Author: Simone Somekh

Leveraging Cognitive Science to Improve CX with Voice AI

Posted on by Simone Somekh

How Human Cognition Impacts the Way Users Interact with Voice AI

When developing and configuring a conversational Voice AI solution, it’s imperative to take into account the experience that end-users will have when interacting with the solution. No matter what the use case is, users should be able to utilize the voicebot to reach a satisfactory resolution, while also having a pleasant experience.

CX is one of the elements that drive the work of Conversational User Experience (CUX) Designers, who ask themselves multiple questions when designing a Voice AI solution: Who is the client and what is its brand identity? What target persona will be interacting with the voicebot, and what use cases will the solution help them with?

To maximize the quality of the user experience and the consequent CX, conversation designers take into account cognitive science. The goal is to design intuitive, effective, and engaging interactions; cognitive science can provide insight into how users process information, make decisions, and interact with technology.In order to understand the role of cognitive science in CUX, we must first define the term “cognitive load.” According to the American Psychological Association, cognitive load (or mental load) is the “relative demand imposed by a particular task, in terms of mental resources required.” As humans, we can only hold so much information in our minds at any given time; our minds are limited, and we can’t overload them. That is why minimizing the cognitive load plays an important role in ensuring a positive user experience.

Let’s analyze these aspects one by one:

Natural language processing: CUX designers take into consideration the way users process language, including speech recognition and text-to-speech conversion, as well as the interplay between different elements of speech, such as prosody, pitch, emphasis, and the consequent tonality, which further contributes to perceptual and contextual semantics. NLP is essential for building effective conversational systems. This process also includes researching and implementing algorithms that accurately recognize and respond to human speech.

Memory and recall: The user’s ability to remember and recall information when necessary is essential to conversation design. The cognitive load is directly affected by the complexity and quantity of the information given to the user. Designers consider how the information is presented and stored, and ensure that users can easily and quickly retrieve it.

Attention and distraction: Understanding how people allocate their attention, what contributes to selectivity in attention in a given context, and how easily users can be distracted. Designers must structure the conversation to keep the user’s attention focused on the task at hand, resulting in better engagement and performance.

Emotion and motivation: Emotions play a significant role in shaping human behavior and decision-making. Designers consider how users may feel about the interaction and how to motivate them to engage with the voicebot. Secondary UX research about user demographics and socio-economic and geo-cultural backgrounds can provide valuable insights to improve CX.

Decision-making and problem-solving: Conversations often involve decision-making and problem-solving, and understanding how people process information and make decisions is crucial for effective conversation design. Factors include biases, heuristics, and cognitive load.

How Do You Reduce Cognitive Load in Conversation Design?

What are the best ways for conversation designers to reduce the users’ cognitive load in a conversation with a Voice AI solution, consequently improving the customer experience? Here are some guidelines you can follow:

Simplify prompts and confirmations: Using as few and simple prompts and confirmations as possible helps reduce the need for users to remember and respond to multiple options, ultimately leading to an optimal cognitive load and user experience. This is easier to accomplish with a well-designed conversational Voice AI than with legacy technologies such as IVR systems, in which users are forced to listen to long menus of mostly irrelevant options.

For example, a legacy IVR system will offer a lengthy menu of options, such as: “For your account balance, press 1; for information on your upcoming payment, press 2; to update your personal information, press 3 … To hear this options again, please press #.”

Instead, a Voice AI solution will simply ask: “How can I help you?”

Another example is the prompt for a user’s date of birth. A poorly-designed voicebot will say: “Please enter your date of birth in the following format—two digits for the month, two digits for the day, four digits for the year,” or a similarly lengthy and confusing prompt.

Instead, a well-designed voicebot will ask: “Could you please say or enter your date of birth?”

Use natural language: Use natural language and avoid complex sentence structures to reduce the cognitive effort required to understand the conversation.

See below an example that highlights the difference between a more robotic language choice and an alternative with more natural-sounding language.

Robotic language: Unfortunately, the payment amount that you have given is less than the acceptable minimum amount of $50. Can you please state an amount that is equal to or higher than $50?”

Natural-sounding language: “Sorry, but the minimum we can accept is $50. Can you please tell me how much above that amount you can afford to pay today?”

Provide clear cues: Open-ended questions can prompt a multitude of responses from the users; the voicebot might not understand many of the possible answers. Therefore, using clear cues to indicate when the user should speak, and using audio cues to confirm that the system has understood the user’s response should be adopted as a standard practice.

For example, here’s what the Voice AI solution will say to negotiate a payment plan: “We offer a choice of 2-month, 4-month, and 8-month payment plans. Which payment plan would you like?”

Another way to provide clear cues is the use of an audio signal informing the user that something is happening; in jargon, this is knows as an “earcon” (a brief, characteristic, harmonized and structured sound and its job is to communicate a specific message, event, status to a user or convey a task being performed).

This type of audio signal gives the user a cue that something is happening (e.g. a payment is being processed), instead of just having plain silence, which can lead to confusion. An earcon, for example, could be the sound of someone typing on a keyboard, which signals that the information is being processed.

Use progressive disclosure: Progressive disclosure is a strategy in interaction design to reveal information gradually and start only with the most essential information. Providing information to the user in a step-by-step manner, rather than overwhelming them with too much information at once, leads to increased engagement and enhanced experience.

See the example below:

Voicebot: “To set up a payment plan, can you tell me how much you are comfortable paying each month?”

User: “$60.”

Voiebot: “Thanks! Based on a $60 monthly payment, we can set up a payment plan with a duration of 4 months. Your payment plan will start on the next billing cycle. How does that sound?”

The reiteration of the monthly payment amount also serves as an implicit confirmation.

Contextual design: Using context to guide the conversation reduces the need for the users to provide additional information. For example, just as we do when we talk with a waiter at a restaurant, if the user has already provided their name, the system should use that name in subsequent interactions. As the conversation progresses, the voicebot will have more and more context and will be able to utilize the information it has collected to improve the user experience.

The voicebot shouldn’t just rely on context of the specific conversation taking place, but also on the context of previous interactions with the same user. Acknowledging previous interactions is a good idea.

Test and iterate: Testing the bot’s conversations with users and iterating the flows based on their feedback helps improve the user experience (UX) and reduce the cognitive load. The conversation flow can be optimized based on the different users’ needs. Additionally, different types of debt, different users, different demographics often require slightly different approaches.

There is no doubt that leveraging cognitive science in the design and development of conversational Voice AI solutions can significantly enhance the customer experience (CX).

By understanding how human cognition impacts user interactions, conversation designers can create intuitive and engaging interactions that reduce cognitive load, leading to more positive user experiences.

