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Why Your AI Chatbot ‘Training’ Matters (and What to Look For)

Posted by
Nupura Ughade
July 27, 2023

When you think about chatbots, chances are you’re focusing on how they will help your customers, how they’ll make your teams more productive, etcetera.

We talk about leveraging conversational AI chatbots in your strategy here on the Sense blog quite a bit, in fact. :)

But when it comes down to taking action and finding a recruiting chatbot for your organization, there’s more to consider. At this point, you know what a chatbot can do and how it can help your business.

Now you need to find the right recruiting chatbot to help achieve your business goals. 

In this blog post, we’ll offer some insight into a particular area of chatbots that is important to consider when vetting potential partners. 

Your AI chatbot’s training.

What is chatbot training?

AI chatbot training is the process of teaching an artificial intelligence (AI) chatbot how to understand and respond to user queries in a way that is accurate, effective, and human-like. 

How to train a chatbot?

The training process typically involves providing the chatbot with a dataset of examples that it can use to learn how to recognize and interpret user input, as well as to generate appropriate responses. Most of the time, this is your own data, rather than an external dataset.

The training data for an AI chatbot can come from a variety of sources depending on the kind of chatbot. For example, a customer support bot can be trained using customer service transcripts, social media interactions, conversations text, other forms of user feedback. A recruiting chatbot should be trained based on recruiting data, such as job postings, resumes, candidate profiles, candidate FAQs, interview transcripts and conversations, etc.

Over time, the AI chatbot can be continuously trained and refined using additional data and user feedback, allowing it to become more accurate and effective in its responses. This iterative process of training and refining is known as machine learning, and it is a key component of many modern AI chatbots.

Why is recruiting chatbot training important? 

A chatbot can only be as good as the data it uses to have conversations with your end users. The quality and value of those conversations will dramatically impact your conversions, recruiter hours saved, candidates hired, candidate NPS scores, and other core hiring metrics — and ultimately, ROI on your AI chatbot. This is a key element in understanding the limitations and benefits of AI chatbot training.

It is ESSENTIAL to vet potential chatbot partners on their AI chatbot training methodology. Potential AI chatbot solutions should proudly share how their recruiting chatbot is trained, as it significantly impacts its ability to generate results for your organization.

For example, we’ve all heard about (and probably even tried) ChatGPT that’s taken the world by storm recently. To train ChatGPT, OpenAI used a large dataset of text from the internet, including books, articles, and websites. And here’s where the importance of chatbot training comes in. While ChatGPT can generate fairly accurate responses, its knowledge is still limited to 2021 data. So it has limitations in providing responses based on current scenarios of 2022 and beyond.

What are the important factors in AI recruiting chatbot training?

If you’re looking for an AI recruiting chatbot, at the end of the day, you probably want a chatbot that has been trained with data specific to the recruiting industry! There are several important factors when it comes to recruiting chatbot training:

Natural language processing and understanding (NLP/NLU)

The chatbot needs to be able to understand and interpret natural language queries from users. To achieve this, the NLP/NLU chatbot needs to be trained on a large and diverse dataset of text data, including job postings, resumes, interview transcripts, etc.

Intent and entity recognition from the chatbot

The chatbot needs to be able to accurately extract relevant entities from the user's input, such as job titles, locations, and skills. To capture the user’s intent, interpret it, and respond appropriately, the chatbot needs to be trained on a diverse set of recruiting data that covers a range of entities and variations.

Chatbot conversation flow

Conversation flow is like a script to ensure an effortless and natural flow of responses in the conversation. Conversation flows vary based on the primary function of your recruiting chatbot, such as sourcing, pre-screening, or data enrichment. Designing a conversational flow from scratch is complicated, but fortunately, there are easy-to-build, drag-and-drop recruiting chatbots that you can deploy within minutes.

Recruiting dataset collection and analysis

A recruiting chatbot will need to answer questions about your company and culture, job openings, the application process, etc. If the answers aren’t naturally flowing and nuanced to your hiring process, you’re writing a recipe for poor candidate experience! That’s why it is important that your recruiting chatbot is trained with recruiting data.

While most AI recruiting chatbots rely on customer service data, leading providers use an abundance of relevant industry-specific data to train a recruiting chatbot. At Sense, we have built and continue to innovate our AI chatbot with recruiting data and that makes it the most compelling recruiting chatbot in the market.

Ready to integrate AI chatbots into your recruiting strategy?

AI chatbots are revolutionizing hiring - no two ways about it! Sense AI chatbot helps maximize recruiter efficiency with a fully-integrated 24/7 digital recruiter. Book a demo to see the Sense chatbot in action!

If you’re still getting started on adopting chatbots in your recruiting workflows and want to know more about how chatbots can accelerate hiring, lower costs, and deliver an improved candidate experience in this red-hot market, explore our blog that details 5 actionable ways to accelerate hiring with an AI chatbot.

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