Customer Service Automation

According to GitNux, employees devote roughly 25% of their time to repetitive tasks that could be automated. Given their ability to manage rule-based repetitive tasks, Robotic Process Automation (RPA) bots can greatly alleviate the burden on customer service teams, creating a more efficient workflow.

To accomplish this, RPA bots retrieve customer answers from business databases, manage customer inquiries and complaints, update customer information, and direct calls to human agents. However, despite these advantages, RPA bots confront challenges relating to user preferences, as some customers may gravitate towards live agents for handling their inquiries.

What are the benefits and use cases of automation in customer service? Let’s explore all of this in detail. 

How does automation improve customer service?

RPA bots mimic human interactions with GUI elements and perform repetitive, rule-based tasks like answering FAQs, downloading customer emails, or retrieving information from databases (e.g., pricing, shipping, troubleshooting). 

Therefore, RPA improves customer service by:

  • Data gathering and analysis
  • Guaranteeing consistent and speedy responses
  • Minimizing data errors (outdated information, duplicate file transfers, unverified customer data)
  • Offering round-the-clock service

7 RPA Applications in customer service

1. Supporting customer representative agents

63% of customers believe that representatives should have a thorough understanding of their needs. In response, Robotic Process Automation bots collect pertinent information such as demographics, purchases, and previous tickets or complaints which can then be shared with the representative in advance. Equipped with this knowledge beforehand, the rep will be able to anticipate the inquiry and move quickly toward a resolution.

2. Establish customer accounts

Each customer has a unique account in a company’s CRM database, including their name, customer ID, contact details, credit card information, and purchase history. Customers usually create their accounts by talking to a customer rep or a chatbot in a recorded conversation. The bot can then automatically extract the relevant information from the recording, fill out the forms to create the customer account, validate the payment details against bank records, and notify the customers once the account is fully set up.

3. Handle customer refunds

RPA bots can obtain customer refund inquiries from emails, messages, or ticketing systems, and start the refund procedures without any human intervention. They can also send a notification to the user through email or text to inform them about the completed refund.

4. Address rule-based problems

Issue information can be collected and entered into the ticket system either by RPA bots or AI-powered customer service chatbots. RPA bots can access the ticket database and automatically resolve straightforward customer issues, such as:

  • Renewing customer password or login details
  •  Updating orders (altering delivery address, requesting return code)
  • Adjusting payment information (credit card number, pay-at-the-door option)

5. Refresh CRM data

RPA bots can extract data from business databases (e.g., customers’ past purchases, interactions with customer service staff, cold calls & emails, documents, and reports) and update CRM data (e.g., contact history, lead scoring, order history) based on new emails, texts, online surveys, or filed reports.

A workflow for issue resolution is created based on the assigned priority level, and the customer is informed of the refund decision.

6. Document customer complaints

RPA bots can utilize NLP and OCR to comprehend customer complaints in emails or texts, extract complaint data (e.g., service downtime, package delay, incorrect delivery), input it into spreadsheets or text documents, and generate reports that can be:

  • Sent to relevant customer support staff
  • Analyzed for detecting issue patterns
  • Logged for compliance and audit purposes

On the other hand, AI-enabled RPA can resolve more complex customer issues by:

  • Using NLP to determine customer intent in an email or text, and directing them to the appropriate customer service rep or IT staff.
  •  Employing ML classification algorithms to understand the importance of an issue and prioritize technical support or customer reps’ schedule accordingly

7. Automate email responses

RPA bots can gather data from various databases and create emails in response to customer requests. For example, bots can obtain data from:

  • Logistics database for emails about shipment tracking or delay information
  • FAQ database for answering store or warehouse locations and opening hours queries
  •  IT documentation to address product troubleshooting inquiries
  • Marketing database to provide information on coupons and promotions
  • Finance database to create invoices for customers and send them via email

RPA bots can also generate ticket closure emails and send them to customers who have filed a complaint or opened an issue ticket.

How have businesses used automation to improve Customer service?

Businesses such as call centers and e-commerce companies are now using RPA and other AI models  to automate their customer service tasks. 

1. Akaike Technologies

A multinational chemical company wanted to create an automated email query resolution system. They needed something that would provide tailored experiences for potential customers while saving time and resources. With over 50,000 employees and operations in over fifty countries, this large corporation offers a wide variety of products ranging from pharmaceuticals to vaccines and healthcare items. To ensure customers receive the right documentation they need to use these products, we developed a Name Recognition Model (NER) that could accurately identify 13000 products and then send the corresponding product specification documents from their website. This solution was successful in automating 55% of all email responses.

2. Cobmax

A case study by IBM demonstrated that Cobmax, a sales call center, utilizes an IBM-built RPA service that cuts back-office operations by half. What is more, the company is able to sell 20,000 products each month and create client reports in less time.

Cobmax uses RPA bots to retrieve clients’ data such as demographics, purchases, past complaints, and tickets and forwards them to the customer care representative ahead of time to assist them in anticipating customer questions, allowing them to resolve issues efficiently.

3. Wrk

RPA bots or AI-based customer care chatbots may both gather and enter issue information into the ticket system. For instance, Wrk’s Ticket Routing & Escalation system automates customer support ticket routing.

The program uses rule-based parameters and machine learning to automate ticket resolution – it identifies the issue, searches the knowledge base for an acceptable solution, and chooses the best internal routing. Finally, it sends an automated follow-up mail to confirm the resolution.

Using this routing system, Wrk can automatically search and suggest solutions to common customer issues, as well as escalate tickets when necessary, helping reduce the number of support calls and improving customer satisfaction scores.

4. IQOR’s Omnichannel Support

IQOR system was designed to provide customer support through multiple channels, such as phone, chat, and email. The system was is able to route customer inquiries to the appropriate channel and CSR automatically. In addition, the system provided real-time updates to customers on the status of their inquiries.

This has helped improve IQOR’s efficiency as 38% of calls were automated digitally, and $180,000 annualized savings in FTE were achieved. This feat was accomplished by identifying and routing millions of contacts on the appropriate channels in the first year.’