AI in Customer Service: 10 Ways Artificial Intelligence Can Enhance Customer Experience

AI in Customer Service: 10 Ways Artificial Intelligence Can Enhance Customer Experience cover

Today’s SaaS market is highly competitive, and in this industry with a lot of similar products and prices, superior customer service makes all the difference.

In spite of this, companies often struggle with it. There is much work to be done, from recruiting and training support agents, to purchasing expensive tools and working shifts. You don’t have to worry though, there is a solution!

All of these concerns can be easily resolved with AI in customer service. The use of artificial intelligence can be an invaluable tool for improving support without putting too many resources at risk.

In this article, we’ll discuss AI and explain why you should embrace it to increase product growth.

So let’s get into it.


  • Customer service uses AI for multiple purposes, including chatbots, answering support queries, and analyzing data.
  • AI is changing the way customers interact with brands. And now, customers will expect you to offer the same efficiency as AI.
  • Using AI in customer service improves your customer service agent’s work, enhances the customer experience, and reduces your operating costs significantly.
  • The different types of AI used in customer service include object detection, AI-powered customer service chatbots, natural language processing, and machine learning.
  • Here are some tactics for leveraging AI in customer service:
  1. Personalize the user experience and use AI to collect data and trigger relevant messages based on the customer segment.
  2. Automate email responses with AI to tag customer emails and send automated replies when it fits.
  3. Add self-service support and use AI to show learning modules based on user needs and segmentation.
  4. Offer proactive support to address problems before they happen.
  5. Use AI to add labels to your support tickets based on categories and organize them.
  6. Collect quantitative feedback and use AI to calculate scores, organize the metrics, and tag your responses.
  7. Measure user sentiment with AI to know when customers feel happy, upset, or neutral in their feedback.
  8. Generate video tutorials with AI and embed them into your UI patterns and in-app messages to provide support and educate customers.
  9. Use AI to quickly localize your help center’s resources, website, and product UI.
  • All you need to set up an AI is to determine what tasks you need to automate and find the right tool that fits your needs.
  • AI isn’t perfect and can’t replace a human, so only use AI for simple tasks—don’t stretch it too much.
  • AI tools are a must in customer service. So why not try a Userpilot demo and start aiding your customer service process, without coding?

How can you use AI in customer service?

In customer service, AI can save time for both users and customer service representatives. And involves:

  • Adding chatbots to your website, using natural language processing (NLP) to host real conversations with customers.
  • Answering basic support questions automatically with 24/7 availability and no waiting times.
  • Reaching out to users with help when their in-app behavior indicates that they’re getting stuck.
  • Collecting and analyzing customer data from customer communications to track behaviors, preferences, and metrics.
  • Sending more complex requests to the right agent so they can resolve customer queries that are important.

How is AI changing customer service?

A Gartner report predicted that AI would handle 15% of customer service interactions in 2021.

But is it true today? With more sophisticated AI like GPT-3 (and GPT-4), these tools are transforming how customers interact with brands, making the customer service process simpler, faster, and more efficient than ever.

With reduced waiting times, instant answers, and personalized help, AI is rapidly raising the standards that customers will expect from you.

What are the benefits of using AI in customer service?

As mentioned earlier, AI has many uses in customer service. And its benefits are real:

Improve agent experience

It is impossible for human agents to always be at their desks. The cost of working in shifts and covering too many hours is high.

AI can’t replace customer service agents (yet), but it does help them avoid fatigue and burnout as they can answer common customer questions and solve simple tasks without getting tired or taking time off.

So, instead of a threat, AI can be a blessing for your support reps (as of now).

Remove friction and enhance customer experience

AI is also a benefit for customers too.

It can track customer behaviors and offer resources when the user seems to be stuck. It can welcome new users to your product and personalize their onboarding experience. Plus, it can quickly solve your customer’s problems and remove any friction.

Lower operating costs

Think about the hours your reps invest in simple and repetitive tasks. And now think about the money per hour you’re already spending on them.