By applying these insights and best practices, business can rely on voicebots to meet their customers’ needs and optimize the use of their own resources. As the technology continues to advance, the potential for Voice AI continues to grow.

Want to learn how Voice AI can transform your business? Use the chat tool below to schedule a meeting with one of our experts!

How Skit.ai Elevates CX in AI-powered Collection Calls

Posted on by Simone Somekh

Debt Collection and Positive CX: Is It an Oxymoron?

Discussing customer experience and debt collection in the same sentence might sound like an oxymoron: for most people, the experience of being reminded about an outstanding debt is not particularly thrilling. Yet, the fact that collection calls are not the most welcome calls a customer may receive does not mean their experience should be dry—even negative.

At Skit.ai, we offer an effective and easy-to-deploy conversational voice AI solution for the ARM industry. There are many ways to make the interaction between a user and a voice AI efficient, easy to navigate, and painless.

What is the role of Conversation User Experience (CUX) Design in fostering a positive customer experience (CX) in AI-powered debt collection calls? In this blog post, we’ll share the best practices we’ve adopted to enhance CX in our automated collection calls.

The Role of CUX Design in Improving the Customer Experience

When creating and configuring our conversational voice AI solution for collections, our designers prioritize three components, all of which are essential and will ultimately influence the customer experience when interacting with the voicebot: voice, verbiage, and interaction.

Voice is the audio component of the voicebot: Does it sound male or female? Young or old? What accent does it have? What’s the inflection of the voice? How does it sound—friendly, professional, clear, direct? How fast does it speak? Fast enough to keep the user engaged, but slow enough for the average user to understand? All these questions are taken into consideration when designing the voice AI solution. There are no correct answers, as different use cases and demographics require different characteristics.

Verbiage is the content of the voice AI’s communications during the call with the user. The aim is to make the voice AI solution speak in a natural language so that the interaction can flow smoothly and naturally. Designers take into account grammar, choices of terminology, and other utterances to ensure that the voicebot sounds natural.

Regarding terminology, designers usually seek to balance industry-specific jargon and simple terminology to accommodate users lacking the background and context around the call.

Voice and verbiage, paired together, contribute to creating the digital agent’s “Persona.” For example, that could be a 30-something-year-old female agent, with a confident yet empathetic voice, sounding efficient and eager to help the customer; she could have a midwestern accent and a friendly, yet professional attitude.

The interaction capability of the voice AI solution is the third key element that defines the user experience. This element is the voicebot’s ability to handle an effective back-and-forth with the user. Timing, here, is crucial: when does the AI pause, and for how long? The devil is in the details: missing a comma can change the meaning of a sentence and make it difficult for the user to understand.

How long does the AI wait to reply after the user has spoken?

How does the AI express its prompts? For example, at the beginning of the call, the voicebot will want to verify the user’s identity for authentication purposes; to do this, it will likely suggest the preferred format of the user’s response:

Example: Can you please verify your date of birth? For example, “July 1st, 1985.”

If the AI pauses between the question and the suggested response, the user might respond before the suggestion, leading to mistimings, disfluencies, interruptions, and a potentially failed interaction. To optimize the interaction, a CUX designer will configure the prompt so that the back-and-forth can take effect as smoothly as possible.

The success of the voice AI solution depends on these three pillars. But the customer experience goes well beyond that—let’s explore more aspects in the following sections.

Common CX Concerns: Quality of Speech Recognition and Agent Transfers

One common concern related to customer experience with conversational voice AI is the quality of the ASR, i.e., speech recognition. The fear is that the technology won’t understand the user’s responses and extract the correct “intents” and thus fail to deliver a smooth, natural-sounding interaction. The technology behind speech recognition and natural language understanding has dramatically evolved over the last few years. While this used to be a major problem a few years ago, today it’s less of a concern.

Of course, poor connection or background noise can still hinder the tech’s ability to understand what the user is saying. That’s where a repair strategy comes into play to take the conversation back on track and prevent misunderstandings. Whenever the AI fails to hear the user’s response, it can politely ask them to repeat or rephrase it. Similarly, when the user is uncertain about how to respond, it can offer to repeat it more clearly or rephrase it using different words.

Another common concern relates to agent transfers. Users often fear that the voice AI solution won’t let them easily transfer the call to a live agent if requested. That’s not the case with Skit.ai’s solution. Whenever the customer’s needs are too complex for the AI to handle, and whenever the customer requests it, the solution will always transfer the call to a live agent from the collection agency.

The Role of Personalization as an Effective CX Tool

To achieve a seamless customer experience, a company must know its customers. That is why, in addition to outlining the voice AI’s persona, we also consider the user persona, i.e., the user demographics. Incorporating personalization into the conversation with the voice AI solution helps make it more engaging and fosters trust. However, it’s important to maintain a balance—while personalization is great, you also don’t want to overdo it in order to protect the user’s privacy. This was recently highlighted in data showing that the majority of consumers expect personalization, as long as the data is handled responsibly.

One small touch is incorporating the user’s first name throughout the conversation. For example, after the user authentication is completed, the voicebot can say: “Thank you, Sarah,” to confirm that it’s verified the user’s identity.

Showing that the voice AI solution is aware of the context of the conversation can also improve CX. For example, during an inbound call, the voicebot may say: “I see that you have an outstanding balance of 241 dollars and 50 cents. Is this what you are calling about?”

After the user has made a payment, the voicebot can express enthusiasm like this: “Good news, Sarah! I received your payment of 241 dollars and 50 cents.”

Regional languages and dialects also ensure that the solution is tailored to specific markets. For example, Skit.ai’s voice AI solution speaks over half a dozen languages along with understanding several regional accents.

Incorporating Empathy in Automated Collection Calls

When it comes to sensitive use cases such as debt collection and medical-related calls, empathy is an important component of the voice AI solution’s capabilities. The choice of words, tone, and inflection used by the voicebot can greatly affect the voicebot’s ability to convey empathy, particularly when a user expresses their inability to pay off their debt.

For example, the user may say: “I just lost my job, I can’t deal with this right now.”

How should the voice AI solution respond? The role of empathy in AI is a complex matter: If the voicebot says, “I’m sorry to hear that,” it might irritate the user, given that a computer cannot truly grasp the emotions of someone who has lost their job. However, a common phrase like “I completely understand the situation” is a conventional expression to indicate that the AI solution has acknowledged the user’s challenge.

The voice AI solution is designed to offer options to reach a satisfactory resolution. If the user can’t pay off the debt right away, the solution can offer a few alternatives, such as a payment plan or the ability to connect again in the future.

