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Automation In Action: 6 Ways Companies Are Nailing Customer Service

Automation In Action: 6 Ways Companies Are Nailing Customer Service

September 5, 2024

Automation In Action: 6 Ways Companies Are Nailing Customer Service

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Two centuries ago, customer service meant long walks to factories or handwritten letters. The First Industrial Revolution transformed production but left customer support cumbersome. Then, Alexander Graham Bell's telephone invention in the late 19th century marked the first major shift.

Fifty years later, call centers, and toll-free numbers revolutionised customer service, introducing mass production efficiency. However, even with the 1980s Interactive Voice Responses (IVRs), the burden on human agents remained, leading to widespread outsourcing.

The dawn of the 2000s brought a new era of customer service. Remote support tools enabled tech support to resolve issues quickly and efficiently, fostering direct interactions and prompt solutions.

However, just when we thought customer service had peaked, along came AI and Chatbots. To meet these demands of today’s customers, many companies are now integrating AI across all customer service channels. 

It's no surprise that 61% of customer service professionals predicted that by 2024, most representatives will be using AI and automation in their roles. 

In this blog post, we explore the top customer support automation examples and use cases, showcasing how these tools are reshaping the future of customer service.

The growing importance of customer service automation

Modern customer service teams have to face significant challenges every day. Take, for example, ticket backlogs, which can pile up overnight, leaving teams with a daunting task each morning. The increasing number of support tickets stretches wait times, leading to customer frustration. 

Customers eagerly awaiting updates often find themselves left in the dark, turning satisfaction into dissatisfaction.  75% of online customers expect help within five minutes, underscoring the need for rapid response times​. 

Additionally, without the right tools, businesses struggle to proactively address customer needs, often reacting to issues as they arise. Therefore, Customer service automation is necessary for modern businesses, enhancing efficiency and effectiveness in meeting customer needs. 

Strategically employed customer service automation can transform support interactions by employing advanced technologies like AI chatbots, automated ticketing, and intelligent routing. 

Types of customer service automation

Type of Automation Automation Automation Impact
Communication Chatbots: Instant responses for FAQs Efficiency

Increases the speed of handling requests and reduces wait times

IVR systems: Route calls efficiently
Automated email Responses: Quick replies
Operational Self-service portals: Reduces support calls Cost Reduction

Lowers operational costs by reducing the need for human agents

Knowledge bases: Decreases query volume
AI-driven solutions: Minimizes human workload
Omnichannel Personalized recommendations: Enhances user experience Customer Satisfaction

Can improve satisfaction by providing quick resolutions or enhance frustration if not well-implemented

24/7 support systems: Availability boosts satisfaction
Analytical Automated workflows: Ensures consistency Error- Reduction

Reduces errors by following programmed guidelines

Predictive Analytics: Identifies issues proactively
Optimization Interactive training modules: Efficient onboarding Training and Onboarding Automates training processes for consistency
Knowledge management systems: Streamlines training resources

6 real-world B2B customer service automation use cases with examples

👉Use case #1: Responding to common customer questions

Sephora's AI-driven virtual assistant enhances the retail experience by seamlessly integrating physical and digital touchpoints. This led to the attraction of over 9,000 users within a year (6,000 in Singapore and 3,000 in Malaysia), facilitated over 332,000 conversation sessions, and contributed to an average incremental monthly revenue of $30,000.

How does the automation work?  

  • Allows customers to reserve products and pick them up in-store
  • Checking product availability.
  • Answering questions about store timings and return policies
  • Scheduling in-store makeover appointments
  • Directing customers to relevant FAQs or knowledge-base articles
  • Generating service tickets by collecting customer information and issuing details

💡Tip:  AI-driven self-service chatbots can manage customer queries around the clock, ensuring that common questions are addressed even when your support team is offline.

For more useful handling of frequently asked questions, consider using AI solutions that can be trained via custom data sets. Make sure it integrates easily with your existing knowledge base, allowing for better training and more accurate responses. Also, check if the tool can facilitate quick handover to human agents for complex queries. 

👉Use case #2: Streamlining call transfers and escalations

T-Mobile uses AI to streamline call transfers and ticket escalations, ensuring that all its 12,000 call center agents are equipped with comprehensive customer information to provide effective and timely assistance.

How does automation work?

  • Gathers issue details and billing history
  • Routes calls to the right department
  • Pre-fills agent interfaces with relevant information
  • Facilitates smooth escalation and call hand-offs for  higher-level support
  • Reduces repetition by customers

💡Tip: Practical features like a Unified Agent Desktop can streamline operations by providing a clutter-free interface where agents can easily switch between calls, messages, and multiple channels like email, voice, live chat, text/SMS, and WhatsApp.

Real-time access to comprehensive customer information helps ensure more personalized interactions, while
automated ticketing systems classify and route complex queries to the right point of contact.

👉Use case #3: Improving self-service accessibility

IKEA’s self-service portal revolutionizes customer support by giving users a powerful platform to handle their needs independently. When this was done, IKEA secured significant growth for eCommerce, increasing its revenue share from 7% to 31% over three years. This approach not only boosts customer satisfaction but also reduces the strain on support teams.

How does the automation work?

  • Access a comprehensive library of articles, tutorials, and FAQs
  • View and update account information, track orders, and download invoices
  • Submit and route support tickets automatically
  • Utilize features like virtual kitchen design and real-time product availability checks

💡Tip: An information-driven knowledge base promotes self-help and integrates quickly with AI chatbots, nudging customers to detailed solutions when they encounter specific issues.

