Enhancing Zendesk with AI

Enhancing Zendesk with AI

Can you imagine a sports team without its star player, Batman without Robin, or Rick without Morty! Whether fiction or not, the fact is that every individual or team needs their secret weapon for success.

The same goes for customer support teams; they need the right tools to deliver a stellar customer service that will help improve customer experience.

And that rings true, now, more than ever.

With more data to sift through, more tickets to tag and route, and more customer issues to solve, support teams struggle to meet customer expectations because their tools can’t keep up.

You probably know that a well-run help desk relies on software like Zendesk. But did you know that AI tools can further enhance your help desk software?

In this guide, learn more about how AI and ML-driven tools can enhance Zendesk’s capabilities, how they are helping businesses better automate and improve support processes, and discover how easy it is to integrate AI tools with Zendesk.

Let's get started!

A New Era of Zendesk

By implementing machine learning into its help desk software, Zendesk has been able to transform the way customer service teams work, as well as the experience for their customers and their customers’ customers.

Many AI companies have also have built integrations with Zendesk, which means you have endless options when it comes to further enhancing Zendesk’s capabilities.

We'll take a look at some of Zendesk's AI options later on. First, let’s go over some of the benefits of enhancing Zendesk with AI.

The Benefits of Enhancing Zendesk

With more and more customer service teams turning to AI, customer expectations are growing and businesses that don’t adopt AI technology will get left behind. Let’s take a look at how AI is already supercharging Zendesk to automate customer support processes and improve the customer experience:

Automate ticket tagging and routing

Equipped with advanced AI tools, Zendesk is able to automate processes like tagging, routing, and responding to tickets. All these processes require time and patience, especially when you have vast amounts of data to sort. Zendesk and AI combined can carry out these tasks automatically, accurately, and a lot faster than humans, saving time, money, and improving the customer experience.

Imagine that you’ve just released a new product and incoming tickets begin to escalate. Instead of hiring extra manual labor, an AI-powered Zendesk is able to support customer service teams by tagging and routing these incoming tickets in seconds, and in some cases it will be able to solve them without any involvement from a human agent.

You can also set rules within Zendesk, otherwise known as triggers, which help machine learning tools automate processes. For example, let’s say you receive an urgent ticket that needs immediate attention from your team. Instead of waiting for your support team to read this ticket and tag it as urgent, you can use AI to automatically analyze incoming tickets and tag urgent issues.

Then, by setting up a trigger in your help desk software, you can alert your support team about this urgent issue right away, so they can provide a response to the customer much faster and work on solving the issue sooner.

Instant support wherever you customers may be

AI helps Zendesk recognize recurring issues and automatically send personalized automated responses. This means customer agents don’t waste time responding to repetitive issues and can focus on queries that require more time. It also means customers receive faster and more effective responses.

Perhaps a customer has interacted with you via various channels – first a chatbot and then by email. A human agent can’t possibly know that. However AI-powered multi channel support platforms store this information and use it to make informed decisions about which knowledge base article or automated response to send.

Uncover more in-depth customer insights in real time

Zendesk helps you understand your customer data easily and quickly, so you can improve the overall customer experience.

Their customer analytics tool, Zendesk Explore, integrates data from every channel – emails, social media, chats etc – in real-time. It automatically collects, learns from and helps you act on your data.

However, by integrating AI tools like topic and sentiment analysis, you can discover even more detailed insights about your customers.

You might want to track which themes customers mention most often in support tickets. By monitoring aspects such as Response Times, Questions, and Personalization, you can use Zendesk’s analytical platform and MonkeyLearn’s AI tools to deliver fine-grained results in real time.

Instantly, you’ll understand what’s going on in your customer service – like why there are sudden spikes in customer complaints or the overall sentiment toward your support team.

All these insights will help you make data-based decisions, and tailor your services and products to meet your customer needs.

Improve the customer experience

With Zendesk and AI tools, you can deliver faster, more relevant, and customized responses, improving the customer experience tenfold.

AI tools that have been integrated with Zendesk are constantly monitoring incoming tickets from all connected channels, gathering data and helping support teams solve issues, either with or without the help of a human agent.

They can also learn from historical data across all channels, so customers never have to repeat themselves, for example a customer may contact an agent about an issue via social media and then follow up with an email. AI can connect all this data, so that when a machine or agent deals with the issue, they have all the necessary information to solve it.