When designing the voicebot to express empathy, we want to avoid the so-called “uncanny valley” effect. If the voicebot switches abruptly from an overly empathetic statement to a neutral tone, it can cause the user to experience unease and irritation. Therefore, there needs to be consistency in the voicebot’s naturalness and tone, avoiding excessive variation and unexpected changes in its behavior.

And Finally… Regular Quality Checks

While old systems were static and rigid, new-generation conversational voice AI solutions like Skit.ai are dynamic and adaptive. The solution is built to improve over time. Additionally, after the solution is implemented, CUX Designers regularly perform quality checks and listen to calls with customers to ensure that the voice AI functions correctly. This way, they’re able to regularly train the solution to add new capabilities, understand more user utterances and intents, and offer the most appropriate responses.

Are you curious to watch Skit.ai’s voice AI solution for collection calls in action? Contact us using the chat tool below and schedule an appointment with one of our collection experts!

Are You Still Using an IVR Menu for Debt Collections?

Posted on by Simone Somekh

What is an IVR System for Debt Collections?

IVR stands for “Interactive Voice Response,” and it’s a legacy technology that enables companies to automate both inbound and outbound calls by using a pre-recorded voice that interacts with consumers and guides them through a pre-set menu, which can be navigated by inputting DTMF (dual-tone multi-frequency) from the phone keyboard.

Virtually everyone has interacted with an IVR system at some point. Whether you’ve called a business, a bank, a pharmacy, a doctor’s office, or a phone service provider, you are certainly familiar with prompts like: “For hours of operations, press 1.”

Call automation for call centers and businesses is not a new concept. IVR became popular in the 1980s when it emerged as an essential customer service technology. Debt collection agencies have been using IVR for over a decade, for both outbound calls (such as payment reminders) and inbound calls (such as consumer inquiries).

However, the fact that IVR is so common does not mean that it’s an optimal solution. In this blog post, we’ll go over the limitations of IVR and explain why adopting a conversational Voice AI solution is a far better option for collection agencies.

Why IVR Is Overwhelmingly Unpopular

IVR reduces wait time for consumers, but it does not eliminate it, as it forces users to listen to lengthy menus that are for the most part irrelevant. At least 61% of consumers think that IVR systems make for a poor customer experience (CX).

A survey conducted by Vonage with Opinion Matters in 2019 revealed that having to listen to seemingly endless, irrelevant menu options is the primary factor that contributes to the consumers’ negative experience. Additionally, the respondents complained that IVR menus are usually too long, that the reason for their call is sometimes not even listed, and the system prevents them from speaking directly to a live customer representative.

Building the right IVR for your company can be tricky. When the system is not designed well, users will get frustrated and abandon the call. IVR is notoriously difficult to navigate, especially when a business offers different services or targets various sets of consumers.

In one sentence: consumers don’t like IVR. So what’s the alternative?

Voice AI Is the Best Alternative to IVR

Conversational Voice AI is the cutting-edge technology behind what is commonly referred to as a “voicebot.” It enables companies to automate both inbound and outbound calls with customers without the involvement of a human being. In recent years, SaaS platforms offering Voice AI solutions have become more affordable and easier to deploy.

In the ARM industry, Voice AI can transform the operations of collection agencies for the better; these solutions are infinitely scalable and can handle the vast majority of calls with consumers. The AI can handle the most repetitive and mundane calls, empowering live agents to focus on the most important and revenue-generating calls.

Skit.ai’s solution can handle intelligent, personalized, and effective conversations with consumers, eliminating wait times and significantly cutting costs for the company adopting it. The AI is aware of the context and will tailor the service it offers based on the specific needs of the user. The technology not only understands what the user says but also the semantics of the conversation.

Voice AI for Outbound Collection Calls

Collectors are usually expected to go through thousands of files per month; a large number of those files remain untouched since it’s impossible for a human collector to contact and speak with so many consumers. This process leads to substantial losses in potential revenue for the agency.

When fed with large quantities of files, a Voice AI platform can initiate and handle an extraordinarily high number of calls. These are some of the solution’s capabilities:

The solution can easily transfer the more complex calls to a live agent when it cannot reach a satisfactory resolution. When agents see that a call is being transferred from the Voice AI, they know the customer is usually inclined to make a payment or reach a settlement.

Why You Should Not Use IVR for Outbound Collection Calls

Using IVR for debt collection calls is limiting and is unlikely to lead to a successful debt recovery on a consistent basis. The system can’t capture meaningful dispositions and is capable of handling a limited number of actions. Let’s say the consumer refuses to pay or disputes the debt—can your IVR capture the reason? Let’s say the consumer is willing to pay but can only pay off part of the debt at this time; can your IVR handle a negotiation? If the consumer is busy right now, is your IVR able to capture call-back dates and times? Probably not.

Voice AI for Inbound Queries

When a customer calls the collection agency, rather than having to deal with an annoying IVR menu, they get to interact with the Voice AI solution.

The AI picks up the call right away, eliminating the wait time of a regular call; additionally, the user does not have to patiently listen to a long list of options. The AI typically authenticates the caller’s identity and, if relevant, informs them of their due balance. Here the customer gets to have an intelligent, effective, multi-turn conversation with the Voice AI solution.

In revenue-generating inbound calls, the Voice AI can easily help the customer make a payment. In non-revenue-generating inbound calls, the solution will answer the customer’s questions based on the information it has on file, and will transfer the call to an agent when needed.

Why You Should Not Use IVR for Inbound Queries

Whenever a consumer is interested in making a payment and resolving their debt, they might be turned off by the poor customer experience offered by the IVR. In non-revenue generating inbound calls, the IVR system is often incapable of resolving the query, and therefore will likely transfer the call to a live agent.

U.S. debt collection agencies report that their agents spend about 20% of their time answering inbound calls! Many of these calls are not revenue-generating, so they consume time and resources that could be easily allocated to collection calls.

The Benefits of Adopting Voice AI for Debt Collection Agencies

Here are some of the benefits reported by collections agencies that have adopted Skit.ai’s Voice AI platform:

Interested in learning more about how Voice AI can help you streamline your collection strategy and reach your full potential? Schedule a call with one of our experts using the chat tool below!

Tips for an Agile, Digital-first Debt Collection Agency

Posted on by Simone Somekh

The State of the U.S. Debt Collections Industry in 2023 

Let’s start from the data. The U.S. debt collections industry is worth $20 billion in 2023, according to IBIS World research. Given that the industry was estimated to be worth only $11.5 billion in 2018, the growth has been remarkable—approximately 73.9% in just five years.

About half of the market share is dominated by the 50 largest ARM companies, over a total of almost 7,000 businesses.

