation of the voicebot will be opaque to the contact center.
No Clear Visibility: The elementary constitution of the voicebot and its functioning will have no visibility.
Lack of Agility: For every minor tweak, the user must catch hold of the engineering team to code and execute the change. This is a waste of time, resources, and money.
Operational Friction: Constant and copious communication between the user and the Voice AI vendor will decelerate the pace of implementation of changes.
Slower and Patchy Delivery/Updates: Delays in deployment, updates, and upgrades
Absence of a Marketplace Advantage: A robust platform grows rapidly, and with its growth comes the network effect, i.e. the presence of third-party solutions that can augment performance in many dimensions.
Lack of Control on Quality: Giving absolute control over the creation and deployment of the voicebot helps the users engage more deeply with their voicebot and mold it with their vision. The outcomes are much better and are sustained for a longer period.
Some great ways to identify these telltale signs is to engage in a free-of-cost pilot or to ask relevant questions during detailed demos.
The essential thing is, a Voice AI vendor must possess a great product that can converse intelligently with consumers or callers. Additionally, this product must be facilitated by a robust underlying platform that enhances its capabilities, adding to the overall experience of creating, deploying, and improving the voicebot.
To learn more about Voice AI solution and what it can do for a contact center, book a consultation now: www.skit.ai
CFOs see numbers such as ROI and behold the beauty hidden within them. Today, Voice AI is churning out such convincing stats that every CFO must consider investments in Voice AI in an amicable light.
Business-customer interaction is a two-way street. Interestingly Voice AI solutions are ideal for both Outbound and Inbound calls. Companies are spending millions to reach out to potential customers. Engaging human agents has proved expensive and a significant managerial challenge. Deploying Voice AI helps companies achieve their most coveted goal – cost-efficient scale.
Voice remains the most-preferred channel for customer service. However, around 70% of all customer service requests are non-critical and repetitive, making it challenging for human agents to remain engaged, motivated, and empowered to solve everyday challenges. By taking away the bulk of the calls, Voice AI helps agents create value by solving complex customer problems and enjoying their job. Also, every company covets 24/7 intelligent customer support that is not entirely human agent dependent, and Voice AI is the perfect solution.
Core Challenges Contact Center Face
Contact centers for any organization, small or big, are complex institutions and face some key challenges:
Human Dependent Processes
Optimizing Resource Utilization
Updating Legacy Systems
Delivering Consistent Customer Experience
Sadly, with IVRs, most contact centers have reached a point of saturation, where they have automated, measured, and monitored the operations with no further scope of improvement. Augmented voice intelligence is a technology that opens up new opportunities for creating value and growth.
Automate Non-revenue Generating Transactions with Voice AI
Shockingly, agents spend over 30% of their time on zero-value, non-revenue generating tasks that Voice AI could easily automate. Here are a few examples:
Providing account balances
Removing wrong numbers
Updating phone numbers and addresses
Do not call handling
Bankruptcy data capture
Frequently asked questions
These functions are essential to proper functioning but do not create revenue for the company. They prove costly as they consume expensive agent time and loss of opportunity cost as the same effort could have gone into revenue-generating transactions.
These are just the lowest hanging fruits of Voice AI, and the technology is capable of creating enormous value.
IVRs have reached their zenith and are now causing customer dissatisfaction. Advanced solutions are the need of the hour. Chatbots are advanced and capable, but they suffer from one serious drawback—‘voice’ is the most preferred mode of customer support, not text. Voice AI can be a disruptor, accelerating digital transformation and creating a world of difference in the customer experience.
How do Voicebots help achieve operational excellence and reduce customer acquisition costs (CAC)?
Banks and financial institutions looking for growth and expansion reach out to hundreds of thousands of potential customers. An Intelligent Voice Agent can help a company reduce its customer acquisition cost by executing, with perfection, the various steps of the process such as:
Onboarding, and Documentation
Instead of a human agent calling, following up, and coordinating, which is time-consuming and costly, a voice agent can finish the tasks at a fraction of the cost and expedite the sales cycle. It reduces the customer acquisition cost as a result.
Perfect execution of such efforts at a large scale can make a radical difference for companies. Not only does CAC go down, but the results are also better. A win-win for companies.
Voice AI will always come as a powerful tool when a company wants to run various campaigns at scale. According to the Deloitte report, the global conversational AI market that includes both chatbots and intelligent voice assistants can grow at a 22% CAGR growth from 2020–to-25, reaching a US$14 billion market size. By partnering with the right augmented voice intelligence platform, businesses can optimize contact center OPEX.
How does automation of voice conversations help organizations enhance cost efficiency?
