When we talk about Voice AI for customer service, we immediately think about the benefits of the technology for the customer experience. Having an intelligent Digital Voice Agent address customer queries results in no wait time and a quick resolution to the most common issues.
Augmented Voice Intelligence (AVI), however, also deeply transforms the human agent’s experience at the contact center. This is what we can refer to as employee experience.
As a Senior Solutions Product Manager at Skit.ai, I’ve visited several large contact centers both before and after the implementation of our AVI solution. I’ve had the opportunity to chat with many agents and hear their perspectives on their work and feedback on our technology.
In this article, I’ll explore how AVI affects the employee experience and how this ultimately impacts the overall business performance.
Contact Center Agents Before AVI
Contact center agents have a very monotonous job, as they often have to perform the same tasks and address very similar customer queries countless times per day. “Please verify your name,” “What’s your order number?” and “This is your current balance” are just some examples of sentences that contact center agents have said thousands of times.
This type of job tends to be quite tedious for human agents, since they are not required to think creatively and critically to solve the customer queries and they’re mostly just reading from a script.
Additionally, there is not much room for growth for agents. Because the tasks they are asked to perform are so repetitive, they’re likely to change jobs as soon as the opportunity arises. The current data suggests that contact centers have at least a 35-40% attrition rate.
In summary, all of these factors often contribute to an understimulating environment, lower employee morale, and a high attrition rate.
Contact Center Agents After AVI Implementation
Enter AVI — Augmented Voice Intelligence.
The concept of Augmented Voice Intelligence is based on the belief that the combined power of humans and AI can lead to a much more effective, smoother workflow for contact centers, improving both customer and employee satisfaction. AVI is collaborative in nature: the Voice AI technology performs routine tasks while human agents can focus on more complex queries.
So what’s the experience of a contact center agent once AVI is implemented?
First and foremost, the vast majority of queries are addressed by the Digital Voice Agent, which only reroutes the more complex queries to the human agents at the contact center. Once a customer is routed to a human agent, the Voice AI interface provides the agent with the contextual information on the customer and their case, making the conversation flow smoother and easier for both parties.
Because AVI implies a collaborative effort between the agents and the technology, it’s important to familiarize the employees of the contact center with the Augmented Voice Intelligence Platform upon its implementation. In my experience, agents tend to get quite excited as they learn about how the technology works and the way it affects their day-to-day workflows.
It’s always fun to see the excitement in the eyes of the agents—they usually want to talk to me, learn more, and ask for more in-depth training sessions.
How AVI Empowers Contact Center Agents to Get Involved and Suggest Improvements
Not only Voice AI improves the agents’ experience at the contact center. Because the agents are so familiar with most use case scenarios, they often have valuable ideas on how to improve the Digital Voice Agent.
During my visits to contact centers, I’ve often encountered agents who asked me: “Can you please involve me in the machine learning process?” They want to pitch ideas and contribute to the features of the Digital Voice Agent.
Other times, the agents asked me for insights coming from the Digital Voice Agent: “What are the main keywords customers are using? What are the patterns the AI has found so far?”
In summary, this is how the employee experience is enhanced by Voice AI:
Agents are no longer confined to the same, repetitive tasks all day
Agents get to be more productive, feeling more helpful and motivated
Agents can get involved in the machine learning process
At Skit.ai, we’ve been big proponents of the idea that the combination of customer experience and employee experience shapes the broader business experience:
If you want to learn more about Skit.ai’s Augmented Voice Intelligence platform and speak to one of our experts, you can book a demo.
The world and Indian economic growth find themselves precariously placed in 2022, with bleak economic data raising concerns. People are reeling under the increasing cost of living, and rising defaults on loans are beginning to be a worrying trend. The rise in default rates was seen in every segment, without exception, with Loan Against Property (LAP) having the highest default rate at 4.14% in November 2021; loans due past 90 days in the two-wheeler segment are also high at 3.64%, up 140 basis points, while consumer durable loan delinquencies are the third highest. Delinquencies in the credit card segment have eased sharply by 77 basis points to 2.22% (data from credit monitoring agency Transunion Cibil). Also, the spike in fund disbursement will increase the asset size of NBFCs, while the GNPA rate will also increase significantly to 6-8%.
