Chatbots are evolving at an accelerated pace, and there’s a pretty good chance that we have all interacted with an artificially intelligent chatbot at least once.
In recent years, chatbots have started to play a more prominent role in enterprise operations across industries. Today, chatbots can be integrated into apps, social media platforms, and websites to enhance customer service functions and marketing strategies. Going forward, chatbots will be the underlying force that helps businesses scale, boost productivity, enhance customer service, and cut costs.
However, before we go any further, let’s clearly define them.
What Are Chatbots?
A chatbot (or chat robot) can be defined as an artificial conversational entity that leverages text-based signals or key pre-calculated user phrases to stimulate interactive human conversation. While chatbots might be the rage at present, they have been around for decades.
One of the earliest examples of chatbots is ELIZA, a simulation of a Rogerian psychotherapist that first emerged in 1966. Another example is PARRY, which in 1972 attempted to model the behavior of a paranoid schizophrenic.
With significant strides made in the fields of artificial intelligence and machine learning, chatbots have come a long way. Today, they can adapt and learn based on every human interaction and perform simple tasks on their own without human intervention.
This has lead to bots being developed for specific purposes, like virtual assistants (like Alexa, Siri, and Watson) that access data to answer questions or perform tasks. In 2016, Facebook opened its APIs to chatbot developers on its messaging platform.
Twitter followed suit the following year, enabling businesses to use chatbots to perform basic customer service or customer engagement functions. However, we are still a long way from closely replicating human conversations.
Read here about the AI use cases in Chatbot working, complementing the work of human programmers.
What Are the Different Types of Chatbots You Can Build?
While there are many types of chatbots serving different purposes, the following are the main types of enterprise chatbots that businesses can build:
- Support Chatbots
- Skills Chatbots
- Assistant Chatbots
Support Chatbots
Support chatbots are primarily constructed to master a single domain. This can be, for example, expertise in a specific area (like extensive knowledge about the company). These types of chatbots need to have context awareness, multi-turn capability, and personality.
Support chatbots should be able to seamlessly walk users through major business processes and quickly answer FAQs. So when you build support bots, it will be essential to take a short-tail and long-tail combination solution.
It will be critical for support bot developers to make sure that the bot is extremely easy to navigate. They should also spend time ensuring that the bot can execute tasks that the users actually care about.
Skills Chatbots
Skills chatbots can be described as single-turn-type bots that don’t need much contextual awareness. They only need to focus on a set of commands that can make life easier for people. These tasks can be something as simple as turning the lights on or off.
Skills bots will demand speech functionality, so the user doesn’t have to turn on a device or click buttons. The key here is to build a skills bot that can follow commands quickly and allow the user to multitask while engaging with the bot.
As people usually learn what to say (and how to say it appropriately) quickly, there isn’t any need to build contextual awareness unless you’re developing an advanced skills chatbot. Developers of skills bots will need to focus more on keeping integration with home appliances as simple as possible.
Assistant Chatbots
Assistant chatbots are more or less a combination of support bots and skills bots. They work best when they have a little bit of knowledge about a variety of topics. Assistant bots have become common because of the extensive adoption of Alexa, Siri, and Google Assistant.
Assistant chatbots need to be highly conversational and entertaining. Siri is an excellent example of an assistant bot that’s often engaged because it tends to be quite amusing.
Developers building assistant chatbots need to make it easy for others to understand how the bot is trained. The most challenging part of this scenario will be to cover the extensive range of questions that individual users may ask.
Enterprise Chatbots
For enterprises, chatbots offer the benefit of further communication that helps solve problems. According to a recent study conducted by Drift, SurveyMonkey, Audience, Salesforce, and myclever, 37 percent of respondents stated that they expected to receive quick answers to questions during an emergency. Another 35 percent said they expected detailed answers or explanations to their questions. However, another 34 percent indicated that they used chatbots as a means to get connected to a human. This emphasizes the need for businesses to always have that option.
The respondents called out other key benefits of chatbots:
- 24-hour service (64 percent)
- Instant responses to inquiries (55 percent)
- Quick answers to simple questions (55 percent)
Customers also preferred a swift answer to their questions as opposed to a wholly accurate one.
It doesn’t come as a surprise that 43 percent of respondents stated that they preferred to communicate directly with a human instead of a chatbot. This can be directly attributed to their concerns about the following:
- 30 percent of respondents were worried that a chatbot might make a mistake
- 27 percent worried that it could only be accessible via a specific medium like Facebook Messenger
- 24 percent didn’t think that a chatbot would engage them in a friendly manner
Interestingly, when it came to human interaction, these concerns remained the same. So what does this means for enterprises and chatbot developers?
When developing chatbots for specific business purposes, developers need to focus on end-user experiences. This means that the chatbots need to be designed thoughtfully and intelligently to deliver enhanced customer experiences.
At this juncture, it’s also important to note that chatbots aren’t suited for every type of business. For example, it’s well suited to online retailers, but maybe not for the healthcare industry, where miscommunication to lead to serious negative repurcussions. The same is true when it comes to a software-as-a-service model, as the needs are considerably different.
While customers may always prefer to talk to a “real person,” enterprises can’t ignore the fact that chatbots generate leads, engage with the customer at the right time during the buyer’s journey, and are capable of interacting with thousands of customers at the same time, cost-effectively. One example: Tommy Hilfiger’s use of a Facebook Messenger chatbot resulted in an 87 percent rate of returning customers.
This is probably the reason behind the exponential growth of the chatbot market. Research suggests that the chatbot market is currently growing at a compound annual rate of 24.3 percent and is forecasted to be worth as much as $1.25 billion by 2025.
According to Conversational Commerce, about 35 percent of users have purchased products like clothing or food with the help of a voice assistant. Approximately 44 percent of users would like to initiate a bank transfer with the help of a voice assistant.