Hitherto, IVRs provided a source of rudimentary automation. But their cognitive inabilities are resulting in customer frustration as no one wants to wait in lines for a human agent and start all over.
Voice automation is helping businesses free their operational bandwidth by answering simple calls, saving human-agent time, and reducing operations costs by 40-60%. Voice AI is thus empowering businesses to address significant challenges by automating repetitive queries, reducing wait time, and providing a delightful customer experience through human-like conversations.
Optimizing and automating processes is key to enhancing cost-efficiency. Here is how Voice AI helps in achieving this goal:
Self-service Optimization: On average, around 70% of calls fall in the non-urgent category. The intelligent voice agent can take most of these calls without engaging the human agent, enhancing a company’s ability to serve customers 24×7 without a human agent.
Scalability: The most neuralgic point of contact centers is team scalability. With the waning and waxing of call volumes, there is an urgent need to scale the support team. It is a nightmare for managers and has significant cost underpinning. By deploying a Voice AI solution, the intelligent voice agent will handle the bulk of the calls, passing only a fraction to the human agents.
Call Routing and Distribution: The primary focus of augmented voice intelligence solutions is to enhance customer experience. Tier 1 customer issues are resolved automatically with a voice AI agent. Voice AI solutions can prioritize requests and route them to the right human agent where needed. Such intelligent call distribution results in better customer satisfaction.
Meeting Compliance: More significant for collections space and banking, but every industry has a set of protocols and regulations to honor. Human agents handling large portfolios are prone to err. Calling a customer on the DND list or calling outside of time limits often results in lawsuits and penalties. A voice agent can easily be trained for any protocols, saving companies time and money.
Voice AI for Sustainable Business Benefits
Augmented Voice Intelligence has displayed tangible improvements in all of the core metrics targeted by support centers, such as First Call Resolution (FCR), Average Handle Time (AHT), Customer Satisfaction (CSAT), Average Speed of Answer (ASA), Queue Length, Abandonment rate, and other Service level metrics.
The other significant advantage of using an AI-enabled voice product is that it gets better with time, and new use cases emerge. Voice will continue to play the cardinal role in customer support, and early adopters will create lasting competitive advantages.
Owing to far-reaching repercussions, compliance management has become an issue of gravitas. It’s a challenge of change. Often, frequent regulatory changes create ambiguity for collection agencies. For instance, Regulation F of the Consumer Financial Protection Bureau (CFPB) came into effect on November 30, 2021, and is the most significant debt collection rulemaking. Any creditor–either the original issuer or a debt buyer–faces challenges in responding to it. And even more tedious is training and retraining agents, reiterative setting up processes and tools to meet regulatory requirements.
When it comes to compliance, the devil is in the details. A human agent under varying stress and performance pressure is prone to make mistakes. But even an innocuous breach of compliance results in hefty fines and penalties. Even without state or local mandates around debt collection practices, federal regulations must be followed to avoid penalties or lawsuits from consumers or enforcers. CFPB levied $1.7 billion in civil penalties and over $14.4 billion in relief for American consumers in the last ten years. Compliance has thus evolved as a significant pain point for debt collections agencies.
We have reached a point where compliance is not just an expense item but also a source of differentiation for collection agencies. Unsurprisingly, most debt collection agencies are looking for tech solutions that can help them be more agile and efficient. Voice AI is one emerging solution with the most disruptive potential and growing use cases.
Too Many Calls, Too Little Communication
One of the prime objectives of compliance is to protect the customer from unfair practices and harassment. CFPB bases much of its enforcement authority on the concept of UDAAP (unfair, deceptive, and abusive acts or practices).
A call at the right time, to the right person, and with the right message can achieve the 3 Cs of debt collection: Cost, Compliance, and Customer Experience. A human agent may struggle to accomplish the triad, making too many or too few calls, but it’s a cakewalk for an intelligent voice agent.
The formal, statutory fees and levies, which are increasingly hefty, represent just the tip of the compliance cost iceberg (around 10%) of total regulatory costs. The broader cost of compliance is much bigger, making it a formidable force.
Here are the common challenges faced by debt collection agencies today:
Ever-Expanding List of Laws: Fair Debt Collection Practices Act (FDCPA), Telephone Consumer Protection Act (TCPA), Federal Fair Credit Reporting Act (FCRA), Payment Card Industry compliance (PCI), and Health Insurance Portability and Accountability Act (HIPAA) are a part of a growing list of regulations, adherence to which is a core driver to the success of debt collection agencies and similar financial institutions.
High Cost of Continual Training and Vigilance Process: A survey of sector firms by the Credit Services Association (CSA) reveals that in staffing terms, the proportion of resources involved (in compliance) seems to trend generally between 15% and 25% of total resources. That is a significant percentage and an opportunity to cut down the cost.