On account of inflationary pressures, and a slowdown in the growth of fresh credit, the situation is becoming challenging for companies in the debt collection space. To maintain profitability, NBFCs are faced with the dual challenge of improving their performance, while improving cost-efficiency at the same time. This calls for a different approach, leveraging technology such as Voice AI to automate a significant portion of their outbound customer reach outs.
In this blog, we shall explore the role of Voice AI as the ‘agent of change’ in the growing debt collection space, and why the shift to Voice AI is one of the most profitable moves NBFCs and debt collection agencies can make in 2022.
Voice AI Is Redefining the Future of Debt Collection
Customer experiences are critical to the brand and business performance agree 73 percent of the business leaders, suggests a study by the Harvard Business Review. The global proliferation of voice-led technologies and voice-assisted interfaces built on AI-based NLP across industries have set massive expectations in the way customers prefer digital interactions and engagements. IVRs have proven to decrease CX, and bulk robocalls have proved ineffective. This is of significance in debt recovery, because as companies lose time, the probability of recovery dwindles.
On the other hand, AI-enabled voice agents are capable of engaging in meaningful conversation that runs beyond generic reminders by gathering insights and feedback that may facilitate on-call payment, rescheduling, and dispute resolution.
Money talks are uncomfortable, Voice AI exactly helps debt collection agencies achieve that, allowing human/machine partnership, the future of intelligent work.
Human-Machine Partnership: Voice AI platform built specifically for the debt collections industry also helps automate voice conversations while enabling context transfer capabilities from across modalities (text, chat, email, and speech), empowering the agents to operate without burnouts whenever call volumes peak. Automation of cognitively routine work also allows more time for contact center agents to prioritize their bandwidth and use it for solving complex challenges without the need to upscale the team.
All in all, integrating Voice AI can help create three ideal scenarios—NBFCs can improve their Collection Efficiency Ratio while reducing the cost and even improving customer experience!
Skit.ai’s Augmented Voice Intelligence in Action
Challenges Facing Indian Debt Collections Companies (NBFCs)
These are challenging times for NBFCs trying to improve their recovery rate. As CXOs look forward to improving the performance of the debt collection agencies here are the core problems they are trying to solve:
Intensifying competition is putting pressure on profitability
Low Collection Efficiency Ratio
High Cost of Collections
Slower campaigns and limited customer coverage
Before we deep dive into how Voice AI can solve all the major challenges, let’s first look at the definition of Collection Efficiency Ratio.
Understanding the Performance of a Debt Collection Agency or an NBFC
The entire performance of a collection agency can be expressed to a large extent by these metrics:
Collection Efficiency Ratio
The collection efficiency ratio is a measure of how well the collection department collects debt. It’s essentially a way to determine the effectiveness of the collections team.
The collection efficiency ratio is calculated as a percentage that depicts the proportion of debt collection achieved out of the total portfolio. The higher the percentage, the better the debt collection performance of the company.
How to Calculate the Collection Efficiency Ratio
The total collectible amount for month X – This includes the overdue at the start of the month as well as all the due dates throughout the remainder of the month.
Remaining recovery amount for month X – This is the amount remaining on a specific day that the team failed to collect.
A higher percentage depicts greater success in the collection of debt, ie., better debt recovery.
How Important is Collections Efficiency Ratio for NBFCs?
The collection efficiency ratio gives an overall monetary recovery status. Irrespective of the number of accounts recovered, at the end of the day, the Rupee value counts.
It is also a good measure because it gives a clear picture of value at risk (VaR) which is the most important thing to monitor for a debt collection agency.
Age at List (AAL)
Time is important when it comes to debt collection. If your account is 7 months old, its recovery rate drops to 50%. After 12 months, it drops to only 25%.
Therefore, Age-at-List is one of the most important KPIs in the collection. This is the average number of days your account has been in expired status. AAL provides a general overview of the collection cycle. This is an excellent comparison indicator between collection agencies and the industry.
Successful agencies are aiming for a low AAL. A high AAL indicates that the agency needs to be more effective in debt collection. However, AAL tends to fluctuate. Therefore, you need to review the data for about a year to gain valuable insights.