As the industry continues to grow, it has become challenging for executives to keep up with the times. While recovery rates are a key factor influencing competitiveness, technological innovation is the other element defining a company’s success. Digital transformation is no longer a “plus” for agencies, but rather a “must,” and while many ARM companies have embraced change, there is still a long way to go.

In this article, we’ll discuss what it means for a debt collection agency to be agile and adopt a digital-first approach and we’ll go over a few examples of types of technology that agencies are adopting.

What Does It Mean for a Debt Collection Agency to Be Agile?

Business agility is defined as the ability to make changes and decisions quickly. Usually, companies become agile by prioritizing data-driven decision-making, efficiency, flexibility, and innovation. In other words, agility is the exact opposite of stagnation.

According to Entrepreneur, agile decision-making can be related to a variety of issues, such as responding to new competitors or market changes; solving problems as they emerge; launching new products and services; and minimizing time spent internally.

Why is it important to be agile? McKinsey has found that companies that undergo a successful agile transformation gain a 30% increase in operational performance, efficiency, and customer satisfaction.

Digital transformation is a key process influencing agility.

“Some ARM companies have been slow to adopt new technologies and, as a consequence, they are now at a competitive and operational disadvantage,” explained Scott Carroll, industry veteran. “Some didn’t know they needed technology, or they didn’t know exactly where to look and where to start. But now the industry is quickly catching up.”

Carroll explained that tight regulations, concerns over compliance, and widespread litigation are some of the reasons why the industry has been lagging behind in innovation. “Businesses have been naturally more cautious. But now, as they get a better understanding of the regulations, they’re finally looking toward technology to improve their operational efficiency,” he said.

One strength the collections industry has is that it’s usually prepared to pivot: “Because of fast-changing regulations and client needs, the industry needs to be prepared to respond to change.”

How the Industry Is Catching Up by Becoming Digital-first and Tech-savvy

A growing interest in innovation is driving the push toward agility in the ARM industry. Staying updated on new technologies, monitoring emerging tech companies and solutions, and investigating how leading technologies like artificial intelligence can be applied to debt collection are the key tips to implement an agile transformation.

In January 2023, the industry held its first-ever conference entirely dedicated to technology. ARMTech, which took place in Nashville, was a four-day event aimed at helping executives understand the technology that is revolutionizing how debts are collected. The event was organized by Mike Gibb, industry leader and editor of the website AccountsRecovery.net.

The industry is moving toward a digital-first model, as it’s evident that consumers prefer to deal with companies offering omnichannel services and interact through digital channels. Omnichannel includes a wide range of channels, such as website, mobile app, social media, telephony, chatbot, voicebot, SMS, and email.

Telephony systems and dialing platforms are essential for any contact center, including a collection agency, whose business largely depends on outbound and inbound calling. These platforms include TCN, Twilio, Genesys, LiveVox, RingCentral, 8×8, Five9, and more.

Collection management software is the other most common type of software adopted by collection agencies. These systems of record enable agencies to manage their portfolios in one easy-to-use, centralized platform updated regularly by the agents.

Conversational Voice AI, the technology behind voicebots, is gaining ground as a widely popular technology in the ARM industry. Skit.ai has developed an AI-powered Digital Collection Agent, which handles human-like outbound calls to collect payments from consumers. The voicebot intelligently interacts with the consumer, handling payment reminders, negotiation, and processing. The Digital Collection Agent does not substitute the human agents but rather augments their work by handling the most repetitive and tedious tasks. This solution can be easily integrated with the other tools in use.

Voice AI should not be confused with IVR (interactive voice response) systems, a legacy technology that requires consumers to navigate lengthy menus through DTMF inputs or basic voice-enabled inputs.

Key players in the industry are also adopting business intelligence and analytics solutions that support agents during and after their calls with consumers. Prodigal’s solution offers real-time agent assistance, auto-writes call summaries, and analyzes collection calls on dozens of parameters to monitor and boost performance and compliance.

What’s Next?

It looks like 2023 will be a defining year for the collections industry in regard to digital transformation and agility.

“Agility is a key operating factor for success,” advised Scott Carroll. “My tip is to stay current on technology, investigate new tools, stay on top of the latest trends, and keep your eyes open for anything that helps you increase your margins and reduce your exposure. This will ultimately lead to increased collections.”

How Voicebots Can Help Collection Agencies Prepare for Tax Season

Posted on by Simone Somekh

Tax season is the busiest time for collection agencies. With 3 in 4 U.S. residents receiving a tax refund from the government during this season each year, many of those who need to settle a debt wisely take advantage of these reimbursements to pay off their outstanding balances. In 2022, the average tax refund for individuals in the U.S. was $3,039.

Collection agencies can take advantage of this window of opportunity to maximize recovery rates and agency profits. During tax season, the industry usually experiences a peak in payments, paired with a general openness of consumers to engage with collectors. This year, due to the high inflation rates, many consumers will be relying on tax refunds to pay off their debt.

Call automation with Voice AI — the technology behind voicebots — can transform tax season for the better, making it a less stressful and more profitable time for collection agencies. In this article, we’ll go over how agencies can prepare for the volume surge in calls during tax season by adopting Conversational Voice AI.

The Challenges Collection Agencies Face Before and During Tax Season

While tax season undoubtedly represents a window of opportunity, it also presents several challenges for collection agencies. The best way for management to tackle these challenges is to prepare in advance and to involve their collectors on the floor in these preparations.

Here are some of the most common challenges collection agencies face before and during tax season:

Hiring new collectors: To handle the surge in call volume, collection executives often need to hire new collectors to join their staff. How many collectors should you hire? Hiring takes time and resources, as managers don’t want to hire the wrong person; since the COVID-19 pandemic, it’s become more challenging to find new talent, as people are inclined to seek more flexible jobs, and salaries have become more competitive. You’ll need ample time to find new talent and train new hires.

Training staff to prepare for the season: Whether newly hired or seasoned, all collectors should receive the appropriate training before the beginning of tax season. All training materials should be easily accessible, focusing on the challenges and skills specific to this time of the year.

Updating the agency’s compliance management system: Every agency should have a compliance management system — often found within the collections management software. This system is used to store and organize the current laws and regulations of the ARM industry. Before tax season begins, the agency’s compliance officer or manager should ensure that the system is up to date with the latest regulations; outdated regulations should be removed. Additionally, this system should be easy to access and browse for collectors.

