Many debt collection companies are evaluating emerging technologies and looking into digital transformation. You can’t blame them: due to a faltering economy, rising costs, and high agent attrition, new processes and solutions are needed.
As a result, within the next three years, one in every ten interactions with call center agents will be voice bots driven, according to the new Gartner report. These findings are directly attributable to the spectacular rise to the advances in conversational artificial intelligence (AI), along with the mounting challenges we detailed above.
The report also estimates that by 2026, Conversational AI could save about $80 billion in labor costs! That is a significant number, indicative of the merits that early adopters will have in terms of cost, CX, and expansion of top and bottom lines. But, starting early is key to competitive advantage.
It is an open secret that high human agent churn is due to the fact that most calls are low-value and tediously repetitive. By handling these calls, Conversational AI will make the agents’ jobs more exciting and fulfilling, allowing them to focus on high-value and complex calls.
Globally, there are approximately 17 million contact center agents, and their cost makes up 95% of contact center costs. By intelligent call automation led by voice-intelligent technology, Voice AI, a big part of unproductive calls can be taken over by Digital Voice Agents, yielding high cost and CX advantages.
The Direct Cost and Efficiency Benefits of Voice AI for Debt Collection Agencies:
The most significant takeaway for the debt collection agency is that the benefits of Voice AI implementation are tangible and quickly realizable. But before we go into stats, here is a simple explanation of what essentially happens in a debt collection agency when they deploy a voicebot.
Voicebot Functioning
A voicebot is a conversational Voice AI application that can understand what the customer is saying as it is trained for a specific customer problem. It can strike a meaningful conversation with the customer. This happens because the entire conversation design has been done keeping in mind all the possible difficulties a customer can encounter.
So for every customer query, the voicebot has a ready answer as it pulls out relevant information from the client system and informs the customer, cutting the duration of the conversation remarkably.
Digital Voice Agents (DVA) Vs. IVRs: It is worth mentioning here that DVAs are remarkably different from IVRs; in fact, there is no comparison between the two. DVAs are at the cutting edge of the technological spectrum, while IVRs are legacy technology.
IVR can not converse. It is an unintelligent technology that runs a tedious exchange of inputs and outputs. For something as sensitive as debt collections, it is remarkably unsuitable.
Digital Voice Agent is AI-powered, built on Spoken Language Understanding (SLU) and context-rich conversational designs.
For a debt collections company, the two main categories of calls are Inbound and Outbound. Here is the process of value creation:
Inbound Calls: Many agencies cannot process a significant portion of customer calls. From them, a tiny fraction of customers have called to pay and perhaps need guidance.
Answering Non-revenue Generating Calls
The data from various sources is precise: A majority of calls are so simple that answering them by a human agent does not add any value to the company.
We’ve discussed the value of adopting a Digital Voice Agent for call automation. If you want to learn more, take a look at our Resources page, in which we regularly explore current topics related to the ARM industry.
Understanding the Top and Bottom Line Impact of a Voice AI Solution on a Debt Collection Company
The Final Word
Voice AI has proved its capability in bringing about a transformation of contact centers either with a small team or a big one. As its adoption increases, it will become a technology that can deliver sustainable cost advantages as well as a competitive advantage.
Refer to our Voice AI page for more information about its transformative potential.
What’s common among interactive voice response (IVR) systems, ATMs, knowledge base, mobile applications, virtual assistants or chatbots? They are all self-service options that can help dispense answers and resolve queries at lightning speed! Self-service or self-help tools and options make for an empowered customer support team and a loyal customer base.
Self-service equals simplified customer journeys!
In a mobile-driven digital economy, a brand’s relevance and value is measured in terms of the speed, convenience and the level of autonomy offered to their customers. Digital self-service is the central objective of today’s automated customer support, but tailored for better CX and performance. Since the COVID-19 pandemic, the usage of digitized self-service by customers across demographics accelerated with sudden digital transformation (DX). With newer entrants into the market— more digital native brands, always-on, smartphone users and Gen Z customers, numerous possibilities await businesses using digital self-service in their customer support. As per the recent OnePoll study involving over 10,000 respondents from 11 countries to explore humanity’s shifting relationship with digital tech and experiences:
Nearly 58% percent of participants said they will continue their digital brand interactions more than their pre-pandemic levels.
Most study respondents felt that the digital experience was fast and convenient, making it better or on par with the real-world, face-to-face customer service interactions.
Almost 66% reportedly had a ‘good’ or ‘excellent’ experience using online customer service options.
Diving a little deeper, the research summed up the exact reasons for positive reactions:
Instant issue/query resolution (48%).
Convenience (46%).
Speed (45%).
These findings form the crux of self-service. In this blog we will begin our exploration on why self-service tools are truly adept in capturing customers’ interest, and meeting productivity and performance goals of brands’ customer support.