Another 56 percent of users would like the help of voice assistants to order food from restaurants. The same study also found that users were highly satisfied with using voice assistants to order food (87 percent), make financial transactions (87 percent), buy a variety of products (86 percent), and order taxis (83 percent).
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Best Practices: How to Use Chatbots to Grow Your Business
If you’re considering building a chatbot to grow your business, you have to first identify its primary purpose and then follow a set of best practices that go beyond the natural language processing (or NLP, which falls under the domain of data science and artificial intelligence,) and personality of the bot. and the personality of the bot. This means that your chatbot development team will have to account for multiple ambiguities, interruptions, and unexpected scenarios that are innate in real-life conversations.
Chatbot software like MobileMonkey can be especially helpful, especially if you’re already identified a specific set of needs, like integrating a chatbot into your marketing strategy.
Think Like a User
At the planning stage of the project, it’ll be crucial to take a step back and start thinking like a user. You can get everyone in the company involved in this exercise to cover all bases and answer as many questions as possible upfront before building the bot.
This approach will help you save time by negating the need to make a lot of changes in the future. It’ll also go a long way in making a good impression on the end-user.
Establish a Standard Welcome Message
The welcome message is one of the most important messages that your chatbot will deliver. It should be conversational but designed to help your users (or customers) understand that they will be engaging with a chatbot (and not a real person).
List What Your Chatbot Can Do
In your welcome message, you can also list all that the chatbot is capable of accomplishing. This will help users avoid wasting time on activities that aren’t supported by your bot.
The welcome message should also provide users with the ability to restart a conversation. This will help users feel less trapped while engaging with your chatbot. At the same time, make it easy for users to transfer the conversation to a human.
Give It a Personality
Siri’s popularity has a lot to do with its personality. So when you start developing your enterprise chatbot, make sure that it has its own character that’s closely aligned with your brand values.
However, it’s best to avoid setting a gender. In this scenario, a neutral gender is the best option as it doesn’t draw too much attention to its personality. This approach will help the end-user focus more on the task and not the bot.
Intent Training and Natural Language Processing
Chatbots need intent training as part of the natural language processing phase of the project. This can take the form of conversation training that helps the bot identify the right conversation it needs to start with the user.
Entity training is also essential to help the bot recognize “entities” from the conversation with the end-user. Imagining the set of conversations that a chatbot might have will make it much easier to design your enterprise chatbot.
Seamlessly Manage Interruptions
Your chatbot also needs to be well equipped to deal with interruptions effectively. A user might change their mind halfway through the interaction, for example, and want to change the topic of the conversation.
The chatbot should also be able to switch topics on demand instead of pushing the user to stick to a fixed decision tree that it’s programmed to follow. If the user is unsure about how to proceed, the bot can also provide quick suggestions to help them make a decision.
Versatility Is Key
When you talk to a human being, it’s very rare that they would use the same words or sentences during an interaction. To make chatbot experiences feel natural, developers need to make the conversation as versatile as possible by including a variety of messages a bot can choose from.
Develop a Protocol to Deal With Ambiguities
Sometimes, a bot can identify a variety of values for a given entity, but it won’t be able to handle something it wasn’t designed to accomplish. For example, if you ask an online retail chatbot which smartphone was better, the bot won’t be able to engage unless it was developed to compare smartphone models.
In this scenario, the chatbot will come back to whether or not the user is going to make a purchase decision. Whenever a conversation runs out of steam and the user has stopped engaging, it’s best to ask the user if they want to continue the conversation 30 minutes after their last message.
Have a Plan to Manage Risk
When you build chatbots that pull dynamic data from multiple sources, there’s always a risk of running into technical issues. This makes it vital to set up robust error handling mechanisms on all dynamic services to ensure that users are informed when things go wrong.
Test the Chatbot Internally and Externally
Before launching the bot on your website or mobile app, it’s essential to test it internally and externally with trusted users. This approach is the best way to capture all the different variations in conversation including nuances of the product or service.
When it is launched, it’s important to have a human element monitoring and improving the intelligence of the chatbot. As mimicking humans is extremely difficult, it’s best to start with most basic and common questions and then build over time.
Guard Rails
Whenever users stump the chatbot or ask a question that’s beyond its scope, developers need to ensure that the bot can make an elegant transition into a live chat with a human. As user experience is paramount, ensure that the bot doesn’t repeat “I don’t understand your question” more than three times.
In this scenario, depending on the type of business, you can also employ some humor to diffuse any potential issues that may arise.
Bots in Action
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The travel industry has quickly embraced chatbots. Expedia’s Facebook Messenger bot lets users book or manage a trip on the go. For new customers, it requests basic information about where they want to stay and then shows the most popular hotel options in that location. The bot shares links that will move users to Expedia’s website to make the booking, but after a transaction, the conversation will move back to Facebook, where the bot will share a link to the traveler’s itinerary.
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Real estate companies around the U.S. are working with Roof to help boost lead generation and lead assignment. This bot responds to user queries immediately and prompts potential leads for additional information before assigning the lead to a sales agent, decreasing leakage.
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Duolingo built a bot to help keep users on the app longer and solve a major pain point: practicing their conversation skills in a safe and judgment-free environment. There are multiple characters with whom a language learner can converse, including a chef and a police officer, which adds to the fun.
The benefits of chatbots are becoming clearer all the time. These AI features aren’t going anywhere anytime soon. They will continue to play a prominent role in brand engagement, generating leads, and delivering enhanced customer experiences. Advanced chatbots developed by data scientists and AI engineers will help in the medical field in the near future by earning people’s confidence.
So if you’re thinking about leveraging a chatbot to grow your business, make sure to build one that can provide a unique experience that can set you apart from the competition.
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