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ASAPP Executive Interview

ASAPP Helps Businesses Empower Agents with Efficacious Desktop AI Technology   

In today’s increasingly complex contact center environment, attrition has become an even greater threat. Disenchanted employees are more likely to run out of patience quicker when they feel they are not given proper support. It’s critical for organizations to provide tools that allow individuals and organizations to realize their full potential. ASAPP takes an agent-focused approach, offering research-based AI, machine learning, speech recognition, robotic process automation, and natural language processing tools to empower agents and make it easier for them to serve customers.

CrmXchange caught up with Chris Arnold, VP CX Strategy for ASAPP as the company was preparing to exhibit at CCW in Las Vegas to discuss what differentiates their AI solutions in the marketplace. ASAPP also struck a partnership at CCW with TaskUs, a leading contact center provider (BPO) focused almost entirely on digitally native, hyper-growth companies that won the CCW Excellence Award for BPO of the Year. 

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Chris, please tell us a bit about yourself.

As someone who started his career as a phone agent, I was motivated to join ASAPP by my sense of empathy for those who are trying to succeed at their very complicated and difficult jobs. I spent much of my career somewhere between the front lines-- supervisor, contact center director, and operations-- making numerous technology and process decisions on behalf of these customer-facing employees. I was responsible for purchasing a lot of technology over the years and also had the unique perspective of being an ASAPP customer. I have sat on both sides of the table.

As an ASSAP customer, what was it that attracted you to use their technology?

I was initially attracted by their focus on the agent, an area which has not been developed as much as it should have been. Suppliers have needed to modernize and bring intelligence…in this case, artificial intelligence… to the complex contact center space. This should be done across both the voice and digital channel in service of agents whose job has grown more difficult over the years. Much of the technology I bought was based on automation: chatbots, IVRs, conversational AI. But with all that, we infrequently had the opportunity to put high-functioning technology on the desktops of the agent that they could use in real time. That is a key difference that makes ASAPP stand out.

Walk me through how the technology works.

In my world, agents took between 40 and 50 interactions each day. That could have been in a chat or voice environment; we did both. But the desktop technology—the actual UI—was ASAPP. While some customers might not choose to use the ASAPP UI, the agents I worked with were using it. Particularly in the digital environment, they were using the UI to chat and message with customers. We were also augmenting the agent by having numerous micro processes automated.

One of our products, Auto Summary, automatically summarizes the conversation and can save 1-2 minutes per interaction. It is particularly effective for repetitive, mundane tasks that agents seem to go though in about every interaction.  We try to automate as much of that as possible. Think about troubleshooting a wireless smart phone outage where there were a number of back-end systems.  Prior to ASAPP, our agents had to manually seek out information from those 20 systems. With ASAPP sitting on top of the desktop, all the information was brought In front of the agent, whether it was in a knowledge base or in an outage management system. Having all the information at their fingertips allowed the agent to focus on the conversation as opposed to the transaction.

Is ASAPP monitoring the conversation in real-time?

ASAPP transcribes the conversation in real time which can take place in a voice environment where it utilizes real-time automatic speech recognition (ASR), which automatically transcribes the verbal conversation between the customer and the agent. In a digital environment, the agent already has the transcript as the conversation is being typed back and forth. You can take those words from the conversation—what we call ‘entities,’ keywords, or key phrases—and through machine learning, ASAPP has a high degree of confidence for bringing up a specific knowledge articles or can invoke a specific action, automate a workflow, or mine an outage management system to pinpoint that particular customer’s location. There are applications across all verticals.

How does a company prepare for an ASAPP implementation?

Many customers have antiquated legacy technology in their technology stack. In many cases, there are APIs available. If you think about deploying artificial intelligence, specifically machine learning (ML) algorithms, they function on large quantities of data. It really matters what data a business feeds through to train these models so there can be continued effective learning. Ultimately, what gets produced for the agent has a high degree of efficacy:  producing information in real time to resolve issues, drive higher customer satisfaction, net promoter scores, and reduce AHT…all of those critical KPIs.

But the business has to make sure that the data the agent requires is running through the machine learning algorithm in real time is accurate. There’s so much data in every organization that provides context for swift resolution, but APIs aren’t always available. So, the most important thing is ensuring that the data needed to amplify the agent’s work, to feed these machine learning algorithms, is available.

There were times when we had to take an antiquated legacy data warehouse stream, normally batch processed, and do work on the back end to make that data accessible to agents in real time by using an API.

A good way for a company to get started is to take a look at its data architecture.to see if it can be made available. The conversations back and forth are easy to obtain and are what is needed to feed the algorithm.

Along with the data, what else do companies need to think about?

Beyond the data, enterprise companies need to look at all of the technologies in their stack. A tool like ASAPP can facilitate the conversation between a customer and agent, expediting the conversation to clarify offers to customer for increased success. Businesses need to look at what they have and gauge its efficacy and if it’s doing what is needed. A big part of driving efficiency and improving customer service is simplifying an overly complicated tech stack.

Does ASAPP guide the agent with what to say, or does it provide information on the desktop only?

