Automation in Customer Service: Use Cases, Benefits, Best Practices in 2024
The competitive marketplace relies heavily on excellent customer service for businesses to stand out. In this regard, businesses have been adopting automated customer service systems to elevate their service offerings. In fact, McKinsey research shows that many business operations related to customer service are the business areas where contact center AI is taking place mostly (see Figure 1).
Figure 1. Top applications of AI in business operations
The implementation of an effective automated customer service platform can help businesses harmonize their processes. There are steps to implement for achieving this, including the selection of a matching customer service automation software among alternatives.
In this article, we will delve into automation in customer service by explaining its use cases, benefits and best practices for achieving it.
What is customer service automation?
Customer service automation is the process of using technology to automate and streamline certain customer service tasks that were traditionally done by human agents. This can include:
- Responding to common inquiries
- Directing customers to the right resources
- Providing real-time updates
- Troubleshooting issues
Automated customer service tools can handle routine customer service processes like updating customer records, tracking service levels, generating reports, etc. This reduces manual work and allows customer service agents to focus more on the complex customer issues.
Salesforce is the CRM market leader and Salesforce Service Cloud platform designed specifically for customer service and support with AI-driven assistants. Service Cloud enables workflow automation for many branches of the customer service by streamlining customer support processes, managing cases, and providing an exceptional customer experience by centralizing customer interactions and data in one unified platform.
What is included in customer service automation?
Chatbots and virtual assistants
These technologies use natural language processing (NLP) and machine learning to understand customer inquiries and provide responses in real-time. More sophisticated chatbots can even perform tasks like scheduling appointments or placing orders. Some businesses also employ voice-activated virtual assistants for customer service.
Automated email responses
Apart from autoresponders that are typically used for confirmation emails or tickets, automated email responses can also be used for personalized marketing, follow-ups, and notifications based on customer behavior.
Self service portals
These may contain a range of resources including video tutorials, user manuals, step-by-step guides, community forums, etc. Advanced systems may use AI to recommend relevant articles based on a customer’s query or browsing behavior.
Interactive voice response (IVR) systems
These systems have evolved to provide more complex interactions, like personalized greetings, customer identification, integration with CRM systems, and even predictive routing to the most suitable agent.
Automated systems for creating, assigning, tracking, and managing customer service tickets can improve efficiency and ensure issues don’t fall through the cracks.
Social media automation
Apart from auto-responding to messages and comments, these tools can also track mentions of your brand, schedule posts, and provide analytics.
Predictive customer service
Advanced AI models can predict customer behavior, like the probability of a customer churning, which products they are likely to be interested in, or when they might need support. This allows businesses to proactively address issues and opportunities.
Customers are reaching out to companies from various social channels (see Figure 2). Automated systems can integrate support across multiple channels – like email, phone, live chat, social media, etc. – providing a consistent and seamless customer experience.
Figure 2. Top 10 channels preferred by customers in customer support
Source: Salesforce Research (State of the Connected Customer Report)
Check out our data-driven and transparent article on social customer service software.
10 customer service automation use cases
Customer service automation has a wide array of use cases across different industries and types of customer interactions. Some common examples include:
Chatbots and automated email responses can address common inquiries, providing quick answers without the need for human intervention.
Automated ticketing systems can streamline the process of issue reporting, assignment, tracking, and resolution.
Order status and updates
Automation can help provide real-time updates about orders, deliveries, and returns, reducing the need for customers to reach out for such information.
Automation can guide new customers through the setup or onboarding process, delivering important information and addressing common challenges.
Booking and reservations
For industries like hospitality and transportation, automated systems can handle booking and reservation requests, including modifications and cancellations.
Customer feedback collection
Automated customer satisfaction surveys and feedback forms can gather customer opinions and satisfaction levels post-interaction or post-purchase.
Upselling and cross-selling
Based on customer behavior and purchase history, automated systems can recommend additional products or services.
Automation can tailor promotional messages and offers based on individual customer preferences and behavior. Personalized email marketing is an example of this practice.
Advanced AI can predict when a customer might encounter an issue (for instance, based on their usage patterns) and proactively provide assistance or resources.
In industries like healthcare or financial services, automation can help remind customers of upcoming appointments, payment due dates, policy renewals, etc.
The benefits of customer service automation
Automating customer service can bring many benefits:
Automation can handle routine tasks and common inquiries faster and more efficiently than human agents, reducing response times and increasing the overall productivity of the customer support team.
By automating certain tasks, businesses can reduce the workload on customer service representatives, potentially decreasing the need for a large customer service team and thus reducing customer service costs.
Automated systems can handle a large number of requests simultaneously, allowing businesses to easily scale up their customer service skills and operations during peak times without the need for additional staff.
Unlike human agents, automated systems can provide customer support around the clock, ensuring customers get help whenever they need it, regardless of time zones or holidays.
Automation ensures that every customer receives the same high level of service, with consistent information and prompt responses, reducing the risk of human error or variance.
Data collection and analysis
Automated systems can collect and analyze customer data to derive insights about customer behavior, preferences, and satisfaction levels. This data can be used to further improve customer service and tailor offerings to customer needs.
With predictive analytics and AI, businesses can anticipate customer needs and issues before they arise and proactively provide solutions, enhancing the overall customer experience.
As a result of these benefits, automation in customer service also benefits customers and customer service teams:
Improved customer experience
By reducing wait times, providing accurate information, and resolving issues quickly, automation can significantly improve the customer experience.
Increased employee satisfaction
By automating routine tasks, employees can focus on more complex and rewarding tasks, which can improve job satisfaction and reduce burnout.
What are the best practices for achieving automation in customer service?
1- Analyze your needs
Start by identifying the areas in your customer service that require automation. Look for repetitive tasks, frequent customer queries, or areas where speed and efficiency could be improved.
2- Choose the right technology
Depending on your needs, to automate customer service, choose appropriate automation tools. This could include any of the technologies we mentioned above. You might also consider investing in CRM software with automation capabilities.
However, the best technological investment to achieve automated customer service is to pick a customer service software that can potentially offer most of these solutions. Also, you can consider investing in customer self service tools to help your customers solve problems on their own.
For helping businesses in selecting the best automated customer service software, we have an in-depth vendor selection article where we list the top vendors.
3- Train your staff
Make sure your customer service agents understand how to use the new tools and how they fit into the overall customer service strategy. They should also know how to step in when the automated system can’t resolve a customer’s issue.
4- Maintain a human touch
While automation can handle many tasks efficiently, some situations require human intervention. Make sure customers can easily reach a human agent when they need one.
5- Start with the customer in mind and communicate changes to your customers
Consider the customer’s perspective and needs when implementing automation. The ultimate goal should be to enhance the customer experience, not just cut costs or increase efficiency.
Let your customers know about the new automation features and how to use them. Ensure they also know how to reach a human agent if they prefer.
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If you have questions or need help in finding vendors, don’t hesitate to contact us:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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