Contact Center Automation

Intro

/In the past decades, a great deal of power and responsibility shifted from enterprise representatives to customers, B2B partners and employees. Self-service became the norm: We don’t have insurance agents fill out forms for us, we do it ourselves. We don’t physically visit a bank to transfer money, we use our mobile apps. We plan our family trips without travel agents assisting us. For most people, self-service is not only accepted but desired. It’s fast, convenient and foolproof – until it’s not.

Anything that is not explicitly anticipated in a self-service process can bring the customer journey to an abrupt halt. An uncommon requirement, a technical glitch or a struggling user – there are millions of incidents each day where self-service finds its limits and customers pick up their phones to talk or text.

When self-service fails and visiting a physical business location is not an option, contact centers become the forefront of B2C, B2B and B2E interaction. Unlike traditional call centers, contact centers extend beyond phonelines by allowing to receive and transmit various types of communication such as emails, social media, live web-based chat, etc.

The quality of contact center operations directly impacts crucial business areas: Customer satisfaction, revenue opportunities, churn and many more. At the same time, contact centers are expensive to operate and their KPIs are under constant scrutiny from top management.

Attempts to automate (phone-based) customer interaction have been around for many years. First-generation IVR (interactive voice response) enabled machines to interact with humans via voice recognition and/or keypad inputs. Its primary application was to automate straightforward processes like transferring money or making appointments. The advent of web interfaces offered the same features in a much more convenient way and rendered its phone-based equivalents soon obsolete. At the same time, technology was not yet mature enough to successfully handle more complex cases.

Today’s generation of contact center automation is fueled by tremendous advancement of AI-powered natural language processing, sophisticated voice bots and the understanding that human and virtual agents are rather co-workers than competitors.

This article will provide you with insights on how to improve contact center operations with conversational AI, voice- and chatbot technology. The result? Better customer experiences at lower costs.

What is contact center automation?

A contact center is a crucial piece of infrastructure for any large company that routinely handles external or internal customer service requests at a large scale. Contact center automation aims to successfully handle some of those interactions through intelligent algorithms without interference of a human agent. Users most often encounter contact center automation in the form of chat- and voicebots.

Strong automation initiatives are characterized by supporting multiple aspects of interaction:

• Use of natural language in digital channels: Conversational AI as a core component of contact center automation enables customers to express their intentions or questions in spoken or written language. This approach shifts the paradigm of self-service from operating a user interface to engaging in a natural and dialogue with a partner.
• Supporting omnichannel: Contact center automation can span multiple touchpoints such as phone, SMS, messenger, website chatbot and others. Best-in-class implementations enable seamless switching between channels.
• Allowing multi-experiences: Combining language-based communication with – where applicable – visual elements and point-and-click UI elements makes human-machine-interaction much more convenient and appropriate for a variety of tasks.
• Empowering action: Automating simple questions/answers (FAQ bot) is often a starting point for contact center automation. However, transactional conversations have a much higher value for both parties involved. “Getting things done” through taking actions in backend systems (ranging from completing a purchase to resetting a password) is the showcase field in contact center automation.
• High discourse flexibility: Unlike a filling out a form, contact center interaction is oftentimes not highly structured and predictable. As every customer is different, there is a broad variety of strategies, expressions and pronunciations involved when engaging with a contact center. Contact center automation needs to deal with the fuzziness of human communication to maximize the number of successful journeys and minimize friction.

The impact of Contact center automation

Across all industries and all times, increasing efficiency and lowering costs has always been a driver for automation investments. Contact center automation is not an exception, but its impact – when well done – affects more business areas than operational spending.

Increase customer satisfaction

As Forrester indicates, almost 3 out of 4 customers agree that valuing their time is the most important thing a company can do to provide them with good online customer service.

Yet many customer interactions over the phone begin with the dreaded on-hold music. Automation allows to start the interaction right away with qualifying questions and – if applicable – identify and authenticate the customer.

In many cases, customers will be able to fully handle their request within seconds with the help of a virtual agent. Issues such as “I forgot my password”, “I need a copy of my last statement” and many more can be handled through the combination of natural language processing (written in chat or spoken over the phone) and smart processes that link customers and backend systems / data.

In other cases, issues need to be solved by human agents. Through intelligent routing, contact center automation bundles all relevant information (such as customer account data and type of inquiry) and transfers customers straight to a qualified agent. This not only means less waiting for customers, it also reduces the average handle time as customers are pre-qualified, authenticated and sent to the best-fitting agent.