In the light of the pandemic, consumers are rapidly moving toward using chat or messaging to communicate with companies. ASAPP is nudging the agent, giving them options on how to reply in real time. These prompts are based on what best agents have said historically to drive higher satisfaction and achieve greater efficiency. In a voice environment, there’s a balance to be struck that doesn’t get the agent frustrated by limiting their options and diminishing their authenticity with the customer by popping up knowledgebase content that is relevant and helpful.

Often agents have to click as many as 4 or 5 times to find an appropriate article and in many cases read through multiple paragraphs while trying to keep up the conversation. This can be awkward in real time, sometimes leading the agent to have to put the customer on hold. This is no longer necessary in this AI Native world where the solution is transcribing the conversation and bringing forward the answers to the consumer’s questions—and guiding the agent on what to say but allowing them to do it in their own way. ASAPP produces a summary of the article in real time with a latency of milliseconds—instead of minutes—which is imperceptible to the customer on the other end. ASAPP allows agents to avoid lengthy delays while engaging in a free-flowing, natural sounding conversation. So, instead of having to focus on getting through the transaction, agents equipped with ASAPP can focus on servicing the customer while driving desirable outcomes like first contact resolution.

How does call summarization help the agent?

Call summarization is a feature that is quite important. It not only listens to the call but can invoke actions, such as when an agent says they will get back to the customer in three days, it triggers an automated action so that no promises are broken resolving another common CX issue. Instead of relying on agents to type two minutes’ worth of notes at the end of the conversation and hope they remember to follow up, all promised actions have been captured as the interaction progresses. The company eliminates virtually all of the call summarization time. The positive effect goes beyond each individual call; since most agents operate in queues with back-to-back calls, they don’t always have breathing room to write up cogent notes for each one. This often has the effect of having them go into every call distracted fueling agent frustration.

In what other ways is ASAPP different from other solutions?

Another attribute which separates ASAPP from other solutions is that all of the AI models are designed for our customers' data, which is specific to their operations. We’re also looking at outcomes and we’re taking every signal to feed those models. The solution currently works in English and Spanish.

Do you find that agents using the ASAPP solution enjoy their jobs more and leave less?

40% of contact center workers leave their roles within 12 months. We’re seeing this problem being alleviated among companies using our technology. High turnover rates are not new.  In my 20 years in the contact center space, it’s always been an issue. But in that timeframe, the environment has become very different. The modern contact center employee who often comes from the Twitter generation learns very differently and expectations are higher. The contact center itself has not always evolved to keep up with the times. So, from a workforce management perspective, while we talk about work/life balance, it’s still very regimented. It’s not just the technology side. Businesses have to be cognizant of the needs of today’s agents to create an environment that keeps people around longer.

Where does ASAPP help in training agents?

Companies often have training programs that often involve 10-to-12-week onboarding, feeding prospective agents an overflow of knowledge that they can’t always assimilate. It’s difficult when agents don’t have technology on their desktops to help them manage the information. The training program starts them with a huge brain dump of information which they are supposed to remember in real time conversations with highly emotive customers. This causes anxiety and leads to frustration, putting a significant cognitive load on the agent. Most agents who graduate from these lengthy programs are scared before they even start. Technology like ASAPP can not only reduce the amount of time needed for training but also simulate customer interactions in a safe environment. Very few companies have evolved into using artificial intelligence to update their training programs to keep up with the changing characteristics of 2021 employees.

It seems that this environment also provides more employee empowerment.

Yes. Having this type of support at hand enables agents to better own contact center issues. They want to take care of customers without having to escalate to supervisors or transfer them to a different department. Not having this kind of empowerment drives friction and fragmentation which can lead to total frustration, because they do want to be the hero. Instead of deploying desktop technology for the agent, too many companies have been busy deploying bots or IVRs that do nothing for empower their representatives.

What was the impetus behind the development of ASAPP?

ASAPP was founded by our CEO, Gustavo Sapoznik, whose impetus—like so many visionaries in this space—was a terrible customer experience. In his case it was with a cable company. The communication went on for three hours unsuccessfully trying to solve a basic problem. While he was on his lengthy holds, he was googling the world of CX, learning just how big the problem was and how great an opportunity it presented. His brief research revealed that it was a $600 billion-dollar worldwide problem. He realized that artificial intelligence, if skillfully applied to CX, had the potential to create massive benefits for consumers. He saw the problem as not lying with the individual agent but with the companies that had not provided their agents with the right tools to resolve issues. Too many organizations viewed customer service as a necessary but nettlesome cost of doing business. Out of his own experience, he was motivated to bring effective AI to fix CX. We now have many prominent customers.

Our focus is on the agent and providing them with intelligent tools that help with issues like attrition and absenteeism in the contact center space.  Now is the time to use AI applied to CX in a meaningful way.  Agent assistance has not been a priority in the past.  We need to look at what agents are both saying and doing; marrying those two can help gather insights that AI can provide to help address the challenges of the agent.  Until we throw a lifeline to agents by assisting them in real time, these issues will get worse.

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