Planning a successful settlement campaign: The surge in collection volume encourages some agencies to offer small discounts for a limited time; other agencies take it to the next level by planning a wide-scale settlement campaign. For a settlement campaign, the agency focuses on a specific group of accounts, typically consumers with higher recovery rates and debt whose age falls within a specific timeframe. If the agency services third-party debt, then it also needs to coordinate the campaign with the original creditors. Executives must decide what balance reduction they are going to offer those consumers and the running time of the campaign. The entire process can make the agency extremely busy, and things are likely to get hectic for the collectors on the floor.

How Voice AI Can Make Your Life Easier During Tax Season

Voice AI, the technology behind voicebots, is taking the ARM industry by storm. Voice AI enables first and third-party collection agencies to automate unlimited collection calls and process on-call payments, making it much easier for executives to scale up their collection campaigns without the need to hire extra or seasonal representatives.

A Voice AI solution like Skit.ai’s Digital Voice Agent contacts the consumer, establishes right-party contact, reminds them of the outstanding balance, and encourages them to make an on-call payment. The agent can also offer the consumer alternative payment options and intelligently handle a dispute. It’s important to note that Voice AI is not IVR (interactive voice response), an outdated and unpopular solution commonly used in customer service.

Call automation with Voice AI is transforming collections across the board, as it enables collection agencies to handle many more accounts simultaneously, recovering debt at a fraction of the cost. Additionally, this technology augments the work of live collectors, who are empowered to handle more complex cases and focus on more revenue-generating tasks.

While this technology is helpful all year round, during tax season it becomes particularly essential. Here’s why:

Make it super easy for consumers to pay. Any roadblock in the payment process can significantly hinder the recovery of the debt. That’s why customer experience plays an important role, and making the payment as easy and frictionless as possible is a priority for your agency. Voice AI makes the process smooth and pleasant for consumers.

No need to hire additional collectors during tax season: Voice AI enables executives and managers to scale their operations, without the need to hire additional collectors during this busy season. This way, they can continue to rely on their trusted team and get the extra help they need from the Digital Voice Agents, who are unlimited in number and can handle thousands of calls simultaneously. Collections with Voice AI are significantly cheaper; additionally, voicebots don’t take any commission!

Fewer concerns about compliance thanks to Voice AI: Executives can worry less about complying with laws and regulations since the Digital Voice Agent is fully trained to comply with regulations at the state and federal levels. Unlike live collectors, the automated agent is always compliant and does not go off script.

Execute a smooth settlement campaign at scale: With Voice AI, collection agencies can execute a settlement campaign at scale, reaching thousands of consumers in a very short amount of time to offer the settlement and collect the payments.

Are you ready to take the next step toward call automation with Voice AI? Schedule a free demo with one of our experts using the chat tool below!

4 Ways AI Voicebots Are Transforming Auto Finance Collections

Posted on by Simone Somekh

There have been a total of 13.7 million car sales in the U.S. in 2022, according to an IBISWorld estimate. Car sales have been declining since the beginning of the COVID-19 pandemic due to many factors, including the growing prevalence of remote work, supply chain issues, and a looming recession.

As a consequence, interest rates have been rising significantly, hitting over 6.0% and negatively affecting the number of car sales. With higher prices, bigger loans, and higher interest rates, comes an increase in delinquencies. It has become an issue for many auto finance companies to keep up with the high number of delinquent borrowers.

In this article, we’ll discuss how Voice AI (the technology behind a voicebot) can transform auto loan collections in different ways.

What Is Voice AI?

Also referred to as a voicebot, Voice AI is a technology that enables companies to automate calls with customers from start to finish without requiring the involvement of a human agent.

AI-powered Digital Voice Agents are capable of handling intelligent conversations with users. The technology understands what the user needs and helps them effectively resolve the issue in just a few minutes. Voice AI should not be confused with Outbound IVR (Interactive Voice Response), a dated technology that consumers tend to dislike.

Auto finance companies that perform collection calls are now turning to Voice AI to automate many of the repetitive, tedious calls they used to perform manually and allow their live agents to focus on more complex and revenue-generating tasks. The Digital Voice Agent engages with the borrower, verifies their identity, and collects the payment on-call, covering up to 70% of the company’s outbound call volume.

To better understand what Voice AI is, think about Siri or Alexa, but for collections. However, there is one difference. While voice assistants like Alexa can only handle one or two conversation turns, a solution like Skit.ai’s Digital Voice Agent is designed to address issues that often require several conversation turns. Just like humans need to gather the context before solving a problem, a Digital Voice Agent might ask multiple questions before proposing a resolution.

What Are the Most Common Uses of Voice AI in Auto Finance Collections?

Voice AI is just one of the many artificial intelligence trends that are taking the auto industry by storm. Its ability to automate collection calls and other common types of outbound calls to borrowers is particularly appealing to auto finance leaders looking for ways to cut contact center costs and maximize profits.

Let’s dive deeper into the four most common uses of Voice AI (the technology behind Skit.ai’s Digital Voice Agent) in auto finance collections:

Welcome calls: Lenders and auto finance companies typically deliver an initial “welcome call” to borrowers to let them know that they are servicing the loan or in charge of collecting payments. While these calls are important, they are not revenue-generating and utilize the precious time of the company’s live agents.

Skit.ai’s voicebot solution can easily initiate an outbound call to borrowers to deliver the message and then answer some of the customers’ most common questions.

Payment reminders: Auto finance agents typically spend most of their time calling borrowers to remind them of payments that are due soon or payments that are already overdue. Reaching borrowers is not always a straightforward process! Agents have to establish right-party contact, explain who they are, and remind the borrower about the payment. When the volume of loans increases, it can be challenging for managers to scale the contact center to fit the need of the moment.

Skit.ai’s Voice AI solution can offload up to 70% of the calls from live agents, handling payment reminders automatically. Skit.ai’s clients have even reported that some borrowers prefer to interact with a voicebot rather than a human agent, as it can be embarrassing for them to discuss pending payments and the risk of going delinquent. The voicebot can easily establish right-party contact, remind the borrowers of the due balance, and offer different ways to pay it off.

On-call collections: The end goal for any collector is to recover the payment from the borrower; if the borrower is willing to make the payment on-call, even better. While this part of the process is directly revenue-generating, it still takes time and resources to complete.

Skit.ai’s Digital Voice Agent has the capability to collect the payment during the call, making the process significantly cheaper for the company servicing the loan. The collection is processed through a payment gateway of the company’s choice.

Autopay or ACH sign-up: Many auto finance companies servicing loans initiate outbound calls to borrowers to offer them to sign up for autopay. With autopay or ACH, borrowers can automate payments from their credit card or bank account so that they can be processed on a regular basis.

Skit.ai’s Digital Voice Agent can easily call borrowers, explain how autopay works, and offer them to sign up on call. This is an ideal scenario for auto finance companies, as it ensures a regular cash flow.

