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How AI Chatbots Can Help You Be There for Customers

We’re in the third decade of the 21st century and many consumer-facing enterprises don’t want their customers to get in touch for a chat

These enterprises will hide phone numbers on websites or tell customers to email and expect a response within five days. This is a strange state of affairs to say the least. 

Many millions are spent marketing to prospects, but when existing customers try and instigate a closer relationship, they’re held at arm’s length.

The reasons for this stand-offish behavior are clear. Setting up contact center operatives to be there whenever a customer clicks their fingers can be ruinously expensive. As can having people on standby to answer every email or text within seconds.

However, the combination of AI-powered chatbots and SMS, RCS, or chat apps (like WhatsApp) gives you a chance to always stay in touch with your customers. Just think about the scope of this opportunity. 

Ease and intimacy

When we want to check in with a friend or family member, our first instinct is to send them a text or chat message rather than call or email. Whether it’s an SMS or a WhatsApp message, we feel comfortable with the ease and intimacy (yet comforting partial distance and detachment) communicating this way gives us.

Now imagine winning a place in your customers’ contact book and being available for text-based conversations at any time. You could be on hand to answer questions about products, to receive comments on services, to provide general updates – or just to lend a helping hand when customers need it.

Being there for customers 24 hours a day puts you in a great position to build trust, loyalty, and advocacy. Bottom line, this tends to mean you will sell more too!

The chatbot future is here 

For some time we’ve spoken of chatbots as ‘the future’. Yet we’re well past the tipping point of automated conversation as a new and emerging technology. It’s time to shift the script. Chatbots are now simply part of modern life. 

The case for businesses putting them to work more widely is a compelling one:

  • Increased availability, with decreased cost
  • More efficient use of human resources
  • A variety of applications across sales, marketing, and customer service
  • Instant, 24/7 communication with customers on the channels they love
  • And of course, that all important increased customer satisfaction

Thanks to advances in technology, the chatbot has evolved beyond the basic rule-based software it used to be – where users had to respond with a limited set of phrases for the chatbot to understand. 

Today’s AI chatbots are trained to understand customer intent through Natural Language Processing (NLP). Customers don’t have to stick to a set script as the chatbot is able to make sense of what’s been said, understand the intent, and generate a suitable answer. This makes interaction much more natural and avoids scenarios where deviation from the script drives the conversation to a grinding halt. And, thanks to machine learning, these chatbots get smarter over time as they’re exposed to more conversational data.

rule based chatbot

AI chatbots perform the same simple tasks that rule-based chatbots can handle, but they also excel in more complicated customer conversations. For example, while a rule-based chatbot could help you book a doctor’s appointment, an AI chatbot could be powerful enough to give you a near accurate medical diagnosis. In finance, a rule-based chatbot might help you check your balance or pay a bill, whereas an AI chatbot could help you improve your money management by offering personalized recommendations.

AI chatbots solve the omnichannel challenge

With the modern consumer using social media, multiple messaging apps, email, SMS, live chat and more, an omnichannel approach to customer communication is a must

Customers expect to reach businesses whenever they want, wherever they want, and for the experience across each channel to be integrated and seamless. A customer might discover your product on Instagram, send a direct message on the app for more information, go to your website for purchase, and then remain in touch via WhatsApp for ongoing support. At every stage they expect consistency.

It’s a big ask, and businesses can only answer it with the help of automation. This is where chatbots come into their own: removing the strain from human resource, delivering 24/7 omnichannel availability without huge overheads, and ensuring communications remain on brand from channel to channel.

Of the many channels available, chat apps are emerging as a firm favorite for talking to businesses. According to WhatsApp, 80% of customers see messaging as a quick and easy way to communicate with a business, and 75% want to communicate with businesses in the same way they talk to friends and family. Thankfully, chatbots can be deployed across many popular chat apps such as:

  • WhatsApp
  • Viber
  • Google’s Business Messages
  • Line
  • Telegram
  • Messenger
  • Apple Messages for Business
  • Instagram

… as well as more traditional SMS and its younger, video-rich, more interactive iteration RCS.

Building AI chatbots doesn’t have to be difficult

There are several chatbot-building platforms designed to streamline and simplify the process. For example, our chatbot building platform Answers lets you build powerful, intelligent bots without needing to know a line of code. The real work of designing and implementing a chatbot starts with a robust knowledge of your customers’ (or prospects’) needs.

Once you know the ‘why’, you’ll be able to decide whether a rule-based or AI chatbot is best suited to the scenario. If it’s the former, you’ll need a conversation flow with a set of keywords for the bot to respond to. The conversation won’t be as natural as with AI, but a rule-based bot can still be effective for quickly answering high-volume queries.

If you opt for an AI chatbot, you’ll need to feed it with customer ‘intents. An intent is the reason why the end user is starting the conversation. A customer intent can be as big as needing troubleshooting help, or as small as saying goodbye. For each intent, the chatbot needs training phrases to help it recognize what your customer wants. Your provider should do the heavy lifting here and deliver as many training phrases as you need (ideally around 400 for an NLP-driven bot) in all the languages you require.

Once the mechanics of your chatbot are established, you’ll want to test it to iron out any teething problems and ensure customers get a seamless experience. And the process doesn’t stop when your chatbots are out in the wild. You can keep an eye on performance through chatbot analytics: drilling down into conversations where intent was missed so you can add new intents, training phrases or keywords for continuous improvement.

If you’re ready to harness the power of chatbots, and make sure your business is one that welcomes customer interaction with open arms, take a look at how Answers can help you achieve all the above and more?

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