The Digital Voice Agent can be trained to pursue B0 and B1 buckets and will be very effective with its precise regime to convert the default accounts. This will lower the age of debt and improve the performance of the company.
RPC rate (Right Party Contacts)
The RPC rate is the first of the more specific metrics in this list.
This KPI measures the ratio of all outgoing calls to a valid phone number for the person (or “right person”) for whom the collection was requested. For collectors, the higher the score, the better the success rate of finding the debtor.
Of course, the first step in collecting claims is to find and contact the right person. If your company has a lower RPC rate than its competitors in other industries, you need to think carefully about what’s wrong and how to improve them.
Percentage of Outbound Calls Resulting in Promise to Pay (PTP)
The PTP rate is just as important as the RPC rate when measuring efficiency and is the next logical step to a successful collection. It measures the percentage of all calls that end with the debtor’s promise of payment. That is if the RPC rate measures the success rate of dialing the appropriate person, this metric measures the success rate of those RPC calls. This is another percentage that you want to get as close to 100 as possible.
Voice AI agents can help companies with lower PTP figures buy prompt calls for which the best agents can train the voicebot whose perfect timing and schedules will help improve the PTP stats.
Profit per Account (PPA)
Finally, PPA measures how much profit each account in your collection makes on average. In short, this KPI measures the impact each account has on revenue.
This metric is calculated by dividing the company’s gross profit (calculated by subtracting total operating expenses from total revenue) for a particular period by the total number of overdue accounts managed for that period.
A Voice AI Agent can help reduce the operational cost to the tune of 50%, along with a faster sales cycle, improving this performance metric.
Improving these numbers is a big challenge and we will now go into detail about how Voice AI can help debt collection agencies and NBFCs transform their performance.
Transform Your Collections Efficiency Ratio with Conversational Voice AI
The effort of a collection agency is to collect as much as possible and as fast as possible from every account, i.e. a higher recovery amount with a shorter collection cycle will improve the majority of performance indicators mentioned above.
Voice AI Core Benefits for Debt Collection Agencies and NBFCs:
Voice Automation: Voice AI will help your company by automating 70% of the calls, primarily tier-I calls, and by automating payment reminders and collection calls at B0 & B1 buckets. This would cut down the time & effort of human agents and they can focus on RTP cases. This would reduce the burden on human agents and improve the use of their time on meaningful and complex problems.
Augmenting Agent Productivity: Since the human agents focus just on RTP cases that require more empathy and intelligence, their efficiency and productivity take a big leap. This has an impact on CX as well as recovery rates as agents are not wasting their time on trivial tasks.
Cost-Efficiency: Be it collection calls or running outbound campaigns for reminders or notifications, etc., the Voice AI Agent can do everything at a fraction of the cost. This has long-term and big benefits for the company.
Quality and Compliance: The Voice AI Agent never fails to follow proper protocols and thus, avoids any potential legal challenges. Also, its delivery is always the same and hence its service quality does not deviate with mood, as with human agents.
9 reasons why NBFCs and Debt Collections Agencies Should Not Miss Out on Voice AI
Allowing human agents to focus on RTP (Refuse to pay) accounts. Thus increasing the profitability by converting high-risk accounts.
Automate simpler calls like reminders & FAQ – Proactively reminding debtors at the right time and helping them with FAQ related to their loan/upcoming payment. plays a far bigger role in collections and Voice AI does it perfectly.
Improve contact-ability & customer coverage – Voice AI is capable of contacting millions of customers in a matter of weeks. Thus the company can reach out to every customer for payment reminders, follow-up on DPD cases, and assist with queries related to the loan.
Shorten collection cycle – Faster reach outs and quicker conversion with Voice AI Agent helps shorten the collection process.
Persistency in follow-ups and call-back requests – Human agent may err in follow-ups but the Voice AI agent follows up as well as calls back at the requested time without fail. This is a big help and improves collections.
Capability to handle spikes in volume – Traditionally the call center teams are unscalable over short periods, but with Voice AI, this is not the case as it can handle any spike in call volumes.
