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
Artificial Intelligence (AI) has disrupted almost every industry in one or the other way, and ARM industry is no exception. However, due to stringent regulatory restrictions in the industry, leaders are being cautious about implementing one.
This paper provides a compliance review of the Voice technologies, especially AI powered virtual/Digital Voice Agents. The intention is to briefly introduce the technology followed by statutory framework to analyze the technology for compliance.
I have attempted to provide the relevant cases to establish my point of view from legal perspective. Also included in the paper is the list of things one should consider before implementing such solution.
It’s imperative that ARM leaders should try to adopt such technologies, though cautiously, in order to stay in the business in this era of labor arbitrage, inflation, and a generational shift in communication preferences.
This whitepaper is written in collaboration with Skit.ai. Skit.ai is an Augmented Voice Intelligence Platform that helps businesses modernize their contact centers and customer experience by automating and improving voice communications at scale. Skit.ai is a vertical voice AI company, which means they bring deep domain expertise and business knowledge along with advanced technical know-how.
Skit.ai is the winner of CCW Excellence Award for Disruptive Technology of the Year 2022. Skit.ai was also named as a Cool Vendor in Gartner Cool Vendors in Conversational and NLT Widen Use Cases, Domain Knowledge and Dialect Support in the year 2021.
Disclaimer: The information in this whitepaper is not intended to be legal advice and may not be used as legal advice. Legal advice must be tailored to the specific circumstances of each case. Every effort has been made to assure that this information is up to date as of the date of publication. It is not intended to be a full and exhaustive explanation of the law in any area, nor should it be used to replace the advice of your own legal counsel.
Introduction of Technology and Background
As a 20-year veteran of the ARM industry, I have firsthand experience as a debt collection agency shareholder and general counsel, I am the named inventor of three patent or patent-pending products that are or will be available in this ARM industry, and I currently provide legal representation of various debt collection agencies for defense litigation, defense of regulatory investigations and preparedness efforts for compliance. In these multiple capacities, I often have and do continually find myself evaluating new and emerging technologies. The evaluation of these emerging technologies is often premised upon a regulatory or statutory challenge that is impeding the needs of the industry.
In this whitepaper, I will address an emerging technology that is fairly new to the ARM industry, Digital Virtual Agent (DVA) technology. DVA technology is not an entirely new concept for ARM as we have utilized Interactive Voice Response (IVR) technology for several years. Both DVA and IVR technologies have regulatory challenges under the Telephone Consumer Protection Act (TCPA), specifically the restrictions on prerecorded messages and artificial voice calls that are placed to cellular telephones. The TCPA statutory construction is predicated on extremely dated technology. Technology that at the time of the statutory construction of the TCPA was primarily focused on landline telephones, pagers, and per minute charges for long distance calls or per minute cellular telephone plans. While the statutory language is predicated on expired technology that in and of itself does not alleviate the requirement for compliance. Instead, it creates the requirement of necessary workarounds to ensure compliance with the statute.
47 U.S.C. § 227 (b)(1)(A) states, in relevant part, as follows: (1) PROHIBITIONS. It shall be unlawful for any person within the United States, or any person outside the United States if the recipient is within the United States – (A) to make a call (other than a call made for emergency purposes or made with the prior express consent of the called party) using and automatic telephone dialing system or an artificial voice or prerecorded voice – (iii) to any telephone number assigned to a paging service, cellular telephone service, specialized mobile radio service, or other radio common carrier service, or any service for which the called party is charged for the call.
