Boost Your Customer Support Efficiency with AI

Efficiency becomes crucial when you’re managing a team of support agents with a high volume of requests.

In high-volume contact centers or quickly-scaling teams, saving just one minute of an agent’s time per ticket can accumulate into hours saved each month. These saved hours translate into significant cost savings for your company — which you can allocate to more meaningful initiatives or to additional team head count.

With the development of AI tools, optimizing support efficiency has reached new heights. To remain competitive in today's market, it's essential to leverage these advanced technologies.

In this article, we’ll explore the concept of customer service efficiency and how you can reduce response and resolution times, automate manual tasks, and improve overall customer satisfaction with the latest AI tools.

What does customer support efficiency mean?

Efficient customer support refers to delivering the best possible service experience with the least amount of time and resources. It’s about optimizing customer interactions to ensure timely resolutions that benefit both parties: Customers get faster service, and support agents optimize their work by eliminating unnecessary tasks.

Imagine receiving an order return request from a customer.

If your help desk doesn’t provide any details about the customer, you’d have to search through various third-party tools to locate the order manually. 

Then, you might need to engage in multiple back-and-forth conversations with the customer to determine the return reason, log it in a spreadsheet, send a return label, and possibly even seek approval from upper management.

This entire process can sometimes cost a business more than the cost of the order itself. On the customer side, the customer experience would be exponentially better if they could request a return by providing all the necessary info via a seamless chatbot, spending under a minute in the process instead of enduring lengthy interactions with your customer service team (friendly as they may be).

The goal of efficient customer service is to improve the customer experience by providing quick and effective support which optimizes the use of your resources.

6 ways to improve customer support efficiency with AI

Improving customer service efficiency starts by understanding your existing support workflow. A simplified customer support workflow can look like this:

There may be additional steps like writing a conversation summary, escalating the ticket to another team, or translating drafts and customer inquiries for teams supporting international customers.

Analyze where your agents spend the most time to identify the biggest pain points and bottlenecks. Is the volume of requests overwhelming your team? Are support specialists spending hours navigating a complex tagging system? Is key customer information missing? 

Choose the most pressing issue and start brainstorming ways to streamline that process:

• Consider what can be automated using help desk triggers and auto-responders.

• Identify common queries that can be outsourced to a rule-based or conversational AI chatbot.

• Think about improving your product or documentation to better address recurring issues and solve root problems, which enables more efficient support. 

While many of these methods will be business-specific, the latest AI advancements offer solutions that can help nearly any business when implemented correctly.

1. Automated conversation tagging and assignment

One of the first steps in handling a technical support ticket is classifying it by type, priority, and urgency — to assign it to the right agent or team for a faster and more accurate response. Tagging tickets based on the theme is also helpful for segmenting insights, monitoring trends, and triggering help desk workflows.

Manual classification can be prone to human errors, inconsistencies, and delays, and it’s not the most efficient use of your resources. With the latest advancements in AI — especially conversational AI that can understand human language and derive themes, emotion, and intent — this task becomes much simpler.

Using natural language processing (NLP), tools like SentiSum can identify the themes, urgency, and intent of incoming requests. They analyze the content and context of the ticket, assign the appropriate labels and tags, and enable you to automatically route tickets to the responsible agent or team — saving time and enhancing efficiency.

Keep in mind that you’ll need to specify clear categories for the AI to assign tickets to, and even then, the results may not be 100% accurate. I recommended having a team member monitor the unassigned queue to ensure nothing falls through the cracks.

Measuring the effectiveness of tagging automation

To measure the effectiveness of tagging automation, look at the response and resolution times, and consider the cost savings associated with the time spent categorizing and manually assigning tickets.

When calculating costs saved, be sure to factor in the cost of AI automation if it’s not included in your default help desk subscription.

Insights extracted based on automatic ticket categorization are hard to quantify. However, you’ll likely see an improvement in how fast critical product issues are solved if you can support your requests with hard data from the insights.

2. AI-powered translations to support international customers

If your customer base is multilingual, offering support in multiple languages can be quite a task. In the past, you had to either staff your team with agents, managers, and QA reviewers fluent in various languages or rely on tools like Google Translate — often providing inaccurate texts, which compromised service quality.

Now, this work can be done in seconds with tools like Help Scout’s AI assist, which can translate your team’s reply or article drafts into Dutch, French, Korean, German, Italian, Japanese, Spanish, and many other languages with a single click.