How Do Auto Finance Collections Work?

Now that we know what Voice AI is and the main use cases in auto finance, let’s go over the main steps of a standard collection call handled by one of Skit.ai’s Digital Voice Agents.

The voicebot follows these steps:

  1. Triggers the outbound call based on pre-determined criteria
  2. Establishes contact with the borrower (RPC) and reminds them about the payment
  3. Collects propensity data and reasons for potential non-payment
  4. If the customer is interested in making the payment right away, the Digital Voice Agent guides them through the process via a payment gateway
  5. Persuades the customer to pay at the earliest, or offers alternate payment plans
  6. Feeds data to the CMS (collection management software) and provides analytics for further action
  7. Performs auto-callback on request, auto-retries, hot transfer to agent

Are you interested in learning more about how Skit.ai’s Augmented Voice Intelligence platform works and how your auto finance company can adopt it? Schedule a call with one of our experts using the chat tool below!

Voice AI: The Answer to Every Major Auto Finance Collection Challenge

Posted on by Simone Somekh

Auto finance companies dealing with collections face a pivotal moment of seemingly unprecedented activity.

Here’s what’s happening right now: car prices have hit a record high, interest rates are skyrocketing, and — as a consequence — the auto finance industry is facing a high number of delinquencies. As they find themselves with very high numbers of loans, lenders and collectors have to drastically scale up the number of outbound calls to borrowers.

While challenging times are not always fun, they also allow us to think outside the box and come up with innovative solutions. In this article, we’ll go over some of the major challenges related to auto finance collections and explain how Voice AI and call automation can solve each of these problems.

A growing number of auto finance companies are starting to look to Voice AI (the use of automated voicebots) as the go-to solution to handle both outbound and inbound calls with customers and borrowers. In particular, voicebots are used for collection calls and payment reminders.

Voice AI-powered Digital Voice Agents can handle human-like conversations with users, eliminating wait times and enabling a much larger number of calls to be handled at the same time. A Voice AI technology like Skit.ai’s Augmented Voice Intelligence platform allows auto finance companies to handle collection campaigns at a fraction of the cost.

Challenge 1: Scalability

Auto loan volume varies significantly depending on the year and the season. Anyone who has been in the industry for a while can tell you that they’ve seen very busy seasons as well as quieter ones. Because of the unpredictability of these changes, it can be difficult for an auto finance company to easily adapt and scale either up or down. When facing a particularly busy period, auto finance companies need the ability to quickly scale up to handle larger volumes of loans and customers.

How Voice AI can help you solve this challenge: Voice AI enables auto finance companies to scale up and down with just a few clicks, deploying as many Digital Voice Agents as they need depending on the year and season. As soon as loan volume goes down, the company can simply scale down its use of the Voice AI solution.

Challenge 2: Cost

Collections can be an expensive process. Agents or collectors typically have very large portfolios, with many accounts to reach out to; because the process still tends to be manual for the most part, it takes time. Additionally, if your collectors take a commission, that can also reduce profits.

How Voice AI can help you solve this challenge: By automating the collection process, Voice AI can significantly augment the work of your live agents on the floor, contact many customers simultaneously, and massively reduce costs. Additionally, an AI-powered Digital Voice Agent does not take commissions!

Challenge 3: Hiring and Training

A poorly-trained team of agents and collectors can be a recipe for disaster. As new loans pile up and many become delinquent, it can be tempting to throw new employees into the midst of the action; but if the agents are not qualified and they are not familiar with the existing laws and regulations, you might find yourself in trouble in no time.

How Voice AI can help you solve this challenge: A Digital Voice Agent requires minimal training at the very beginning of the deployment process. After that, you can easily tweak its conversational flows and capabilities with just a few simple changes to the Voice AI platform, either on your own or with the help of your provider.

Challenge 4: Talent Shortage

Since the pandemic and the Great Resignation, many industries, including the auto finance and debt collection industries, have been faced with a shortage of talent. The lack of human capital poses serious challenges to auto finance companies, whose teams and management need to deal with overwhelming workloads. Attracting talent can be a costly endeavor.

How Voice AI can help you solve this challenge: Automation is the answer to the human capital shortage. Voice AI can fill the gaps created by the lack of talent and help the existing team members handle the most repetitive and mundane calls. The adoption of a debt collection software like Skit.ai’s platform can solve this problem in a very short time.

Challenge 5: Agent Attrition

While it’s hard to define the exact attrition rate in the collections space, from talking to many companies operating in both the collections and the auto finance industries, we know that attrition is a real challenge for them. In a 2016 Consumer Financial Protection Bureau survey, large debt collection agencies reported an average turnover rate of 75% to 100%.

Agents and collectors are often dissatisfied, frustrated, and understimulated, so they hop on to the next job opportunity as soon as they find one, whether it’s because the pay is better or because they think the work will be more rewarding.

Every time your company loses one team member, you’ll have to undergo the process of recruiting, hiring, and training a substitute, which can be costly and time-consuming.

How Voice AI can help you solve this challenge: A Voice AI-powered agent never gets tired of handling repetitive and mundane tasks. With the help of Voice AI, you can also focus on retaining your existing talent, as you can ensure every team member has the opportunity to focus on more rewarding and complex tasks.

Challenge 6: Compliance

The collections industry is affected by so many laws and regulations that, if you haven’t been in this space for a while, it can be overwhelming to understand what you can and cannot do. How often can you call borrowers? Are there any times of the day you can’t call them? What do you do if a borrower asks not to be contacted again? How do you handle the privacy of your customers? How should you safely process payments?

These questions are just the tip of the iceberg when it comes to compliance! Think about the TCPA, the FDCPA, the SCRA, PCI standards, and so many others. Additionally, some of these regulations vary depending on the state where the borrower resides.

An auto finance company pursuing collections must be well-versed in these rules and should stay up to date, as lawsuits abound and regulations change relatively often. Better safe than sorry!

How Voice AI can help you solve this challenge: Digital Voice Agents, unlike live agents, don’t go off-script, misspeak, or get confused. When they are trained to follow a set of regulations, they just stick to it. With the help of Voice AI, you can let the solution do the work while you handle other tasks.

Challenge 7: Recordkeeping

For an auto finance company, few things can be more disastrous than poor recordkeeping! Especially when it comes to collection efforts, notes, documentation, and records are crucial. That’s why total reliance on manual recordkeeping is at best risky and at worst harmful. Collectors should keep track of each interaction with their borrowers so that they can follow up and make progress with each new conversation.

Additionally, other team members — such as fellow collectors and managers — should be able to easily access the notes and track the progress made with each account. Automated notetaking is one possible solution to tackle this challenge.