The purpose of the TCPA at its inception was to avoid tying up emergency lines or saturating new and growing wireless networks. At that time, there were only about seven million cellular subscribers. Cellular telephone plans were expensive costing around $1 per minute of use. In seeking to curb “robocalls,” and the extreme costs associated with those calls to cellular telephones, Congress was attempting to regulate certain broadly placed calls that made use of a specific type of equipment that was prevalent in the 1990’s, with no connection or relationship between the calling party and the recipient. The recipient, if the call was answered, were charged significant fees for just answering the calls. Fast forward several years and the Courts interpreted these rules very broadly to include text messaging. The Courts’ interpretation brought into question communications, both calls and text messages, for prescriptions notifications, security alerts, collection calls, appointment reminders and the like. The Courts allowed the TCPA guiderails to stretch to businesses with existing business relationships which created class action liability in the tens to hundreds of millions of dollars in liability. In many situations, consumers not only desired these calls but were not negatively impacted by the restrictions as they failed to be informed of appointment or past due obligations.
Fast forward again to 2021 where the Supreme Court of the United States (SCOTUS) via Facebook, Inc. v. Duguid, 592 U.S. ___, 141 S. Ct. 1163, 209 L.Ed.2d 272 (2021)resolved a split amongst the circuit courts and rejected the expansive definition of an ATDS, provided primarily by the U.S. Court of Appeals for the Ninth Circuit. The Ninth Circuit rulings essentially considered every cellular telephone in America to have the capacity to become an ATDS. While there is still potential liability regarding calls without express prior consent or without human intervention, the courts have seen fewer cases than prior to the Facebook decision. What Facebook did not assist with is the use of prerecorded messages or calls that utilize artificial voice. Instead, the SCOTUS utilized a textualist review of the statute to determine that in order to qualify as an ATDS under the TCPA that a dialing system must have “capacity to randomly or sequentially store or dial phone numbers.” This completely changed the direction of several courts which were taking individual approaches to consider what constituted “capacity” and often focused specifically on the term “store” to create an expansive definition of an ATDS.
The Federal Communications Commission (FCC) is the agency empowered to issue rules and regulations regarding the TCPA. The TCPA prohibits calls to a cellular telephone using and “automatic telephone dialing system” or an “artificial or prerecorded voice” without first obtaining express consent from the called party. In the early 1990s when the TCPA was enacted, these restrictions were a response to a rise in consumer complaints regarding telemarketing calls placed by systems that utilized sequential number generation for outbound telephone calls that play pre-recorded messages.
Congress enacted the legislation and empowered the FCC to enforce it. The FCC through a handful of declaratory rulings in 2003, 2008 and 2015 expanded the definition of an ATDS under the TCPA to include all predicative dialers and essentially anything that had the capacity to predictively dial or dial from a list of stored telephone numbers.
In ACA International, Inc. v. FCC, 885 F.3d 687 (D.C. Cir. 2018), the D. C. Circuit court reviewed challenges to the FCC’s declaratory orders, namely:
Its definition of an ATDS;
The reasonableness of the one-call “safe harbor” for calls placed to reassigned numbers;
Revocation of consent; and
The FCC’s exemption for certain healthcare-related calls.
The D.C. Circuit court set aside the FCC’s interpretation of ATDS and the FCC’s treatment of reassigned numbers as a whole and upheld the FCC’s 2015 ruling that a called party may revoke consent at any time and through any reasonable means as well as the narrow exemption for certain healthcare-related debt. Thankfully, the Facebook decision years later provided additional clarity. However, that clarity has been again determined by federal district courts throughout the country with mixed results.
Courts have continued to reject what has been commonly referred to as the “Footnote 7” argument – referring to Footnote 7 in the Facebook decision, where SCOTUS suggested in dicta that randomly or sequentially selecting numbers from a predetermined list might qualify as an ATDS – where Courts are focused on the generation of the numbers and not the selection of the number. See generally, Laccinole v. Navient Solutions, LLC, 2022 WL 656167 (D. R.I. Mar. 4, 2022); Montanez v. Future Vision Brain Bank, LLC, 2021 WL 1697928 (D. Colo. Apr. 29, 2021); McEwen v. Nat’l Rifle Ass’n of Am., 2021 WL 5999274 (D. Me. Apr. 14, 2021); Carl v. First National Bank of Omaha, 2021 WL 2444162 (D. Me. June 15, 2021); Barton v. Temescal Wellness, LLC, 2021 WL 2143553 (D. Mass. May 26, 2021).
