Chatbot ChallengesChatbot Training

Practice makes perfect: How to get your chatbots up to speed quickly

By jake ellis | Nov 17, 2021

Practice makes perfect: How to get your chatbots up to speed quickly Cover Image

Your web presence—redefined

The first point of contact with your customer can often be crucial in securing sales. As more purchases are now made online, that first point of contact for many prospective buyers is a chatbot. As new conversational marketing techniques have swept across the digital world, it is more important than ever for businesses to do more than to simply have a presence on the web. A chatbot not only allows you to engage with your customers 24/7 but also to provide a friendly and conversational introduction to any potential sales lead. The quality of chatbot-customer interactions matters, so, how do you train your chatbot and do it quickly?

Why you need to train chatbots

Surprisingly perhaps, some businesses and industries have been hesitant to fully embrace chatbot technology.  But that’s not so surprising to anyone given charge of training chatbots.  Usually, it’s time-consuming, grueling, and can take months to get right.  Until it’s fully trained, it continuously feeds up the wrong answers to questions, or—worse still—doesn’t understand the enquirer at all.

Think of a chatbot without training as an iPhone without apps—useless.  It’s the apps that make iPhones useful.  Similarly, it’s education into what customers might ask, and what they want that makes bots useful.

Missed intents is an industry-wide adoption issue and it’s a characteristic that plagues untrained chatbots. While bots are not delivering the right answers for enquirers they represent a drain on your customer experience; potentially risking losing the sales leads that your digital presence generates. All that hard effort and marketing spend gone to waste.  So how do you rapidly speed the time to value of your chatbot investment?

The rise, fall and rise again of chatbots

Over the last 5 years, chatbots have been promised to provide a revolution in digital customer experience. There was a massive initial wave of optimism and growth in the chatbot market, with Business Insider predicting in 2016 that 80% of businesses would adopt a chatbot by 2020. These predictions are still yet to be fully realized. Indeed, in one study focusing on the insurance industry in the UK, chatbot adoption was found to be 6.75% across the top 100 providers, much lower than the earlier estimates.

You may think that the current low adoption rates are simply because chatbot technology has not lived up to its early promise. However, this assumption would be wide of the mark. Instead, chatbots have gone through a stage of rapid machine learning and AI development. Here, there is a stark difference between the earlier iterations of chatbot technology and the more recent, fully trained, chatbots. Far from being doomed to failure, the technology for successful chatbots is here and the training methods and tools designed to get them up to speed are ready and waiting to be implemented.

woman online shopping on her phone talking to chatbot

The market opportunity for chatbots hasn’t gone away, it’s grown

The demand for chatbots is clear.  Industry leaders want to adopt chatbot technology because it removes the human-from-the-loop of customer service, equips businesses with the means to trade 24/7, and—done well—raises the bar on customer experience.  Chatbots are predicted to save businesses $11bn in customer service costs and 2.5 billion business hours by 2023.  In fact, one report estimates that the chatbot market will grow to $10.5 billion by 2026, enjoying a compound annual growth rate of 23.5%.  This demand is corroborated on the customer side too. In research by Userlike, 68% of respondents felt that they had a positive experience with a site as a result of the chatbot being able to answer their query quickly. Here, respondents felt chatbots provided a much more tailored and conversational response instead of just being greeted by a standard web page. This leaves no doubt then, the appetite for intelligent bots is still alive and well.

What is holding the technology back?

With the demand for chatbots seemingly obvious, you would be right to question what the fundamental technology debt holding back chatbots is. The answer is simple: untrained bots. These earlier iterations of chatbots have been plagued with certain challenges and problems since their release. The biggest one is the missed intents. This is when the customer question or prompt is either not recognized or incorrectly recognized by the chatbot, and typically hovers around 35% of all intents in untrained bots. This not only hampers the user experience but also means that businesses are losing out on both potential leads and sales.

Another big problem for past chatbot technology has been the wide variation in grammar and wording of user prompts. With the potential customer base online being so widespread, so are the individual dialects and grammatical quirks that they have. Would you expect every single one of your customers to ask you the same question worded in exactly the same way? After all, we are the humans here, not bots. Therefore, chatbots are only as good as the training that they have been given and many of the early iterations of chatbot technology are yet to be trained and yet to have their problems ironed out.

female customer online shopping using chatbot

How do you go about training a chatbot?

All this talk of fully-trained chatbots is great, isn’t it? But how can you get your chatbot fully trained? If you have a chatbot that is untrained or you don’t have one at all, this process can seem especially daunting. Yet it doesn’t need to be. To train your chatbot and get it up to speed quickly requires two simple steps:

  1. Data capture: Chatbots live and breathe on data. The only way chatbots can learn and respond to different grammatical and wording variations is by knowing them firsthand and being able to categorize them into different requests.

  2. Automated training: Then a system is required to be able to interpret this data in order to train the bots. This involves more thoughtful natural language processing and breaking down user prompts into specific action words.

Both of these processes do not need to be time-consuming or expensive. While it may seem particularly laborsome to collect all of the necessary language data, there are already existing datasets available. Here, it is better to buy training packages and services for your bot than to try and retrofit and recreate all of the data needed. This is especially true given the current low adoption of chatbots in certain industries.

Here can help. The INTNT engine has been specifically designed to bring chatbots up to speed quickly and efficiently. To achieve this, INTNT automates the bot training process. This includes the auto-detection of false positives, false negatives, and clustering new intents for better recognition. As a result, bots become 102% more accurate in just 3 weeks, and 180% more accurate in 8 weeks. While it may seem a mammoth challenge to overcome, the technology to train intelligence chatbots is here. Despite the low adoption and various problems facing early iterations of AI technology, chatbots can now be brought up to speed quickly and efficiently and provide a much more accurate conversational introduction of your business to customers. In the end, it all comes down to – practice making perfect.