RPA

Robotic Process Automation: Bridging the Widening Gap Between Customer Demand for Service and Real-Time Agent Availability

Driven by the instant gratification offered by ubiquitous handheld devices, consumers want all their issues resolved a minute ago and any other questions answered instantly. In the current contact center environment, these constantly rising expectations have reached a level where it’s simply no longer always humanly possible to meet them.

While call routing and scheduling software are constantly improving, even these solutions have difficulty keeping up with the demand for agent availability in real-time. Add in the ongoing corporate mindset of lowering costs and keeping headcount to a minimum and you often have the proverbial irresistible force meeting the unmovable object.

Fortunately, there is a rapidly emerging technological transformation that is changing this seemingly insoluble equation. Robotic Process Automation (RPA) gives companies the capacity to meet the growing challenges of maintaining service levels while improving efficiency and providing greater bandwidth. RPA automates the routine, repetitive and time-consuming tasks that can slow contact centers down to a crawl, enabling front-line personnel to pay greater attention to more complex interactions that require empathy and a human touch in decision-making.

The improvement starts from the point of contact. In traditional contact centers, when a customer reaches the agent, he or she needs to identify them within the system to get the necessary information such as status, order number, pending support tickets and more This puts the agent in the awkward position of having to interact with the customer while simultaneously toggling from one system to another. Multiple logins can also further slow down the agents, as can silos pertaining to different systems.

By implementing RPA, contact centers can significantly diminish the time required to identify a customer in the system, viewing all necessary details associated with them in one screen. When customers don’t have to wait for the agent to load all the details, it reduces the average call duration, contributing to an improved customer experience.

In addition, the technology can make it far easier to make necessary data updates to a customer’s account during an interaction. Instead of having agents entering data manually across multiple fields in different systems — a tedious and error-prone process– RPA enables integration of data across various fields of associated systems using a single agent entry. RPA can create auto-fill templates that enable simple copy-pasting of information, with limited human intervention. Integrations with CRM and other third-party tools almost totally eliminate the need to spend time on cross-application desktop activities. RPA can also help consolidate customer information over a variety of channels, giving agents information they need to help the customer no matter what touch point the conversation is taking place on.

What is the economic impact of RPA for businesses? According to a KPMG study, use of RPA in financial institutions can help reduce operational costs by as much as 75%. “In terms of its potential to reshape the economy, it will be as significant as the Industrial Revolution,” said noted industry analyst Donna Fluss, president of DMG Consulting “It’s going to create a whole new class of employees, a technically savvy generation of workers coming from the Millennial and Generation Z cohorts. The AI/RPA revolution will be a game changer for companies that welcome the opportunity to improve the timeliness and accuracy of their work processes.”

Fluss will present a detailed analysis of the economic advantages, operational efficiency gains and customer experience enhancements made possible by RPA in a complimentary CRMXchange webcast on Wednesday, October 16 called “Attended Robots Improve Productivity and Agent Efficiency.” Among the topics covered will be

  • An explanation of what RPA entails and present top use cases in the contact center
  • A discussion of the effect of RPA on employees
  • An outline of best practices for implementing RPA

The webcast, sponsored by NICE, is complimentary and those unable to attend it live can download it approximately 24 hours after it is completed. Register now.

Melding AI and Virtual Assistants with Humans: The Right Formula for a Superior Customer Experience

By now, just about all of us have encountered an automated system when reaching out to a contact center. According to research cited in a 2017 IBM Watson blog, by 2020, 85% of all customer interactions will be handled without a human agent. Sometimes, such systems work flawlessly: the bot or virtual assistant (VA) understands customers responses easily and the conversation progresses smoothly as they either get the information they expected or complete the process they hoped to finish. In some cases, customers may not even be sure they are interacting with an automated entity.

But while AI continues to provide increasingly beneficial results in the contact center environment and to grow in its capabilities to emulate human behavior, it is not yet the be-all, end-all technology that can resolve every issue. In some instances, the AI system simply can’t process the information that customers supply, leaving them ensnared in a loop of repetitive responses….and the resultant frustration can have immediate and serious consequences. NICE inContact’s 2018 CX Transformation Benchmark, revealed that only 33% of consumers found that chatbots and VAs consistently made it easier to get their issues resolved.