So, where are we today? We are still in a world where we need to consider capacity, storage of phones and other variables in how the equipment used may or may not be defined as an ATDS under the TCPA.
Interactive Voice Response (IVR)
IVR is an automated phone system technology that allows incoming callers to access information via a voice response system of prerecorded voice prompts and touch-tones without having to speak to an agent. It also provides menu options via touch-tone keypad selection or speech recognition to have a call routed to specific departments or specialists. IVRs provide communications with consumers through speech synthesis based on a series of voice prompts that are pre-programmed by the caller. IVR technology provides an efficient means for consumers to self-service an account, make a payment, identify that they are the correct or incorrect party called, request information, or identify information about their account in order to be routed to the proper call center agent.
IVR technology is useful when built to provide pre-determined, optional responses by consumers, like Press 1 to reach the receptionist, Press 2 to reach a manager, Press 3 to be removed from further call attempts from this company. It allows an outbound call to provide a series of options to a consumer to select from to route a call or provide consumers the ability to respond to a predetermined question and also allows companies to provide pre-recorded disclosures based on federal, state, or local laws, rules, or ordinances. IVR systems have provided for increased customer satisfaction rating and have improved contact center operations and key performance indicators. During peak times of high call volumes, an effective IVR system can reduce consumer wait times by utilizing self-services tasks to answer routine questions. IVR technology is also available any time of the day or night, depending on the consumers preference and work schedules it makes information readily available for consumers at times they otherwise would not be available.
Unlike the IVR technology, DVA technology is not prerecorded or scripted messaging. It is highly conversational technology that has the ability to learn from each interaction. DVA is a software agent that can perform tasks or services for an individual based on commands or questions. The term “voicebot” is sometimes used in place of DVA. Voicebot or DVAs are able to interpret human speech and respond based on machine learning assessments and information that is accessible by the technology. DVAs have become very widely used and accepted by consumers. Many homes now utilize DVA styled technology through products like Google Assistant, Apple Siri, and Amazon’s Alexa. These products are able to verbally accept and respond to questions presented by humans. DVA’s are similarly being used in business applications as some consumers prefer to correspond with DVA rather than humans.
The perceived values of DVA technology over human-to-human communication are:
Speed: Almost everyone has experienced long wait time while calling up a call or contact center mainly due to limilited support staff. On the other hand, unlike humans, machines can be scaled up almost instantly in case of surge in call volumes and can serve every caller without zero wait time. Moreover, machines can perform actions much faster than humans, for instance machine can look up for information from the database or send documents or raising downstream tickets faster than humans.
Convenience: Most DVA or voicebot technology is available for consumer use 24 hours a day, seven days a week. This allows consumers to communicate at a time and place that is convenient for consumers – which is also a requirement under federal statute for certain ARM industry activities. Additionally, machines can communicate with humans without violating laws and judging customers in their financial crisis.
The TCPA is the most significant compliance consideration for outbound dialing, including DVA technology. As previously discussed, the TCPA prohibits calls to cellular telephones using an ATDS or an “artificial or prerecorded voice,” without the prior express consent of the called party. 47 U.S.C. § 227(b)(1)(A)(iii). The TCPA also prohibits “using an artificial or prerecorded voice to deliver a message” to residential landlines. 47 U.S.C. § 227(b)(1)(B). However, commercial calls that do not constitute telemarketing or advertisements are exempt from the residential landline restrictions pursuant to FCC classification. 47 U.S.C. § 227(b)(2)(B); Rules and Regulations Implementing the Telephone Consumer Protection Act of 1991, CC Docket No. 92-90, Report and Order, 7 FCC Rcd. 8752, 8773 (1992). Thus, calls where there is an existing business relationship or where the call is not for telemarketing or advertisement purposes, then the TCPA restrictions are limited to calls to cellular telephones.
