A complete chatbot automation guide: 2024
Discover the benefits, key features, and use cases of automating your support with chatbots
Sep 04, 202415 MINS READ
An introduction to chatbot automation
Providing a timely response to customer questions, queries, and complaints is the bare minimum for businesses that want to stay ahead of the competition. But customers often expect an instant response. You need an army of customer support agents available 24/7 to meet their needs.
By adding automated chatbot support, you can quickly and easily provide customers with answers to common questions and offer basic help.
This frees up a human agent’s time to deal with more complicated technical queries and customer complaints. But automated chatbots aren’t just a great customer support option for your business. They can also promote more sales, capture and qualify leads, and monitor your social media.
In this article, we’ll explore exactly what chatbot automation is. We’ll also dig into common use cases and share why applying them can benefit your business.
What is chatbot automation?
In a nutshell, chatbot automation is the process of using a chatbot to automate tasks that a human would traditionally carry out. Chatbots are designed to mimic human interaction and carry out various tasks, from customer service to lead generation.
Automating these tasks saves businesses time and money while providing a better customer or client experience. Chatbots run 24/7, so they can handle tasks even when you're not around. They never get tired and can handle large volumes of requests.
Chatbots use machine learning and AI to get smarter at what they do without needing a human to get involved. This means that they can learn and adapt to the individual needs of each customer or client. Over time, they can become more efficient and effective at providing your needed services.
Chatbots can be linked to many other pieces of software in your tech stack to automatically populate and update data. This includes things like CRMs, contact lists, and social media platforms. By linking your chatbot to these other tools, you can save time and reduce the chances of human error.
What are the types of chatbots?
Intelligent chatbots are those that use artificial intelligence (AI) to learn and understand the needs of their users.
There are three types of chatbots:
Rule-based chatbots
Smart chatbots
Hybrid chatbots
Let’s review each.
Rule-based chatbots
These kinds of bots are sometimes called simple chatbots. They follow a set of rules that have been programmed by a human.
Simple or rule-based chatbots can understand human language but can only respond in predefined ways. As a result, they are best suited to direct interactions like answering questions or making bookings.
A chatbot of this nature won't get smarter over time as it doesn't learn from its interactions. However, they are simple to set up and require little maintenance.
Smart chatbots
Chatbots that rely on machine learning can understand and respond to user queries more effectively than those that don't. They use artificial intelligence to learn about the user's needs and preferences, which allows them to provide a more customized experience.
Smart chatbots are more complex to set up than rule-based chatbots. You need to track their performance to make sure they’re meeting expectations. If they aren't, you'll need to change their programming.
Hybrid chatbots
Hybrids are the best of both worlds for chatbots.
Hybrid chatbots combine the rule-based and AI-based capabilities of each bot type, which enables them to respond to queries in a more personalized way while still following a set of predetermined rules.
They’re more complex to set up than rule-based chatbots, but they also offer a better experience for the user.
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How does chatbot automation work?
Most chatbot automation tools use artificial intelligence (AI) to learn about the user's needs and preferences over time.
Conversational AI chatbots can understand the way humans speak by using natural language processing (NLP). They can hold up their end of human-like dialogue as well. NLP involves breaking down human language into its basic components, such as words, phrases, synonyms, etc., and understanding the meaning of each one. This information is then used to respond in a way that is natural for humans.
Chatbots use machine learning algorithms to process the data they collect about their users. This data improves the chatbot's understanding of user intent and provides better responses to customer queries.
You can help train the AI by feeding it documentation such as FAQs, customer service scripts, and product manuals. The more data you give the chatbot, the better it will become at understanding your customers and providing useful responses.
For example, if a customer asks for a product recommendation, the chatbot will use its understanding of the customer's needs to give them a tailored answer.
Key benefits of chatbot automation
Chatbot automation has many benefits for businesses of all sizes. Whether running a small boutique store or a large corporation, chatbots can help you improve customer service and increase sales.
Some of the benefits of chatbot automation include:
Supporting customers
Chatbots are on hand to help your customers whenever they need it.
For instance, Freshchat helped Delivery Hero achieve a 90% customer satisfaction score. Its chatbot handles more than 7 million messages per month between riders and agents. By using chatbots, businesses can provide customers with self-service options. This means they can get the answers they need without contacting customer service. If a customer needs to track their order, for example, they can do so using a chatbot.
