How does an automated chatbot work? Benefits and best practices

Businesses today are facing immense pressure to deliver exceptional service while also improving operational efficiency. That’s why automated chatbots are emerging at the perfect time to give companies a leg up. 

As stated by our Customer Service Trends Report 2023, almost a quarter of support teams (23%) were impacted by headcount reductions in 2022.¹ At the same time, customer needs and customer service volumes have been escalating out of control.

This situation presents a significant risk of agent burnout, which can ultimately lead to decreased levels of satisfaction and service quality. Automating routine inquiries offers support leaders a way to take some of the load off of their teams without compromising the quality and consistency of their customer service. 

It is in this precise scenario where automated chatbots excel. They are able to efficiently handle a high volume of queries, freeing up your representatives to tackle more complex, strategic support issues. A study by Gartner. predicts that, by 2027, chatbots will be the leading customer service channel for roughly a quarter of organizations.²

In this article, you’ll learn more about how chatbot automation increases customer service potential and the best practices to implement the technology at your own company.

What is a chatbot?

A chatbot is a conversational technology designed to interact with humans through text or voice-based interfaces. It follows an input-output model: the user sends a command, and the system processes it and returns with a response. When a customer reaches out, an automated chatbot is ready to offer assistance around the clock.

How does an automated chatbot work?

Broadly speaking, automated chatbots can be categorized as either rule-based or AI-powered in their design and implementation. Both have merits depending on specific use case requirements, and can be implemented together as part of a customer service strategy.

Rule-based chatbots operate using predefined conditions and triggers. They are best suited for addressing basic, predictable inquiries through rules that are easy to set. They follow a  strict "if-then" structure that provides reliable responses to standard, predictable questions.

AI chatbots leverage natural language processing and machine learning to interpret language context and continually improve and refine their answers over time. Their adaptive nature allows AI to handle diverse scenarios and makes them well-equipped for complex, unpredictable conversations that rule-based chabots cannot accommodate.

How do automated chatbots increase customer service performance?

Chatbot automation delivers great benefits for customers, offering convenient support anytime, anywhere. But how can they help teams’ and companies’ goals?

Reducing support volume

When the storm of high ticket volumes hits, customer service teams face a challenging task. While adding more staff might help customer support volume in the short term, automation offers a way to provide consistent and scalable service, regardless of the fluctuations in demand. 

By offering self-service and 24/7 support, automated chatbots do more than just ease current workloads; they also prevent future pressures from piling up. 

In fact, our Customer Service Trends report reveals that 75% of support leaders intend to boost their technology investments within the next year to help them manage conversation volume.

Unlocking automation opportunities for your support tech stack

Many people still see automated chatbots as standalone solutions, but their greatest potential lies in their being integrated into your customer service tech stack.

Customer support tech, particularly help desk software, is the backbone of efficient support operations. It's the hub for receiving, managing, and addressing customer inquiries. When you combine it with an automated chatbot, you unlock a world of automation opportunities.

Imagine a chatbot incorporated into your help desk software – a chatbot for help desk automation. With this powerful integration, customer queries that would usually result in support tickets can now be handled straight away by your chatbot. It troubleshoots, collects additional info, and can often even resolve the issue without human intervention.

The integration can also tackle requests that are already in the backlog, offering prompt responses to unanswered issues.

Moreover, you can set up automated processes to gather customer feedback. After resolving an issue, the chatbot can be activated to assess the customer's satisfaction level.

With a platform like Intercom, you can achieve all of this seamlessly, making it an all-in-one solution for managing your team’s chatbot and help desk operations.

Improving employee engagement

With reduced volume and fewer repetitive tasks, you can free up your team to focus on the areas where they can have the greatest business impact.

Data from our Customer Service Trends report shows that more than half (52%) of those surveyed identified investing in technology to alleviate workload as an important means of enhancing support team morale.

On top of that, 81% of support leaders are confident that technology, including automated chatbots, will elevate employee engagement and reduce attrition rates within their support teams.

“Team burnout is often caused by the repetition of answering the same questions, rather than the volume of work. Using chatbots and conversation tags in Intercom, we can identify common questions and provide proactive solutions. Since implementing the chatbots and doing a deeper analysis of customer interactions, we were able to increase efficiency by 75% and free up our team to focus on more complex or unique issues.” – Geronimo Chala, Chief Consumer Officer at Rebag.

Collecting customer context for support reps

Outstanding support means fully understanding each customer's unique situation, and automated chatbots excel at collecting key details upfront so reps come into a conversation fully prepared to make an immediate impact. 

Even when a chatbot can't solve customers' queries on its own, it’s still a useful asset. All the information it gathers from the customer provides valuable context for the support rep receiving the handoff. It's especially useful when solving troubleshooting issues.

Chatbots route the conversation and ensure that support reps are armed with all the necessary information to personalize and resolve issues efficiently. This type of  proactive approach not only saves valuable time but also results in more effective support.

Increasing efficiency

As the need for efficiency grows, support leaders must discover ways to optimize without compromising service quality. Thankfully, automated chatbots have emerged just in time to revolutionize the customer service field, streamlining workflows and enabling teams to do more with less.

According to the Customer Service Trends Report, 68% of support leaders see managing support costs as a top reason to invest more in automation. It's a clear indicator that industry professionals see the unique value chatbot automation brings to their bottom lines.

Make sure you choose the right one for your support needs: Download The AI Chatbot Buyer’s Checklist.

Best practices to implement an automated chatbot

1. Understand chatbot differences

As we mentioned earlier, automated chatbots can work in two ways – rule-based and AI-powered. Instead of perceiving these two approaches as being in competition with one another, though, they should be seen as a powerful pairing.