Boosting efficiency

Automation can impact contact center efficiency on a large scale. From a business perspective, reduction in average handle time (AHT) is the greatest benefit contact center automation brings to the table. AHT describes how much time a human agent needs for 'handling' a contact on average. Depending on use case and business sector, AHT is typically between 240 – 600 seconds, so reducing AHT by a couple of seconds can already have great impact on KPIs.

Many initiatives take a phased approach to incrementally increase the degree of automation, starting with low-hanging-fruits and gradually expanding to more complex cases. Here is an example of how contact center automation for incoming calls can impact AHT in multiple steps:

Phase 1: Intent recognition and optimized routing
Upon call, the customer is asked for their intention and directly routed to the best-fitting pool of agents
--> - 15 seconds AHT

Phase 2: Automate identification and verification process
All issues that require customer authentication are routed through an automated identification process. If needed this can include a multi-factor authentication and / or processes for forgotten passwords or lost credentials. Upon transfer-to-human, the conversation is fully focused on solving the issue.
--> - 30 seconds AHT

Phase 3: Backend integration for issue handling
Recurring customer issues with well-defined handling processes can be handled fully automated through conversational AI and connections to relevant backend systems while ensuring compliance, security and traceability. Being able to handle 20% of incoming calls autonomously is a realistic target mark. This can paradoxically lead to an increase in AHT as human agents get to handle cases that are on average more complex. However, this effect is outweighed by the reduction of the total amount of human-handled calls.

Leverage revenue opportunities

Every contact center needs to balance conflicting goals: Service level and staffing costs. Simply said, minimizing wait times will help drive up customer satisfaction (and eventually result in higher revenue) – but the increase in labor costs can quickly outweigh the profits. On the contrary, cutting back contact center costs by extending wait times may backfire through lost revenue and decreased customer satisfaction.

Even if wait times become critical, scaling up operations by hiring more agents can become a bottleneck: A lack of qualified applicants, time-consuming education and on-boarding efforts limit the contact center managers’ business agility.

Direct revenue loss can occur through abandoned calls, i.e. when a customer or prospect with a question or transactional intention loses their patience while in the waiting loop and eventually turns to an alternative. Indirect losses can be just as impactful: Increase in churn through unsatisfied customer needs, a constant stream of complaints via social media and eventually a harmed reputation can cause sustained damage.

Every contact center has to balance ideal service level and labor costs. AI-powered automation can help shift the needle in favor of higher customer satisfaction and positive returns without increasing the overall contact center costs.

On top of that are opportunity costs for missing out on potential customers who have not even begun their journey: Especially in information-seeking phases of a customer’s journey, talking to an agent comes with a higher threshold for starting an interaction compared to a quick website chat or using a messenger app. Conversational AI enables businesses to tap into the power of more digital channels and reach new customer sections without scaling up contact center costs proportionally.

Employee satisfaction

While automation undoubtedly contributes to a reduction of AHT, its primary goal is not to lay off and replace human agents. Employee turnover is relatively high among contact center staff and the impact of automation kicks in only gradually, therefore automation initiatives generally do not lead to sudden and morale-impacting terminations of employment. Instead, natural attrition is often sufficient to allow staffing numbers to shrink, as automation takes hold.

In fact, most contact center specialists appreciate support from virtual agents as they contribute to work satisfaction and job security:

• Even with state-of-the-art technology and AI-support, virtual agents can only handle the relatively simple, well-defined cases. Most human contact center agents get more job satisfaction from handling complex inquiries which require more training and expertise.
• Active agent support and intelligent routing help agents not only to be more productive, but also to be more successful: Issue resolution can happen quicker and more targeted compared to randomized call distribution which may lead to hand-overs from agent to agent.
• Most associates appreciate the relief from highly repetitive tasks: No agent loves asking dozens of customers the same exactexact same ID questions during their shift.

Even though contact center automation is largely motivated by improving KPIs and reducing total handling costs, the best overall results can be expected from initiatives that acknowledge the teamplay between human and virtual agents: The intellectual, problem solving skills and empathy of human employees and the scalability, precision and tireless efficiency of their robot co-workers.

