Four Tips to Improve Your Chatbots

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The irrefutable truth is that many people hate talking on the phone now, and especially to people they don't really know.

That's why nowadays, people like me who get scared when they're tasked with calling the doctors find solace in the likes of SMS, email and chat app Customer Service systems.

However, these options aren't always perfect. We all know that when emailing a company with an issue or request, your message takes the best part of 10 business years to get a response, so that's not ideal.

As for SMS and chat apps, the contact centre agents are usually so busy that you have to enter an extensive queue to get a word in, and once you do, you can often feel yourself being rushed into an uncomfortable resolution.

It's because of these reasons that chatbots have become so vital in modern day B2C companies. When they work well, chatbots allow many issues and questions from consumers to be solved, without eating into the time of already busy employees.

Sadly, chatbots aren't yet perfect, and a lot of the time it can feel like you're only talking to one in order to eventually be referred to as a real person, but there are a number of ways you can improve on this.

So, how do you make chatbots better?

1. Make your chatbot more personable

Especially during and after this long winded and devastating pandemic, people are very much still craving a human touch in their CX. Naturally though, they know that this isn't all that possible, since everyone is busy all of the time these days.

With that, you want to make your chatbot more empathetic, conversational, and generally convey your brand's tone of voice in its interactions. These goals can be achieved in a number of ways. Firstly, making your chatbot more empathetic requires a lot of training.

conversational chatbot

When complaining, people are usually very passionate and want to be able to convey their emotions, which more or less fall on deaf ears with what is essentially a nicely packaged algorithm. To combat this, the conversation set that is used to train the chatbot before production should cover various emotional situations and be fed data from real conversations.

With that, the tuning team can figure out where the chatbots aren't emotionally in tune and train them more in those situations so they offer better and more personable support.

On top of this, you can use Natural Language Processing (NLP). This makes it possible for your chatbot to seem friendlier and generally better with human interaction.

Basically, an NLP recognises and remembers real language that people actually use, which in turn allows the chatbot software to utilise the data and provide customers with personalised information.

Like the above point, tone is also important, and NLPs can monitor a customer's tone, in order to have the chatbot reply conversationally and more pleasingly.

hellofresh chatbot

An NLP, in short, has chatbots learn regional and colloquial language that it can then use and in many cases, have had customers thinking they are talking to real customer service agents!

Allow your chatbot to have the transcripts and data from every other chatbot conversation within your business and this will nurture it adapting and being able to talk like a customer, using the language that a customer would use when they're typing, and not necessarily when they're actually talking.

There's a big difference in how people talk on different platforms, and it's important that your chatbot understand that.

2. Make sure the chatbot has the company's tone of voice

This one seems obvious but isn't something that companies think of.

If your company is famously fun-loving and casual, then it would be jarring if when a customer got in touch, they were met with a chatbot that spoke like someone writing Magna Carta.

H&M Chatbot

This is easily fixed, as you can programme generic responses and greetings into chatbots, encourage them to use emojis and generally tailor them to what your consumers have become accustomed to.

3. Use AI, machine learning and neural networks

All scary terms with their own frightening implications, there. Nice.

Using the data from customer interactions, AI-powered chatbots can learn from conversations and be able to appropriately respond to new situations.

4. Know that chatbots aren't always the answer

At the end of the day, at least for now, chatbots are nothing more than impressive coding. Consumers will always prefer the human touch and so long as they're able to tell, chatbots will be seen as more of a means to an end, rather than anything else.

Chatbots are great for small issues like finding where an ordered item is, arranging returns and providing generic information, but they don't really excel at personalised product advice, for now at least. 

Working hand-in-hand with a team of real contact agents is best, where the bots can deal with the low-priority/easy customer issues under supervision.

There's a silly amount of constantly evolving technology that improves chatbots doing the rounds at any given moment. At some point in the future, an article like this will be totally unnecessary and us humans will be looking to robots for advice on how to talk to people... I imagine.

Know your software's limitations and allow it to learn from past and present experiences. Given time, a machine learning chatbot will serve you very well.