👉Use case #4: Hyper-personalization with customer insights 

Starbucks leverages advanced data analytics and AI to enhance personalization and optimize various aspects of its customer service and operations. The use of these technologies allows them to offer highly personalized experiences and make data-driven decisions to improve customer satisfaction and operational efficiency.

How does the automation work?

  • Collects extensive data on customer spending, preferences, and visit patterns
  • Uses historical order data to suggest food and beverage choices tailored to individual preferences and times of day
  • Pushes custom recommendations based on user behavior and frequency of visits
  • Analyzes preferences to drive innovation in product offerings, such as new drink options or seasonal specials
  • Utilizes data and AI for revenue projections and identifying new opportunities based on factors like traffic and competitor presence

💡Tip: The ability to monitor the entire customer lifecycle, from initial engagement through ongoing support, all in one place and a comprehensive view of the metrics of customer interactions can enable data-driven decisions and tailored experiences.

👉Use case #5: Predictive analytics for proactive service

Amazon excels at using predictive analytics to manage customer expectations and enhance service quality. They anticipate potential issues and communicate proactively. Also, the company ensures a smooth customer experience and minimizes inquiries related to order statuses.

How does the automation work?

  • Analyzes order data and shipping patterns to predict potential delays
  • Sends proactive notifications via email or app about the status of orders and possible delays
  • Offers compensatory benefits, such as extended prime memberships, to mitigate the impact of delays
  • Reduces customer inquiries by providing timely and relevant updates on order status

💡Plivo Tip: Use predictive analytics to reliably anticipate customer needs and address potential issues before they arise, taking a proactive stance. For example, automation tools can help schedule and send timely updates based on customer actions or milestones.

👉Use Case #6: Identifying Identifying opportunities for agent performance optimization

The British Columbia Lottery Corporation (BCLC), generating $2.9 billion (CAD) annually and employing 1,200 people, has been a Top 50 employer in BC for over 16 years due to its focus on customer experience (CX) and innovative technology. Previously, their customer support division dedicated nine employees to auditing support interactions, but this manual effort rarely yielded actionable feedback. 

Despite this, BCLC's focus on agent coaching has led to a 220% increase in NPS, a 7-point rise in CSAT, a 56% decrease in difficult calls, a 16% increase in advocacy, and a 21% improvement in expectation setting.

How does the automation work?

  • Shows how each agent performs in key areas for every conversation
  • Highlights agents needing more coaching based on performance metrics
  • Indicates which processes and products may need enhancements
  • Provides detailed insights into individual agents’ performances

💡Tip: Using customer service analytics to monitor KPIs and SLAs can help identify top performers who need more training and enhance your team's efficiency.

Addressing critical challenges and considerations

Tackling the complexity of integration 

Integrating automation systems with existing customer service infrastructure can be a significant challenge due to the complexity and variety of platforms and technologies. Successful integration requires careful planning, technical expertise, and a strategic approach. 

  • Mapping out the entire customer journey is crucial
  • Determining the types of customer data collection
  • Understanding how customer information will flow through different systems
  • Overcoming technical hurdles, such as compatibility issues
  • Ensuring new tools work harmoniously with existing systems
  • Regular updates and monitoring are critical to maintaining an effective system as technology and customer needs evolve

The human touch vs. automation debate

The debate between human touch and automation often highlights organizations' challenges when introducing new technologies. Employees may resist automated processes, leading to the need for effective training and change management strategies to ensure a smooth transition. 

Several factors drive the resistance to automation:

  • Employees may worry about their job security and the possibility of being replaced by machines
  • Without a clear grasp of how new technologies work, employees may be hesitant to embrace them
  • There's often a concern that automation undermines their organizational role and value

Addressing these issues requires a thoughtful approach and extensive training to integrate technology while maintaining the sanctity of the human element in the workplace.

The role of data security and trust

Ensuring data accuracy and reliability is paramount for effective automation. Inaccurate or inconsistent data can lead to erroneous outcomes, undermining automation efforts. So, data privacy and security concerns have become increasingly significant. 

With the growing volume of data collected and stored through automation, organizations must take robust measures to safeguard data and respect individual privacy. Here are some approaches:

  • Maintain high-quality data inputs to avoid errors
  • Address data inconsistencies for smooth automation processes
  • Protect data privacy—this is critical 
  • Implement stringent security protocols to safeguard stored data
  • Ensure the confidentiality of personal information to build trust with customers

Maximize the potential of customer service automation

The evidence is clear: customer service automation significantly enhances the customer experience. While the advantages of automation—such as 24/7 availability and improved efficiency—are undeniable, the most effective support systems blend automation with human interaction. 

Plivo CX exemplifies this synergy with its sophisticated tools designed to elevate customer support while adapting to evolving expectations with features like: 

  • Drag-and-Drop Workflow Builder: Without needing to code, quickly design and implement automated customer journeys, streamlining interactions across all communication platforms
  • OpenAI-Powered Self-Service Chatbots: Provide around-the-clock support for complex queries, ensuring customers receive timely and accurate responses
  • Unified Agent Desktop: Deliver seamless service across multiple channels, including email, voice, SMS, WhatsApp, and live chat
  • Metrics and Reporting: Gain insights from real-time feedback and interactions to tailor your approach and enhance service quality
  • Agent Coaching Tools: Leverage call recording, barge, and whisper functionalities to refine agent skills and improve performance

Ready to see automation in action for your business? Book a demo now!

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