Here are some other unique capabilities of conversation Voice AI for debt recovery:
Feeds data to the CRM tool and provides analytics for further action
Persuades customers to pay at the earliest, offering payment plans and options
Helps agent plan post-call follow-up campaigns with Voice AI Agent
These unique capabilities prove indispensable and give the debt collection agency or the NBFCs a big edge over their competitors.
How a Digital Voice Agent Adds Value to Collections Efforts
The Digital voice agents are highly effective at B0 & B1 collection buckets with no human assistance. The later bucket requires a bit more contextual conversation and dunning from the collection agent.
The digital voice agent gets a custom design flow to interact with customers at Bucket Zero and Bucket 1 for debt collection. At bucket Zero, the Voice AI gives out a “The last day of payment” reminder, requesting the debtor to maintain the payment amount balance in their account for auto-debit. The Voice AI also assists in converting manual payment to auto-debit.
At bucket one (1-30 days), the debtors are expected to pay off the due within the grace period so that their CIBIL is not impacted and does not affect their eligibility for future loans. The Voice AI communicates the same to the customer and assists them with on-call payment. The Voice AI can make calls, follow-ups, and take call-back requests concurrently at any time during the week and to which the human agent has limited capacity.
For situations when the customer is refusing to pay or is unable to maintain sufficient balance, the digital voice agent dispositions them accurately and notifies them of a call back from the human agent.
Voice AI Outcomes
It will be interesting to note that the Voice AI agent helps in improving every performance metric.
Collection Efficiency Ratio – Higher, overall collections help improve the collection efficiency
Age at List (AAL) – faster collections help in keeping the debt age towards the lower side
RPC rate (Right Party Contacts) – Voice AI calls and identifies the Right Party Contact so that human agents do not have to waste time. This is a radical improvement, without spending much money and time
Percentage of Outbound Calls Resulting in Promise to Pay (PTP) – Voice AI agent calls at the right time and to the right person when they prefer to interact, thus increasing the probability of recovery
Profit per account (PPA) – since with Voice AI agent, the costs as much lower, it has a direct impact on this metric
Here is what a debt collection agency or an NBFC can expect from Voice AI agents such as Skit’s Digital Voice Agent.
49% of the total collection value recovery per campaign
Debt recovery from 78% of delinquent accounts without any human assistance
Lower the cost of collection by 40% by addressing the collection challenges like unreachability, unresponsiveness, callback request, and collection after business hours
Achieve 90% of collections in the first 3 days
Increase customer coverage by 30%
Speed up the collection campaign TAT by 70%
80% contact-ability rate
84% engagement rate with customers
68% disposition capture rate on CRM allowing your agents to focus on accounts in the B2 bucket onwards for personalized interaction for recovery
The data mentioned above has been taken from project implementations, and will certainly vary for each company. Thus, it is indicative at best, of the results that can be achieved and the potential of the Voice AI agent.
For any questions on the application, operations, outcomes, and pricing of a voice AI agent in the debt collection space, feel free to contact us – Book A Demo.
For more information on debt collection space and the role of voice AI, please visit the page.
You’ve been exploring Voice AI as a possible solution to automate your debt collection agency’s operations; you’re considering adopting an Augmented Voice Intelligence solution to scale outbound and inbound calls for collections. Congratulations—you’re in the right place.
A Voice AI solution can significantly reduce your collection costs and improve the success rate and duration of your collection campaigns. However, not all Voice AI vendors are the same. How do you choose the right vendor for your agency?
Given our extensive experience with the collections space and our tech expertise, we’ve put together a list of topics to consider when meeting with providers and choosing the best one to move forward with, from the understanding of business operations to technical capabilities.
If you can’t count on your Voice AI vendor to fully understand the collections space, you will end up being significantly more involved with every step of the process, which will ultimately take longer, cost you more money, and lead to a disappointing return on investment.
Compliance with Debt Collection Regulations
The very first thing to look for in a Voice AI solution that handles outbound collection calls is the company’s level of understanding of the existing laws and regulations related to collections in the U.S.
A well-trained Digital Voice Agent can comply with the regulations with a consistency and precision that can be hardly achieved by human agents. However, it’s crucial to check whether the provider is up to date with the current laws.