Client Expectation and Audit Requirements: Clients of collections agencies are deeply wary of meeting compliance and exert pressure, even more than regulators, to comply. As per a report by CFPB, collection agencies with large clients face 17 audits in a year. That’s an average of 3 audits every 2 months. The lack of transparency between debt collectors and consumers makes it difficult for agencies to facilitate these audits effectively. It is a formidable challenge to meet such high expectations cost-effectively.
Insufficient Time to Design and Implement Compliance Effectively: A rapid and frequent change in regulation leads to collection agencies running from pillar to post to update their processes. Deploying AI-enabled voice agents can minimize the training and guidance cost.
High Cost of Not Meeting the Compliance Requirements: Failing to meet the compliance requirement has, in the past, led to grave heavy consequences. Encore and Portfolio Recovery Associates, two giants in bad debt collections, were fined $18 million in 2015. They were forced to refund or halt collection of over $160 million in consumer debts. Violating the Do Not Call registry can cost agencies anywhere between $500-$1500 per case, as per TCPA. Moreover, razor-thin margins make the total cost of attorney fees, settlement costs, and the opportunity cost of time too much for agencies to bear.
Voice AI and its Ability to Empower Collection Companies Manage Compliance
More often than not, compliance is a matter of adhering to protocols and procedures. AI-enabled digital voice agents that can religiously follow a given set of instructions prove far superior in adherence to the regulatory framework.
There are numerous instances where small mistakes land collection agencies in trouble. Here are some simple yet powerful examples of how Voice AI can help with compliances:
Honoring Do Not Call Registry and Data Scrubbing: The telephone Consumer Protection Act (TCPA) maintains a register of subscribers who do not want to be called for telemarketing calls and automated dialer calls unless you have consent to do so otherwise. It’s essential to scrub the data before dialing these contacts and check for permission. Solution is to scrub the data against certain database such as Do-not-call registries (external and internal), consumers represented by attorneys and debt settlement companies, deceased consumers, serial litigators, bankrupt consumers, cease-and-desist order consumers. Unlike human agents, who can fumble, digital voice agents perform this with the help of APIs in a fraction of a second.
Calling Within Permissible Hours: FDCPA does not allow collection agencies to contact customers outside of 8:00 a.m. to 9:00 p.m. local time unless the consumer has given explicit consent. Additionally, customers with night jobs may not wish to be contacted during the day. Such personalization in large portfolios prove to be a daunting task for a human agent but an effortless one for a digital voice agent.
Calling Frequency: Regulation F of CFPB limits the frequency of calls under the 7/7/7 rule, restricting the agencies from attempting to establish communication with their consumers for more than 7 times in 7 days. The 7/7/7 rule includes voicemail, unanswered calls, and messages left on the consumer’s phone, and excludes email and text messaging. Furthermore, agencies cannot try to establish contact in the next 7 days after a successful communication. It’s taxing for human agents to consistently follow these rules for the entire customer base while optimizing time and cost at the same time. On the other hand, configuring machines to follow all these rules is possible with a click.
Mini-Miranda is mandatory as per FDCPA in the first communication in any channel. Digital voice agents never fail to comply with such regulatory requirements.
Failure to Discontinue Communication Upon Request: Communicating with consumers in any way (other than litigation) after receiving notice with certain exceptions can lead to lawsuits. Machines follow strict protocols and comply with the request submitted by the consumers.
Communicating with Consumers at Their Place of Employment: It’s illegal to contact the consumer after being advised that this is unacceptable or prohibited by the employer. Human agents under dier conditions fail to honor guidelines. On the other hand, since machines reachout at the right time and frequency have high conversion rate while meeting compliance.
Contacting a consumer represented by an attorney: Agents must not contact the consumers who have chosen not to be contacted by agencies and have signed up attorneys for communication with certain exceptions.
Communicating with a Consumer During Validation Period: Human agents can make a mistake and try to establish communication with the consumer or pursue collection efforts after receiving a request for verification of a debt made within the 30-day validation period. On the other hand, Digital Voice Agents are configured to not engage in any such activities and trigger the automatic collection calls once validation period is over.
Misrepresentation & Threatening Arrest or Legal Action: With variable incentive as a major wage component, it’s quite common for debt collectors to misrepresent as attorney or law enforcement officer. FDCPA prevents such kind of misrepresentation and has punitive enforcement directives. Digital voice agents follow strict protocol and never succumb to such malpractices.
The abusive or Profane Language used during communication related to the debt is prohibited. Digital voice agents never fall back to such practices in order to achieve the results.