As previously discussed, Facebook provides a framework in which to consider risks related to outbound telephone calls. The DVA itself does not have the capacity to randomly or sequentially store or dial phone numbers and therefore does not constitute an ATDS. However, a DVA is not the system or mechanism generating the outbound call on its own. Thus, compliance considerations still require a review and of dialing technology to ensure the systems and infrastructure is not considered an ATDS or that the agency’sies policy has a solid consent defense, which we will discuss later. The other important analysis is that of artificial or prerecorded voice.
The TCPA does not provide a definition of artificial or prerecorded voice. One Court has utilized a dictionary definition of “prerecorded” meaning “recorded in advance.” See Bakov v. Consolidated World Travel, Inc., 2019 WL 6699188 (N.D. Ill., Dec. 9, 2019). Other Courts have reviewed pre-recorded considering the plain language and meaning but failed to provide a definition. See Lardner v. Diversified Consultants, Inc., 17 F.Supp.3d 1215 (S.D. Fla. 2014); Braver v. NorthStar Alarm Servs., LLC, 2019 WL 3028651 (W.D. Oka. July 16, 2019). The definition of artificial has received less attention from the plaintiff’s bar than prerecorded messages or ATDS allegations. Thus, we turn to the legislative intent and FCC interpretations. In 1993, just a few years after the enactment of the TCPA, the FCC commented on the purpose of prerecorded messages and defended the TCPA’s constitutionality. See Moser v. F.C.C., 1993 WL 13101270 (9th Cir. 1993). The FCC further identified that pre-recorded announcements are different from human interchange noting that machines cannot ascertain the propriety or proceeding with a message and that live calls include a dialogue rather than an announcement. Id. at *20.
Pursuant to the legislative intent of Congress in drafting the TCPA and solving the problems associated with IVR outbound dialing in the early 1990’s and the fact that machine learning and artificial intelligence-based DVA technology developed post-enactment of the TCPA, Congress intent was not to ban “live” calls to consumers. Instead, Congressional intent shows that the TCPA was enacted to discontinue the use of artificial or pre-recorded voice systems that were considered a nuisance or invasion of privacy by forcing consumers through a decision tree-based script which often led consumers in never-ending systemic circles. DVA technology is uniquely distinguished from the IVR counterparts as it utilizes machine learning and artificial intelligence that allows the system to make decisions based on voice recognition and continually learn from ongoing interactions.
Artificial Intelligence (AI) is essentially human-like learning and communication behaviors by a machine or system. AI is classified in two categories, functionality, and capability. Functionally AI has no memory and does not have the ability to learn from past actions. Capability, by adding memory and past information, AI can make better decisions. Items like GPS location apps are good examples for AI.
Machine learning is when software is able to successfully predict and react to unfolding scenarios based on previous outcomes. The systems develop patterns, predict, and learn based on disposition data. It can make adjustments to prior outputs without being programmed to do so, therefore is truly more interactive.
Understanding the technological differences between an outbound IVR and DVA are significantly important to the assessment of risk in the use of this new technology in the ARM space. As previously mentioned, there are significant differences in these two types of technologies. The main difference in evaluating risk is what constitutes a pre-recorded message and what constitutes an artificial voice. Let’s begin with pre-recorded messages. Congressional intent on a pre-recorded message was simple – to avoid calls to a consumer’s cellular telephone and leaving a pre-recorded message on a consumer’s voice mail. The DVA does not utilize pre-recorded messages for voice mail messaging, nor does it play a series of pre-recorded scripts to provide consumers with options to select one of several predetermined paths to additional questions. DVA technology corresponds with a consumer based on that consumer’s statements, questions, or responses. It then utilizes real-time machine learning to determine how to respond to the consumer’s inquiry, no different than a human agent in a call center. Systems, like people, will sometimes be unable to provide an answer to a specific question and may transfer the call to another person or system to respond accordingly in an attempt to provide the requested service to the consumer. The ability of the DVA system to interact with a human in real-time and correlate responses to questions posed by a consumer and not pre-disposed by the company, is a major differentiation in the technology and the applicability of statutory constraints provided in the TPCA.
