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4 Ways RPA Can Make Immediate Impact in a Contact Center

Contact centers and call centers leverage the human workforce to field incoming inquiries through phone, email or web chats. Supervisory staff is tasked with hiring and training, shift scheduling, process compliance and workload balancing within the contact center. Customer satisfaction can be measured through first call resolution, quality assurance gauging and CSat metrics gathered at the end of each inquiry. This becomes a very complicated balancing act between the customer, the agent and the contact center to ensure everything happens properly at the right time to close the inquiry within the appropriate service levels. Robotic Process Automation (RPA) can be leveraged to speed up the interaction with the client, provide a more thorough response, decrease the amount of human labor required to field incoming inquiries and increase customer satisfaction through reduction in human error.

There are four areas where RPA can provide a major positive impact within contact centers:

IVR and RPA action

Modern telephony hardware providers like Cisco and Avaya provide an interactive voice response (IVR) system that allows callers to interact with the phone system to be directed into the appropriate response queue through a button press – “press 1 for Sales, press 2 for an Agent, etc.”. However, the rules within the IVR and contact center phone system can be enhanced to enable a more intelligent response through natural language processing and neural networks with inquiry classification, speech to text and text to speech conversion and natural language generation to understand the intent and context for the call. Once the intent and the context for the call is understood by the backend system, the IVR can relay the right answer to the caller through natural language and RPA. For instance, balance inquiries, issue updates, order and shipping status, returns and cancellations and order fulfillment can be processed through IVR systems leveraging backend system API connections to data sources and applications.

Enabling an RPA-driven action enabler as part of the overall contact center communications system provides a faster response to the caller and provides an intelligent automation solution.

Ticket Open and Call Wrap Helpers

On average, it takes up to 8 minutes per transaction to open, update and close a ticket. This does not include the time it takes a contact center agent to identify the reason for the inquiry, diagnose or isolate an issue or remedy the situation by collecting information, fulfill the request or put in a stop-gap solution to be able to move to the next call. This is the tight rope balancing act within a contact center that enables an agent to quickly move to the next call. RPA can be leveraged to work with the caller to gather the relevant ticket information needed by an agent to move faster once the customer is on the line. Available API integration points with BMC Remedy, ServiceNow and other ticketing system providers allow RPA to connect seamlessly to the contact center ticketing system and update fields within that system appropriately. This will allow the contact center agent to move faster during the inquiry. These same integration points and RPA can also be leveraged to prompt the agent to provide the exact information needed to rapidly close the ticket and decrease the call wrap time per agent.

Let’s use that same type of RPA-driven integrated ticketing solution and tie it to the intelligent IVR solution above, and we can collect customer satisfaction details after the call that is then added to the call wrap portion in real time after the agent is already on the next call. CSat metrics are gathered and pushed to the resolved incident fully closing the ticket and providing the quality control team with valuable information regarding the call type and agent handling the call.

Agent Assist RPA

Contact center agents are trained to field known inquiries and have tools and applications to help them gather information, isolate the inquiry and provide a response. However, this often requires swivel-chair methodology to move quickly from one application to another to build a caller profile, gather evidence and update a ticketing system. How many times have you heard, “let me put you on hold while I gather some details”? Agents also have to reach out to supervisory staff for certain approvals or escalations. These elements decrease the efficiency and scalability of the agent and overall contact center. Agent Assist RPA can be deployed for each contact center agent to make them more efficient within their own inquiry processing to autonomically and instantaneously gather caller profile information across multiple systems. This will provide insight immediately to help calm an irate caller and better prepare the agent to know the answer before the question is asked. Additional RPA can be deployed for outbound contact centers to gather report data, call lists and target the right customers outside of operations hours so the agent can show up and tackle the most likely successful customers that the RPA system has worked through over the previous 12-hour unmanned shift.

Think of agent assist RPA as the tools found in Batman’s toolbelt. When Batman needs to climb a wall, he pulls out his trusty bat-a-rang and gets to it. Agent assist RPA is available for all agents in the call center through attended UiPath automation on their desktop. This provides the agents with the tools they need to be more efficient and quicker in their responses and actions.

Agent Shadow RPA with Intelligent Automation

It could take up to 90-days to train a contact center agent to handle the toughest inquiries. This is done through initial new-hire training, on the job training and reinforcement training as the agent progresses through their first 90 days. However, with RPA, this training cycle could be condensed to a 1-week facilitator led training. Picture an agent that has made it through their first week of training. They know the basics, the systems and the call flow, but they lack the experience and expertise needed to handle all call types. Intelligent automation could be leveraged to accelerate their on the job training and provide expert answers for any agent with any experience level. Now, picture that same agent fielding an inquiry to create an insurance policy. An RPA driven “shadow agent” works as a background trainer and assistant. The contact center agent enters in a few keywords from the caller and the expert answer pops up on the screen for the agent to read back to the caller. Upsell opportunities, additional information and known issues can also be provided during the call or through email by the shadow agent to help steer the caller in the right direction and provide a more robust answer.

These expert answers can be populated by the Tier 2 and Tier 3 engineers and changed as responses and services change. These changes take place in one centralized automation warehouse so all agents receive the latest and greatest responses. The first three solutions, once implemented, will provide a reduction in workload for Tier 2 and Tier 3, so they can provide the knowledge and effort needed to further streamline contact center operations through agent shadow RPA.

Summary

Let’s take what’s listed above and put the use of RPA into quantifiable results based on 100 contact center agents fielding 50,000 inquiries per month. The usual contact center staffing model allocates agents with 70% staffing at Tier 1, 20% staffing at Tier 2, and 10% staffing at Tier 3 and Supervisor levels. That leaves 70 of the 100 contact center agents at the Tier 1 level. This is typically where the largest RPA impact can be made. IVR self-help should be able to tackle 30% of the incoming inquiry volume, expertly fielding 15,000 inquiries of the total volume monthly. Ticket update RPA and call wrap RPA could free up 280,000 ticket handling minutes per month (8 minutes x 35,000 inquiries) from the remaining inquiries. Agent Assist RPA can build efficiency and scalability across the remaining incoming volume allowing agents to field more inquiries, decrease backlog and increase customer satisfaction. Agent Shadow RPA with intelligent automation builds an expert workforce with limited training. Pairing all four RPA-driven contact center solutions together can easily offset up to 50% of the Tier 1 staff efforts. In this scenario, the contact center would free up 35 resources from Tier 1 over time. Now you have the additional staffing you’d need to fill vacant positions, handle ongoing backlog and staff your new RPA center of excellence with developers to drive that 50% gain higher. This offset staffing can also help continue populating your Shadow Agents with new knowledge and further drive RPA impact within the organization.

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Want to learn more about contact center automation? JOLT is a specialized Robotic Process Automation (RPA) services provider with specialized knowledge in contact center automation. We can help you, and your company navigate the nuances of setting up a digital-first enterprise.

Contact us to talk to a specialist today about your automation questions and goals, book a free consultation here.

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