The main collections-related regulations in place in the United States are:
Fair Debt Collection Practices Act and Reg F: The FDCPA, most recently updated with Regulation F in 2021, is the most comprehensive U.S. law that restricts, for example, call frequency and calling hours, and mandates the reading of the “Mini-Miranda.”
Telephone Consumer Protection Act: The TCPA ensures that numbers in the Do Not Call registry are never contacted; this can be easily achieved with Voice AI.
Federal Fair Credit Reporting Act: The FCRA protects information collected by consumer reporting agencies.
Payment Card Industry Compliance: PCI regulations ensure that the Voice AI provider takes the appropriate measures to protect stored cardholder data and encrypt the transmission of the data.
Health Insurance Portability and Accountability Act: HIPAA is one of the most well-known privacy laws in the United States.
Read more about meeting debt collection compliance with Voice AI in our blog post.
Provider’s Understanding of the Collections Space
This point goes beyond regulations: How well does the Voice AI provider know and understand the collections space as a whole? Their understanding of the structure and overall operations of a collection agency is likely going to be a helpful factor in the collaboration between the agency and the provider.
The provider should be able to understand the agency’s structure, the challenges related to employee retention and call scalability, as well as best practices for outbound collection calls. This way, you can trust that they will design an optimal conversation flow to facilitate your collection efforts.
Different factors will affect the conversation design. For example:
Nature of debt: There are different types of debt, including credit card, healthcare, student, etc.
Age of debt: A 30-day past due debt is very different from a 180-day past due debt.
Ability to Handle End-to-End Conversations
A Digital Voice Agent needs to be able to handle outbound collection calls from start to finish, without any human intervention—from verifying the user’s identity to completing the transaction.
The Digital Voice Agent will therefore initiate the call, remind the user of the due payment, register the reason of delay, persuade the user to pay right away, collect the payment or offer alternative payment plans, and ultimately feed the data it has gathered during the call to the CRM tool.
One important question to ask providers is: What kind of access will the collections agency have over the Voice AI?
The ideal provider will offer access to a dedicated and user-friendly platform, from which the agency will be able to view and tweak conversation flows.
Additionally, having a good platform will also help with the integration of third-party applications, such as payment gateways, CRM, and other business applications.
Want to learn more about how the technology behind a Digital Voice Agent works? Check out our dedicated blog post.
Actionable Analytics
Once the Voice AI solution goes live, will you be able to easily visualize and analyze its performance and results?
As more and more users speak with the Digital Voice Agent, you gather precious data that you don’t want to waste. Your Voice AI vendor should give you access to a dashboard to monitor the effectiveness and quality of the conversations.
MLOps (Machine Learning Operations)
At the very core of Voice AI lies the capability of the algorithms to continuously learn and improve as more conversations take place.
MLOps stands for Machine Learning Operations and it’s somewhat similar to DevOps. It’s an organizational model and culture designed to help the involved teams manage the operational processes behind machine learning.
AI companies that have a good MLOps system in place are likely to develop a better technology set to improve with time.
After Go-Live: Continued Voice AI Training
Your Digital Voice Agents are ready to go live and start calling your customers to remind them of their due payments. What now?
After the Voice AI platform goes live, the work is far from finished. The Digital Agents must be maintained for further optimization of the technology and the conversational experience, also to ensure they understand out-of-scope intents. The solution must also be monitored, especially at the beginning, for quality assurance purposes.
According to a recent Gartner report, failing to monitor automation tools in post-production is one of the most common mistakes companies make when implementing automation.
Additionally, it’s important to note that Voice AI solutions are typically rolled out in multiple phases: with time, additional capabilities and use cases may be added.
Therefore, your agency will want to work with a Voice AI provider with a clear plan for post go-live training and handling.
In conclusion, watch out for these key questions to ask your Voice AI vendor.
For more information and a free demo, you can schedule a call with one of our collections experts. We’ll be happy to help!
The artificial intelligence industry is growing at vertiginous speed; a recent study valued the global AI market size at $87 billion in 2021, and estimated a CAGR of 38.1% from 2022 to 2030. Voice AI is one of the most promising technological applications of artificial intelligence.
Whenever these numbers are reported, it’s common to see some familiar headlines in the news and on LinkedIn: “AI is coming for your job,” “AI is eating up the workforce,” and so on. This narrative, however, is not accurate.