In the event your risk analysis, in-part due to the limited judicial interpretation of the use of DVA technology, does not meet your risk tolerance levels, don’t stop there. Take a look at other compliance considerations, like prior express consent, human intervention or peer-to-peer solutions that may assist in the analysis to find a compliance strategy to comply with the TCPA. Prior express consent is a viable and solid defense to an alleged violation of the TCPA for the use of outbound DVA or IVR technology.
While pre-recorded messaging and artificial voice are differentiated from ATDS analysis in the TCPA, prior express consent (PEC) is an absolute defense to all three arguments. The phrase “prior express consent” is not defined under the TCPA or FCC regulations. However, in 1992, the FCC addressed the issue of PEC in the context of calling wireless number by stating:
Persons who knowingly release their phone numbers to a caller have in effect given their invitation or permission to be called at the number which they have given, absent instructions to the contrary. However, if a caller’s number is “captured” by a caller ID or an ANI device without notice to the residential telephone subscriber, the caller cannot be considered to have given an invitation or permission to receive autodialer or prerecorded voice message calls.
A process analysis is necessary to ensure that the prior express consent is documented properly, saved, and accessible in the event your company is subject to a TCPA lawsuit or regulatory review. A few considerations for analyzing your prior express consent policy:
Prior express consent can be obtained either directly from the consumer by the agency or passed through to the agency from the creditor. Furthermore, the 9th Circuit Court of Appeals states in summation that the TCPA requires “that prior express consent must have been given either orally or in writing.” Loyhayem v. Fraser Financial and Insurance Services, Inc., No. 2:20-cv-00894-MWF-JEM (9th Cir. 2021). While pass-through consent has been determined by various courts to pass muster under the TCPA, direct consent is obviously better for several reasons.
First, pass-through consent is obtained at the time of service. Depending on the type of service provided a consumer could argue that the consent was obtained under duress or that the required provisions made the agreement a contract of adhesion, meaning the consumer had no choice but to accept the terms without condition. Depending on the type of service obtained those arguments may have merit.
Second, the language in the underlying consumer agreements must contain the proper consents (e.g., calls initiated through an automated telephone dialing system; calls initiated with a pre-recorded or artificial voice). Agencies may be able to influence the creditors consent language in the underlying consumer agreement, but they do not control language modifications over the life of the creditor-consumer relationship which often change through electronic updates to consumer agreements.
Third, underlying consumer agreements are stored and maintained by the creditor. As a third-party provider of collection or care services, the agency is dependent not only on the underlying consumer consent language but also the manner in which the creditor stores, maintains, and reproduces the documentation to prove the consumer provided prior express consent. Fourth, considerations of time between the contractual agreement and the outbound attempt are important as reassigned numbers have created liability for outbound calls. See Soppet v. Enhanced Recovery Co, LLC, 679 F.3d 637 (7th Cir. 2012).
The Consumer Financial Protection Bureau (CFPB) addressed this concern around time in Regulation F, 12 CFR Part 1006 (November 31, 2020). Under Regulation F, it identified concerns regarding reassigned phone numbers in their recommendations regarding text message communications suggesting that agencies consider the use of the Federal Trade Commissions (FTC) reassigned number database scrub anytime more than 60 days has elapsed since the last contact with a consumer. See Regulation F, Section 1006.6(d)(5). While Reg F provides this recommendation and offer for a safe harbor to agencies that follow the recommendation, it is not a rule or requirement but instead an optional compliance consideration that affords a safe harbor or bona fide error defense under the FDCPA. Scrub processes for reassigned phone numbers likely will provide another layer of defense and compliance to an outbound DVA or IVR based call. Finally, consumers should be afforded a simple and clear way to revoke consent or opt-out of future IVR or DVA based call attempts. One way to provide the consumer an opt-out option is to provide it in the IVR or DVA, on a consumer facing website, or via toll free phone number. Agencies should have systemic processes that are regularly audited to consumer revocations where consent is the only or primary defense.
