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Cognigy Takes Conversational AI to the Next Level


Presented By: Cognigy

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Cognigy.AI offers an Enterprise Conversational Automation Platform for customer and employee service automation. Available in both on-Premise and SaaS, Cognigy.AI enables enterprises to connect to their users on any conversational channel, including chatbots, virtual assistants or voice bots on phone lines. The graphical toolset allows both non-technical users and developers to build and manage complex interactions that go far beyond simple FAQs towards automating complex business processes. The company had been recognized in 2018 in “Gartners’ Cool Vendors in AI for Conversational Platforms” report.   

In our series of conversations with suppliers that were scheduled to exhibit at Enterprise Connect last month before it was converted into a virtual event, CrmXchange Managing Partner had an in-depth (non-automated) conversation with Derek Roberti, VP Technology, North America at Cognigy.

Let’s start with an overview of your platform.

The challenge organizations face today is one of volume. The volume of customers has not diminished. Across many industries it has increased. At same time, the number of resources available to service those inquiries, the agents, has gone down. This is due to the changes that had to be made last year. It’s become harder to recruit people who are willing and able to work in agent positions. It’s even more difficult to retain them. This has created a perfect storm in the contact center universe; the mismatch between demand on the customer side and the resources to resolve all their issues.

There are simply not enough agents to handle the repetitive tasks of updating data and providing easily accessible information. This includes inquiries that a customer should be able to do for themselves using self-service tools. It had become a luxury for businesses to have agents performing rote activities that don’t require human judgment or empathy. This also plays into the ability of companies to retain agents. Taking tasks that are both boring and prone to human error off their plates and giving them more enriching work allows companies to better retain agents. The enterprises can then focus on supporting them with the right tools and giving them more compelling tasks.

Cognigy provides the technology that enables companies to automate voice and chat-based conversations and complete end-to-end business processes on those channels. Non-developers are able to quickly become more productive, building out automated conversations in less time and at lower cost than using traditional IVRs.

Have there been any studies that have looked at agent retention and determined if the work is more interesting for them?

At this point, there are no metrics in place to reliably measure retention. The metrics that do exist gauge deflection rates and decreased handle time.  Now, much of the front end of a conversation has been done before it reaches the agent. While there are many ways to evaluate productivity of agents or the volume of calls that they take, we still can only try to interpolate the effects on retention. There is an ongoing dialogue around how automation technologies impact human resources: does it take away the role of a person or does it augment their value? How does it all fit together?

Does the automation replace or augment the agent?

If you put yourself in the position of an agent who takes calls to look up an individual’s information and repeat it back to them, that’s a 3-minute conversation. The next one and the next one is the same thing. Because it is so repetitive and unvarying, that’s nowhere near as challenging as it is mentally exhausting. When we are working with clients who are trying to automate certain parts of the business process, the entire contact center team down to the agent level is always involved. They are the ones who most want repetitive categories of work automated. While it is of course driven by their desire to make their work more interesting, it is also fueled by their passion for delivering meaningful customer service. They feel like it is not an effective use of their time to perform interactions that don’t require the human touch.

One way that we materially contribute is streamlining the front end of the conversation. Often, a large part of the agent interaction is verifying that the customer is who they say they are. We can take that burden off the agent’s shoulders.

What are your first steps when a company automates?

When we start working with a company, we ask them what are the top 10 or even the top 100 questions that come into the contact center. We then triage which ones that can be most easily automated. That would be project 1.  Other companies may identify a niche problem. While it may not be the organization’s highest volume issue, it’s a certain kind of end-to-end business process that can be implemented with conversational AI.  We build that out as a pilot phase and then it is automated. The folks who know the processes best are the ones who perform these activities every day, so enlisting their help is essential. They know both the stated process and the actual process as it plays out in conversations with customers.

Can chatbots be personalized?