This is precisely why it’s critical to ensure that empathetic human intervention is readily available.

When the human touch is needed, it must be prompt, proactive, professional and above all, responsive to the customer’s needs. While many contact centers are increasing their reliance on AI solutions to reduce headcount and deliver rapid ROI on their technology expenditure, they are also learning that not having enough caring flesh-and-blood agents ready to complement their electronic counterparts can result in diminished loyalty and customer churn. Establishing the right balance between an effective, continuously updated AI program and humans who can seamlessly step in at just the right moment is a necessity in an environment where customer satisfaction has become the most significant business differentiator.

Having the capacity to train an AI system to determine the exact point in a conversation on any touch point where the customer needs to be handed off to a live agent is the most important factor in the process. Analytics plays a key role: data gathered within each individual interaction can provide a treasure trove of relevant information enabling managers to better understand what sets a customer on edge, what makes them feel more comfortable in a conversation that is not going well and what can ultimately drive them to take their business elsewhere. Having the right intelligence readily available also enables management to also pinpoint necessary adjustments in policy, procedure or verbiage.

Of course, as AI increases in intelligence through machine learning, it can also provide additional value-added suggestions such as which department is best equipped to assist customers based on analysis of their specific needs. Leading-edge AI solutions can pair such customers with an individual agent with the right skill set to guide them to successful resolution of their issue.

Companies investigating either implementing or upgrading an AI customer service solution need to develop a strategy that offers optimal potential to enhance customer relationships and improve the quality of interactions on all touch points. In addition, they must explore ways to strengthen collaboration between self-service entities and live agents.

On Thursday, October 3rd at 1:00 PM ET, CrmXchange will present a Best Practices Roundtable on Seamless Customer Experience: Combining AI VA with Live Agents, featuring experts from leading solution providers NICE inContact and Verint. Among the topics discussed will be:

  • Current AI adoption trends: how to get the most of early AI investments
  • How is AI impacting customer service today and what’s ahead in the future?
  • Where AI can add the greatest benefits
  • How to define and implement the right mix of automation and human touch—without damaging consumer trust and undermining relationships in the process of digitization.

This informative roundtable webcast is complimentary and those unable to attend it live can download it approximately 24 hours after it is completed. Register now

How Robotic Process Automation Makes Contact Centers More Efficient

Automation isn’t new. Technologies like Interactive Voice Response have been around for a long time. But while advancements like these have reduced costs for the contact center, they’ve also managed to annoy customers. In the case of IVR, callers often get stuck in menu loops or struggle with systems that don’t understand what they’re saying. Enter robotic process automation.

Robotic Process Automation and Artificial Intelligence

Contact centers are in the business of serving the customer, and in an effort to improve the customer experience, technologies are always emerging. Robotic process automation (RPA) is one of them, automating tasks and freeing up agents to personally handle complex issues. RPA uses Natural Language Processing, which is related to artificial intelligence, an even more advanced type of automation that can make human-like judgments about tasks.

Interactive Text Response for Customer Service

Interactive Text Response (ITR), more casually referred to as chatbots, goes hand-in-hand with the increasing popularity of messaging apps. Brands that want to improve the customer experience are making themselves available on chat – and it’s working. More than 70% of 1-800-Flowers’ chatbot orders come from first-time customers, and the company’s commitment to new tech has attracted tens of thousands of users. Chatbots are more effective than IVR because text input is easier for the system to understand than spoken language. AI can then be used to gain a deeper understanding of what the customer is saying, accounting for the different ways a customer may phrase a sentence or question.

Sample Phone Call with RPA

RPA can also be used with phone calls, not just chatbots. Here’s an example of how RPA can help with a live call:

  • Jane calls to speak with an agent.
  • Your RPA takes the call and authenticates Jane by confirming her account number and call-in PIN.
  • Your RPA analyzes Jane’s account and sees that she has an open ticket and that she’s just been on the website to look at the status.
  • Your RPA says something like, “I see that you have an open ticket with us. Is that the reason for your call?” Jane confirms that this is the reason for the call.
  • Jane is transferred to an appropriate live agent.

Contact center technology like RPA can help customers solve their issues more quickly, but it can also provide much-needed support to agents by making them more efficient.