This allows your team to process the inbox faster, write better responses, and ultimately build better customer relationships.

As with any AI feature, translations may occasionally be inaccurate, so you’ll want to have QA reviewers familiar with all the languages you support. Alternatively, you can track customer feedback related to translations to address any concerns promptly.

Adding a quick sentence to every response informing customers that the text has been translated by a machine can also minimize the consequences of incorrect translations and word usage.

Measuring the effectiveness of automated translations

If you no longer have to hire dedicated teams to support each customer region, the efficiency of implementing AI-powered translations will be reflected in your cost savings.

Additionally, look at response times, as agents will save time by quickly drafting replies in their native language and translating them within seconds.

Tracking Customer Satisfaction (CSAT) score is also important. If you notice a decrease in CSAT after implementing AI translations, you may need to consider a different AI service provider (if translations are low-quality) or revisit your agents’ workflow to identify any issues.

3. Writing improved by AI

Similarly to AI-powered translations, modern AI help desks can automatically fix spelling and grammar errors and help with tone in your agents’ drafts. It helps reduce the time needed for accurately typing and drafting responses, allowing agents to quickly input their ideas, click a button, and transform drafts into cohesive text that aligns with your brand.

This feature is especially beneficial for non-native speakers, who typically spend more time proofreading and correcting their responses. While it may not seem like a significant amount of time, these seconds add up during each shift. In a high-volume environment, automating these tasks can free up hours of time that your team can reinvest into initiatives with higher ROI.

Many help desk providers are beginning to offer AI-powered writing functionality.  Help Scout’s AI assist is an excellent example of this. 

Measuring the effectiveness of AI-powered writing assistance

Implementing AI-powered writing assistance should positively impact your response time and free up your team’s capacity to handle more tickets per shift since they don’t have to spend extra minutes proofreading drafts before replying to customers.

To measure the effectiveness of this process improvement, check if there's a reduction in the time your team needs to respond to tickets and if agents are able to handle more tickets per shift.

4. Automated conversation summaries

Writing clear conversation summaries when escalating an issue is a crucial skill in customer service. Quick summaries allow anyone to get an overview of a conversation without reading through the entire exchange. This is useful for handing off a conversation to another teammate, for managers reviewing quality, or for non-support team members checking in on conversations.

However, crafting these summaries takes time. It requires re-reading the ticket, identifying key moments, and writing a clear, concise, and logical summary.

The good news is that AI tools can now handle this task in seconds. For instance, Help Scout’s AI summarize generates a conversation summary in a second with just a single click.

Of course, AI isn’t here to replace human agents. Sometimes the generated summaries can be inaccurate or misleading, so it’s essential for agents to review and, if necessary, correct AI-generated summaries to ensure accuracy.

While some organizations prefer to rely on manual summaries due to these occasional inaccuracies, this approach isn’t sustainable in the long term. Having your team quickly verify and correct automated summaries is more efficient, freeing up time and mental energy for other tasks.

Measuring the effectiveness of automated summaries

To measure the effectiveness of AI-generated conversation summaries, you can monitor agent capacity and ticket handling. As the escalation process becomes more efficient, you should see an increase in the number of tickets handled per shift and a decrease in resolution times.

In my experience, automated summaries have been helpful in improving collaboration as well. They allow agents to quickly generate an overview of a full case before asking a question, which reduces the frustrating back-and-forth often required to gather all the necessary details for answering that question.

These summaries are also helpful for creating quick internal or even external FAQs and articles for cases that haven’t been documented yet, minimizing the time and resources you need to maintain a robust and up-to-date knowledge base.

5. AI chatbots

AI-powered chatbots are perhaps the most popular AI solution for enhancing support efficiency. They tackle basic customer queries, answer frequently asked questions, guide users through processes, and escalate complex issues to human agents when necessary.

Offering instant responses and 24/7 support, AI bots free up your team from repetitive tasks and allow them to focus on more critical operations. You’ve probably interacted with AI chatbots on ecommerce, hotel, or airline websites, where they handle common issues based on help center content without human intervention.

If you have an up-to-date, AI-optimized knowledge base, configuring your bot is a breeze. You can launch in just a few clicks by choosing the right personality for the bot and granting access to your knowledge base resources.