Communication with Third Parties: revealing or discussing the nature of debts with third parties (other than the spouse or attorney) is prohibited except to know the location of the debtor without mentioning debt related information. Intelligent Voice Agents can confirm the right party before giving out any information.
Raise a Dispute: Voicebot can also help consumers raise a dispute over a call and tag it in the CRM so that the relevant team can pick it up.
Validation: Upon asking for validation information, the voice bot can immediately send the electronic copy of the validation notice and mark the contact with a relevant tag so that human agents can see the status, and neither the voicebot nor human agents try to communicate to the consumer for the next 30 days.
Raise Tickets: Voicebot can even raise tickets to send the physical copies of the validation notice if explicitly requested by the consumer.
With Distinct Advantages, Voice AI Will Play a Bigger Role in Compliance Management
Apart from numerous other use cases, the utility of Intelligent voice agents in improving the compliance of debt collections agencies is fast emerging and very promising.
Apart from the direct costs of compliance, indirect costs such as fines and penalties take a heavy toll on companies. Today, compliance has become more than an expense but a source of differentiation. Many companies have already begun adopting Voice AI, and its ever-expanding use cases will help them create a distinct competitive advantage.
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said Alexander Grahambell for the first time ever on the telephone.
And the world has never been the same again.
Speech-tech intersection has always been and will be revolutionary. Why? Maybe because speech is hardwired into our DNA and is one of our most natural, intuitive ways of communication.
While text largely connects humans and tech at present, it is very different—and in many ways, premeditated and poker-faced—extension of communication when compared to its primal, spontaneous counterpart – speech. The coming together of our most basic natures and tech, our most advanced pursuits, seems inevitable (and utterly exciting, of course!). Speech tech is key to opening the doors of accessibility for machines, complete with their own unique strengths, to truly be part of functional human ecosystems of interactions.
Understandably, with this kind of scope, Voice AI has made incredible strides in the last decade and continues to grow. True to AI’s brilliance, it is also further fueled by that very growth and is getting better and more human-like everyday, driven by advancements in Machine Learning, Data Science and NLP.
Which brings us to a question though – Is becoming as ‘human’ as possible the end goal for Voice AI? If not, what is? Existential ponderings aside, our exploration of the potential value of Voice AI led us to something that could empower human interactions, make them more meaningful and not replace but augment the human workforce. We call it Augmented Voice Intelligence.
What is Augmented Voice Intelligence?
At Skit, we have always worked with the belief that AI could evolve to seamlessly plug into businesses and augment the work of the human workforce. With the goal being smooth conversations that solve problems, technology has to clear hurdles, not create new ones. It cannot be achieved with a platform that handles every channel out there with the same underlying technology. It cannot be achieved with a solution that’s simply a chatbot with speech engines duct-taped to it. And it cannot be handled as mere voice commands, with no orientation to the nuances of conversational speech. If an enterprise wants to provide the best experience in every voice touchpoint, in every call, they need to invest in a solution that was purpose-built to handle conversations.
Rather than replace humans by doing what they do better, we wanted to intercept cognitively routine tasks and allow humans to focus on more intricate challenges. Our technology stack has also fast evolved to meet this vision, and out of it came the philosophy of Augmented Voice Intelligence. This is the new paradigm of expanding your workforce to combine the power of humans and AI. It is collaborative in nature—a collaborative effort in service of customers. Essentially, it is a purpose-built voice intelligence platform that is not just a point solution, but a system that integrates with businesses to make the most out of every single conversation. It is flexible, scalable and very versatile.
What Does it Mean for CX and Business Transformations?
Businesses today understand that how they deliver to customers is just as important as what they deliver. The focus is more on customer experience over just customer service; journeys over just touchpoints. Conversations are becoming more powerful than ever. Similarly, customers are also viewing their engagement with brands as end-to-end experiences rather than separate interactions.
At Skit, we took it up a notch higher with Augmented Voice Intelligence and have been working on layering just the right solutions for businesses to enhance not just customer experience but overall business experience and employee experience too.
Particularly within customer service, Augmented Voice Intelligence is here to set new standards for user-agent interactions and exponentially widen the scope of value-creation for businesses.
How Does Augmented Voice Intelligence Work?
While Augmented Voice Intelligence opens up endless possibilities across domains, our primary focus has been within contact centres. The biggest pain point call centers have today is creating smooth IVR experiences (the unending frustrations of which need no introductions). Customers, who are likely to be calling with an issue at hand, are frustrated handling the long menus with confusing options. They lack a direct way to reach a human agent.