Voice AI has the unparalleled ability to shift the way contact centers function by automating countless customer interactions and lifting the weight of tedious, repetitive tasks off the shoulders of customer service agents. But does that mean that AI will take away jobs in customer service?
In this article, we’ll unpack how Voice AI affects contact centers, human agents, and operations.
Voice AI Can Solve the Most Pressing Contact Center Challenges
Rather than taking away jobs, Voice AI is more likely to take over specific tasks and activities that are currently performed by human workers.
While all types of jobs are likely to be affected in some way by automation, McKinsey estimates that only 5% of jobs could be fully automated with the AI technology we have today. Some of the fields that are likely to be most affected by AI are customer service and data-related jobs, such as data entry, collection, and processing.
Here is a summary of how an Augmented Voice Intelligence (AVI) solution can help solve the most pressing contact center challenges; below, we’ll dive deeper into each point, explaining how AVI can empower human agents.
Enhancing the Day-to-Day Work of Human Agents with Voice AI
Let’s look at the issue from the human agent’s perspective.
At a busy time, a contact center receives multiple inquiries per minute. However, the vast majority of calls and requests that contact centers receive are simple and repetitive. The work of human agents therefore tends to be tedious and underwhelming.
A Digital Voice Agent is able to sort through the inbound calls and manage those basic tasks.
The same idea applies to contact centers that mostly focus on outbound calls; a Digital Voice Agent can proactively initiate outbound calls to users at a scale that would be impossible for a human agent.
Mundane tasks that can be easily automated include authenticating callers, providing account balances, and updating phone numbers and addresses.
The Digital Voice Agent can redirect the more complex requests to the human agents, whose skills can be best used for such requests. If the caller needs to speak with a human agent, the transfer is contextual and intelligent. This way, human agents will address more interesting or pressing issues, and will feel more helpful and stimulated.
Rather than “taking away” the human agents’ jobs, Voice AI can actually make their jobs more pleasant and help them focus on more interesting issues in their day-to-day work.
Now let’s take into consideration the contact center management’s perspective.
The challenge of managing a contact center can be easily identified when looking at attrition rates. The current data suggests that contact centers have approximately a 35-40% attrition rate. This places an enormous strain on customer-facing enterprises; it takes approximately eight months to hire, onboard, and train a new agent.
According to a McKinsey report, satisfied contact center employees are 8.5 times more likely to stay at their workplace than leave within a year.
Another major issue contact centers face is the volatility and seasonality of the work.
Let’s say your contact center faces an unforeseeable situation which causes a massive surge in inbound calls. All of a sudden, you need many more agents available to take the calls. Scaling up and down so fast is not possible.
Voice AI eliminates this problem, as it’s easy to scale up and down as needed, managing call fluctuations and seasonal changes.
Voice AI Facilitates a Collaborative Effort Between Machines and Humans
Whenever a new technology emerges, people fear that it can pose a threat. Just think of the First Industrial Revolution as an example; during this time, industrialization was at first seen as a threat. A similar thing happened at the beginning of the Digital Revolution, especially with the introduction of home computers and the subsequent digitization of data.
The idea that within a few years robots will completely replace human agents at contact centers is not very realistic. The most likely path to success will consist in a collaboration between voice bots and humans.
A seamless customer experience requires a combination of efficiency, effectiveness, and empathy, and that can only be achieved with a combination of human and automated efforts—what we call augmented intelligence.
While Voice AI can help enormously to improve speed and effectiveness of a customer service response, bots are unlikely to be able to substitute the empathy needed to assist a customer with a more challenging or complex issue to solve.
In most cases, AI doesn’t learn new information and acquire new skills on its own. It requires specialized engineers who prepare the data, determine datasets, remove any possible bias, train, and update the software on a regular basis to integrate the knowledge and prepare a learning cycle. Only at that point, the AI can be used to aid human agents.
The space that Skit.ai has created is Augmented Voice Intelligence. The name itself acknowledges the importance of a partnership between humans and machines. Through Augmented Voice Intelligence (AVI), contact centers can enhance their operations and better retain human agents.