The key principles for optimizing content so that both your AI bot and your customers will love it are:

1. Stick to the “one article one message” rule: A long read of FAQs won’t help your bot fetch the best answer. Whenever possible, break multi-section articles into separate docs. The more organized, easy-to-navigate, and concise your content is, the better outcomes you can expect from your AI bot.

2. Use a standard title format: To help your AI bot easily sift through the content, choose a consistent title format and stick to it. Ideally, each title should include the product name (if you support multiple products in the help center), feature name, and article theme. Retaining customer question phrasing in the title can also help the bot find relevant answers more quickly.

3. Create templates: When your content guidelines are documented, create templates for different article types to ensure consistency and quality across your knowledge base. This consistency is crucial not only for human readers but also for your AI bot, which relies on predictable patterns to locate and retrieve information.

From my experience, a robust knowledge base can deflect up to 90% of help page visits, providing visitors with the answers they need without having to open a ticket with the support team. This saves time and allows the support team to focus on more complex issues that do require human intervention.

It's crucial to remember that AI chatbots excel at answering straightforward questions and are only as effective as the content in your knowledge base. If your support tickets often require accessing logs, viewing billing history, or analyzing user account activity, existing AI bots might not yet be up to the task without compromising user experience.

Measuring AI chatbot effectiveness

To gauge your AI chatbot’s performance, focus on the resolution rate — the percentage of tickets resolved without human intervention. A higher resolution rate signifies better performance. To improve this rate, analyze the tickets where the bot failed to provide correct responses and update available resources to cover more scenarios.

To quantify the impact, multiply the resolution rate by the number of incoming tickets over a specific period. This will show you how many tickets your team didn’t have to handle, thanks to the bot. Then, multiply this result by your average cost per ticket to calculate your savings, which can be redirected to other areas.

Bear in mind that conversational AI bots require substantial processing power, so the cost per ticket can be significant. This factor should be considered when evaluating the overall effectiveness of your investment.

6. AI-generated drafts

When using AI bots, especially in scenarios with high ticket complexity, there's a significant risk of sending incorrect, irrelevant, or misleading information to customers.

This is why some companies avoid AI bots altogether, fearing the potential negative impact on customer experience. This is particularly true in SaaS, where the complexity of tickets is typically higher than in other industries.

For teams dealing with such complexities, AI drafts can be a more effective tool than AI bots. Help Scout’s AI drafts, powered by OpenAI's GPT-4, allow your team to generate reply drafts for customer inquiries based on previous conversations and help articles.

When a ticket is assigned to an agent, it can create a high-quality draft with a single click. Agents then review and revise if necessary before sending out replies to resolve the tickets.

You can set preferred greetings (e.g., “Hi, [name]”) and closings (e.g., “Best, [name]”), saving time on repetitive typing. The voice and tone of the drafts will mimic that of your agents in closed tickets, aligning with your brand voice.

As with all AI-generated texts, it's important to instruct agents to review drafts before sending them to customers to correct inaccuracies. 

Additionally, if your industry requires HIPAA compliance, using AI drafts that rely on the OpenAI framework won't be an option.

Measuring the effectiveness of AI drafts

To assess the impact of AI drafts on your support efficiency, look at response and resolution times. These should decrease as agents spend less time writing responses and researching information.

You should also see an increase in the number of conversations handled by your team since each ticket takes less time with AI drafts.

However, keep in mind the cost associated with these tools; in high-volume environments, costs can add up significantly. You should weigh this against the potential savings and consider if using an AI bot to deflect simple queries without requiring team intervention might be more budget-friendly.

Supercharge your support with AI

At Help Scout, we’ve made using AI feel effortless. Learn more about how our AI features can save you time and energy on every conversation.

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Working alongside AI to boost customer support efficiency

The AI revolution offers exciting new ways to provide faster and more personalized support at scale. To stay competitive and maintain a high-performing team, it's essential to leverage these new tools.

According to Salesforce, 69% of high-performing support agents actively seek out opportunities to use artificial intelligence, compared to just 39% of underperformers. By embracing AI tools, your team can enhance efficiency in customer support, easing the burden of routine tasks and freeing up time to focus on more complex and engaging challenges.

But as advanced as AI is, it can't match the care and heart that support teams bring to their work every day. AI is a powerful ally, but it's the human touch that ultimately makes the difference.