From an agent’s perspective, IVR often doesn’t route the right kind of calls to the right agent. When the agent receives the call, there is a lack of context and the customer has to repeat themselves all over again. The more complex the calls become, the bigger impact it has on the business as well. Instead of maximizing on customer conversations, businesses end up struggling to resolve basic issues.
The Skit Solution : Augment human workforce with digital intelligence
Towards our vision of building tech that entwines human interactions, we designed and built a Digital Voice Agent that resolves tier 1 customer service issues, and automates cognitively routine work while human agents can focus on more complex customer problems.
The Digital Voice Agent works in a custom-built environment of conversation design that is modeled on the nuances of human interactions, vertical, domain-specific Voice AI, and integrated business logic that lends direction. This enables contact centres to provide a seamless experience to customers and employees alike while also taking care of scaling and efficiency issues and optimizing costs.
Machines are not superhuman, neither are humans inferior to machines. Rather than one replacing the other, the future will be defined by human-AI partnerships. With Augmented Voice Intelligence, that path has opened up to a very promising start for us here at Skit.
So now, what else does Augmented Voice Intelligence have to offer? How can we make it better? What other businesses can it impact? Well, we are exploring every single day as we dream of the perfect friendship between humans and machines.
Systems that can handle mundane tasks have existed for several years. But in the recent past, we have seen an uptick in conversational assistants such as Siri, Alexa, Google Home, and Samsung Bixby. These systems handle human conversations and respond in a human-like manner. In fact, it has become an internal part of our daily lives.
The speech and voice recognition market is expected to grow from USD 8.3 billion in 2021 to USD 22.0 billion by 2026; it is expected to grow at a CAGR of 21.6 % during the forecast period.
When it comes to CX, the always-on customers expect more when it comes to customer service. They need personalized and faster resolutions. They can no longer wait for minutes together to connect with an agent or navigate through complex IVR menus.
Solutions like voice bots are disrupting customer service as they promise the same level of customer experience as a human agent. Advanced AI-powered Digital Voice Agents can help CX leaders elevate their customer experience while reducing costs, thereby solving two of the biggest challenges faced by them on a daily basis. The solution is scalable and more efficient than other channels like email and IVR.
What is a Digital Voice Agent?
A Digital Voice Agent is a conversational robot (commonly known as a voice bot), that has the ability to interact with a user and take a certain set of actions in order to meet an end goal. It is very similar to voice assistants like Apple Siri, Google Assistant, Alexa we use on a daily basis.
But what’s the difference?
Voice assistants are designed to handle one or two turns of the conversation to meet generic day-to-day goals.
Example of a single turn conversation
Digital Voice Agents, on the other hand, are designed to solve specific problems which require much more than two turns of conversation, just the way we humans solve queries by first asking multiple questions to understand the context and all the required information to solve any problem.
For example, a lost credit card is blocked by asking a series of standard questions: the first couple of questions to verify the caller, and the next set of questions to confirm which credit card to be blocked and then followed by an action where the customer is sent a new credit card. Typically, this is a 6-7 turn conversation that generic voice assistants are not designed to handle. Specialized voice bots are required to be trained to handle such tasks.
So, How does Skit’s Digital Voice Agent work?
Fundamentally, there are at least four components (engines) to any voice bot:
ASR (Automatic Speech Recognition): This converts the voice into text transcription. This is alternatively called Speech-to-text or STT Engine.
SLU (Spoken Language Understanding): This is the brain of the voice bot. It extracts intents and entities (data points) from the text sentence produced by ASR and then comes up with the best possible action. That action can be performed in terms of voice reply or sending a document or a text message, or transferring the call or raising a ticket etc.
TTS (Text to Speech): The block that translates the text into voice for generating a reply.
Dialogue Manager (Orchestrator): The block that manages the flow of data among the above three blocks and the flow of the conversation.
All these processes happen in real-time and within milliseconds. This is only one turn of the conversation and this process gets repeated for subsequent turns.
All these processes are performed in the cloud after the voice packets are received from a user. So it doesn’t really matter which device the caller is using, whether it’s a smartphone or a feature phone or a wired telephone. Skit’s Digital Voice Agents leverage all these layers to seamlessly plug into contact centers and augment the work of human agents.
How are Digital Voice Agents different from Chatbots?
Technically, an AI-powered voice bot has two extra engines that a chatbot doesn’t need. Since chatbots do not deal with voice, the two engines related to voice (ASR and TTS) are not required. The text input is fed directly to NLU and the intents and entities are extracted and the response is synthesized in text format and relayed back to the user.
Furthermore, voice queries on call bring with it certain challenges like noisy backgrounds, different accents and dialects of speaking the same language, language disfluencies and unique way of adding filler words and pauses, barge-in by a person while the other one is speaking; all of which directly impact accuracy.