How Voice AI can help you solve this challenge: A Voice AI platform automatically keeps track of all customer interactions, taking notes of every conversation and capturing payment disposition and propensity to pay. With Voice AI, you get to automate conversations with borrowers, and you can be fully aware of the background and context of each account. Whenever a live agent wants to take over, they can easily do so by looking at the record of the relationship between the auto finance company and the borrower.

Are you curious to learn more about how Skit.ai can transform your auto finance operations, customer interactions, and collection efforts? Schedule a free demo with one of our experts using the chat tool below.

Year in Review: Skit.ai’s Most Notable Moments in 2022

Posted on by Simone Somekh

2022 has been a pretty eventful year for Skit.ai! In this article, we will re-live some of our company’s most notable moments in the U.S. in 2022, including media mentions, award recognitions, and more. This was an exceptional year for our company and the Voice AI industry at large. Get a cup of coffee or tea ready, and join us as we go down memory lane!

Skit.ai Establishes New NYC Headquarters

The year was marked by the announcement of Skit.ai’s new New York City headquarters.

In the announcement, Skit.ai’s CEO Sourabh Gupta said: “We’re continually listening to our customers, conducting market research, and making enhancements to our artificial intelligence system to deliver a best-in-class solution that helps contact center agents offer modernized and reliable customer service, leaving a lasting impression and positive satisfaction rate for their company. We look forward to expanding our U.S. customer base and building new relationships to help elevate the customer experience, optimize costs, maximize operational efficiency and increase company revenue.”

Skit.ai Mentioned in the Washington Post

In the summer of 2022, Christopher Elliott, a reporter at the Washington Post, quoted Sourabh Gupta in an article about customer service in the travel industry. The piece explained that Skit.ai develops an artificial intelligence-driven voice technology.

Gupta was quoted saying, “Travelers should look for companies that offer round-the-clock assistance and a way to reach key information, even when human support agents might not be available.” The article continued: “You can tell your travel company has this by looking for a ‘contact us’ feature on its site that offers 24/7 phone, chat and email support.”

Skit.ai’s Big Win at the CCW Excellence Awards

In July 2022, Skit.ai was given the “Disruptive Technology of the Year” award at the CCW Excellence Awards Gala held in Las Vegas. The event is part of Customer Center Week and recognizes “the most innovative companies and top-performing executives for their extraordinary contributions to the customer contact profession.”

Upon accepting the award, Gupta said: “We are thrilled to be recognized by CCW. This award underscores the reason for our existence – to improve contact center operations, so both the agents and customers have a more seamless experience. Being recognized for the most disruptive technology solution in contact center operations is a reminder of why we all come to work each day. We’re excited for what the future has in store for our company and the industry at large.”

Skit.ai India Certified as a Great Place to Work®

In August 2022, Skit.ai’s Indian branch was certified as a Great Place to Work® for the year 2022 in the mid-size company category.

As part of the Trust Index Employee Survey conducted by GPTW, employees ranked the company favorably on parameters such as Credibility, Respect, Fairness, Pride, and Camaraderie. The certification affirmed the company’s core cultural values of striving for excellence, being a learning organization, building a client-first mindset, exercising constructive disagreement, and fostering commitment at work.

Skit.ai Named Among Best Business Technology Solutions at the International Business Awards

In August 2022, Skit.ai was honored with yet another award in the United States. The solution was named a Bronze Stevie Winner in the Business Technology Solution: Artificial Intelligence/Machine Learning Solutions category as part of the International Business Awards.

This award recognized Skit.ai’s Augmented Voice Intelligence Platform as an innovative technology solution that fuels effortless contact center conversations to manage customers’ needs more efficiently and painlessly.

The Stevie Awards are the world’s premier business awards that honor and generate public recognition of the achievements and positive contributions of organizations and working professionals worldwide.

Skit.ai’s Other Notable Media Mentions in 2022

CMSWire quoted Skit.ai’s CEO Sourabh Gupta in an article about the ways the COVID-19 pandemic has affected the Voice of the Customer. Gupta said: “Especially in customer service roles such as restaurants and stores — employees have reported that customers are more demanding than ever before. With many employees in this industry switching to better-paying industries, this only increases customer frustration as these establishments try to find help.”

In another article, CMSWire asked Gupta to share his insights on how AI is shaping the future of customer interactions. “With Voice AI, brands can cut down on customer wait times, shorten the time they spend on the phone, and effectively answer their questions faster,” said Gupta.

TechBullion published an extensive interview with Gupta, who shared his vision for the company and the conversational AI industry at large. “Our vision in creating the company is to elevate customer experiences and lay the groundwork for the future of voice interactions,” Gupta said.

Also VentureBeat featured Skit.ai in an article about the ways AI predicts hurricanes and answers calls for help in their aftermath. The reporter noted that, “with emergency hotlines, hospitals and utility call centers being inundated with calls, speaking with a voicebot during a time fraught with anxiety and fear can help.”

“In a sensitive or dangerous situation, Voice AI can be used to provide customers with crucial information in real-time, answer questions and redirect the more complex calls to a human agent,” Gupta told VentureBeat.

Last but not least, Authority Magazine published an extensive interview with Gupta conducted by Tyler Gallagher. In the interview, Skit.ai’s CEO discussed his personal journey, his vision for the company, and the AI industry’s current challenges.

We are looking forward to an even more exciting and productive year in 2023!

Hungry for more? Follow our page on LinkedIn and stay tuned for many more updates in 2023. Happy New Year!

Why Auto Finance Companies Are Looking to Artificial Intelligence for 2023

Posted on by Simone Somekh

Since the COVID-19 pandemic, massive supply chain delays, and the ongoing recession, auto finance companies have had to be as competitive and forward-thinking as possible. As they close an unprecedented year, many companies are looking to invest more in technology, specifically artificial intelligence, in 2023.

What’s Happening in the Auto Finance Industry Right Now

As we approach 2023, four facts are defining the auto finance industry:

  • Car prices have never been as high as they are right now
  • Record car prices are leading to higher auto loans debt
  • Auto loan interest rates are climbing
  • Auto loan delinquencies are increasing

Let’s break these statements down with the help of a few data points.

Car prices are record-high: According to the Consumer Financial Protection Bureau (CFPB), the average price for a new car reached a record-high price of $48,182 this past summer. Also used car prices are nearing a record high, as they have been averaging $28,219.

High car prices = higher auto loan debt: The total dollar value of outstanding auto loans increased by $33 billion from Q1 to Q2 in 2022.

Interest rates are climbing: In Q3 of 2022, interest rates climbed to 5.7% for the first time since 2019.