The business experience of the future is going to strongly rely on this cooperation between humans and AI.
For more information and a free demo, you can schedule a call with one of our experts.
We have all been in dire straits and dealt with frozen bank accounts and medical or travel emergencies. We can vividly recall the palpitation and frustration felt during those moments, waiting for customer support, navigating IVRs, or a chatbot.
Companies have long wanted to change it, but challenges such as high attrition rates, unscalable teams, inconsistent CX, and cost pressures have curtailed their capability to serve customers.
Consequently, customer frustration is on the rise. A 2019 report said that customers are annoyed by the irrelevant options presented by the IVR. In fact, two out of three Americans (66 percent) say they would choose AI-powered voice-over chat if it were effective at answering their questions.
Riding the wave of recent advancements in NLP and AI, we are graduating from machines automating crude, low-value tasks to a new era where AI-enabled voice customer support would help companies create enormous value, conversing in their preferred language with semantic understanding to resolve their problems.
For Exceptional CX – Technology and Channel Strategy Matters
A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as critical to the overall business performance of their company.
Companies now realize that multi-channel or omnichannel strategy has failed to live up to the expectations of improving CX, primarily because different customer segments prefer specific channels to connect. Thus, an optichannel or optimal channel strategy is more prudent as it focuses on the capability to support a customer journey via a channel/modality optimal for that problem.
Even today, after years of decline in customers’ preference for voice support to troubleshoot, voice is still over 50% in contact volume. Though companies may pursue an omnichannel strategy, if they are not good at voice support, they must be cognizant of its impact on CX. Optichannel is thus a more prudent strategy as being good at different modalities such as emails and chat will not compensate for the damage done by poor voice support. Companies have to choose wisely, there is no one-size-fits-all solution.
Text and Voice: Don’t Mix and Serve
Acing CX means that the company must be good at serving customers with their preferred channels. Voice is complex, subtle, and requires semantic understanding. Nuances of a voice conversation such as a change in the rate of speech, voice modulations, and more that convey a customer’s feelings are lost if your solution is not built from scratch for voice. Bundling a chatbot with a readily available Automated Speech Recognition (ASR) to add voice capability just kills the beauty of spoken conversations because it can transcribe but not converse.
Shortcuts like these fulfill notionally the goal of being present in every channel but defeat the goal of being good at the relevant channel.
Moving Beyond the Complexity of Digital Transformation with Voice AI
In the last few decades, the world moved from voice to text to chatbots. But as customers still prefer voice over other communication channels, even brands are taking notice. WhatsApp, a chat messaging platform, is building voice-led solutions for businesses. A Deloitte study reveals that by 2030 there will be a proliferation of voice-led technology across the globe and that 30% of sales will be via voice by then.
As companies hustle to achieve digital transformation, the low success rates, and disturbingly lower rates of sustainable DX success are proof of the precarious journey.
Fortunately, there is one way to not only automate contact centers with the most cutting-edge technology but also ensure that it succeeds without a big resource commitment from the organization. Yes, Voice AI is one such solution with stand-alone deployment and stunning success rates.
Companies must consider deploying Augmented Voice Intelligence for contact center automation as a good starting point toward digital transformation. But before that, brands must ponder over the most significant question – What does the shift towards voice entail as we cross the voice automation rubicon? What is its impact on the market and competitive landscape?
Look before you leap!
Only if you feel that your human agents are doing zero-value repetitive tasks, and there could be enhancement of their productivity. Your company is continuously facing resource, cost, and compliance challenges. Perhaps it’s time to contemplate and change.
For more information and free consultation, let’s connect over a quick call; Book Now!
Just over a decade ago, with our first tryst with Siri, little did we imagine its significance and how Voice AI will change customer support forever. Several generations, from baby boomers to millennials to gen Z, are using voice searches on popular platforms such as Google Assistant, Alexa, Siri, and others is a testimony of its potential. Today, we stand at the cusp of Voice-tech revolutionizing customer service.
Since speech is an integral part of being human, we covet meaningful conversation to connect and express. But today, even the thought of being stuck with Interactive Voice Response (IVRs) and chatbots in an emergency/urgent situation gives us the heebie-jeebies, right? And the long wait for a customer service agent to pick up, if at all, forges a lasting negative emotion towards the brand.
