How to Train a Chatbot: 8 Powerful Tips for Building a Better Chatbot

Chatbots have rapidly become a crucial way for brands to engage customers and provide helpful automated service. But much like a new pet, a chatbot takes proper training and care to become useful and avoid messy mistakes.

Think of the infamous case of Tay – the AI chatbot released by Microsoft in 2016. Tay was designed to engage with users on Twitter and learn from them.

How to Train a Chatbot

Unfortunately, internet trolls bombarded Tay with offensive comments. And since the bot wasn’t properly trained, it started spewing incredibly inappropriate tweets before Microsoft shut it down. Clearly this shows why thorough bot training is so vital.

So how exactly should you go about training an intelligent and effective chatbot? This article will provide 8 actionable tips to get your chatbot behaving properly right off the bat.

Chatbot Lingo: Key Terms to Know

But before we dive in, let’s quickly define some key lingo you’ll need to know:

  • Utterances: What a user might actually say to the bot
  • Intents: What the user wants or intends to get from the interaction
  • Entities: Key details the user provides to clarify their intent

For example:

Utterance: “Show me today’s news about sports”

Intent: Get-news

Entities: “Today’s”, “sports”

Got it? Great, let’s move on to those all-important training tips!

1. Clearly Define Your Chatbot’s Purpose

It’s tempting when creating a new chatbot to throw in every bell and whistle you can imagine. But that shotgun approach rarely works well.

The first step should always be narrowly defining the exact problems your chatbot aims to solve. What scenarios and use cases will come up most for your customers? Avoid rarely used features and edge cases early on.

For an e-commerce site, allowing order tracking might seem useful. But if only 3% of queries are about orders, it shouldn’t be the initial focus. Nail down specific high volume use cases first.

2. Create Distinct Intents

One of the keys to effective AI chatbot training is making sure your bot can clearly differentiate between requests. We do that by creating very specialized intents that serve distinct purposes.

For example, you may want intents like:

  • #faq_shipping
  • #return_policy
  • #track_order

The more targeted your intents are, the less chance of confusion.

3. Include Diverse Utterance Examples

Remember, your chatbot has no experience with actual human conversations. The only way to teach it is by providing tons of potential utterances to associate with each intent.

The development team should continually iterate by adding new sample phrases. Get creative and think of all the possible ways users might try to invoke a particular intent.

Don’t just include simple statements either. Use questions, exclamations, typos – whatever you can think of! The more real-world variability you account for, the better.

4. Get Inputs from Diverse Sources

While iterating and expanding the sample utterances, it helps massively to collect inputs from a varied set of people. You want to expose your bot during training to as diverse a set of voices as possible.

That means getting feedback from colleagues of different backgrounds, ages, geographic regions, and so on. The more diversity, the less chance you’ll overlook certain speech patterns and terminology.

5. Make Entities Purposeful

As mentioned earlier, entities allow your chatbot to pull out key details from utterances. This can enable variables the bot needs to fulfill intents.

But don’t get entity-happy and tag every single noun or adjective. Only extract details that will serve an actual purpose for the intents. Otherwise you risk diluting the effectiveness of entities.

For example, in “Show me the weather in Barcelona” – the city name is crucial. But words like “show”, “me” and “the” can likely be ignored.

6. Give Your Chatbot Personality

It’s important to remember that your chatbot serves not just a practical purpose, but also a branding one. The tone, personality, and language it uses all affect a customer’s perception of your company.

While some brands opt for an ultra-professional bot voice, don’t be afraid to take a more casual or fun approach if it fits. As long as you stay on-brand, an engaging chatbot personality drives satisfaction.

Experiment to find just the right balance of useful and entertaining.

7. Incorporate Interactive Elements

Text alone does not an effective chatbot make. To truly engage users, incorporate interactive elements like:

  • Images
  • Buttons
  • Suggestion cards
  • Confirmation messages

E-commerce chatbots, for example, should suggest potential products to purchase whenever logical. Quick access to purchases drives conversion rates.

8. Continuously Train Your Chatbot

Releasing your chatbot is not the end – it’s only the beginning! The ability to interpret and respond to real-world user queries in an iterative process is at the core of quality AI.

Pay close attention after launch to situations where your bot struggles or fails. Use logs and transcripts to determine new gaps in intents, entities, utterances, flows.

View unsuccessful interactions as data and opportunity to improve rather than failure. A good chatbot is perpetually a work in progress.

Chatbots Don’t Require True Intelligence…Yet

One final note before we wrap up – while advanced AI does empower chatbots, don’t get overwhelmed trying to create the next Skynet. The truth is most basic chatbot capabilities rely on simple data flows rather than machine learning.

Carefully mapping expected user conversations as decision trees gives you a great framework to build on. Identify probable queries, build branching logic to guide users to appropriate resolutions, rinse and repeat.

Over time you can then incorporate more predictive AI elements like NLU (natural language understanding) to recognize intents automatically.

But for starters, focus on structuring dynamic conversations over making a brain.

Let’s Chat!

And there you have it – 8 rocksolid tips to whip your fledgling chatbot into shape. Training may take significant trial and error, but the effort pays back exponentially in customer satisfaction.

What other bot training wisdom can you share? Feel free to reach out with any questions or ideas. I’m always happy to chat more about helping brands build better automated assistants!

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