Psychology behind Self-service
Self-service is not the same as automation. Sure, digital self-service gives automated responses to repetitive queries in blazing speed. It is not only about allowing customers to resolve things on their own but also empowering them to address them faster. The overall value of the self-service strategy is measured in terms of its impact on CX. The faster, more convenient and more cutting-edge the self-service options, the better would be the CX scores. Moreover, the intuitiveness and simplicity of self-service helps reduce customer effort while solving problems on their own. This lowers the customer effort score (CES), another key metric for frictionless CX!
An intuitive, anytime self-service strategy across the platforms or channels also helps evade a laundry list of options for customer service-related interactions and unnecessary contact with human agents. This is integral for curbing additional contact center operations costs and allocating resources and human efforts in areas that build proactive and customer-centric impressions. No wonder, in the U.S. 88% of customers prefer self-service for dealing with their everyday problems. The number is equal to the global average of customers that expect brands and businesses to include a self-service support portal.
The Most Common Types of Self-service Options
Now, let’s have a look at this run-down of the widely adopted self-service support options.
Knowledge Base and FAQs: Internet-savvy customers leverage business/brands’ digital presence to find their way from the search engine platform to access information in a variety of forms (videos, landing pages, texts, infographics, illustrations, audiobooks, guides, and icons) for problem-solving. Dedicated FAQ pages that are brief and true-to-context is another form of self-service option that guides customers through specific customer service-related scenarios on the company’s website.
Integrated Contact Centers: Customer data is created across multiple channels. Integrated contact centers bind sales, contact center agents or other representatives with unified data sharing, collaboration and improved access to customer data across customer journeys and omni-channels for customer service. The intention is to boost CX and reduce the need to repeat information as customers navigate different customer service departments to solve issues on their own.
Interactive Voice Response (IVR) Systems: IVRs have existed for more than five decades. They are customer-facing phone systems that offer (inbound and outbound) support with pre-recorded messages and self-service menu responses to customers’ text inputs. They are cost-effective, scalable, and automated alternatives to human agents.
Chatbots: Chatbots use text-based or voice interfaces that are integrated to websites or mobile apps’ chat/message window to interact with customers. They are AI-driven and created based on the planned interaction flow chart to respond to customers in a matter of seconds.
Mobile Applications: Mobile apps with intuitive and interactive UX and UI give information to customers via dashboards, push notifications and updates in their moments of need, on their mobile devices.
Voice AI: A Quantum Leap in Self-service
The common forms of self-service options are the building blocks of the new age customer support. But there’s always the expectation for solutions that drive up the cost savings and operational efficiency while also helping brands’ contact centers meet their CX objectives. Imagine, if brands were able to achieve that while also offering self-service support that was voice-led, personalized, empathetic and proactively responds in real-time! For today’s automation and customer-first era, Skit.ai’s purpose-built Voice AI platform redefines self-service for optimizing customer support not only for better CX but for enhanced employee and business experience.
Built to enable conversations that are modeled on human interactions for prompt query resolution and personalized caller experiences, Voice AI is a next level of innovation in self-service. It delivers the best of voice experiences for brands through their contact centers that go beyond the capabilities of generic voice bots.
Voice AI is built to be domain-specific unlike generic voice-first platforms by Amazon and Google. The spoken language understanding (SLU) layer of Voice AI helps capture short, conversational utterances and is capable of deciphering semantic details that helps identify the right intent.
Voice conversations are the most natural forms of human communication and still remain one of the most sought after brand-customer interactions. Live voice conversations are critical to delivering high-quality customer experience. Customers interacting with self service options such as IVRS and messaging chatbots think before inputting a text command and hit send. Voice AI is a technology built to understand the intricacies of spoken language and not limited to text. It can quickly grasp customers’ voice interactions and filter through pauses and repetitions.
The Digital Voice Agents plug into the contact centers for automating cognitively routine work and independently resolving tier 1 customer problems. This would aid the human workforce to focus on more complex customer queries and contact centers to adopt intelligent human-machine collaboration. This way customers can stay in control and brands also get to pick the best self-service strategy for delightful CX.
Now, let’s dig into various features of Voice AI that makes it a better alternative to conventional self-service support:
Natural human-like Interaction: Digital voice agents that can mimic human-like conversations and comprehend interactions at a semantic level. It doesn’t feel like interacting with IVRs. It feels like holding conversations with the brands’ contact center agent.
Problem Recognition: Customers navigating through the self-service option can feel like they are lost in translation because of the complex IVR loops, limited menus or options that do not cater to their requirements. Sometimes chatbots are built with an ASR layer on top of NLP. They are great for transcriptions, not conversations. They deliver the same experience as going through a rigid IVR system. Digital Voice Agents can understand the right sentiment and nuances of human conversations, allowing the customer support to accurately identify and solve customers’ problems.
Always-on, Human Agent-free experience: One of the core value propositions of implementing a digital voice agent is its ability to function 24/7 for the ‘always-on’ customers without the dependency on human agents. This translates to cost savings by automating high-volume, zero-value and repetitive customer queries.
Quick Resolution: Self-service platforms optimized by powerful AI-capabilities and strong data sets based on customers data can be used for competitive advantage. It allows fast resolution, impacting customer satisfaction and CX.
