In other words, boosting customer satisfaction is the main purpose of all marketing efforts, customer relationship management, and corporate strategies.
In the ever-evolving market where customer preferences are king, businesses must provide precisely what customers want.
To achieve that goal in the present-day digital world, organizations should pay special attention to resourceful, innovative, and interactive customer engagement solutions. More and more businesses do so by providing customer-centric services twenty-four seven.
In the past, it used to be incredibly expensive and tedious to achieve. Today, you can do it with ease with the help of conversational artificial intelligence.
Below, you will find a list of ways in which conversational AI can help you to boost customer engagement, as well as common mistakes that you should avoid before you start using it.
What Is Customer Engagement?
In short, customer engagement is about communicating, interacting, and building relationships with customers.
The said interactions can occur over a number of different channels and with the help of a wide range of tools, all of which act together to boost brand exposure and brand loyalty.
So, if you want to appear trustworthy and increase long-term brand loyalty, investing in customer engagement strategies is a must, regardless of whether you sell BIA software, designer clothing, or dairy-free desserts.
Customer Satisfaction and Customer Engagement
Those two concepts are often confused, but they are not entirely the same. Customer satisfaction is about the customer’s overall impression after interacting with your brand.
If the customer got what they wanted, and the process was smooth, you can say that their satisfaction levels are high.
This does not mean that the customer is also engaged with the brand, though. It might be that a specific characteristic of your product is more appealing to people in comparison to other similar products on the market, regardless of your marketing and engagement efforts.
An engaged customer will be more likely to talk about your brand with others, participate in loyalty programs, and become an advocate for your product.
So, if you want to focus on building long-term customer relationships and turn your customers into your brand ambassadors, you should pay close attention to customer engagement.
Customer Engagement Strategies
The best customer engagement strategies involve meeting customers where they are and providing them with a personalized experience.
This stems from the fact that people today are overwhelmed by the number of brands, product types, and services available. Having a business that appears to care for them and their individual needs can quickly turn them into your loyal customers.
There are three types of engagement strategies that businesses use to interact with their customers, namely emotional engagement, transactional engagement, and functional engagement.
What Is Conversational AI?
Conversational artificial intelligence is a piece of software that combines natural language processing, machine learning, intent analysis, and other language technologies to help a customer through an interface.
Whether the customer is responding to an automated email or a virtual assistant, conversational AI is working hard behind the scenes to analyze what the customer is saying, determine the correct response, and respond in a way that sounds natural and is easy to understand.
The key to success lies in making the interactions between artificial intelligence and customers as human-like as possible.
Aside from that, the answers that the AI gives should be clear, precise, and, of course, accurate and helpful. Otherwise, it is likely to prevent or discourage potential customers from making a purchase.
Related: AI In Customer Support: How Chatbots Transform Business Interactions
Natural Language Processing
The first approach to AI was based on rules, where artificial intelligence worked on a set of pre-defined procedures. Whenever the bot stumbled upon a specific query, it used the most relevant rule to find an answer.
Instead of understanding the context, it relied on finding keywords in the text. However, such a system turned out to be ineffective, as human language is very flexible, and often one sentence can be said in several ways.
The studies concerning the way in which humans acquire languages paved the way for a different approach to conversational artificial intelligence.
That approach is called NLP, which stands for natural language processing. In the NLP model, artificial intelligence is exposed to a variety of texts.
Based on the said texts and by using self-developed neural networks, it starts understanding the context and the way in which human language works, in a similar manner to how human babies learn to speak.
Doing so allows the bot to understand the customer's intent, regardless of how it is phrased, with minimal limitations.
Bots based on the NLP model are developed using grammatically correct sentences, which are then fed into the system. For that reason, such bots might struggle with non-standard varieties of language, such as slang, as well as misspellings and otherwise incorrect messages.
Machine Learning
Machine learning is very similar to the NLP model in a way that it also relies on self-developed neural networks. However, it does not focus specifically on interpreting human language but instead on finding patterns in arrays of data.
This means that it can be used for a number of tasks, such as facial recognition or identifying objects in pictures, but it may not be the perfect tool for developing a conversational artificial intelligence solution.
The main advantage of machine learning is that it can process data much faster than NLP. The downside, on the other hand, is that it requires a lot of data to be effective, as well as a lot of processing power.
