Top 7 RPA Use Cases to Transform Customer Service in 2024

Hey there! Do you manage a customer service team? Are you looking for ways to improve productivity and free up your staff for more rewarding work? If so, you’ll be excited to learn how robotic process automation (RPA) can overhaul customer service operations.

In this comprehensive guide, we’ll explore the top 7 use cases for deploying RPA bots across customer service and support teams.

We’ll look at real-world examples, data on results, and expert advice to help you determine if RPA is right for your business. Let’s dive in!

The Growing Case for RPA in Customer Service

Providing prompt, accurate and personalized support is crucial for customer satisfaction today. However, customer service agents spend countless hours on repetitive manual tasks like copying data between systems, filing paperwork and answering routine questions.

This frustrates customers with long waits and distracts agents from higher-value work. It also leads to errors when agents have to rush through repetitive chores instead of focusing on service quality.

This is where RPA comes in. RPA software utilizes AI-powered bots to automate high-volume, repetitive tasks. According to a Research and Markets report:

• The RPA in customer service market is projected to grow from $680 million in 2022 to $1.8 billion by 2027 as more businesses adopt automation.
• Key drivers include improving customer satisfaction, reducing costs, enhancing data accuracy and increasing compliance.

Let‘s look at some key numbers demonstrating the benefits of RPA for customer service:

• 80% of organizations say RPA has met or exceeded their expectations for speed, quality and compliance.
• 75% of firms achieve payback on their RPA investment within less than a year.
• 43% of customer service leaders say automation is crucial to support business growth.
• Forrester predicts over 50% of customer service interactions will be automated by next year.

Clearly, RPA adoption is accelerating across the industry. Next, let‘s explore some of the most popular and valuable RPA use cases for elevating your customer support.

Top 7 RPA Use Cases to Automate Customer Service Tasks

1. Increase First-Contact Resolution with Customer Data

Delighting customers often comes down to solving issues quickly on the first try. But agents waste precious time toggling between systems to gather necessary customer data.

RPA bots can automate this process – fetching profiles from the CRM before interactions so agents have all the context they need handy.

Let‘s consider a couple examples:

• Inbound calls – The bot screens the number, pulls up the matching account details and displays them for reference as soon as the agent takes the call.
• Live chats – When a customer connects, the bot immediately searches for them in your knowledge base and shares relevant purchase history, past issues and personal data with the agent.

According to Forrester, 77% of customers are more likely to buy again after a positive service interaction. Equipping agents with customer data via RPA helps facilitate prompt, tailored resolutions that create happy repeat purchasers.

2. Accelerate Onboarding with Automated Account Setup

Manually creating new customer accounts is time-intensive, requiring data entry across multiple systems. RPA can automate the busywork while ensuring accurate onboarding.

For example, during a recorded sales call where the agent gathers the prospect‘s information and makes the sale, the RPA bot can:

• Extract relevant details from the call transcript using optical character recognition and natural language processing.
• Auto-fill forms to create user profiles in your customer database.
• Validate submitted credit card numbers and billing addresses.
• Input payment options for account activation.
• Send a customized welcome email confirming new account creation.

This frees up your team from hours of repetitive paperwork after each sale. McKinsey found that RPA can deliver the equivalent work of up to 5 full-time employees – accelerating growth without expanding headcount.

3. Slash Customer Refund Processing Time

Managing returns and refunds brings massive admin work, from verifying eligibility to processing payments. RPA can help your company handle refunds accurately at scale.

When a customer emails their refund request, the RPA bot could instantly:

• Check the CRM records to validate the purchase details and confirm refund policies were met.
• Create a return request in inventory systems and monitor status.
• Calculate the refund amount and submit the approved refund to financial systems.
• Send the customer a confirmation email with details on receiving their refund.
• Log full notes on the interaction in the CRM for agents.

Aberdeen research found companies with RPA see agent productivity rise 35% or more. Automating repetitive lookups and data entry for refunds is one way to realize these significant gains.

4. Boost Self-Service Resolution through AI-Enhanced Bots

Many customer issues like password resets, changes to existing orders, or updates to payment methods can be easily resolved through self-service. But conventional RPA lacks the contextual awareness to handle these without human intervention.

By combining RPA with AI capabilities like natural language understanding, bots can automatically handle more complex requests:

• Change delivery address – Read customer emails or chat messages requesting address changes, then update the relevant order record in the CRM.
• Modify a subscription – Identify intent when a customer describes desired subscription changes. Then navigate the subscription management portal and make the requested adjustments.
• Account verification – Request and validate identifying information before providing access to sensitive account details.

Expanding RPA with AI enables easy self-service resolution for customers, reducing calls and live chats. According to Salesforce, AI automation increases agent productivity by nearly 3x.