With AI, these customer service costs are significantly reduced (if not eliminated). And your reps can invest their time in tasks with better ROI. So it’s no secret how AI can also relieve your budget.

Examples of AI in customer service

Now, AI isn’t one single tool. It has many forms and shapes. Hence it’s important to understand how they work before engaging with them.

Object detection

Object detection is the AI’s ability to recognize the object in an image or video.

For example, you can take a photo of your cooler, and the AI will show you similar items on sale.

In SaaS, tools with object detection are still limited. Still, it can become important soon when customers can get automated help by simply sending a screenshot.

AI-powered chatbots

Chatbots are the most common way to use AI in customer service.

It allows you to automate customer interactions, answer common customer inquiries, like feature-related questions, account status, or questions about the plan, and pull resources from your knowledge base to show the relevant information needed.

Chatbots can be embedded in the support page, website, and inside your product, and they are a great way to direct users to relevant resources and leverage self-service support.

ai in customer service chatbot example kommunicate
Kommunicate’s chatbot on their homepage.

Natural language processing (NLP)

Natural language processing (NLP) is a type of AI that can understand natural human language and replicate it through machine learning. It can receive information, understand it, and throw a relevant response.

Any tool that’s able to process natural language uses this protocol. For example, many chatbot tools use NLP to make customer support interaction more sophisticated.

Machine Learning

Machine Learning (ML) is just as important as NLP. With machine learning, an AI application can learn and improve from experience without explicit programming.

As a result of this technology, chatbots become more efficient. Automated responses become more consistent and concise as AI learns from the customer’s needs.

9 ways to leverage AI in customer service

Now, knowing how AI can help you scale your customer service and the different types. What can you do to make the most out of it?

Here are some tactics:

1. Personalized user experiences

A personalized product is essential for a good customer experience.

Indeed, Salesforce found that 75% of customers expect companies to deliver personalized experiences—which means you can no longer get away with merely calling users by their names.

A truly personalized product experience is based on specific use cases, jobs to be done (JTBD), and stages in the journey. And AI would help you collect the required data to:

  • Recommend new relevant features to each user persona.
  • Show in-app guidance when the user is stuck.
  • Offer an upgrade when the user has reached their plan limits.
  • Send email sequences to support users.
  • Trigger in-app experiences according to their in-app behavior.

For example, you can leverage AI to collect data and segment users based on their needs, in-app behavior, NPS responses, and product usage—making personalization possible:

user segmentation example userpilot
Segmenting users on Userpilot.

2. Automating email responses

The same AI that can automate chatbot inquiries can also automate your email responses!

AI-powered tools can automatically tag customer emails and notify you when there’s a more complex or urgent request, and also send automated replies when it fits.

Based on previously answered tickets and company data, agents can have access to an AI widget on top of their helpdesk that surfaces the correct information for customer questions they are answering.

Those tools also enable you to create actionable datasets from email data using an AI-powered tool. Depending on the tag, you can respond manually or automatically, or be notified of urgent requests. In the event that the email response is classified as Out-of-Office, you may need to send a second reminder seven days later.

What’s better, you can already use email marketing software like Sendgrid to start automating email responses.

sendgrid email marketing software
Sendgrid’s email dashboard.

3. Customer self-service portals

According to a Zendesk report, 69% of consumers try to solve their issues independently, but less than one-third of companies offer self-service options.

Your app or SaaS product should provide customers with the help they need, so customers don’t have to leave your app, google your website, scroll down to find the support button, and browse through messy documentation to find answers.

Provide them with personalized content recommendations so they can self-serve. In addition, allow them to request assistance right then and there if needed.

For the best user experience, combine all the self-help resources in an easily accessible knowledge base, such as articles, video tutorials, and webinars. Use AI to hide and show learning modules based on user needs and segmentation.

userpilot resource center example
Create a self-service.

4. Track in-app behavior and offer proactive service

To elevate your customer service, you should offer proactive support to address problems before they happen (including self-service support).