Diversify Customer Service at a Lesser Cost: When more problems that are unique in nature can be handled by voice agents and automated, it helps brands’ customer service be a one-stop-shop for addressing customer queries at a fraction of a cost.
Smarter Human Resource Allocation: Self service options in contact centers make it easier to address trivial problems or anything that is repetitive in nature using Digital Voice Agents. Human agents can be allocated only for complex customer service issues, allowing for better resource planning and empowered customer support teams.
Make Self-service More human: Digital voice agents add a human touch to the overall experience without involving a human. The datasets are designed for SLU and built for domain-specific words which makes it easier to hold contextual conversation with the customers even via self-service options.
Hyper-personalize Customer Support: Brands can guarantee hyper personalization leveraging Voice AI’s extensive language support. It helps break spoken language barriers for enhanced query resolution and overall caller experience.
If you still have questions, refer to the infographic below for a brief comparative analysis between Voice AI and three most popular self-service tools.
Features
Voice AI
IVR Systems
Chatbots
Mobile Apps
Primarily Built for Voice Input
Yes
No
No
No
Analytics and insights Capabilities
Very High
Low
High
Low
Elasticity of Customer Service
High
Low
Moderate
Low
Hyper-personalized and Contextual dialog Capability
High
Low
High
High
Handling time
Lowest
Very High
Moderate
Low
Quick Query Resolution
Quickest
Slowest
Quick
Quick
Our Titbits
Envisioning customer service in the age of self-service is all about setting the right priorities. With the hope of keeping up with the trends for relevancy, brands and businesses need not steer away from their cost, profits and resource management goals. That’s the core objective of reimagining customer self-service using Voice AI. Brands across industries can supercharge their CX with befitting self-service strategies to be more result-oriented and insight-driven to add a competitive edge.
Our reflections for the future—customers never settle and self-service alone is not enough! Therefore, we believe Voice AI is the most robust and well-rounded technology to improve customer support capabilities that go beyond conventional contact centers, adding a desired level of autonomy and self-sufficiency in customer service.
Refer to our Voice AI page for more information on actively engaging with your customers and unlocking the power of self-service. Book a demo with one of our experts–www.skit.wpenginepowered.com
For the second article of our “Meet the Team” series, we sat down with Joseph DeMarzio, one of our Customer Success Managers for the U.S. market. Joe lives in Staten Island, New York, and joined Skit.ai earlier in 2022.
Hi, Joe. Tell me a little about your professional background.
I’ve been working with start-up companies for the last seven years. I’ve specifically worked in the hospitality and travel industry, introducing a suite of tech products tailored to the hotel industry. Within the start-ups I’ve worked with, I’ve taken on many roles, including sales, customer success, technical integration, partnership development, building internal teams, and more.
What is your role at Skit.ai?
I maintain our relationships with our U.S. customers. I manage the onboarding process, product deployment, pilot testing, and KPI achievement. The overall goal of my role is to convert the pilots into long-term customers for Skit.ai; this is done by building a strong relationship. Additionally, I also work on partnership development. This includes managing discussions and integrations with third-party vendors — who help us enhance our product — and third-party sales organizations — who can help us by selling our product on our behalf.
What do you enjoy the most about working for a start-up company?
A CEO once told me that working at a start-up is like flying a plane while building it. That is very much true, as every day is a new challenge, and days are filled with both wins and losses. With that being said, the idea that my work contributes to the long-term success of the company is unrivaled. I love the fact that my input is heard and helps shape the product we are building. Start-ups also allow you to craft the company culture from the ground up. Start-ups grow at a rapid pace and thus it’s key to hire the right people also from the perspective of company culture.
What does a day in the life of a customer success manager look like?
A customer success manager’s responsibility is to bridge the gap between a client and the internal departments within the organization. A typical day starts with going through inquiries from our delivery team in terms of what is needed from the client, as we are responsible for both client onboarding and the life cycle with Skit.ai. Our job throughout the day is to understand and manage our clients’ expectations. We are responsible for keeping the client informed throughout the technical onboarding of the Digital Voice Agent. A customer success manager also focuses on the overall experience of the client through onboarding, testing, and ultimately live periods. We want the client to have financial success with our product as well as enjoy the experience of working with us along the way.
What do you think are the key factors that lead to a successful partnership with a customer?
Communication, transparency, and availability.
Frequent communication is healthy in normal relationships as well as business relationships. There should be an open flow of communication throughout the entire life cycle.
Transparency is key as you must always be honest with a client. If you are honest they will work with you instead of you feeling like you work for them.
Availability in the sense that the client knows they have someone they can always talk to. The experience of working with a “real” person should never be underestimated.
Tell me a fun fact about yourself.
Just one? I have an identical twin brother, my family owns a pizzeria restaurant, I have a JD (law) degree from Touro University, and I am an avid sports fan (specifically the Jets, Nets, Yankees, and Rangers).
Do you want to learn more about Voice AI? Check out our blog.
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.wpenginepowered.com