Around 2008-2010, the ARM industry experienced a rash of TCPA litigation claims premised on the use of an ATDS for outbound calls. Technology was developed to overcome these restrictions that required human-intervention prior to an outbound dial regardless of the type of dialing systems that was utilized by the calling party. [Insert MCA Patent reference]. This technology was designed to allow for continued efficiencies in call center routing, reporting and compliance which was built into dialing systems over the prior years.
The ARM industry commonly has and continues to lean on dialing system infrastructure to maintain a rules-based process to ensure compliance with various state and federal regulations that restrict the time and number of calls to consumers in a given period of time. Human intervention is conceptually very simple – it requires a human to click a button or dial the ten key number prior to call initiation from the dialing system. The first case to address this technology was Strauss v. CBE Grp., Inc., 2016 U.S. Dist. LEXIS 45085 (S.D. Fla. Mar. 28, 2016) ruling that human intervention, such as through the click of a button, the system does not qualify as an autodialer under the TCPA. This instrumental rule blazed the litigation trail and provided a path to the 10+ additional federal court rulings throughout the country. This additional compliance consideration provides protection against the allegation of the illegal use of an ATDS. However, it does not provide any real protection for (or at least has not been addressed by the Courts) in regard to pre-recorded or artificial voice allegations.
Peer-to-Peer (P2P) technology is very similar to human-intervention technology and is primarily used today in outbound text messaging campaigns. P2P is similar to human-intervention prior to an outbound phone call with a few differentiations. First, P2P was built for outbound text messaging but could be deployed on outbound phone call attempts as well – although I have not seen the technology utilized in this manner, yet.
Human-intervention for outbound dialing is customarily provided by a human in a call center environment and oftentimes is generated off-shore. The human intervenes in the dialing system to generate the outbound dial by pushing a button (key on a keyboard, computer mouse, or similar device). P2P processes are built into the texting process and its application based. The application sends a message to employees or contractors with a message to log into the P2P system. The employee or contractor then presses a button on their cellular device, iPad, computer, or other electronic device to initiate the text to be sent to the carrier or aggregator for delivery to the consumer.
The efficiency of P2P is better than human-intervention and has also been reviewed by the FCC, wherein the FCC opined that a P2P process is not an ATDS. See FCC Declaratory Ruling, In the Matter of Rules and Regulations Implementing the Telephone Consumer Protection Act of 1991, P2P Alliance Petition for Clarification, GC Docket No. 02-278, DA 20-670 (June 25, 2020). P2P provides a very solid defense to an allegation of that an ATDS was illegally used to generate the outbound call or text message but like human intervention has not been vetted by the Courts as it relates to artificial or prerecording voice allegations.
So, why even discuss P2P for IVR or DVA technology if it does not protect against the TCPA concerns regarding artificial or prerecorded voice? Consent. P2P technology provides ARM companies an affordable and effective means in obtaining direct consumer consent prior to the use of DVA or IVR technologies. Companies today have the ability to send documents to consumers via text messages through P2P platforms that can be signed electronically and returned to the sender for consent capture. Once consent is obtained (either direct consent or pass-through consent), then the outbound DVA and IVR options to communicate with consumers become extremely viable and significantly defensible. Consent is a must for a pre-recorded message defense and human intervention/P2P is a must for defense against an ATDS allegation.
As previously addressed, there are several different compliance considerations to evaluate and determine what to deploy as internal business strategies and to document in policies and procedures. The type of systems used drives the risk analysis. Individual risk tolerance will determine which compliance considerations to implement or maybe how to develop multiple layers of protection utilizing some, all or more options than those compliance considerations discussed in this article. What I believe to be true is doing nothing and not utilizing these technologies is not a good long-term plan or option.
