Innovation and change are required but can be difficult to achieve. Using an evolutionary instead of revolutionary approach, every company can join the new age of digital customer self-service with automated visual solutions.
Customer Experience (CX) and Customer Care have always been one of the most critical components of customer satisfaction for every business, and a key indicator of customer retention and of the health of the organization as well. With the digital era progressing rapidly over the last two decades, digital customer service solutions have also become necessary. Our digital world has created an expectation of speed and simplicity for consumers that businesses must now meet. To catch up to customer expectations modern companies must deploy mobile-led self-service technology to improve their customer experience as quickly as possible.
The Challenge: Revolution or Evolution
Modern consumers expect services delivered quickly whenever they want, wherever they are, and through whatever channel they choose to use. Modern Customer Care leaders know they must deliver a new level of customer self-service capabilities to encourage customer retention and loyalty as well as attract new customers.
Introducing new solutions can be complicated as businesses’ legacy systems struggle to adapt to new modern demands. Many legacy technology stacks are built using disparate systems that can make adapting to the new standards of customer care cumbersome. Customer Care leaders can look to two different paths for change: revolution or evolution.
A revolutionary approach means launching a complete system transformation. This approach tries to solve the core problem by completely replacing old systems with new modern ones. The risks of doing so are high: high costs, long implementation times, disruption to the business, among others. A high percentage of IT projects fail, especially large projects — the larger the project, the higher the likelihood of failure.
The evolutionary approach, by contrast, introduces lower risks: a much faster timeline and lower budgets. The evolutionary path typically overlays new innovative applications and solutions on top of the existing legacy systems. This process creates a gradual change of mission-critical business processes over time, giving businesses the time to shift without disrupting different departments. Evolution gives consumers time to be introduced to new technology and time for the business to evaluate the benefits and shortcomings.
The Need for Self-Service
Today’s customers demand self-service. According to Zendesk, the highest performing companies’ customer service experiences are 76% more likely to offer self-service. Even though the need for automation and fast, effective self-service experiences is clear, many companies are still in the process of adapting to the new standard. According to the same survey, less than 30% of companies offer self-service. To bridge the gap between what customers want and what CX departments offer without exceeding budget constraints or completely disrupting business operations, companies need to plan a thoughtful evolution from outdated technology capabilities to new solutions.
Innovation and change can be difficult, but if approached properly, every company can join the new age of digital customer self-service and enjoy the benefits of visual, fast, and automated solutions.
To meet shifting customer preferences and expectations, customer care professionals must identify the low-value, high-volume interactions perfectly suited for self-service automation. By innovating these use cases first, and by deploying the right level of automation for their needs, businesses will experience the best return for their investment.
Overhauling an entire customer service model is a lengthy, expensive process that requires manpower and resources, and could do more harm than good for most businesses. Automating each and every customer service function and removing all the contact center agents are not the path to success. Understanding which interactions are ready for automation and which should be kept with human agents is critical to knowing which steps to take first.
Self-Service Doesn’t Apply to Every Interaction
Not all interactions are equal. Most customer service use cases should be automated, but there are also complex, high-value interactions where customer service representatives’ human touch and personal skills are absolutely necessary. The amount of complex problem solving or human emotional intelligence needed to answer a request or solve a specific customer service issue determines the amount of added value live customer service agents bring to an interaction. Some customer service functions are simply too complicated for automation to handle effectively, or require a uniquely human perspective to accomplish.
Self-Service Does Apply to a Lot
Knowing how much a specific customer owes on their current bill and accepting payment for that bill is a straightforward, simple process, but can take up agents’ valuable time unnecessarily. Asking a customer for their ID information, looking up their account in a database, verifying their payment details, verifying their payment amount, and accepting payment for a bill is a tedious process that at best can take minutes to accomplish.
Accepting payment can be completed in seconds with effective self-service automation connected to businesses’ backend systems.
Bill payment is a great example of a customer interaction that deserves automation, but many other types of common insurance calls are ready to be digitized and automated immediately. With digital self-service, many customer service interactions can meet today’s standards:
- Appointment scheduling
- Account management
- Order and returns tracking
- Insurance claims submission
- Utility outage reports
- Price quote requests, etc.
Identifying Where to Evolve First
The Pareto Principle applies here — just a few common types of calls to the call center usually make up a large volume of interactions. By automating these high-volume interactions businesses can quickly create a big impact on customer satisfaction.
To find the best return on investment (ROI) from their self-service CX evolution, customer service leaders need to determine which type of calls make up the highest volume of calls with the least value-added from live agent guidance. Plotting call types on a four-quadrant graph can be useful for identifying the right functions to automate for your business. Place “Value” on the x-axis and “Volume” on the y-axis (below). This method makes categorizing calls a lot easier and more strategic than educated guesses. Customer care professionals can determine which call types to automate first, which to leave for later, and which are best suited for live agents’ skills. I call this the “Matrix of Evolutionary Automation.”