How to calculate the ROI of contact center Automation

Imagine this: Your contact center analytics show that many customers spend far too long navigating the IVR system or being on-hold. When they finally speak to a human agent, they are likely to be transferred to another service representative or even receive a callback. Your NPS scores are alarming, your average handling costs too high. You know conversational AI and virtual agents can help tackle many of these issues – but how do you make this a business case?

Once successfully deployed in one area within your contact center, you can step-by-step and in an agile fashion explore more complex use cases or extend to other departments, unlocking more value.

Contact Center Technology & Voice Automation

Contact centers rely on a variety of technologies to provide efficient and valuable customer support. These technologies include networks in place that allow receival and transmittal of many types of communication such as calls, emails, social media, and live web-based chat. Additionally, contact centers today tap into technologies including, but not limited to AI, chatbots, automation, and natural language processing.

Incorporating Voice Technology

Technology is always improving, and many contact centers frequently update their tools, technologies, and services. Since most contact centers already have a foundational technology infrastructure in place, it is important that new tools and technologies are able to integrate with existing services.

Text-based support channels involving human agents are relatively easy to extend with chatbot functionality as they are designed to process text-based communication. Yet most contact center interactions occur on voice-based channels (such as SIP Trunk, PSTN/cellular, WebRTC, etc.) However, as voice-based inquiries are relatively costly and inefficient to handle for human agents, it is desirable to use virtual agents to resolve simple requests. One solution is to use a tool such as Cognigy Voice Gateway, which allows contact centers to integrate voice bots into their processes.

The gateway is a flexible solution that can connect existing voice networks with cognitive services, including conversational AI frameworks, speech-to-text (STT) engines, and text-to-speech (TTS) engines. It also provides advanced call management functions such as call disconnect, call transfer, and call recording.

When a customer connects via a voice-based channel, Voice Gateway provides a link for information to flow between a chatbot service and the customer as shown in the figure below

Voice Gateway consists of two primary components – the voice engagement channel and cognitive services. The voice engagement channel is responsible for interfacing with voice-based channels. Its capabilities include media handling, security, translation, SIP interoperability, high availably, and scalability. The underlying session border controler (SBC) manages the information flow between Voice Gateway and outside services such as bot frameworks and STT/TSS engines. Voice Gateway can easily integrate with existing frameworks and services, as shown in the figure below.

Speech Technology

Contact centers that use bots rely on many speech-related technologies such as continuous automatic speech recognition (ASR), speech synthesis markup language (SSML), and barge-in. ASR enables bots to recognize when a person is speaking. SSML allows bots to deliver customized audio responses and can be used in conjunction with TTS engines to provide details on pauses, text that should be censored, and audio formatting for unique text such as dates and abbreviations. Barge-in refers to when a user interrupts a bot when it is speaking; it is important to consider how a bot will respond to barge-in.

The Voice Gateway utilizes all of the above speech features, in addition to others such as language configuration and TTS caching. Continuous ASR enables Voice Gateway to collect speech from a user; it can detect silences and concatenates text segments output from STT engines into a single message to the Conversational AI to ensure that no segments are cut off. When a user barges-in on a conversation, the AI can be programmed to either ignore the interruption or immediately stop responding and process the new speech from the user.

Conversation Initiation and Call Control

The ability to customize and optimize communication with customers via conversation initiation and call control is invaluable for contact center operations. Conversation initiation includes activities such as SIP messaging, establishing a connection, and welcome messages between a bot and a user.

A good conversation initiation process is critical because it is the first step in customer support – without a good connection or the appropriate initial messages, customers may be unable to get the support they need. Similarly, call control abilities such as call transfer are essential features because they allow calls to be managed based on the customer’s needs. For example, if the Conversational AI is unable to resolve a customer query, call transfer enables the customer to be seamlessly transferred to a human agent.

An Enterprise Voice Gateway solution hence needs to provide features for both conversation initiation and call control. When a user begins a conversation, the Voice Gateway sends an initial activity message to the Conversational AI; the content of this message can be adjusted, or the message can be disabled. Controls are also in place for when the Voice Gateway connects a virtual agent to a user and when/if it sends an initial message to the AI and welcome message to the user.

In contact center setups, it is common for IDs associated with calls to be required by Conversational AI applications and sent to the AI in a SIP header. Furthermore, Voice Gateway can be configured to extract values from the SIP INVITE message and include them in the initial message to the AI. Call transfer and disconnect features are also included, which allow the virtual agent to easily transfer or disconnect the call at any point during a conversation.