Chatbot technology enriches the customer experience.
It provides around-the-clock accurate customer interactions through your website or mobile apps like Facebook Messenger or WhatsApp.
Supporting internal employees
Chatbots can take on many of the tasks that human IT service agents typically handle.
Using chatbots improves first-contact resolution by at least 4.29% for organizations of all sizes. Chatbots also decrease average resolution time by 10.65%, meaning employees don't have to wait as long to get the help they need.
AI-powered chatbots can streamline the entire support process, taking a lot of the stress out of an internal employee’s day. This frees the employee up to handle complex, interesting, or thought-provoking tasks, which improves job satisfaction and builds their reputation.
It also boosts employee productivity. In fact, MakeMyTrip saw a 3x increase in agent productivity after using Freshworks chatbot.
Many believe that AI chatbots replace human agents. But the truth is, they help human agents immensely. They also allow employees to open new doors for themselves.
Supporting leadership
AI chatbots also help leaders make strategic decisions.
With access to in-depth customer data collected from AI chatbot messages, business executives, CS managers, and marketing directors can optimize their sales, marketing, and support processes. From creating better CS templates to tailoring sales offers to better segmenting their marketing campaigns, leaders can apply rich customer data to uplevel their organization.
Chatbot automation use cases
There are many ways you can use chatbot automation to improve your business. Here are some examples:
1. Customer support
Use chatbots to provide customer support 24/7.
They can answer common questions, help customers troubleshoot problems, and escalate issues to human agents when necessary.
Using a chatbot for customer support can help you improve customer satisfaction and reduce support costs.
2. Sales enablement
Chatbots can provide information about products and services and then help customers make a purchase.
They can also upsell and cross-sell products and services, which can increase revenue.
You can also use them to decrease cart abandonment by providing reminders and customer support during the purchase process.
3. Lead capture and qualification
Use chatbots to collect information about potential leads and qualify them based on their needs.
This helps you save time by only focusing on leads that are a good customer fit for your products or services.
4. Helpdesk support
Use chatbots to provide first-line support for IT issues.
This can help employees resolve common problems without the need to contact the IT department.
A chatbot can also pull data from your knowledge base to answer common questions, helping agents resolve customer queries faster.
5. Social media monitoring
Use chatbots to monitor social media channels for brand mentions.
They can then respond to positive and negative sentiments in real time. This helps you build relationships with customers and resolve any issues they may have as soon as possible.
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Essential features of chatbots
Before implementing an AI chatbot service for your business, there are several essential features you’ll want to look out for. Below, you’ll find a list of four major features that should come standard with any worthwhile chatbot system.
Features of chatbots
Omnichannel support
Modern customers want an omnichannel experience from the companies they deal with, making the customer experience uniform across all platforms. This means support ticket records, past purchases, preferences, and more can be available at every touchpoint between the business and the consumer.
Your chatbot should be an integral part of the omnichannel experience. It should be able to visualize the customer journey of any user it comes into contact with. This way, when a customer starts engaging with the bot, it can access historical data and alter its responses accordingly.
Integration with existing systems
For the very best customer engagement, your chatbot should completely integrate into vital systems.
Full chatbot functionality should mean integrations with every system that contains customer information. This includes your email marketing platform, your CRM, the support ticketing system, and other relevant tools you use.
In a retail environment that would include prior support tickets, buying habits, and past interactions with sales and marketing team members. In the healthcare industry, it might mean access to medical records and prescriptions.
Sentiment analysis
Your chatbot needs to be able to read the intent and emotions of the customers it interacts with. This means having an advanced sentiment analysis function that lets it “read the room” so to speak, and respond accordingly.
For example, if a customer is sarcastic or angry, the chatbot should know. If they’re irate and rage-typing in all caps, the chatbot should take steps to de-escalate the situation.
But, if they don’t have sentiment analysis built into their programming, it’s possible they could make the problem worse through their lack of awareness.
Machine learning
A good AI system should be able to get smarter over time. That means it needs to be able to learn from interactions with customers.
Over time, the AI should come to understand your audience better, getting smarter and more familiar with how they communicate from every exchange. This guarantees the chatbot will age well and become more competent and effective with experience.