We often say that voice bots and chatbots are as smart as the systems and data to which they have access. We want to have the mechanics in place to be able to fulfill users’ requests. But the other side of that is having the ability to personalize the interaction while making it as fast as possible. One example of how that works would be some of the major airlines who instantly know who I am when I call based on my phone number. Depending on the industry, some businesses might want to employ a second basis of information. It could be the last 4 digits of the social security number it could be zip code or flight number. With that level of verification, the business can not only say they know who the customer is but ask if they are calling about their flight that was just cancelled. This not only still surprises some customers that a system can work that well but demonstrates to them that the company cares about them enough to invest in technology that improves their customer experience.

One mistake that we still see is that when a customer is passed on to a human agent, the agent is required to repeat that verification process. This is not only an unnecessary activity for the agent, but disappointing from the customer perspective they think “Hey, didn’t I just do that with the machine and now I have to repeat it with the agent? It is quite important for companies to figure out how it all works together to provide a seamless end-to-end customer experience.

We are talking about inbound interactions at this point. What about chatbots for outbound calling?

While the technology to deliver such experiences is available for outbound, many companies haven’t yet thought ahead in terms of the user experience they want to design. What we see in outbound is companies which want to qualify lead generation: where people may have filled out a form on a website and are then called to verify information, at which point they are passed on to a human agent. This is the most common automated outbound scenario at this point.  We can see other applications in the future, such as flight rescheduling or a healthcare provider setting up appointments for flu shots. The trickiest part of outbound automation is the trust level of consumers who already are wary because of the volume of dubious calls they receive.

Perhaps one of the biggest advantages of conversational AI is that it is multi-channel in its most effective manifestations. We can have conversations that go from voice to SMS to webchat on a website and have that be a seamless experience. One area that can be credible and successful is SMS-based notifications. We’re able to take those text messages and make them conversational either through having a dialogue with an SMS channel or by bringing them into a webchat experience or even by having a user request a call to them. A business could start an automated conversation in that fashion.

When you look at things in the multi-channel context, what we are trying to do is optimize things for the user by keeping them in the self-service mode and help them as much as possible. This creates a competitively strong experience. Many of the things you will see in this space are legacy players that are focused on the voice channel and newer players who are optimized for digital channels. Our technology ensures that these channels work together seamlessly without needing two separate products to enable it or not to have it be double the work with one product because you have to design different voice and digital experiences. These elements need to be considered together.

What differentiates Cognigy?

Cognigy is a low-code or no-code platform for building out automated conversations. What does that mean? In the traditional mode of IVR creation, business have two options. They either pay the vendor for the professional services to make whatever IVR menu or functional changes necessary. The other is that they have someone in their organization who can figure out the tooling that their vendor provides. In either case, it’s not fast and it requires using outside resources and often necessitates having skill sets that the contact center doesn’t have unless they are able to lean on internal IT. The vision of low-code or no-code platforms is to provide tools that a non-technical or non-developer person could use to iterate quickly instead of making changes and then having them implemented immediately instead of a month later. This empowers the non-technical personnel to design and evolve and improve automated conversations at will.

Cognigy puts the tooling in the hands of the subject matter experts who know the business processes and the information they need to share with users—and do everything possible to empower them to use these tools to create automated conversations without having to knock on IT’s doors or incur professional services fees. We’re moving into the era of what is called the citizen developer where non-technical user has the power to build applications on their own using non-coding approaches.

There are many conversational AI products on the market.  What are some of the differences?

In the conversational AI market, what you’ll see on the lower end are genuinely easy-to-use tools that are usually employed for a specific purpose. For example, if a business wants to do lead capture on its website, it might have a simple wizard-based tool that enables it to click on someone’s name and email address to schedule a message, appointment, or callback. On the other end of the spectrum, there will be tools that enable organizations to do just about anything. But the catch is they will need heavy IT involvement to accomplish anything.

What Cognigy provides is an offering that serves the needs of audiences with both simple and complex application requirements. It also enables them to get tasks done quickly with very facile user interfaces that allow them to push the complexity of conversations to a point farther than other tools could do without the need to write code.

Regardless of who is doing the implementations, they can be as much as 10 times more productive accomplishing it with our platform as opposed to traditional coding-based approaches. The power of our platform has not only been validated by our customers who have compared us with every other significant vendor in the marketplace, but also by Gartner and other analysts who see that low-code capability as our sweet spot.

Who in the organizations do you find is responsible for pulling everything together?