Companies have been trying hard to deliver a delightful customer experience; but with existing legacy systems, it is just not possible. The emerging answer to CX woes is Augmented Voice Intelligence that not only understands and responds but is semantically capable of comprehending the context of customer queries or problems.
For brands, customer experience can make or break their reputation. A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as being critical to their company’s overall business performance.
The Conversational AI space has been experiencing explosive growth, and within it Augmented Voice Intelligencesits at the frontier, with the incredible potential of disrupting the way companies interact with their customers.
Why Voice-first Solutions Will Take it All!
Written language differs significantly from spoken one. Spoken content has more information, hidden in the form of pauses and pitch modulations, Chatbots bundled with ASR can transcribe, but not converse. As organizations pour millions into automated voice support, they would want their virtual agents to understand the semantics, such as sarcasm, and not take “oh, you did a good job’ at face value. Those subtle nuances of human conversations get annihilated when we strap a readily available Automated Speech Recognition (ASR) over a chatbot.
Though chat has distinct use cases it excels at, a simple conversion of text to voice and vice-versa does not meet even the table stakes of a voice conversation.
Nearly 9 in 10 people preferred speaking to someone over the phone rather than navigating a pre-set menu, showed research from Clutch. That is why the future belongs to Augmented Voice Intelligence!
Companies cannot simply use generic voice engines, as they are built for contextless conversations. Simply because a customer interacts with a company with a very specific context, and expects it to troubleshoot as skilled human support would do.
Voice-tech solutions that are built for voice, from the ground up, will be the ones delivering successful conversations. This boils down to conversing with customers within a specific context enables automated voice support to solve their problems, even complex ones, in a frictionless manner. It requires training in domain-specific knowledge at the speech recognition layer and creating different design guidelines for every vertical and for specific use cases within those verticals.
It is an uphill task, but what’s the prize for all the effort? The biggest prize indeed: Conversations that your customers will love!
The Conversational AI space has been experiencing explosive growth, and within it Augmented Voice Intelligencesits at the frontier, with the incredible potential of disrupting the way companies interact with their customers.
Augmented Voice Intelligence focuses on empowering an enterprise’s workforce by combining the power of human voice and AI. A Digital Voice Agent can easily resolve tier 1 customer service issues and automate cognitively routine work while human agents can focus on more complex customer problems.
Human/machine collaboration is the future of intelligent work. The intent is not to replace the human workforce, but to enhance their productivity by taking away the mundane workload.
The opportunities for the Voice AI ecosystem are only getting started. Data from research platform Allied Market Research showed that the conversational AI space has the potential to touch $32.62 billion by 2030, registering 20% YoY growth between 2021-30.
For brands, customer experience can make or break their reputation. A Harvard Business Review survey revealed that 73% of business leaders view reliable customer experience as being critical to their company’s overall business performance.
End-to-End Customer Support
The main applications of Voice AI or AI-enabled Intelligent Voice Agents can be subsumed into four categories:
Resolving Tier-1 Issues: All calls can be routed through the Voice AI agent, and it will be able to answer a large chunk of calls completely, without any human assistance.
Pre-Call Assistance: As the call gets forwarded to the human agent, Voice AI can fetch all the relevant information for the agent to engage in the most meaningful way.
On-Call Assistance: TheDigital Voice Agent listens to the conversation and provides instant data and help to the human agent, augmenting the agent’s capability to serve manifolds.
Post-Call Assistance: Call summary is essential for feedback, and the agent needs to fill it out. An AI-enabled Digital Voice Agent can perform such post-call activities with semantic understanding; the agent simply has to look and approve.
Think of a contact center with a seamlessly scalable team available 24*7, with agents who have customer data at their fingertips, where the quality of calls never drops and no one gets frustrated. Where personalization, relevant up-, and cross-selling are table stakes and call data analytics and feedback are available on the fly.
Sounds like utopia, right?! But this is well within the grasp of businesses, with the right voice technology solution. Now imagine the competitive edge your company can derive from the successful adoption of augmented voice intelligence.
This is the defining moment for custom-centric companies, as their voice strategy will have ripples far into their future.
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