When a customer initially faces an issue, a rule-based chatbot can display a menu to determine the nature of the problem. For instance, suppose a customer requires assistance with a delayed delivery order. 

The rule-based chatbot can prompt them to provide an order number through an input field to give them an order status. If the customer is not satisfied, it can either connect to a support rep or provide a new menu with further resolution choices, such as "request a refund."

If the customer needs help with more tricky matters for their order, the AI chatbot takes over, engaging in exploratory questions to better understand the query. 

The automated AI chatbot can also potentially resolve the issue by drawing from your knowledge base. If the chatbot still cannot provide a satisfactory resolution to the customer’s issue, it seamlessly hands the query off to a human agent.

The key to success lies in discerning your customers' specific needs and deploying the appropriate chatbot according to their journey.

2. Set up the automated chatbots

First of all, you need to understand your user's journey and in what contexts they’re interacting with your chatbot.

For instance, in what situations does it make sense to offer an experience with a structured framework (rule-based)? And in what scenarios is a more fluid, conversational interaction (AI) a better fit for your customers?

Once you’ve made those decisions, you can kick off the implementation process. A customer support solution like Intercom allows you to create intricate workflows with ease, setting up a rule-based chatbot and determining when the AI counterpart comes into play.

An automation-first customer service solution requires no coding – using an intuitive visual builder, anyone can design and launch automation in minutes. 

These workflows offer extensive customization options, enabling you to create tailored customer journeys that provide genuine value.

Even more impressive is the fact that an AI chatbot help desk automation requires no training. You can simply direct it towards your support content source, whether it’s Intercom Articles, Zendesk Help Center, or any public URL of your choice.

However, to maximize the effectiveness of your automated chatbot, it's essential to take a few practical steps to optimize your content.

💡 Find out how to make sure your knowledge base is ready to work with an AI chatbot.

3. Configure the chatbot handover

When the automated chatbot can't resolve a conversation, it’s up to you to determine what happens next. You can route the conversation to a human support representative who can address the issue through chat messages, or you can redirect customers to email or phone support.

Just remember to keep track of your customer’s journey. Set up an automated workflow that collects essential information from customers about their specific queries.

By collecting data upfront, your support team won’t have to spend time manually tagging conversations to identify common customer pain points for your proactive support.

4. Test your automated chatbot

Before releasing your automated chatbot to customers, take it for a dry run. Bring automation live in a sneak preview to give yourself the opportunity to spot issues ahead of time.

Pose a variety of queries to see how well your chatbot responds, and make sure it understands and delivers accurate, relevant answers. Share the chatbot with your team to let them test it out for themselves and provide additional feedback.

Instead of launching the platform to all customers at once, consider a staggered approach. Begin with lower-tiered customers or specific regions that would benefit most from self-service. This method allows for close supervision and ensures your chatbot operates seamlessly within your product.

5. Monitor chatbot analytics

Your chatbot is a valuable tool, but deploying it is just the beginning. To maximize its benefits, you need to closely monitor chatbot analytics.

Monitoring chatbot analytics involves keeping an eye on reports and metrics. It helps you understand what's working well and what needs improvement. A data-driven approach allows you to refine your chatbot's responses, ensuring they meet customer needs effectively.

Furthermore, analytics helps you identify trends and patterns in customer queries, giving you a glimpse into future needs. This foresight allows you to stay ahead of customer expectations.

Some metrics to keep track of include:

• Deflection rate: The percentage of all support addressed by the chatbot where the team didn’t need to get involved.

• Resolution rate: The percentage of support requests addressed by the chatbot where the user indicated the chatbot answered their question or left without asking to talk to a rep.

• Abandonment rate: The percentage of conversations in which the customer left without receiving an answer or after reacting negatively to the last answer delivered.

• Routed to team rate: The percentage of conversations in which the automated chatbot got involved and the customer requested to talk to a teammate.

• CSAT: The percentage of positively rated conversations out of all chatbot requests.

Examples of chatbot automation 

Hospitable, an advocate of Intercom's AI chatbot, Fin, has experienced a remarkable level of transformation in its support operations since day one. In fact, it was able to instantly resolve the 500 support queries that were in the company’s backlog.

With Fin in action, 30% of all incoming customer queries are now swiftly resolved, saving the Hospitable team valuable time.

By offloading a significant chunk of their incoming queries to the AI chatbot, Hospitable has been able to efficiently manage their support demand. They've managed to scale their operations without needing to substantially expand their team.

Because Fin can take care of the routine stuff, Hospitable's support team is able to focus on the more complex and nuanced customer inquiries that need a human touch.

“What drew us to Fin was simply the pain we were experiencing. We had a big backlog of support queries and were going to need to increase support team headcount to meet the demand.” – Pierre-Camille Hamana, CEO and Founder of Hospitable.

What customers love about our automated chatbot, Fin 

"Within 6 days, Fin is successfully resolving 42% of conversations. It's truly surpassed my expectations." – Dane Burgess, Customer Support Director of Linktree.

"Within 2 weeks, we've seen a massive drop of 40% of conversations being routed to our team." – Dean Kahn, Customer Support Manager of RateMyAgent.

“The results are groundbreaking, double-digit gains in engagement and resolution rates." – Sam Forde, Merchant Support Manager of Zapiet.

Discover the power of automated chatbots in alleviating your support workload and ensuring that your support team doesn’t drown in repetitive tasks. Embrace automation and elevate your support game – ask for a demo or start a free trial today.

Sources

1. Intercom, Customer Service Trends Report 2023. We surveyed 1,700 global support leaders and decision makers.

2. Gartner, Inc, Gartner for Customer Service & Support Leaders. Survey of 50 customer support leaders conducted online in January and February 2022.