Delinquencies are increasing: Loans started in 2021 and 2022 show higher delinquency rates than the ones started in previous years. This is likely due to the increase in loan size, interest rates, and monthly payments.

Financial institutions, in general, have been eager to adopt AI solutions to process loans and vet borrowers. But AI can do much more than professionals in the auto finance field might expect.

The Different Uses of AI in the Auto Finance Industry

With the high demand for auto loans, providers have been adopting new solutions to streamline operations. One of the biggest focuses in auto finance right now is the digitization journey—starting with digital contracting. Digitization makes operations more efficient and scalable, helps to improve compliance, and enhances the customer experience. Yet, artificial intelligence can achieve much more than just “going paperless.”

AI can expedite many processes, saving time, money, and other resources; it can generate data-driven predictions much faster and more accurately than humans. While AI can be extremely helpful, it does not substitute human work but rather augments and simplifies it. Paired with human expertise, AI can be an incredible asset for auto finance companies.

Here are some of the applications of AI:

Document management with AI: Document management with AI enables companies to classify, process, and cluster documents, extract data, secure sensitive information, and recognize signatures. This can be useful when processing applications; it helps reduce errors, improving the consistency and accuracy of the data.

Decisioning with AI: AI can assess risk and help auto finance companies in the approval process. While AI should not make irreversible decisions independently, it can help companies to make data-driven decisions.

Predictions and behavioral models with AI: Predictive models allow auto finance companies to better understand their customer base and its behavior as they identify patterns that can be useful for future decisions.

Customer service and communications with AI: Chatbots and voice bots have the ability to transform and streamline customer service, improving the company’s customer experience and providing a distinct competitive edge.

Collections and payments with Voice AI: Conversational Voice AI can also help auto finance companies in the collection process, as it automates outbound calls to customers, reminding them of outstanding payments and collecting payments over the phone.

Agent intervention with AI: Thanks to AI-powered predictive models, auto finance companies can flag accounts that require additional communications and facilitate agent intervention.

Voice AI Could Be the Big New Auto Finance Trend in 2023

Of all the existing trends we’ve mentioned, Voice AI seems to be the one that will get a spotlight in 2023. More providers are turning to Voice AI to automate customer service calls for both inbound and outbound use cases.

Voice AI companies like Skit.ai develop voice bots to augment the activity of human agents, handling the majority of repetitive, mundane calls.

Collection calls and payment reminders are one category of customer interactions that a Digital Voice Agent can easily handle from start to finish—from dialing the number and establishing right-party contact to engaging in a conversation with the customer and collecting payments via gateway.

The Voice AI platform enables auto finance companies to call thousands of different customers simultaneously, sending them reminders and collecting payments on-call or via a third-party gateway. The Voice AI platform can be easily integrated with multiple tools and applications, such as telephony platforms, CRM systems, payment gateways, and messaging tools; all while complying with the latest laws and regulations.

Context is critical: The Digital Voice Agent keeps track of the information obtained from the customers, feeding the data to the CRM in real-time and providing helpful analytics for future action.

As a result, companies adopting Voice AI can collect payments more efficiently, saving a lot of time and money they would otherwise spend if they did everything manually.

Voice AI can be adopted for many use cases, not just payments and collections. Voice bots can be employed for both inbound and outbound use cases, customer service, and other types of communication.

Interested in learning more about how Voice AI can transform the auto finance industry? Schedule a call with one of Skit.ai’s experts using the chat tool below.

How Skit.ai Tackles Positioning and Marketing for Its Voice AI Solution

Posted on by Simone Somekh

For the third article of our “Meet the Team” series, we had a conversation with Vignesh Ramalingam, our Director of Product Marketing & Demand Generation. Vignesh (a.k.a. Vicky) is based in Bangalore, India, and manages over 12 team members across Product Marketing, Content Marketing, and Demand Generation.

Hi, Vicky. Tell me about yourself and your professional background.

Hi, Simone. I’ve always been curious about technology and human-centric design. For over a decade, I’ve been working in marketing for software companies, and I really enjoy being immersed in this space. One of my favorite aspects of Skit.ai’s Augmented Voice Intelligence solution is that it can be used for many verticals and use cases.

Voice AI is a very hot space right now, and many vendors that previously focused on other AI technologies are now tapping into it. How do you ensure that Skit.ai emerges as an industry-leading voice-first company?

Our clients see how advanced our technology is and how committed our team members are to quickly delivering seamless voice interactions with customers. I think that the quality of our technology and the commitment of our delivery team are two defining factors of our success.

While it’s true that more companies are starting to explore Voice AI, we believe that being a voice-first company — which has been focused on developing industry-leading voice technologies for several years — gives us a great advantage.

Without a competent marketing team, selling even the most exceptional solution would be challenging. What are the key ingredients for a B2B SaaS marketing team to succeed?

We certainly rely on talented and passionate team members across all teams to deliver an ever-evolving marketing strategy and help our sales team explain what our solution can do for them and what our technology capabilities are. Our team includes professionals in product marketing, content marketing, demand generation, and graphic design.

A key ingredient for success is ensuring that the marketing team is aligned with all the other teams — such as sales, delivery, product, etc.

One framework I’m fond of is “GACCS,” an acronym that stands for “Goals, Audience, Creative, Channels, and Stakeholders.” I encourage my team to take a minute to think about these five principles before diving into a new project:

  • Goals: The OKRs and KPIs towards which the project contributes.
  • Audience: The prospects or customers the project targets.
  • Creative: The creative elements and the value they add to the project
  • Channels: The channels used to distribute the work.
  • Stakeholders: The team members involved in the project.

What were some of the challenges that companies might face when they expand into new regions, and what are some of the lessons you’ve learned along the way?

New York City has been a great home for Skit.ai in the United States. The company has focused on hiring some of the best talent to join the team at our Madison Avenue office.

When it comes to expanding into a new region or industry, taking the time to do research is one of the most critical tasks for the marketing team to undertake. You have to understand your target audience: who they are, what they’re looking for, and what type of content they consume. Only then can you invest resources in developing strategies and assets.

While the technology we build is very complex, one of the tasks of the marketing team is to simplify it. What are your thoughts on this, and what strategies do you find to be most effective?

Sometimes it’s important to take a step back and look at the solution and technology with the eyes of an outsider. Many people who may benefit from our Augmented Voice Intelligence platform might not be familiar with the intricacies of Voice AI, spoken language understanding, and the integrations needed for our solution to be effective. Our mission is to explain how our technology works and how it can transform a company’s customer service and customer experience.

Do you want to learn more about Voice AI? Check out our blog.

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