Given how fast the technology is developing, machine learning has become obsolete for many tasks that it used to be perfect for, and more complex models, including NLP, have taken its place.
User Intent Analysis
User intent analysis is a process of understanding what the user wants to achieve. It can be determined by analyzing the user's past behavior or asking follow-up questions.
User intent analysis is important for two reasons. First, it helps you understand your customer better. Second, it allows you to give them the information they need in a more effective way.
With the help of user intent analysis, conversational AI bots can better understand the customer's needs and wants and adjust their responses accordingly. This is another step in the development of artificial intelligence that pushed it toward human-like conversations.
It allows the bot to see through the customer's words and understand the real problem that they are facing, helping them to address it in the most efficient way possible.
Knowledge-Based Systems
Knowledge-based AI systems, also known as expertise-based systems, are a model in which the artificial intelligence system is fed a lot of information about specific things.
The system then analyzes this information, but unlike NLP or ML, it does not try to operate on the information included in the content.
Instead, it uses it to examine the user’s problem and suggest an appropriate solution. This makes such systems very good at solving problems faced by specialists, such as diagnosing minuscule changes in a person’s X-ray pictures.
Consequently, knowledge-based AI systems are very limited in their application, and they are rarely used in the development of conversational AI.
In many cases, a well-trained NLP bot will do a much better job than a knowledge-based system when you consider its overall costs and efficiency.
An Ever-Changing Market
The global conversational artificial intelligence niche was worth around $6.8 billion in 2021.
It is estimated that it will grow at a compound annual growth rate of 21.8% and reach a value of $18.4 billion by 2026.
The growing number of solution providers in the market, the rising demand for AI-powered customer support, and a big return on investment for companies that have already deployed conversational artificial intelligence solutions are the things that are driving the conversational artificial intelligence market forward.
How Can Conversational AI Help You Engage with Your Customers?
Nowadays, customer engagement is essential for becoming a successful business owner, as it affects the business’s capacity to attract, convert, and retain customers.
By investing in customer engagement solutions, such as conversational artificial intelligence, and having more suitable, user-friendly, and relevant interactions with each customer, you can build a large and loyal customer base that will keep coming back for more.
Deliver Omnichannel Support
A chatbot can help you with customer engagement by answering questions on a number of different platforms, ranging from a business website to mobile applications and social media.
It can give a customer an answer to a simple question, redirect the said customer to the part of the application that contains the answer, or collect useful information, such as email addresses.
All in all, it can really come in handy if you want each customer to have a consistent and helpful customer experience across all manner of devices and digital platforms.
Provide Support in a Number of Languages
We live in an incredibly globalized world. For that reason, customer support is no longer a specialized offering.
Instead, it has grown into a global endeavor, particularly when it comes to businesses selling products in many different countries around the world.
Unfortunately, it can be quite challenging to recruit a team of experienced customer experience specialists who speak numerous languages and dialects.
In such a situation, you can choose to rely on conversational AI and train chatbots to understand and use a large number of languages, as well as switch between languages. Doing so will help you reach a much wider, global audience.
Nurture Clients via Email
Replying and sending emails to customers by hand can be a tiring and tedious process. Luckily, with an automated marketing tool like an email bot, you can instantly respond to incoming emails and generate sales leads.
Using intent analysis and artificial intelligence, the email bot will deliver personalized replies to emails, giving you the ability to reply to tens of emails with the appropriate message and keep potential customers happy and engaged.
Boost Social Media Engagement
Social media is a useful tool that brands can use to communicate with both potential and existing customers using focused customer engagement strategies.
Such strategies can make customers feel special and valued. You can start using social media to its fullest potential by organizing polls, contests, and quizzes, as well as making use of conversational artificial intelligence.
When set up correctly, conversational AI could help you provide customers with a steady supply of content to consume and interact with.
For instance, when it comes to social media platforms like Facebook or Instagram, you could invest in a messenger bot and start having fully automated, two-way conversations with your clients.
Offer Personalized Experiences
Conversational AI can also be used to maintain a more personal connection with clients.
It can help you provide customers with tailored experiences, suggesting solutions that match their interest levels, demands, and background based on data gathered from previous interactions and back-end systems.