Common challenges with chatbot automations
Of course, the AI chatbot experience isn’t without challenges. Here’s a list of several issues your company could encounter when integrating this vital and helpful service.
Public opinion
AI is a hot-button issue with the public right now. Customers might become angry once they realize they’re speaking to a machine and not a person.
No matter how advanced AI gets, there will always be some customers who refuse to communicate with them.
On top of that, the narrative that AI chatbots run human support representatives out of their jobs is still prevalent despite it having no basis in reality. Because of this, you might get some customer backlash when rolling out your newest robotic employee.
Consider educating your audience so they understand how AI chatbots help support them, your employees, and your business.
Nuance
Human beings are very nuanced creatures. We think in creative, outside-the-box ways, and that can be difficult for a machine to comprehend. Chatbots run on logic and programming. Depending on the AI solution you choose, the system might not pick up on certain subtle shifts in the conversation.
Sarcasm, for instance, could go right over a chatbot’s proverbial head. This could escalate a bad situation at worst and become a meme-worthy, mockable moment at best. Either way, it’s not great for your company.
You can solve this issue by making sure that your AI adapts and learns more about human behavior from each encounter.
Security
Your AI system needs protection from cybercriminals. This is especially important for ecommerce companies and healthcare organizations that store a lot of precious information on customers and patients.
All conversations with the chatbot should have encryption and the system should have protection against hackers. Make sure that you’re keeping up with the latest trends in the cybersecurity world to avoid a costly breach.
Best practices for chatbot automation success
So, you’ve decided to take the plunge and implement an AI chatbot as a cost-effective customer support solution for your business? Before you do, there are a few best practices to keep in mind.
Below, we’ve listed some AI advice you should follow before and after unveiling a new chatbot to your audience.
Understand your audience
The first best-practice advice for implementing a chatbot has nothing to do with the bot itself. Instead, it has everything to do with your customers and what you know about them.
Keep their likes, dislikes, wants, and needs top of mind when determining your AI needs. This is going to be important when you start looking at chatbot services as you’ll need to pick one with the right features.
This is also crucial to giving your audience what they want from a sales or support interaction without eating into profits.
You should also understand:
Who your audience is
Where they live
What they do
How they like to communicate
And what their pain points are
Then, make sure that your chatbot is trained to know all of this information. This can make a major difference when it starts interacting with customers.
Give the bot personality
Whether using paid or free chatbots, remember that just because it’s a robot doesn’t mean it needs to be robotic.
You can program your chatbot builder with a specific personality. This can go as far as assigning it a name, a voice, and even a photo. This cost-effective, smart brand advocate should have a personality that matches your brand identity.
For example, an AI chatbot at Disney should be overly polite and kind. Alternatively, an AI for a sports memorabilia ecommerce store might be more laid-back and conversational with users.
Clearly define objectives
You’ll need to set your objectives and KPIs with the chatbot so that it knows what you’re expecting from it — just like any human employee that needs training on your expectations.
For example, is it going to help with lead generation or chat routing? Or will the bot tackle support tickets?
Once you know this, you can start scripting some of the bot’s greetings and responses to give it a sense of what you want to see.
Run tests before launch
Before launching, run chatbot test automation. Put the chatbot through its paces in a long series of tests.
Come at it with every kind of off-the-wall scenario, see how it handles the situation, and then make adjustments accordingly. Chatbot automation testing can help you work out any kinks before launching.
Show value to users
After working with chatbot automation testing tools, you’ll be ready to launch.
When the chatbot starts to engage, you can get out in front of the eye rolls and abandonment that sometimes come with AI engagement.
How?
Showcase the value of the bot right away. With its initial greeting, have the bot show its personality and what it can do.
This could mean displaying a series of buttons or showing a video. Once the customer sees how the bot can help them achieve self-service support with no wait, they might be eager to try it out.
Design fallback messaging
Not every interaction is going to be a major home run.
Sometimes, the customer service chatbot won’t be able to understand what the user is asking. This means it’ll need to rely on fallback messaging to get back on track.
Avoid generic statements like “I don’t understand.” These tend to aggravate customers, and they’re likely to just get frustrated and leave. Instead, have the bot ask clarifying questions to gain a better foothold in the conversation.
For example, try something like “I’m sorry, I’m still getting used to my new role, but I’m determined to help you get the support you need. Can you clarify what you mean by … (enter specifics of the conversation here).”