Chatbots can deal with high frequency and low-touch tickets by suggesting relevant articles to customers while they wait for an agent – by which time they may have already solved their issue.

This creates a frictionless journey, which is crucial for generations that expect fast, simple and frictionless customer experiences – the simpler the path-to-purchase is for millennials, the more likely they are to repeat the process.

AI-powered tools like text analysis also free agents to focus on more sensitive issues that require a human touch, and collect data that can help agents personalize responses, improve customer relationships and prevent issues from arising in the first place.

Deliver faster, more accurate responses

While traditional help desks streamline processes, making them faster and more efficient, those that are implementing AI are able to deliver even faster, more accurate, and timely responses.

Imagine if you started receiving an influx of negative comments about a new product. AI tools integrated with Zendesk can spot those comments in real-time and tag tickets as Urgent or Negative bumping them to the top of the queue, so you can deal with them immediately.

The customer is never kept waiting either, no matter what time of day, because AI tools in Zendesk can function 24/7. This also means that when agents start their shift, they don’t have to spend hours sorting or routing tickets. They can start solving more complex issues that AI tools have highlighted first thing, leading to faster response times, enhanced agents, and happier customers.

Improve employee satisfaction

Solving simple requests and creating and editing macros could become agent tasks of the past, thanks to AI-equipped software. Imagine all the time your agents could save when you consider that 80% of tickets are solved in the first level of support tier 1 (T1) and agents spend anywhere from one to 10 minutes on each ticket.

The huge amount of simple tickets customer support teams receive every day can easily be delegated entirely – or at least in part – to AI tools. They’re able to monitor and tag thousands of tickets in Zendesk in seconds, and solve low-level issues that don’t require the help of a human agent. As a result, agents are free to focus on more complex issues and carry out their work more effectively without businesses hiring extra support to handle large amounts of data.

By adding AI to Zendesk, you’ll also eliminate repetitive and mundane tasks, leading to an increase in agent satisfaction and retention – losing agents because of poor job satisfaction hurts your department and it hurts your company’s bottom line – as well as better customer experiences, enhanced brand reputation, and well-informed actions.

Gain more accurate insights

By delegating simple tickets in Zendesk to machines, you’ll not only increase agent satisfaction, you’ll also improve your insights. AI tools like text analysis are trained using the same criteria, so they will never be biased, like humans, and as a result will always deliver objective results. Human agents might tag tickets differently, for example, because they disagree on what an urgent or low level ticket is after reading a text.

AI tools, on the other hand will always be consistent and they’ll become better at making accurate predictions over time. Plus, they’ll never get tired or bored of the same, monotonous tasks.

Zendesk’s AI Toolkit

While Zendesk has seamless multi-channel support, automation, and analytical abilities, there are many AI companies that have built powerful tools with integrations for Zendesk.

Let’s take a look at some of these tools and integrations in more detail:

AI Ticketing

There’s lots of hype when it comes to chatbots, but there are other ways in which AI is powering customer service teams, including AI ticketing. 

AI ticketing is the process of automatically tagging and routing incoming tickets. It’s a process that customer agents are all too familiar with. When they receive tickets, they need to sort them by tagging them with relevant categories, after which they send them to the appropriate team member to deal with the customer issue or query.

This tedious and often frustrating task is slowly being replaced by AI ticketing tools that use text analysis.  tw Zendesk’s customer support platform can easily be integrated with AI ticket tagging tools such as MonkeyLearn that use text analysis to help support teams automatically classify tickets based on their content, and extract important information. Depending on the problem you’re trying to solve, there are a range of text analysis models you can use, some of which we’ve outlined below:

Sentiment Analysis

Sentiment analysis is the rising star of the text analysis world. It’s a quick and easy way to find out how your service, product, or a particular aspect of your business, such as customer service, is perceived by your customers. Do they mostly talk about your customer service in a negative or positive way, for example? A sentiment analysis tool recognizes words and expressions, such as poor, bad service, disappointed, excellent, easy to use, as either negative or positive to come to a conclusion. 

Within Zendesk, you can use MonkeyLearn’s pre-built sentiment analysis model, or you can build your own custom model with your own data and criteria. Either way, those incoming tickets will soon be classified by sentiment and you’ll be able to use Zendesk’s analytical tools to make sense of this ‘classified’ data.