And for the same reason, voice bots are much more difficult to build. Everything has to be real-time within milliseconds and there is little to no room for error, else communication experience is hurt.
What sets voice bots apart is that they’re faster. Voice is the quickest and most natural form of human communication—faster than typing or navigating drop-down menus with a mouse. It continues to be one of the most sought-after by end customers seeking support.
What are the common applications of Digital Voice Agents and how does it add value?
The key to improving customer service is not just automating cognitively routine communications, but augmenting human agents and freeing up their time. This creates great self-service options, increases customer satisfaction and makes your employees more productive.
At a broad level, a Digital Voice Agent can be used whenever businesses want to communicate with their customers en-masse. However, let’s make it simple for you. There are two types of business communications:
This is when a customer tries to call a business to get their queries resolved. For example, to register a complaint, to activate or deactivate a service etc.
Companies have contact centres to resolve the customer queries where human agents are trained to resolve the customer complaints coming from various channels such as calls, emails, social media etc.
How does a Digital Voice Agent add value here?
Automate mundane support queries: It can automate the simple repetitive queries end-to-end such as knowing the account balance in case of banking, the status of the order in case of e-commerce etc. Your human agents can now move to solve more complex queries. So your average service levels will drastically improve as your customers will be served without any waiting time.
Reduce average handling time: For more complex queries, Digital Voice Agents help reduce the average handling time of the human agent by collecting basic tasks, for example, caller verification, collecting basic information such as order number etc that is mandatory for the human agent to solve the query. After performing the preliminary checks the call can be transferred to the human agent with the context of the query and data collected so far.
This is when a business tries to reach out to customers for a variety of reasons such as lead qualification calling, welcome calling, reminder calls, renewal calls.
How does a Digital Voice Agent add value here?
Lead Qualification: Since the Digital Voice Agent is a scalable machine, it can reach out to thousands of prospects concurrently in real-time as soon as the prospect has shown interest in the product or service to gauge interest and thereafter transfer the call to live agent in real-time to convert the customer. In the case of semi-qualified leads, it can mark those and send them to nurturing workflows. Your human agents are only given the more qualified leads to work on and hence human agent productivity shoots multifold.
Reminder calling: The Digital Voice Agent can place the automated calls to your existing customers based on pre-defined triggers such as on the nth day of the month or if the payment is not received by this day of the month etc. It eliminates the need for human agents for such simple tasks. It can take a propensity to pay or renew, the date by which it will be done, objection & FAQ handling, the reason for non-payment etc.
” About 75% of companies plan to invest in automation technologies such as AI and process automation in the next few years. AI, chatbots, voice bots and automated self-service technologies free up call centre employees from routine tier-1 support requests and repetitive tasks, so they can focus on more complex issues.” (Source: Deloitte)
Broadly, various kinds of voice bots are among the most popular automation solutions, and are quickly becoming a must-have for any contact centre. Skit’s Digital Voice Agents take it up a notch by being able to forge seamless human-AI partnerships for contact center modernization and optimization.
What are Digital Voice Agents good at compared to humans?
On-demand Scalability: Humans cannot be replicated on-demand. When we want to add a number of agents in the contact center, it takes its own sweet time of hiring, onboarding, and training. And it has to be repeated for every single agent we hire.
Digital Voice Agents can be scaled up and down as and when required with marginal cost.
Economic & Reliable: Employing human resources for repetitive mundane tasks is costlier. There would be a high cost of hiring, training, retraining, associated with a higher churn rate. And that has to be done for every human resource we employ. Bots on the other hand need to be built and trained only once and the benefit of incremental learning and retraining is huge and available across the board.
We all know that machines are exceptional at performing repetitive tasks with high efficiency and high reliability. If a Digital Voice Agent is asked by a customer not to call during office hours or to call at specific times in future, it can do so without fail. Humans are not so good at it.
Available 24×7: Machines don’t get tired or complain either. Sad but true that they don’t have a family to go to or need time to sleep. So you can be available to your customers round the clock.
Looking up for information in a knowledge base: Digital Voice Agents can easily fetch information from a knowledge base for answering a wide range of support queries.
Consistent learning and training at scale: Apart from using Artificial Intelligence for answering questions, Skit’s Digital Voice Agents also leverage different machine learning models and past conversations to automatically improve the quality of answers.
In this age of information, the most important asset that enterprises rely on is data. With rapid improvements in data analysis and visualization techniques, it has become the norm for enterprises to leverage the power of data for streamlining and improving business processes.
However, what we don’t often realize is that contact centers can prove to be one of the most important sources of data for enterprises. The thousands of hours of call recordings are a storehouse of information for consumer attitudes, complaints, and feedback that enterprises can use to gain valuable insights.
