Why Your Customer Service Emails Aren’t Working (And How To Fix Them With AI)

Despite the rise of newer digital channels, email remains one of the most widely used customer support channels. According to our research, 90% of service organizations still rely heavily on email.

Email is particularly useful for handling more complex and less time-sensitive issues. Its asynchronous nature allows customers to send inquiries at any time, without needing to wait on hold. Email also creates a record of the entire interaction, which can be invaluable for customers.

Despite its advantages, email can be notoriously slow – a big risk for companies in a time where customers demand faster and more personalized support. AI in customer service can address these problems by ensuring customers receive timely, accurate responses 24/7. Below, we delve into a few key ways AI can solve customer service email challenges and how your business can get started with your strategy.

What you’ll learn:

Common problems with customer service emails

Though email is still a popular customer service channel, it comes with its own challenges for both customers and service teams.

Delayed responses

Despite being one of the most used support channels, email is also one of the slowest. This delay can be frustrating for customers, who expect timely responses. According to our research, 77% of customers expect to interact with someone immediately when they contact a company. However, some companies take days to respond – if they respond at all.

High volume of emails

A big reason for delayed email responses is due to the sheer volume of emails that businesses receive daily. This high volume can lead to backlogs, making it difficult for service reps to keep up with customer inquiries. Unlike other support channels, email doesn’t scale well, and businesses often need to hire more service reps to handle the workload. This can be costly and inefficient. Employee burnout is also a major risk of email pileup.

Lack of visibility

Another issue with email support is the lack of visibility and access to customer data across systems – the service rep receiving the email might not have all of the information needed to deliver quality responses to the customer. 

Let’s say you have multiple accounts with a financial advisor and need to research a tax form, so you send an email about it. The advisor might not know which account you’re referring to without additional context, so they email you back to ask. Instead of getting the answers you needed right away, you had to go through several rounds of emails first. This back-and-forth can lead to delays, miscommunication, and a subpar customer service experience.

Lack of personalization

The high volume of emails and the manual nature of the channel can lead to a lack of personalization. Service reps may resort to quick, generic responses to manage their workload (ever receive one of those “thanks for reaching out! We’ll get back to you soon” emails?) which can feel impersonal to customers. 

This can contribute to poor customer retention, a damaged brand image, and reduced customer satisfaction and loyalty – especially when 65% of today’s customers say they expect companies to adapt to their changing needs and preferences. (Back to top)

How AI and automation can help overcome customer service email challenges

An effective solution to these challenges is the use of AI and automation, specifically through tools like Agentforce for Service. 

Agentforce for Service is Salesforce’s autonomous AI agent that can automatically handle customer inquiries across channels, from chat and messaging to email. It works by deploying AI agents that are trained to handle both common and complex inquiries, and can seamlessly escalate to human service reps when necessary – all within the trusted guardrails your business has set.

Some benefits of Agentforce for Service include:

• 24/7 availability and improved response times: AI agents can analyze and respond to customer service emails in seconds, significantly reducing average response times.
• Consistent, accurate, and personalized responses: AI agents can provide consistent and personalized responses because it’s grounded in your trusted business data and knowledge base, ensuring that each customer feels valued and heard. This can help improve customer satisfaction and loyalty.
• Cost-effectiveness: By automating email support, businesses can ease the workload on their customer service teams and potentially reduce staffing needs over time, helping to lower operational costs.
• Fast deployment and ability to scale: Set up Agentforce for Service in minutes using pre-built, service-specific templates and existing Salesforce objects, like Flows. You can even create custom actions that are specific to your business needs using low-code tools. (Back to top)

Ways to get started with AI in customer service emails

1.  Define the scope and purpose of your AI agent: When building an AI agent, the first step is to define its tasks and functions. Get your team together to review each contact driver and determine which channels serve each best. This allows service reps to focus on high-value interactions, while Agentforce handles the rest.

2. Collect and prepare training data: Training your AI agent with diverse datasets, including FAQs, knowledge bases, and chat transcripts ensures it can provide accurate and relevant responses. Start by identifying content gaps in your knowledge base and auditing it for accuracy and relevance. 

3. Start small, then scale: Focus on one achievable use case to build momentum– for example, automating the process of sending a copy of an invoice or changing a delivery date. Starting small with AI agents allows you to test and iterate quickly, helping improve performance over time. 

Remember to not aim for perfection – the key is to start small and build up to more complex implementations. (Back to top)

How to measure success

To measure and optimize the performance of your AI agent, here are some key metrics that every service leader should track:

• Automated resolution rate: Measures how many conversations Agentforce was able to resolve automatically.
• Containment rate: Measures the percentage of customer interactions that an AI agent handles successfully without requiring escalation to a service rep
• First contact resolution: Tracks the percentage of issues resolved on the first contact. AI can help increase this rate by providing quick and accurate responses.
• Customer satisfaction (CSAT): Tracks how satisfied customers are with the support they received from your AI agent. Though AI is fast, if it’s not effective it’ll leave customers feeling frustrated and dissatisfied.

Email remains a table stakes channel for customer service. As organizations face increasing pressure to provide exceptional customer service while managing costs, AI can help service teams scale their email support without putting a strain on existing resources. 

With AI, you can transform your customer service emails and drive significant improvements in both operational efficiency and customer satisfaction. (Back to top)