Topic classification

This is a great way to delve deeper into conversations with customers. You can hone in on exactly what your customers are talking about in support tickets, emails, or chat conversations.

Let’s say you automatically convert public tweets that mention your Twitter handle (for example, @zendesk) into tickets, and you run a sentiment analysis model on your tweets using the Zendesk MonkeyLearn integration. You receive a bunch of results that categorize your tweets as positive, neutral, and negative. Now, let’s say you want to know what these negative tweets mention, so that you can turn these negatives into positives, and prevent customer churn. You’d run a topic classification model.

Let’s use this tweet as an example:

A sentiment analysis model would classify this customer tweet, above, as Negative. Then this pre-built topic classifier would tag it as Customer Support. While AI models can recognize the collocation Customer Support, _they can also recognize words and expressions that are related to this topic, such _as service, customer attention, help desk, and customer experience. 

Here’s a fun fact: a sentiment and topic classifier combined is also known as aspect-based sentiment analysis. By combining aspect-based sentiment analysis with triggers in Zendesk, you can automatically route support tickets to the appropriate teams.

Urgency Detection

This type of model is useful for managing your most urgent customer issues. At the same time Zendesk receives incoming issues from every channel, in real-time, you can use MonkeyLearn’s pre-built urgency detection model to flag any urgent tickets, and set a trigger within Zendesk to send urgent issues to the top of the ticket queue. This way, you can avoid a potential PR crisis and retain customers by responding to their urgent issues quickly and efficiently.

Let’s take a closer look at the MonkeyLearn urgency detection model to understand how it classifies a text as urgent:

Test with your own text



In this example, we can see that the customer has requested immediate attention using the words ‘right away’. This model has been trained to recognize these types of expressions (as soon as possible, immediately, high importance, ASAP etc.), so that is able to detect urgent issues correctly. Of course, you can train your own custom model using ‘urgent’ expressions that are unique to your customers. 

Text Extraction

All the tickets that drop into your Zendesk queue contains important information about how your customers perceive your product or service. However, there’s also more specific information that you might want to collect, such as email addresses, business types, telephone numbers, names, and more. 

Instead of manually going through each ticket, and copying and pasting all this information into one document, you can integrate a text extractor to recognize this information and gather it for you. For example, you can use a keyword extraction model to quickly find out what customers are talking about. Since it only extracts words and expressions that already exist within texts, it can provide you with a quick overall summary of what the ticket is about.

Let’s imagine you want to find out what a first batch of NPS surveys are saying about new software you’ve just released. You can go to the NPS channel in your Zendesk software and use MonkeyLearn’s keyword extractor to find out the main focus of this customer feedback. That way, you can ask your dev team to take a look at the recurring topics that crop up, and make amends early on.


Now that we’ve looked at some of the text analysis tools you can use in Zendesk, let’s take a look at Zendesk’s arsenal of chatbots. While chatbots have been touted as a silver bullet with infinite magical powers, it’s text analysis that actually enhances them. What makes them so appealing is their human interface system that allows customers to have conversations with them in real-time, both through text and audibly. The idea is for AI chatbots to simulate how a human agent would respond to questions posed by customers, instead of human agents spending hours conversing with customers over the phone or via live chat. 

In the same way that text analysis carries out simple tasks and solves simple issues, chatbots can solve simple requests from customers that they have been trained to answer. Of course, over time they can get smarter and deliver even more accurate responses, just like text analysis, all thanks to machine learning. 

Let’s take a look at some of the chatbots available to Zendesk users

Answer Bots

Zendesk’s AI Answer bot works exclusively with Zendesk Guide and ‘provides answers faster than humanly possible’ by responding to customer's questions with relevant knowledge base articles, thereby increasing self-service efficiency. It recognizes speech, data, and specific patterns so it can decide how to respond in the best way. It can also work alongside human agents in customer service, recommending articles, and receiving feedback from agents if they think an article wasn’t a good match. 

Zendesk can also connect to Alterra Answer Bot, said to be the most accurate answer bot on the market with up to 90% precision. One reason for its accuracy is that it finds answers by meaning, not keywords. It also uses deep learning to understand language used by your customers to deliver relevant and timely answers.

Live Chat Bots

There are many third-party AI chatbots that you can integrate into your Zendesk platform, including Ada, Aivo, and KeyReply, and if you’re feeling up to it, well, you can also build your own bot. Zendesk AI chatbots are able to automate responses to high-volume questions that you receive via your help desk, in real-time and 24/7. However, more complex or sensitive issues that require a human touch will be passed on to a human agent.