However, proactive support goes beyond your resource center. You can also use AI to:

  • Offer in-app guidance to remove friction and decrease the need for support.
  • Monitor customer conversations on social media and respond appropriately.
  • Constantly collect feedback from your users to anticipate the need for help.
  • Inform customers and keep them updated when issues happen.

AI can sense human behavior patterns and trigger different messages. So you can, for example, show a tooltip when a customer seems to be stuck:

onboarding tooltip example userpilot
Leverage Ai to provide in-app guidance when users get stuck with Userpilot.

5. Use AI to categorize support tickets

Like email tools, you can also use AI to add labels to your support tickets based on categories, topics, problems, etc.

This way, you can easily organize your support inquiries and process them in a way that makes sense.

Furthermore, you can set the AI to reply automatically depending on the attached label. So if, for example, a user opens a ticket to get help with a segmentation feature, the AI can easily recognize it, send a message, and include a relevant resource from the knowledge base.

6. Analyze collected data

One underrated aspect of AI is how it can be used for data analysis, as it can structure and collect quantitative data.

And how does this help in customer service? Well, you can collect qualitative feedback like NPS surveys and use AI to calculate scores, and tag your responses.

For example, here’s how you can watch over your NPS on Userpilot:

Userpilot automatically calculates your NPS score for you from the collected quantitative data.

7. Sentiment analysis of customer feedback and surveys

Using artificial intelligence, we can now identify how a customer feels about their customer support ticket request. It is possible for AI tools to determine whether a customer is upset, angry, happy, or neutral, and then direct the appropriate agents to address these concerns.

Sentiment Analysis identifies the customer experience components that have the greatest emotional impact.

For instance, sentiment analysis powered by AI might reveal that customers are ‘dissatisfied’ with one of your core features. As a result, you can prioritize the development of this feature based on feedback.

8. Automatically generate video tutorials

We’re in an age where you can create videos by simply typing text.

That’s what you can do with Synthesia, an AI video creation tool that can generate video tutorials with AI and improve your onboarding, or quickly repurpose product guides into videos.

Plus, if you want to bring it to the next level, Synthesia integrates with Userpilot (a customer success tool), allowing you to embed automated video tutorials inside your UI patterns (tooltips, checklists, etc.) to educate new customers.

Turn text into support videos and embed them into targeted in-app messages thanks to Userpilot.

9. Provide multilingual support

Being available in multiple languages is essential for scaling your business and preserving a good customer experience.

With AI, you can easily auto-translate and localize the resources from your help center, your website, and your product UI so it can be accessible to international markets.

Not only that, but your site can also auto-detect your user’s region and change its language accordingly—increasing your chances of retaining customers.

For example, did you know you can automatically translate your resource center with Userpilot in 32 languages? It’s as easy as heading to your resource center and going to the localization tab.

Automatic content localization based on location in Userpilot.

What are the steps for setting up AI for customer service?

Thankfully, you don’t need to code if you want to leverage AI, as plenty of software solutions facilitate this for you.

All you need to do is:

  1. Determine the primary purpose of using AI. Is it to reply to support inquiries with a chatbot? Analyze data with NLP and machine learning.
  2. Choose the primary channels. Do you only need a chatbot for your website? Or do you want to follow a multi-channel approach based on AI?
  3. Test and tailor your solution to your needs. Then, adapt your chosen tools to your needs and ensure they integrate with your current tech stack.

What are the challenges of using AI in customer service?

AI is not all sunshine and rainbows. It can’t replace humans.

The challenge with AI is not the implementation itself, but where and when your customers would appreciate it or hate it.

For example, how often have you received a generic response from a customer service team when your problem required dedicated help? That’s what you risk offering to customers when you use AI.

So, put yourself in your customer’s shoes and use AI for simple tasks—don’t stretch it so much.

Wrapping up on AI for customer service

AI technology will only improve over time. And the more they do, the more you’ll need them for your business.

So get used to understanding it, using it, and knowing when to embrace or reject it.

As for AI in customer service, it’s already a must in a few areas.

So why not try a Userpilot demo and improve the customer service process without coding?

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