Customer service is all about keeping your users satisfied. The better you are able to cater to their needs, the happier your customer relationships will be. With the increasing customer rush on digital channels, delivering good customer service consistently is a hassle. Nearly 60% of customers say long wait times frustrate them the most. For businesses that want to scale or improve user satisfaction, implementing customer service automation becomes crucial.
Customer service automation helps businesses attend to users quickly and resolve their queries on time. But, there are several benefits to using an automation tool to streamline your customer service process. In this blog, we will talk about why you need to deploy AI to automate your customer support, along with the step-by-step process to do it!
Why do you need to implement customer service automation?
Chatbots are proving to be the for customer support teams to build more efficient service processes. Deploying AI chatbots is, in fact, turning out to be one of the top priorities for industry leaders who truly believe in the value innovative tech can drive. 79% of CX leaders are looking to invest more in AI and automation capabilities in the coming days.
Here are the reasons why you need to, as well:
Timely and efficient support
AI chatbots work remarkably to reduce the volume of queries that previously needed human intervention. With customer service automation AI capable of resolving 80% of queries on its own, agents can contribute their time to more pressing tasks.
Happier customers
Customer service automation is available to help your users throughout the day, even outside business hours. Every second you take to respond to your user nudges them closer to switching to a faster competitor.
Reduced waiting time
With waiting times reduced to milliseconds, help from AI chatbots is on-demand. When every customer feels duly attended to, they are more likely to stay loyal to your business.
Self-service is the way to go
Quite honestly, customers really just care about finding the right solution as fast as possible. Customer service chatbots trained to answer all of your most frequently asked questions can be very resourceful to your users.
For example, for an e-commerce company, “returns and exchanges” is a relevant use case. Every time a user reaches out to the brand requesting an exchange, the automation chatbot can quickly jump in to walk the user through the complete process of filing to exchange process. It can collect relevant information like the reason for exchange, new size or color, mode of delivery, etc.
How to prepare for customer service automation implementation?
Introducing a new technology like artificial intelligence to your customer service process can be too big a change to implement in one go. And so, it requires the right planning to set your customer service chatbot up for success. Here are the steps you can follow to ensure your digital transition with customer service automation is seamless:
1. Understanding your business needs to set goals
Every industry is different. And so is the effort needed to build customer experiences in each of them. For instance, for some brands, the goal could be to speed up resolution times while for others it could be to generate more leads and higher upsells. When you assess the change your brand would benefit the most from, you can lay down a clearer blueprint for your chatbot’s implementation.
2. Assessing current customer service to identify pain points
AI chatbots can help you mend broken customer experiences. To implement a customer service chatbot, you need to first identify the opportunity gaps in your current process.
Are your customers always reaching out to you with the same issue? Or is it tough for your users to navigate using your product? Once you know the pain points and how your current customer service lacks in assuaging them, you can more effectively build and implement an AI customer service chatbot.
3. Collecting datasets for training AI
Before you begin gathering data to train your AI, you must have a clear idea of the set of problems you are trying to solve through automation. You can only expect your chatbot to stay efficient when it’s thoroughly trained and tested on the use cases.
Leverage your history of customer service interactions as training modules for your chatbot. To ensure your chatbot works optimally, it’s vital to periodically train and refine the AI with the latest data.
4. Communicating with team and stakeholders
Implementing customer service automation is a big change for a company going digital. And so, all the relevant people must be in the loop. The change will impact your company’s sales and service cycles, so ensure to communicate about the upcoming change with them.
5. Setting a timeline for implementation
Deploying customer service chatbots should not be an overnight event, ideally. Lay down the stages in which you want your automation system to come into effect. You can first make an early attempt to automate and address queries that are your low-hanging fruit. If the implementation works smoothly, you can continue to automate other use cases.
Implementing customer service automation
After you have laid out the foundation for implementing customer service automation, it’s time to get into action. Here’s how you can start deploying AI chatbots in customer service:
1. Integrating customer service automation with existing systems
All your third-party tools must work in synchronization with your customer service chatbot. For example, your chatbot should seamlessly integrate with your CRM system to fetch user data and your payment gateways to ensure smooth transactions. Understand that AI should fall in line and work in tandem with your existing tech capabilities.
2. Training team members on using customer service automation
It’s not new to find employees in an organization resisting new tech changes. This is usually because new implementations often bring uncertainty and disrupt the set flow of a process.
Now, this is exactly why you need to make sure all your team members are confident about why you’re implementing automation and how they can best adapt to the change. Hold training sessions where you walk them through utilizing AI to streamline their productive hours.
They should be able to welcome the shift, instead of seeing it as a threat. Customer service automation can help your agents be more productive, so make sure they are on board with this idea before implementing it.
3. Monitoring and adjusting the implementation as needed
Running your automation chatbot for some time can be remarkably illuminating. It can help you identify the lags in the chatbot’s conversational design. You can also find out areas of improvement by identifying where most of your chat drop-offs occur. This will help you narrow down faulty chat flows so you can iterate and refine the bot to function better. The first few weeks of implementation will also highlight the cases in which your agents seem to be struggling the most while using the bot. This will help you troubleshoot issues that hinder the chatbot’s internal usability as well.
How to measure the success of implementing customer service automation?
Don’t let your customer service chatbot simply run in the wild, untethered! Track and measure the impact it is making on your customer service KPIs and quality. Here’s how you can do it:
Take into account your top metrics
Measuring the quality of the impact your customer service initiatives are making is the only way to improve it. As they say, what gets measured, gets managed. Stay on top of some of the indicators like:
CSAT: Customer satisfaction is a simple measure of just how happy your users are with your survey. It’s usually measured through feedback given by users at the end of an interaction.
NPS: Your net promoter score tells you your users’ likelihood of recommending your business to someone else. When customers are delighted with great customer service, they are more likely to tell about their experience to other people and influence them into using your product too.
FCR: First contact resolution helps you track the percentage of inquiries that were resolved the very first time a user raised them. Higher FCR means most users had their queries resolved in the first interaction and fewer customers had to come back with the same problem again.
Analyze the business impact
Remember you had laid out the problems you wanted to fix by using automation during the preparatory stage? Now, is the time to use the data to draw insights to paint a clearer picture of how your team is truly performing.
For example, a low FCR would shed light on the poor quality of resolutions given to users during the conversation. Whereas, a high NPS score would point toward more customer retention and higher ROI. Analyzing your metrics can bring, both, positive and unfavorable insights to light. Whichever the case, knowing the end business impact can help you strategize effectively in the future.
Next, read: Customer Service Automation Trends of 2024
Conclusion
Customer service implementation needs meticulous planning. You should be able to answer “why do we need it?” before jumping onto “how to do it?”. Pick out the use cases you want to automate, discern the pressing pain points, gather the right data for training, set a timeline, and communicate it to relevant stakeholders.
While building and implementing customer service chatbots from the ground up can be daunting, it doesn’t have to be! At DeepConverse, you can easily train and deploy a no-code chatbot in multiple languages to resolve up to 80% of your queries. Get started today.
