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The use of automation in customer support is expected to accelerate in the coming years. According to Dimension Research, 72% of customer interactions in 2022 will be through emerging technologies such as Robotic Process Automation (RPA). Phone interactions will drop from 41% to 12%. In light of this forthcoming big change, here are four errors to avoid when automating customer service functions.

1. Not re-engineering processes before automating

One of the core capabilities of RPA is that the software robots (“bots”) you create with it can mimic human users as they perform digital tasks at the keyboard. For example, if a human worker manually transfers data from email and call center speech-to-text systems into the customer transactional system, an RPA bot could imitate the keystrokes and menu selections and automate the entire process without coding. Because of this, many organizations are using RPA to automate customer service functions and, in fact, are achieving high ROI on their investments.

But there’s a downside to this imitative capability of RPA. That’s due to the old programmer adage, “garbage in, garbage out.” If the manual way that the human worker did the task at hand was not particularly efficient, neither will be the bot’s automated version. RPA doesn’t fix bad processes. It just speeds them up. So your customer will still get a mediocre experience—just a faster mediocre experience.

Part of the hesitancy of re-engineering customer service processes before automating them may simply be due to workers’ poor understanding of the processes such as knowing which steps are essential and which are superfluous. By collaborating with your best customer agents, you should figure out the best way to challenge the current way of doing things and hone each process that impacts customers before applying RPA. That way, you should see radical improvements in customer experience.

2. Automating the wrong processes

Many companies are eager to automate that they often start implementing without a clear goal and strategy in mind. Defining your scaling approach from the beginning is important to mitigate redundant efforts and RPA silos or using the wrong tools. Generally, processes that are highly variable with analytical decision-making aren’t the best suited for RPA. Your initial scope should start with the processes that are repetitive and rules-based for the greatest ROI.

Here are six questions, which answered affirmatively, indicate a process that is appropriate for automation: 

  • Can the task be done manually by a human sitting at a keyboard (or moving between several keyboards) working with one or more applications?
  • Does the task have to be performed repetitively, without variation, multiple times a day or week?
  • Does the task require simple decisions to be made that follow strict, well-structured rules?
  • Does the business system lack an API, or is the database behind the application inaccessible?
  • Does the task involve sensitive data? (RPA bots may be better suited for working with sensitive information. Among other reasons, it can reduce the probability of that data being mishandled as a result of human error.)
  • Does the task need to be regularly completed within tight or exacting time limits?

3.  Attempting to deploy the wrong type of bot for your process

A major benefit of RPA is that it’s adaptable to meet a wide range of automation needs. With the options available, don’t choose the wrong type of bot for your process or miss out on the benefits of a digital assistant.

If you have processes that run on a scheduled basis, don’t require human involvement, and can reside on a remote machine, an unattended bot will do the trick. These are generally high-volume back-office processes such as handling invoices or conducting system maintenance. If your processes are based on predefined events, attended bots will respond to the triggers. These are more prevalent in front-office scenarios such as customer service to help agents boost their productivity.

To help interact with these bots in an easy, scalable way, you can leverage a digital assistant to enable human-bot collaboration. For instance, digital assistants become helpful in customer service scenarios when each request is different but must be resolved quickly. Most times, the agents must search through multiple systems to find the information they need. Doing this manually for every situation takes too much time, so the digital assistant presents the agents with options for pulling data. Then, it instructs bots to search across those sources. The information comes back in the same screen, allowing the agents to review and run subsequent bots to complete the task.

In addition to choosing the right type of bot to automate your process, don’t miss out on the flexibility and control your users could have to leverage automation on their terms when they need it most.

4. Creating RPA silos in customer service

Poorly planned RPA deployments can spell trouble. Instead of resolving silos, RPA can add to the problem when done piecemeal and not fully integrated into the overall business strategy. It’s important to think about how the process moves beyond your team and connects to the back-office operations that support it such as from customer service to engineering. Taking into consideration the entire process enables you to automate workflows end-to-end for greater efficiency. By breaking down the siloed approach and taking a more holistic, integrated approach, organizations can deliver customer service automation and bots that smoothly work inside the larger IT vision for the company.

Making the most of the potential

Using RPA to automate the customer service function is a growing trend. As you begin using RPA for processes that get closer to customers—perhaps even touching them directly—it’s important to do it right. After all, customer service is usually the channel through which your customers most frequently experience your company. So give them an experience that will help boost brand loyalty. 

Make the Most of RPA.

About Sharon Liu

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Sharon is the Senior Product Marketing Manager at Automation Anywhere, focusing on front-office automation and cognitive solutions.

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