Jesus Latorre-SocasSeptember 03, 2019
Topics: Candidate Experience

The Evolution of Recruiting Chatbots

Originally, website chatbots were designed to help answer basic questions from a list of FAQs. Now, however, visitors are looking for a more hyper-personalized experience—which is why chatbots have evolved from strictly FAQ chatbots to conversational chatbots.

So, what’s the difference between the two, and how does a chatbot benefit your career site visitors?

It all started with FAQ chatbots.

FAQ chatbots were designed to have an FAQ repository that is trained and modeled by a human behind the scenes. If you were a chatbot user looking for more information about company benefits, you would be met with this:

You: What are your benefits?

Chatbot: Here is a list of our benefits <example benefits>

Chatbot: Can I help you with anything else?

But what would happen if you asked the same question in a way that the chatbot wasn’t trained for? Here is what that would look like:

You: Tell me your benefits

Chatbot: I’m sorry, I can’t comprehend, please rephrase.

You: Benefits

Chatbot: I’m sorry, I can’t comprehend, please rephrase.

You: What are your benefits?

Chatbot: Here is a list of our benefits <example benefits>

By this time, you would be aggravated and more inclined to leave the site. Ideally, an FAQ chatbot would be trained to answer questions phrased in various ways, but it’s impossible to capture every option.

Let’s now take a look at conversational chatbots.

Conversational chatbots deliver information in a more natural way.

A conversational chatbot is more than just an FAQ answering machine. It can simulate a more natural conversation by using artificial intelligence. A conversational chatbot can understand the intent of the message and convert it into something meaningful. In some cases, users might not even know they’re talking to a bot!

Here’s an example conversation:

You: What are your benefits?

Chatbot: Here is a list of our benefits <example benefits>

The intent here is benefits, so the chatbot knows you are asking for very specific information about the company’s benefits. It looks into its knowledge base and extracts the answers. But what if we rephrase the question?

You: Tell me your benefits

Chatbot: Here is a list of our benefits <example benefits>

You: Benefits

Chatbot: Here is a list of our benefits <example benefits>

The intent is still benefits, so the chatbot can understand this type of question in any number of ways, as long as the intent is mapped to an answer. This enables the chatbot to be more aware of what visitors are asking for and be more productive in answering their questions.

What does a more complex conversation look like?

Chatbot: Welcome to our <company site>. How can I help?

You: Tell me your benefits and who your CEO is

Chatbot: Here is a list of our benefits <example benefits>

Chatbot: Also, our CEO is <CEO>. Here’s a quick bio. <link>

Chatbot: Would you like to learn more about us? I have tons more information if you’d like.

You: Yes, tell me more

Chatbot: Okay

Chatbot: Here is the history of our company. We stand for these core values: <core values>

Chatbot: We are also looking to hire as we continue expanding our workforce. Are you looking for a job?

You: Yes, I’m looking for change and am interested in open jobs.

Chatbot: Great! Here are some of our current openings <show jobs>

As you can see, the flow of conversation is more natural, and the chatbot is able to answer your questions, and even make suggestions based on context.

It is possible to take this type of conversation even further, and hyper-personalize the experience by collecting information from you. This can make the experience that much better.

An example of this can be seen below:

Chatbot: Welcome to our <company site>. Can you tell me your name?

You: John Doe

Chatbot: Thanks John! Now tell me, how can I help you?

You: Tell me your benefits and who your CEO is

Chatbot: Here is a list of our benefits <example benefits>

Chatbot: Also, our CEO is <CEO>. Here’s a quick bio. <link>

Chatbot: Would you like to learn more about us, John? I have tons more information if you’d like.

You: Yes, tell me more

Chatbot: Okay

Chatbot: Here is the history of our company. We stand for these core values: <core values>

Chatbot: We are also looking to hire as we continue expanding our workforce. John, are you looking for a job?

You: Yes, I’m looking for change and am interested in open jobs.

Chatbot: Great! Here are some of our current openings. <show jobs>

Chatbot: I can help personalize the jobs more to your skills as well, John. Do you want me to personalize this? If so, please provide me more information about yourself such as skills, experience, and interests.

In the above conversation, not only can we determine the intent of the conversation, but we’ve also made the experience personal to John. This helps retain visitors to your site, and even gets them to engage more with your company and apply for a position.

The Future of Chatbots

With the advancement of the chatbot experience, and the evolving state of users conversing over virtual messages, it’s becoming necessary for companies to offer a chatbot on their sites to retain visitors. In fact, a recent survey showed 80% of all businesses already have or plan to have some sort of chatbot experience by 2020. Even messaging services such as WhatsApp and Facebook Messenger have moved into designing chatbot-based experiences.

FAQ Chatbot + Conversational Bot = Phenom Bot

We have taken the best parts of both of these chatbot experiences and developed our own take: Phenom Bot. Phenom Bot is both an FAQ chatbot and a conversational chatbot, which helps hyper-personalize the candidate experience for your company and ensures all of their questions get answered.

So, what are you waiting for? Request a demo to get started with Phenom Bot!

Jesus Latorre-Socas

Jesus is a product manager at Phenom People, where he focuses on creating exceptional conversations through chatbots. He enjoys spending time with his dogs and traveling to a new country every year. 

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