What's the difference between automation and hyperautomation?
Customers expect personalized service from businesses, no matter how big the company is or the industry it's in. To meet these growing demands, brands are focusing on using automation to scale up improved customer experiences (CX) and develop more streamlined and individualized interactions.
Notably, automation offers brands many benefits, including:
- Greater customer satisfaction. In addition to reducing call wait times, support team members can spend more time with customers as automated digital solutions will have helped filter out cases that do not need the attention of a live agent.
- Higher team member satisfaction. Frontline team members can spend time engaging in more meaningful interactions instead of performing simple, repetitive tasks.
In fact, there are actually two different kinds of automation in customer service: Robotic Process Automation (RPA) and hyperautomation. Knowing the differences between them and using each to their full potential is essential for brands to make the most of their investments in this technology.
While RPA has been used for decades, hyperautomation is an emerging trend recognized by Gartner as a key part of CX strategy. While companies are skilled at identifying opportunities for RPA, brands often miss ways to improve the customer experience through hyperautomation. They may also not understand how RPA can help build hyperautomated processes.
Here are five key differences between hyperautomation and robotic process automation, to help you better identify opportunities that are ripe for change and investment.
1. Hyperautomation simulates human reasoning ability
With RPA, the system follows a series of programmed actions that are the same for every task, such as a traditional assembly line using robotic arms to put the same product in every box. Hyperautomation makes decisions for each task depending on factors and data collected during the task. Consider the same assembly line, but envision being able to detect and ensure that each product meets quality standards.
2. Hyperautomation incorporates artificial intelligence, machine learning and natural language processing
To simulate human reasoning ability, hyperautomation relies on technologies that allow systems to make predictive decisions based on data. For example, hyperautomation may use past purchase history to preselect a customer's shipping address based on the type of purchase, such as sending large purchases to their office address and smaller ones to their home. By using these technologies, hyperautomation learns from each decision and becomes smarter with the data that is continually collected. However, the success of the reasoning depends largely on the amount and quality of data gathered and fed into the technology.
3. Hyperautomation focuses on business outcomes
With RPA, you automate each task as a standalone function, such as printing shipping labels. Hyperautomation addresses a complete business process. This begins with determining the business goal you are tackling, and then the specific outcome you are looking to address.
For example, a business may be looking to reduce their cart abandonment rate, which involves a number of complex factors and processes. The AI and machine learning aspects of hyperautomation can help companies predict which products and options a customer is likely to choose based on the customer's history, decisions similar consumers have made and the customer's current behavior on the website.
By analyzing this data, the technology can make decisions at specific junctures along the process that create a personalized experience for the customer, such as recommending products, using photos that are likely to appeal to them and offering customized shipping options.
4. Hyperautomation easily enables future integrations
Once you automate a process using RPA, the task exists in a silo of its own, which can sometimes make it challenging to integrate it with other tasks. There may also be a limit to how many tasks can be performed. Because intelligent reasoning is built into hyperautomation, businesses can more easily modify processes as customer and business needs change.
5. RPA is a tool in the DigitalOps toolbox used to create hyperautomation
Many brands assume they need to choose one type of automation over the other, but companies often use both types, especially in using RPA to help hyperautomate a business process.
This will be an ongoing trend. Gartner predicts that by 2022, 65% of organizations that deploy RPA will introduce artificial intelligence, including machine learning and natural language processing algorithms. When creating the hyperautomation of the entire business process, companies should consider which parts can be automated using RPA, with hyperautomation integrating the tasks into a single process.
Brands that are focused on improving the customer experience often start by using hyperautomation in one business process with a defined outcome, and then expand it to other processes. Not surprisingly, those that are not using automation may quickly fall behind competitors that are more efficient. Brands should consider leveraging hyperautomation as a key component of moving towards engaging consumers more effectively and seamlessly.