By creating a highly personal connection with each customer, you are guaranteed to boost customer engagement and brand loyalty in no time!
Most Common Mistakes in Conversational AI
Unfortunately, current artificial intelligence systems are not omnipotent.
If set up the wrong way, chatbots and other conversational artificial intelligence solutions might provide customers with incorrect or misleading information, which can be quite problematic for the company using it. But that is not the only mistake that you can make when using conversational AI.
Working with an outdated system, not naming the bot, or not having a clear strategy for the use of conversational artificial intelligence are all common mistakes that can result in a conversational AI system that does not meet customer needs and expectations.
AI Chatbot Providing Unclear Information
When setting up the chatbot, you need to be clear about what you want it to say to your customers. The information provided to the chatbot should be clear, concise, and to the point.
To give an example, if you want to use the conversational AI chatbot to route customers to the right department or person, you need to be sure that the name and contact information of the department or the person in question is correct.
Otherwise, you will end up with frustrated customers who feel like they are being passed around from one department to another just because the bot they first contacted led them astray.
Not Updating the System
If you want your chatbot to be useful, you need to keep it updated. Most current artificial intelligence systems work on the above-mentioned NLP model, which means that they are constantly learning from the interactions they have with customers and other texts that they are exposed to.
In other words, there is no final version of the bot, and you need to constantly monitor its interactions with customers and improve the way it works.
If you neglect to do that, you risk having your chatbot give your clients incorrect, repetitive, and robotic answers, which can have a negative impact on customer engagement.
Not Focusing on Behavioral Analysis
In artificial intelligence, behavioral analysis is the process of understanding how people interact with technology and seeing the patterns in their behaviors.
In the case of conversational AI, it means understanding how customers interact with the chatbot and checking whether the predictions you made during the development process were correct.
Unlike humans, AI chatbots cannot think beyond the code they were given, so even though the current systems are outstanding compared to what we had just a few years ago, they still may struggle with messages formulated in a way that their developers had not thought of.
Behavioral analysis helps you identify and analyze such cases, allowing you to improve your chatbot over time.
Making the AI Chatbot Sound Forceful
Your conversational AI system can be taught to act in a specific way. If you are using it to boost your customer engagement, you probably want it to encourage customers to take specific actions, such as buying a product or signing up for the newsletter.
But it is important to keep the responses balanced, without being excessively pushy.
Imagine that someone is constantly nagging you to buy something. Would you want to continue the conversation or would you just walk away?
With that in mind, instead of leading your customers directly to making a purchase, you should try to make your chatbot sound more like a consultant that is there to help with whatever the customer needs instead of an annoying salesperson.
That way, you can show potential clients that you actually care about more than just making a profit.
Not Naming the AI Chatbot
This one is deeply rooted in human psychology. We are social animals that like interacting with other people, so it is only natural that we would feel more comfortable talking to a chatbot named Mark or Julie rather than one just called Chatbot.
Using an actual name can help you conceal the fact that the entire conversation is being handled by a machine.
Doing so will create a sense of identity for the chatbot and make it feel more human.
In addition to that, it should come in handy when it comes to approaching people who still remember the early days of conversational bots and may feel discouraged to interact with them thinking that it is going to be a waste of time.
Not Having a Strategy
You should determine the purpose of a bot before you start using it. In other words, you need to have a clear strategy of what you want to achieve. Do you want to focus on just boosting customer engagement?
Or maybe you also want to reduce customer support costs or increase sales? Your chatbot should be aligned with your business goals. Otherwise, it will not be as useful as it could possibly be.
Deciding the role of conversational AI in your business will help you develop it in the way that will be most beneficial for your company. The more focused the chatbot is, the better results both your customers and you will get from it.
Ultimately, it all comes down to the fact that a chatbot is a tool, and, like all tools, it needs to be used in the right way to help its user achieve the desired results.
In Conclusion
Customer engagement is vital for the success of any business in the present-day market. Luckily, with the help of conversational artificial intelligence, you can engage with your customers on a more personal level, providing them with the information they need when they need it.
Just keep in mind that, like all tools, conversational AI needs to be used in the right way to help you achieve the desired results.
So, make sure that you are clear about what you want the chatbot to do, keep it updated, and focus on behavioral analysis to further improve its performance over time. Doing so will allow you to use it to its fullest potential!