Human/Bot Hybrid

While bots are great in practice, the reality is that customers prefer speaking to humans, since they can connect on an emotional level. And in some industries, an emotional connection is extremely important. That’s why human and bot hybrids are a great option. 

Meya.ai is a bot that can listen to all incoming messages connected to Zendesk and respond when it knows the answer, acting as a sort of sidekick so agents can get more done. It also gathers information and passes it on to a human agent, so that teams can respond in the best way possible. And, if you’re assigned a ticket that requires a more human touch, you can set this bot to pause.

Suggested Responses

Ever noticed the suggested responses in Gmail? Well, in Zendesk you can integrate True AI, which automatically provides smart macro and response recommendations to all your incoming tickets and chats in Zendesk by using artificial intelligence. For example, as you type a response in Zendesk, True AI will finish the phrase for you, and instead of opening a ticket to see which macro to apply, True AI will provide an option, such as ‘Customer not responding’ or Downgrade and Inform’.

How to Get Started with Zendesk AI

The benefits of adding AI to Zendesk are huge, and the good news is that there are many AI integrations available with Zendesk. To get started, we recommend trying out text analysis, since it’s the foundation of all AI tools, plus it’s easy to set up with MonkeyLearn.

MonkeyLearn provides easy-to-use machine learning tools, and has even built its own integration with Zendesk. That means you won’t need to enter a single line of code during set-up, and you can get started with text analysis in Zendesk right away. MonkeyLearn also offers many machine learning models that will help you automatically tag your support tickets, streamline your customer service, and deliver solid insights in mere seconds. 

To begin your journey towards customer service automation with Zendesk, follow the steps below on how to set up MonkeyLearn’s integration for Zendesk:

1. First, You’ll Need an Account with MonkeyLearn

Now is as good a time as any to open your account with MonkeyLearn! You’ll also need an API key to connect with Zendesk, which you’ll get when you sign up to MonkeyLearn for free

2. Install the Integration

To install the MonkeyLearn integration for Zendesk, go to Zendesk’s Marketplace and click ‘install’. 

3. Give MonkeyLearn the OK to Access Zendesk Tickets

Once installed, you’ll need to provide permissions and add your MonkeyLearn API key. This connects the Zendesk integration with your MonkeyLearn account and gives you access to both text analysis models you create and our pre-built public models.

4. Choose the Models You Want to Use

You can choose as many machine learning models as you like and map them to the ticket fields you would like to tag automatically. You can either select an existing ticket field or create a new one. 

Once you’ve done this, go to settings and select the automation confidence level you’d like to apply. This instructs MonkeyLearn to tag only the tickets with the most confident results.

5. Activate the Integration 

Now you’re ready to activate your integration with Zendesk and begin tagging incoming tickets automatically.

And that’s it! Your Zendesk is now equipped with an AI that can help tag and sort your tickets automatically. If you want to get started right away, use our pre-built models, then, once you’re familiar with how text analysis works, start creating your own customer text analysis models for a more tailored analysis of your Zendesk tickets. 

The Final Word

As more and more tickets infiltrate customer support help desks, and customer expectations continue to rise, businesses need to equip agents with the right tools to stay on top of their workloads. That’s where AI-equipped software like Zendesk can play a crucial role. 

Most customer support teams already have a help desk in place, and there are plenty of powerful AI tools with smart integrations that you can use to enhance your help desk software. Zendesk, for example, can easily be integrated with MonkeyLearn’s ticket tagging tool, as well as various chatbots, which function seamlessly with this customer service software. 

Zendesk with AI can supercharge customer service teams by automating processes that are often time-consuming and tedious, allowing customer support teams to focus on more important and fulfilling tasks. Not only are AI-equipped tools like Zendesk transforming business processes from within, they’re also changing perceptions of customers from the outside. Customer experiences with AI are better, because they’re more relevant, personalized, and faster – creating a frictionless and seamless customer journey.

It’s time for you to enhance Zendesk with AI and bring your customer service teams up to date. Get started with Zendesk powered by AI using the MonkeyLearn integration, following the steps outlined above, or request a demo and one of our experts will get in touch!

Federico Pascual

September 30th, 2019

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