Poll users on efficiency
One of the best ways to figure out how your chatbot performs is to poll customers who interact with it. If there are glaring issues present, you’ll be able to figure it out quickly by analyzing patterns in these responses.
Monitor support team metrics
If the chatbot is doing its job then certain customer support metrics should be positively impacted. Regularly examine the analytics from your support team, specifically checking items, such as:
Average hold time
Customer satisfaction scores
Support team productivity
First outreach resolutions
Response time
Employee satisfaction
Adjust as needed
Once you have your chatbot analytics laid out in front of you, adjust the chatbot as needed.
If everything’s going great, stay the course.
But if you notice areas in which things could improve, make those improvements right away and then poll the audience again to see if your efforts paid off.
Consult an expert on which chatbot automations are right for your business
Future trends in chatbot automation
The future of chatbot interactions is creating a more human conversational experience.
Advancements are constantly being dreamt up to give chatbots more humanity and create a seamless experience for the end user. Over time, we’ll see an extra emphasis on personalized user experiences and voice chats.
Bots will also continue to collect data on each interaction and compile this information into reports. This data will provide business owners with actionable insights into their audiences’ needs and behaviors.
The data chatbots collect will also be richer and more contextually relevant. AI predictive modeling will also track shifts in behavior to accurately gauge where industry trends will shift next.
This means data gathered from AI chatbots will factor into preemptive marketing campaigns meant to give you a leg up over your biggest competitors. Do you know the top chatbot stats?
Why should you choose Freshworks for chatbot automation?
Freshchat is a cloud-based platform that helps businesses of all sizes create and deploy chatbots. The platform provides a range of features that make it easy to create, train, and deploy chatbots.
These features include:
Multilingual support: Freshworks chatbot understands language and intent in more than 33 languages. Use your chatbot to support your international customers and offer them exceptional service.
Handle customer requests: Use Freshworks to handle customer requests 24/7. Customers can get the answers they need, even outside business hours. Freshchat can answer open and closed questions and provide support for common issues. If the bot identifies a query that needs more help, it can escalate the case to a human agent.
Customizable workflows: Create and customize workflows to fit your business needs. With Freshchat, you can automate ticketing, customer onboarding, and lead capture tasks.
Bot triggers: Use bot triggers to automatically start a chat when specific events occur. For example, you can set up a trigger so that a chat begins as soon as a customer visits your website. Or, use a trigger to tackle cart abandonment. (Start a chat when a customer adds an item to their cart but doesn't complete the purchase.)
FAQ
Where can I use chatbot automation?
Chatbot automation occurs on your website with a chat widget or through apps like Facebook Messenger, WhatsApp, X, Instagram, and more. It can also work through phone support systems using voice chat.
How can I improve the performance of my chatbot?
To improve chatbot performance, provide the bot with accurate information on your audience. Make sure it can learn from each conversation. This can help it become more efficient over time as it comes to know your audience.
Are chatbots replacing human customer service representatives?
No, chatbots are not replacing human customer service representatives. If anything, they’re improving the work experience for these people by freeing up their time to handle more difficult or thought-provoking assignments. It’s amazing to see how automated chatbots increase customer service productivity and efficiency. The work chatbots take off the plates of human reps is typically answering mundane frequently-asked questions or going through automated admin duties.
How do chatbots handle multilingual interactions?
When a chatbot interacts with a customer, it either automatically detects the language the customer speaks and adapts, or the customer selects their language before the interaction begins.
Are chatbots considered automation?
Yes. Chatbots are conversational AI systems that listen to questions from users and generate an appropriate response. This is a form of advanced automation.
What is chatbot automation?
Chatbot automation services occur when an AI chatbot has conversations with users, automatically generating responses based on what it’s been asked.
How do you automate chatbots?
You can set parameters for chatbots, including scripts and corrective dialogue like fallback lines when the bot doesn’t understand a question. You can also set triggers for the AI bot to respond to. When a customer hits one of these triggers through their actions, the conversational AI takes over and generates responses.
What is the difference between automation and chatbot?
A chatbot is a conversational AI. It’s not automating the same task over and over. It’s instead listening to a query and then generating a response. This is a more advanced form of automation using natural language processing as a trigger.
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