But how to go about it? The answer lies in the burgeoning field of speech analytics.
Gartner says “Audio mining/speech analytics embrace keyword, phonetic or transcription technologies to extract insights from prerecorded voice streams. This insight can then be used to classify calls, trigger alerts/workflows, and drive operational and employee performance across the enterprise.”
Intelligent solutions like Skit’s Digital Voice Agent can not only handle customer service calls but perform advanced speech analytics in the very near future.
Using advanced Spoken Language Understanding (SLU) algorithms, the recorded speech in contact centers can be analyzed to extract crucial insights that can help enterprises streamline their performance.
Read on to know more about the three ways in which speech analytics with SLU can help your enterprise.
Provide personalized services
With a continuous focus on innovation, Skit.ai has added the revolutionary “idiolect” layer to existing cutting-edge capabilities. In the world of linguistics, “idiolect” simply means the unique speech style of a group of people that differentiates them from other groups.
The state-of-the-art technology in the idiolect layer will enable VASR to perform advanced speech recognition and analytics to uncover more information about the speaker such as gender, age, language, and accent- and build a unique speaker profile.
Moreover, the application of certain SLU algorithms can help can further insight into the customer’s attitude and state of mind:
Sentiment Analysis: These algorithms can detect whether the customer’s attitude is positive, negative, or neutral during the call.
Emotion Detection: Such algorithms can help determine the emotions of a customer and their state of mind during the call.
With the combined help of unique customer profiles and SLU-enabled analysis of customer’s speech, it becomes easier to deliver personalized services to the customer- depending on their characteristics and current state of mind.
Research by Epsilon has indicated that 80% of consumers are more likely to make a purchase from a brand that provides personalized experiences.
With hyper-personalized customer service experiences, you can keep your customers satisfied and reduce customer retention costs in the future.
Gather consumer insights
With multiple agents handling multiple customers in a day, it is not possible for agents to always correctly determine what consumers want or expect. Moreover, customers themselves might often be confused as to what they expect from a brand and what improvements they want in the service or product they receive. As Steve Jobs had once famously quoted:
“It’s not the customer’s job to know what they want !”
However, it is crucial for any enterprise to determine the needs of their consumers to provide better services. With COVID changing consumer behavior and expectations, analyzing consumer insights can prove crucial to the path ahead.
“Businesses need to understand how this new world affects all of their touchpoints with the customer if they are to actively reinvent their own future and not be at the mercy of external events.” (PwC)
The advancements in research in Spoken Language Understanding have made it possible to use different techniques to derive important information from analyzing customer service calls. Some algorithms that can be used to derive such insights are:
Topic Modeling: This is a technique in SLU with which customer calls can be analyzed to create a list of natural topics that frequently occur in service calls and can help companies realize what services/products frequently need troubleshooting and have scope for improvement.
Text Summarization: The duration of calls might often be extremely long. With summarization algorithms, it can become easier to create summaries of calls that can be easily read through/analyzed for consumer insights.
Aspect Mining: It refers to a class of SLU algorithms that discovers different aspects or features in data, and along with sentiment analysis, can be used to determine the different sentiments associated with those features. For example, in a customer call, the customer may express a positive sentiment when it comes to pricing but a negative opinion on customer service quality.
With easy access to consumer insights with SLU, enterprises can easily leverage them to make crucial decisions on how to improve business processes and products in a way that makes their customers happier.
Improve automated quality assurance
By harnessing the power of SLU, it not only becomes possible for Voice AI platforms to provide quality service but also to ensure that call quality is maintained at all times in contact centers- be it a service agent or a virtual agent.
Traditional QA teams depend on the right data to correctly analyze service quality and with contact centers handling an immense amount of calls, the process is bound to become time-consuming and even inefficient.
The use of SLU and speech analytics algorithms can provide structured insights by analyzing calls, which makes it easier for QA teams to act on those insights to streamline contact center processes for increased KPI metrics.
As brands continue to explore innovative ways of connecting with customers, they need to plug in AI technologies into their business processes to glean consumer insights that can be the driver to elevating customer experiences
Indeed, the future is undoubtedly bright for Voice AI platforms that can truly harness the power of Spoken Language Understanding. Even as we talk about these improvements, researchers are working to improve SLU and develop newer techniques that can have an even greater impact on Voice AI systems.
Voice-first platforms are here to stay and without doubt, they will play an important role in accelerating the adoption of technology across personal and commercial spheres. Users are growing increasingly comfortable with voice-first platforms as they are much more hassle free when compared to traditional written modes of communication, and this is reflected in consumer behaviour across industries.
