Agent assistance software (also known as agent assist) is among today’s leading business investments, and it’s easy to see why. In today’s digital-first world, the remote customer experience reigns supreme. And when customers have questions or concerns about a company’s product or service, they increasingly reach out to its customer service department for answers and resolution. How well (or poorly) its agents respond to customer requests directly impacts a brand’s image, loyalty and repeat business.
It should come as no surprise that businesses would want to control the agent and customer experience as closely as possible. Frequently, this means developing and deploying agent assistance technology that leverages conversational AI and automation to handle the rise in remote (and often complex) customer interactions. But with so many agent assist options available today, what does that mean? Should businesses partner with CX vendors or try their hand at building an agent assist platform from scratch?
Agent assistance: what you need to know
There’s a growing interest in agent assist solutions today, fueled largely by shifting trends in consumer behavior. Noticing that customers increasingly prefer remote interactions, many businesses invested heavily in self-service solutions, particularly during the height of the pandemic. However, many soon discovered that while self-service can effectively resolve simple customer issues, the technology has its limitations.
According to Gartner, of the 70 percent of customers who attempt self-service, only 9 percent resolve their issue through that channel alone. For complex issues, 81 percent would rather speak to an experienced agent. And that complexity is on the rise. According to Gartner, contact center agents face four main areas of complexity today:
- Discussing and diagnosing difficult problems: As much as 67 percent of customer interactions involve a time-consuming diagnosis.
- Deciding the right course of action: Customers often expect agents to provide solutions outside the scope of company policies (i.e. providing a refund after a warranty has expired). Agents need to know when to supersede or comply with protocol to resolve an issue.
- Validating customer concerns: A Calabrio report found that 69 percent of consumers expect agents to be more empathetic.
- Managing upset customers: Many callers simply want to vent their frustrations and expect agents to understand the root cause of their anger
Agent assist in-call guidance
In response to the growing complexity of agent workloads, contact centers have turned to artificial intelligence (AI) and automation technology to assist agents and boost productivity. While solutions, like learning, performance and quality management tools, are certainly beneficial, they often come up short when it comes to helping agents deliver a flawless customer experience. One of the biggest concerns is the lack of in-call guidance at the precise moment agents need assistance—when they are serving a customer.
For agents to succeed under current conditions, contact centers need to shift their agent assistance strategies so they help staff during live interactions rather than rely on follow-up reviews after a call has ended. The solution: in-call guidance software that leverages conversational AI and automation to assist agents in real-time.
There are three steps that are foundational to providing agents with real-time, dynamic and actionable in-call guidance:
Assist: Guide agents on next-best actions and deliver a consistent customer experience regardless of interaction complexity.
Understand: Understand customer intent in real-time with conversational AI, robotic desktop automation alerts and other insights.
Automate: Rapidly integrate your disparate tech stack, and automate tasks, processes and conversations using RPA and more.
By intelligently applying conversational AI and automation to live customer engagements, businesses can improve key customer experience metrics and drive hyper-efficiency among call center staff. And the benefits are cumulative. AI-enabled in-call guidance allows agents to learn and improve their skills through real-time coaching. As a result, agents are more empowered, less stressed and less likely to churn.
Automating after call work
While conversational AI and automation are ideal for optimizing the entire conversation, it’s important to realize that the agent’s effort isn’t over when the interaction ends. What happens after the call can be just as important to your contact center’s business outcomes as what happens during the conversation. That’s because the time spent in after call work (ACW) impacts average handle time, call waiting times, customer satisfaction (CSAT), costs and agent productivity and satisfaction.
Just what constitutes after call work and, consequently, ACW time? Common call work activities that occur after a live customer interaction include:
Call categorization and summarization: Contact center agents must frequently categorize calls by type (i.e. billing, troubleshooting, etc.) and generate a call summary for record-keeping, quality assurance and/or agent coaching purposes.
Updating systems: Depending on the nature and outcome of the call, a contact center agent may need to update his or her company’s customer relationship management (CRM) or other business-supporting systems.
Follow-up actions (i.e. promise management): Few tasks impact call wrap-up time—not to mention customer experience—more than promise management. Promises made to customers during calls must be logged and the appropriate follow-up actions must be taken to ensure total resolution and customer satisfaction.
Given the large amount of time spent on completing after call work, it should come as no surprise that lowering ACW time is a major contact center objective. Because automation can reduce ACW time—and subsequently improve agent performance—there is a strong business case for automating after call work. (To learn more, read our article, “Creating the Business Case for Automating After Call Work.”)
Want to learn more?
Check out our ACW buyer’s guide, Choosing the Right Solution for Automating After Call Work.
Developing an agent assist solution: should you build or buy?
With the availability of conversational AI toolkits, RPA development platforms and open-source NLP/NLU software, your company may be considering a do-it-yourself (DIY) approach to creating an agent assist platform. While appealing in terms of upfront costs and project control, ultimately many companies underestimate the long-term cost and resource commitments of developing and maintaining their own conversational AI and automation capabilities over multiple years. Optimizing outcomes using conversational AI also requires deep expertise that many companies don’t have in house. That said, if your company has the resources available internally to write, test and maintain custom code, you may be able to create a custom agent assist solution in-house or with the help of consultants. However, before you decide, consider the following:
Scope: Are you automating one isolated part of the customer conversation or the entire journey? Which capabilities must be included? Which ones will you add in later iterations of the software?
Timing: How long will the project take? How long are you willing to wait before the automation is ready to use and can start delivering benefits?
Resources: How many engineering resources and AI/NLP experts will you need? Will you need to hire consultants?
Integration: How many systems will your solution need to integrate with? Do you have the resources to commit to maintaining custom integrations as contact center systems evolve?
Maintenance: What will it cost to scale and maintain the solution as new capabilities are introduced or new use cases supported?
Budget: Based on scope, resources and integrations, what will be the total cost of the project?
Unless your company wants to own the intellectual property for your custom agent assist software and sell it to other contact centers, choosing an off-the-shelf conversational AI and automation platform is almost always the faster, more cost-effective and most beneficial option.
What to consider when choosing an agent assist software vendor
Beyond evaluating the technology and capabilities required for your in-call guidance, after call work and other agent assistance needs, you also want to choose the right vendor. The ideal conversational AI and automation partner should offer:
- Visionary leadership and a technology roadmap that aligns with your vision
- Deep expertise in AI, NLP/NLU, RPA and related technologies
- Domain expertise in optimizing customer experience/contact center operations
- Deployment methodology and services to help you achieve rapid time to value
- Security and privacy of customer data
As the leader in conversational AI and automation, only Uniphore offers an end-to-end AI-enabled solution for the entire customer experience. Our comprehensive X-Platform allows businesses to unlock the full value of every conversation, with unique insights into customer sentiment, intent and emotion that you’ll only find here. And our fully integrative, low-code / no-code software makes it easy for you to build the experience you—and your customers—want. No need to start from scratch or call IT support. It’s that simple.