As an industry and in society in general, we continue to experience a shift in communication modalities in society. We are also facing labor arbitrage, inflation, and a generational shift in communication preferences. At the end of the day, finding a preferred communication method is key to right party contacts and a right party contact is the key to success in the ARM industry. Thus, ARM companies must consider generational shifts, labor arbitrage and current financial impacts.
The current workforce and debtor community is comprised primarily of Millennials and Generation Z. These generations communicate primarily by electronic means and prefer to speak to a computer or artificial voice rather than a human call center agent.
Furthermore, we are experiencing inflationary pressures and worker shortages, due its large part to the retirement of the baby boomers, which continues to drive hourly rates to unprecedented, and, at some point in the near future, to unmanageable levels at current fee rates.
Over the years, the ARM industry solved or attempted to solve the labor concerns with near-shore or off-shore solutions that again utilize human’s doing similar work but at lower labor rates and lower overall costs. While labor concerns continue to exist and likely always will, the more impactful change is the shift in consumer communication preferences. You can staff call centers all day long, but if people will not pick up the phone and communicate with a live representative then the model has to change.
The technological advancements and shift in communications preferences make the utilization of this technology paramount to the continued success of any ARM business into the future.
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.
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.
For more information and free consultation, let’s connect over a quick call; Book Now!
Voice has forever been the preferred means of communication, and today the global shift towards voice is becoming more conspicuous. It has become increasingly popular across generations and geographies. There are 135.6 million people in the US using voice search features, and as of 2021, nearly one in three (32 percent) US consumers own smart speakers, according to Statista. Consumers are using them for shopping, searches, and much more. Studies have found that today, even voice ads are an engaging multitude of users. Over half of all online US shoppers and 40% of the US population use voice assistants to explore products (Narvar, 2018).
The rise is visible across the globe. In India, for instance, the number of people using voice queries daily on Google is nearly twice the global average. With higher consumer adoption of voice-led searches, its incorporation in CX strategy is now a business imperative.
By 2030, there will be a proliferation of voice-led technology across the globe, and 30% of sales will be via voice, a Deloitte study revealed. These are disruptive times, and as MIT research seconds, the risk of not investing in technological capabilities during downturns is nothing less than existential.
In the new normal, competition has intensified over the capability of companies to deliver CX. Until now, IVRs and chatbots did help in improving CX in a limited way, but an enormous value gap and the chasm of unaddressed challenges remain. The traditional bottlenecks are still constraining the ability of organizations to serve customers. Scalability of the support team and cost pressure are the top two debilitating challenges. Given the plateaued capabilities of present legacy systems, companies have begun to pin their hopes on new technologies such as augmented voice intelligence that can help them break the status quo.
Mounting Challenges of Customer Support
In the new normal, disruption has resulted in the rise of customer support expectations. Here are a few focal pain points:
High Attrition Rates: Even the best contact centers struggle to retain.
Unscalable Teams: It is near impossible to match the ebbs and flows of call volumes with support team size.
Faltering CX: IVR only resolves rudimentary tasks, rerouting customers to nightmarish waiting lines for human agents to solve their problems.
Cost Pressure: Infra, training, retraining, and retention efforts cost a fortune.
Consequently, customer frustration is on the rise. Nearly 9 in 10 people preferred speaking to someone over the phone rather than navigating a pre-set menu (IVR), showed research from Clutch.
Assessing the Tech Solutions Available Today
Technology has always had the answer to most business challenges. Here are the tech solutions available today:
IVRs: They had been game-changers when they came. But most IVR implementations are created with the objective of reducing call volumes or preventing callers from getting to an agent. They do not differentiate between customers or their intent, leading to time-consuming and frustrating systems. Also, confusing navigation and terminology with poor integration capability with other channels is a big miss at value creation. IVRs still create value, though in a limited way, and maybe apt for companies where customer experience is not a priority.