5. Maintain Quality Customer Data with Automated CRM Updates

With customer interactions spread across channels like email, chat, phone and social media, data quickly becomes scattered and outdated. RPA can tackle this by continually updating CRM systems to create a "single source of truth".

For example, bots can:

• Log every customer service interaction in the CRM system – from live chats to survey responses.
• Pull data from purchase orders, delivery systems, marketing platforms etc. to maintain complete profiles.
• Standardize data formats when consolidating info from different systems and reports.

Keeping CRM data current ensures agents always have the full picture so customers don‘t have to repeat themselves. Pega found real-time data updates using RPA drive a 36% increase in first-contact resolution rates.

6. Improve Issue Routing with Intelligent Complaint Tracking

When upset customers vent on social media or flood your inbox, efficiently routing their complaints is crucial for redressal. RPA can digest these unstructured data sources and accelerate assignment and tracking.

For example, RPA bots with AI capabilities can:

• Analyze customer emails to classify issues into categories like billing, delivery, return etc.
• Assess severity based on factors like frequency of complaint, lifetime value of customer etc.
• Log issues in tracking systems and flag priority cases to managers.
• Route each case to the right team or agent for resolution based on pre-defined rules.

Centralizing and automating complaint capture ensures no issues get overlooked, and each is handled promptly by the appropriate rep. DataRobot found AI-driven routing and prioritization can decrease resolution times by 20-30%.

7. Handle High-Volume Inquiries with Auto-Replies

Customer service teams get bombarded with repetitive questions on order status, store hours, product availability and other common topics. RPA can help manage the deluge.

Bots can be programmed to search databases and instantly respond to FAQs like:

• Order status – Fetch delivery date and tracking info from logistics systems.
• Billing questions – Pull up invoice details from the CRM.
• Promotions – Check the marketing platform for applicable coupons.
• Product inventory – Connect with ecommerce and warehouse systems to confirm availability.

Automating routine inquiries improves response rate and accuracy while freeing up agents for more complex issues requiring human intelligence. ResultsPositive found RPA-powered chatbots resolve 60-70% of common queries, reducing call volumes.

With relevant data and examples for each of the top 7 use cases, you can make a strong case to leadership on RPA‘s transformative potential for your customer support teams. Now let‘s discuss some key considerations for successful bot deployment.

Overcoming Challenges to RPA Adoption

While interest and adoption are growing rapidly, RPA still faces some hurdles when it comes to customer service applications:

Reluctance to Use Bots

Despite the benefits, many customers still prefer human representatives. According to BusinessWire:

• 75% favor live service agents over bots.
• 60% say human touch is very important.

To shift perceptions, setting proper expectations through customer education will be crucial:

• Assure users bots will only handle simple issues, routing complex problems to highly-trained agents.
• Communicate how automation helps agents focus more time on providing thoughtful support.
• Share case studies of other firms seeing performance boosts with RPA.

Limitations of Rules-Based Bots

While great for repetitive tasks, RPA bots rely on programmed rules and lack flexibility to handle novel situations. Expanding RPA with AI as illustrated in use case #4 will be key to automating more sophisticated issues.

You can also look for RPA platforms with built-in optical character recognition, natural language processing and machine learning capabilities for smarter bots.

Ensuring Effective Bot-Human Handoffs

Companies must carefully design workflows to smoothly transfer customers from bots to human agents when needed. Best practices include:

• Provide agents visibility into bot-customer interactions before taking over.
• Train agents to acknowledge and briefly recap bot conversations when engaging.
• Set clear criteria for bot escalations to agents to avoid handoff delays.

With the right bot-human transition protocols, your customers won‘t realize when they move between automated and human support.

Are Your Service Teams Ready for RPA?

Based on the top use cases and results outlined here, my recommendation is a resounding "Yes!" RPA promises immense service productivity gains through around-the-clock automation of repetitive processes.

Key points that make customer service an ideal environment for RPA success include:

• High volume of rules-based tasks – Data entry, information lookup and routine inquiries all lend themselves well to automation.
• Multiple complex systems – Bots excel at connecting data across CRMs, knowledge bases, logistics systems and more.
• Growing call volumes – Automation enables meeting rising demand without exponentially growing staff.
• Expectations for quick response – Bots can instantly answer common questions and pull data for agents.
• Need for personalized service – Automating repetitive tasks allows agents to focus on building customer relationships.

Hopefully the real-world examples and data shared here illustrate the immense potential for RPA to transform your customer service center. Please feel free to reach out if you need any guidance assessing RPA solutions or building the business case for your organization. I‘m happy to help you determine the best approach to leverage automation for happier customers and employees!