Data from OC&C Strategy Consultants shows that voice-shopping is expected to jump to $40 billion by 2022 from $2 billion in 2018, suggesting that voice-first platforms might be the next disruptive force in the retail industry.
Voice-activated virtual assistants like Siri or Cortana have become an integral part of our daily lives and enterprises have started implementing Voice AI platforms for enhancing business processes.
There have been several recent breakthroughs in the field of Spoken Language Understanding (SLU) and this has enabled the rise of SLU-enabled Voice AI platforms that are capable of holding seamless human-like conversations.
One of the industry sectors that illustrates a supremely successful use case for intelligent virtual assistants is the field of customer service.
“…businesses across industries are also aware of this on-going shift in the technology and customer behavior. In fact, many have already begun their voice journey and are transforming the way how customers interact with their brand.” (Trantor Inc)
With an increasing base of digital consumers worldwide, contact centers have been reeling under the pressure of ensuring good customer service while efficiently handling the immense call load that contact centers face. This has led to the adoption of Voice AI platforms for contact center automation- and advances in SLU have allowed such voice assistants to turn into quality customer service agents.
Here is how SLU-enabled voice AI platforms deliver superior customer experiences:
Increased Ease of Usage
Since the beginning of human history, voice has been the primary mode of communication for people and has been around for much longer than written communication systems. It is no surprise that humans tend to be “voice-activated” naturally and find it much easier to interact with technology through voice commands.
Now, with rapid progress in AI-enabled speech-to-text and text-to-speech services, seamless voice-driven customer experience is a reality. As the ecosystem around voice enabled technology matures, customers are starting to rely more on voice. (PwC)
SLU has helped the development of such voice-first platforms, allowing your customers to easily connect with virtual assistant platforms in your contact center.
Such platforms do not require your customers to trudge through the interminable IVR options, enabling them to easily express their concerns or queries in simple spoken language statements, leaving your customers happy about their experience with your brand.
Understanding the Customer
Spoken Language Understanding has taken voice AI to a new level with the ability to simulate a near-human understanding of speech by such platforms. SLU-enabled platforms don’t merely react to a fixed set of commands but rather use various techniques and algorithms to arrive at the true purpose of the customer in making the call.
Intent Recognition– No matter how customers frame their queries and statements, intent recognition algorithms are able to decipher the customer’s intent at one go using keywords or action words, without requiring multiple clarification from customers.
Named Entity Recognition– These algorithms extract important information from the customer’s speech to recognize important names, places or times that the customer talks about.
All these SLU techniques have enabled voicebots to easily achieve human-like “understanding” capability that allows them to easily converse with the customer, eliminating the machine-like qualities from a conversation.
Innovation in voice technology is reshaping consumer behaviour and brands need to pursue creative approaches to accelerate the adoption of Voice AI to align with customer expectations and maintain a competitive edge
Quick Query Resolution
In a world where each second matters, time is of the essence – for you and your customers. If they spend precious time on hold with your contact center while agents are busy, it can only be expected that customers will get frustrated with their experience and shift their loyalties to other competitors.
SLU enables voice AI platforms, which act as virtual agents, to easily access the required information from databases and respond quickly to customer queries. Intelligent solutions like Skit’s Digital Voice Agent have been shown to result in a 50% reduction in average handling time in contact centers.
A Zendesk Research Survey discovered that 69% of respondents associated good customer service experience with a quick resolution of their issue.
This will result in improved customer satisfaction and increased customer retention rates, translating into increased revenues and goodwill for your enterprise.
Consistent Service Experiences
Every time customers engage with your brand, they develop an opinion about the brand. To ensure that the impression your brand gives to consumers is excellent, consistency is key. No matter when and where your customers approach the contact center, their service experience needs to be consistent.
According to Forbes, 71% customers desire a consistent experience across any channel, but only 29% receive it. About 76% receive conflicting answers to the same questions from different agents which leads to loss of customer confidence.
Advances in SLU have enabled voice AI platforms to maintain a uniform dialog flow across the board in all customer interactions. From a standard welcome greeting to the last goodbye, everything progresses in a pre-planned flow which gives customers a sense of stability and familiarity. Every time they get in touch with your contact center, they know exactly what to do and how to do it.
Customers will come to trust your brand as the reliable option and will increasingly engage with your enterprise and not your less-consistent competitors.
There are, thus, several ways in which SLU has enabled voice bots to deliver superior customer experiences that keep your customers pleased and induce loyalty in them.
Keeping customers happy not only helps enterprises increase customer retention, but also helps reduce customer acquisition costs by increased word of mouth marketing and recommendations from loyal customers.