The people responsible for making it work are those in customer experience roles who can live in different parts of the organization. Some are in customer support focused on serving customers while other companies look at it more broadly, incorporating customer acquisition as well. The business problem that most businesses look for us to resolve is the need to be more efficient. This has accelerated within the past 10 months or so as they find that they either can’t hire people fast enough or at sufficiently affordable rates to handle the volume they are experiencing. They know it’s imperative to reduce hold times to improve their NPS scores and frequently, it is the contact center VP who approaches us to say that they’ve got to get a handle on what is happening, and the ownership lies in terms of how well they do.

Sometimes we encounter experts within the companies themselves who tell us that they know conversational AI is part of the roadmap for the future of customer service within the organization. Thus, they want to start developing dedicated resources who can become experts in deploying this technology.

When I am out in the world attempting to do business as a consumer, many of the chatbots I see are basically glorified search engines…and not particularly good ones. There are several reasons for this, and I believe the most obvious one is a failure of companies to develop a vision on how they are designing these conversations from a user experience perspective. But I also can attribute the problem to many companies seeing the end result as saying, “How can we take the take the traditional FAQ on our web page and put it into a chatbot?”

The more appropriate perspective would be for them to realize that chatbots are most powerful in every dimension when they can be used to solve end-to-end problems for customers. Having the right API integrations is essential for creating the ability to deliver this more comprehensive experience.

Cognigy has many out-of-the-box pre-built integrations with leading enterprise-grade technologies. What’s more important is how we created these extensions using our proprietary extension framework which is a blueprint for how to build extensions into applications. We thought about how companies often have legacy or homegrown systems that have no available published APIs, yet we still need to be able to integrate with them. If you build such APIs using our blueprint, they become surfaced in our graphical low-code editor as though they were native parts of the platform. The impetus is to write the code once and give the non-developer access to the integration within the Cognigy application.

We also have out-of-the-box channel integrations with everything from WhatsApp and Facebook Messenger to webchats such as those a company would have on its website to SMS, voice and all of the most widely used channels. We can automate conversations on internal channels such as Slack. But we can’t predict everything out there and sometimes, in such areas as mobile apps, there’s no one standard for how a specific one is going to communicate with an external application. So, we’ve built in the ability for a company to create its own channels. We call these Transformers, which is our technical name for it, but we make the platform extensible in that ways as well. As an example, a major insurance company which is a long-time customer of ours, wanted to integrate Cognigy into their mobile app. They didn’t have to change anything in their mobile app to be able to connect and they were able to accomplish it due to the ability for a business to either create its own end points or customize our out-of-the-box end points.

What sort of questions do you ask people as they stop by your booth?

When we are at a live event, usually the customers who come to our booth are thinking about automating some aspects of their customer service. One of the first things we try to determine is what kind of money are they trying to save and what problems are they trying to crack. Many times they want to increase their contact center efficiency by handling use cases that don’t require human decision making. Sometimes it’s getting them to understand that they can resolve a gap where their competitors are able to provide more personalized experience. In other cases, it’s finding out what their pain points are that automation can solve for them. We also want to learn what channels they are looking to automate: voice or text or both. Surprisingly, some companies are even new to live chat, much less automated chat. But what we really want to do is help them think through the business problems that automation can solve for them.

The domain of conversational AI is new to many contact center operators. While immersed in data in such areas as agent productivity, average handle time and NPS, they might not be aware of some of the conversational analytics that come out of interactions with automated bots, whether voice or chat.

You have a new feature, Insights.  Can you tell us about that?

We have introduced what we consider a unique feature this year called “Insights” which is a way to glean knowledge that can’t be produced by traditional analytics in contact centers with human agents. We create funnel metrics that tell businesses how many people started interactions with a bot and what was the nature of their inquiry. And of those, how many created this end-to-end business process. This allows them to see where any drop-offs came in the process and how they can optimize the information to create a better user experience. They can categorize conversations and resolution types to see what reasons people need to speak to a human agent or determine if there are any ways that the automations are not working. This gives them empirical means to measure the effectiveness of their investment and have the means to make better, data-driven decisions to improve their customer and employee experiences.