Identifying which calls are low-value (straightforward, easily automated tasks like bill payment or start/stop service requests) AND high-volume allows businesses to prepare and execute the evolutionary style of innovation. Automating these interactions first provides a fast return on investment and makes integrating and launching customer self-service tools like Visual IVR, chatbots, online portals, and other options worthwhile.
Choosing the Right Self-Service
Once businesses identify the right use cases to automate, the next step in a successful customer service CX evolution is choosing the right type of automation to implement. On one end of the spectrum of modern automation are macros and scripts and on the other end is AI, machine learning, and cognitive computing. Between these two extremes lies the best choice for most businesses — Robotic Process Automation (RPA).
1. Artificial Intelligence (AI) and Machine Learning (ML)
Technology like IBM Watson and Google Assistant that “think on their own” and robots that code themselves over time are understandably exciting for any business leader trying to dig deep into automated solutions. These brand new technologies offer the biggest opportunity for automation, but any company looking at AI opportunities needs to know how to swim in the metaphorical deep end already. Such a brand new technology is inherently complex and experimental.
Without a highly trained and talented IT department or the budget to support a stellar third party team, AI and Machine Learning are typically too complicated and too expensive to implement well today for most companies. Technology develops at an astounding pace, so keep an eye on AI to become commonplace over the next decade. Those opting for AI today must be willing to invest serious time and money before they expect a return.
2. Macros and Scripts
At the other end of the spectrum of automation are simple, straightforward computer scripts. These unique, custom scripts tell computers to run specific tasks and complete individual actions in a rigid order. Anyone can write and run these simple scripts with a couple of days of research and practice with programs like Windows PowerShell and Apple’s Automator for Mac. Programs like these can automate writing emails or creating calendar appointments when users run the scripts they’ve created.
Contact centers have used response macros for years to the great benefit of agents and customers. For individual employees willing to invest some personal time in learning how they work, creating their own macros and scripts can be a helpful bit of automation to enhance productivity and efficiency for repetitive or common tasks in any job. This level of automation is not scalable, however, and doesn’t create true self-service capabilities. Macros and scripts can be helpful, but they will not satisfy the demands of modern consumers.
3. Robotic Process Automation (RPA)
Somewhere between these two extremes rests a goldilocks zone for business automation. Balancing the business-wide and bottom-line improvements AI and advanced automation can provide and the much smaller costs and learning curve required by scripts, Robotic Process Automation (known as RPA) is transforming the way contact centers and live agents do their jobs. The efficiency of RPA applied to the high volume, low-value calls identified by the Matrix of Evolutionary Automation improves the customer experience, but also impacts agents’ employee experience.
Efficiency is the defining characteristic of RPA. No matter how good a contact center agent is, an RPA bot is more efficient for certain tasks. RPA can handle more tasks faster than an agent would, and can handle many times more customer interactions at the same time. Since RPA and self-service platforms take care of the repetitive jobs, the calls that do make it through to contact centers are more complex and high-value interactions. Without the burden of tedious interactions, live agents have the freedom to treat these complicated interactions with the attention they deserve, and the energy to really care for customers since the rote, repetitive tasks that might cause agent burnout have been taken off their plate.
Customers benefit from this efficiency as well. RPA bots achieve the same results as agent interactions in a fraction of the time. The simple tasks already primed for automation like tracking an order or initiating the returns process are easily fulfilled by RPA. The bots can find recent orders associated with an account in an enterprise’s database, verify a product purchase and return eligibility, then populate forms and automatically create the appropriate labels a customer will need to print and use for returning products in seconds. These speed and efficiency create a highly satisfactory experience for consumers.
Evolve with RPA to Enable On-Demand Digital Self-Service
Self-service is becoming increasingly important to customers and businesses around the globe. With a variety of options to explore, choosing the best self-service solution can be difficult.
Business leaders know every industry must deliver faster, easier to use customer care whenever and wherever customers demand to keep up with the evolving landscape of customer service. Our modern world is increasingly digital and mobile-based, and services are delivered on-demand. By identifying the types of customer care cases that fit automation best, businesses will be able to afford the big shift towards digitization and self-service that their customers will appreciate and enjoy.
Artificial Intelligence (AI) and Machine Learning deserve the headlines they garner, but practical applications of this technology are still a few years away. Robotic Process Automation (RPA) strikes a balance between the speed and efficiency advanced technologies like AI can provide and the ease of implementation, shorter launch windows, and risk-free projects that simpler automation excels at.
By taking the evolutionary approach of automating high-volume calls with RPA-based self-service solutions businesses can quickly and safely provide their customers a digital, mobile-oriented customer experience.