Chatbots: For companies looking for a cost-efficient solution whose products or services have a Non-linear User Journey a chatbot can be an effective means. They have been here for a while and owe their popularity to-
Increasing demand for self-service
Are easier to train
Ability to give 24/7 customer assistance at low costs
Can engage audio-visual media
But they too have their shortcomings – they miss out on two core pillars of customer experience, i.e., emotions and ease of use. It is impossible to convey emotions over text for ordinary folks. Also, it is taxing to type repeatedly, especially if the customers are not tech-savvy, too young or old, or in atypical situations.
Voicebots: A meaningful conversation can light up the darkest day! And in customer support, it is even more critical as consumers call their providers with the hope of speedy resolution.
Today, tech advancements have made Voice AI Agents capable of executing biometric authentication and looking up all the relevant information when a user calls from their registered mobile. With data handy, the intelligent voice agent then uses it to quickly solve customer problems with only a few sentences exchanged with the customer. It is the holy grail of customer support, and now with augmented voice intelligence, it is possible.
Changing itineraries, travel plans, canceling or booking tickets, registering complaints, or changing mutual fund portfolio allocation are tasks that can be accomplished with no waiting lines or tedious conversations. There is nothing more satisfying than voice conversations because it’s natural, intuitive, and gratifying.
Augmented Voice Intelligence Vs. Google Assistant, Siri, and Alex
Alexa, Siri, or Google Assistant are the gold standards of voice automation, but they are built for generic conversations, answering any type of query from almost any language. Revolutionary that they may be, they are not suitable for customer support because the expeditious resolution of customer problems requires a solid foundation of context.
An Intelligent Voice Agent, powered by AI, is trained for thousands of hours on specific customer problems. They understand the vocabulary, the decision process, and what solution to propose. Most importantly, unlike the most popular search engines designed to provide one answer, intelligent voice agents are capable of multiple rounds of questions and answers. For customer-centric companies, Voice AI is a suitable solution.
Listen to Voice AI Agent In Action
Voice-first Solutions Will Transform Contact Center Automation
Written language is significantly different from the spoken one. Chatbots bundled with Automated Speech Recognition (ASR) can transcribe but not converse. When it comes to voice, only pure voice solutions, built from ground up for voice, will be able to deliver tangible business outcomes.
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 ASR over a chatbot. A simple conversion of text to voice and vice-versa does not meet even the table stakes of a voice conversation.
The attrition among call center employees is the highest. Seamless collaboration of human and machine intelligence is the future of work. Voice AI is perfectly poised to augment human agents and multiply their capabilities.
How? As intelligent beings, we prefer to do meaningful tasks that create value. By taking away a chunk of repetitive and low-value tasks an intelligent voice agent helps human agents focus on significant and complex tasks. Also, it provides information in response to the contents of the conversation, assisting them to perform remarkably better and feel engaged with their work.
Take Your First Step
Brands have to ask themselves – What does the shift towards augmented voice intelligence entail for their market? How can they use voice as a growth engine? Here are a few outcomes organizations have achieved by deploying Augmented Voice Intelligence:
Up to 70% automation of customer support efforts
50% reduction in operational costs
Over 4.5 customer satisfaction scores
Up to 40% reduction in average handle time
Enabled analytics-driven informed decisions
If the answer to the questions below is a “Yes”, you should seriously consider incorporating augmented voice intelligence:
Are your human agents involved in zero-value repetitive tasks?
Are you facing resource, cost, and compliance challenges continually?
Do your talented agents feel they could perform manifolds more with proper tech support?
Is customer experience at the core of your business?
Never before has investment in Voice AI made more sense. The advancements in NLP and AI have enabled companies to move from crude automation of non-value tasks to the epoch of Augmented Voice Intelligence, assisting companies to create value by automating customer support and enhancing CX with multi-language support with semantic understanding.
The voice strategy of customer-centric companies will have ripples far into their future. After all, vox dolor, vox Dei, i.e., the voice of the consumer, is the voice of God.
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