Customer Service Innovation — How Chatbots are Evolving


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Image by Unsplash
Image by Unsplash

A year ago we’ve written an article about leading bot solutions in the market place, as we went to update and looked through the top bot solution of 2016 it became clear we had to address the changes in the chatbot echo system, next wee we will follow up with the update on the bots solution to follow.

One of the biggest changes happening in customer service right now is in automating the customer experience. Whether it’s onboarding, purchase, fulfillment, or after sales support, there’s an increasing drive to automate as much of the process as possible. Now that so much of the customer experience is self-service, businesses need to make every part of a customer’s interaction fast, easy, and intuitive.

Enter the bots. These automated software agents guide consumers through every aspect of their customer experience. They’re learning to chat and respond like a customer service agent, using a variety of techniques. They can read, see, hear, and interact relying on NLP, computer vision and voice recognition, laying the groundwork for future, autonomous, intelligent customer service machines. These bots will be able to answer questions, provide support, and ultimately get a customer the results they need, quickly and easily.

Chatbots are currently going through the hype cycle of being “the next big thing” with mixed results. They are settling into their natural position in the tech landscape as a dominant, AI driven interface for enterprise customer communication and relationship management.

Developing Customer Service Chatbots is Getting Easier

The pace of chatbot development over the last couple of years has been extremely rapid — it’s a sign of their importance and relevance. It’s also an indication of what we will experience in the next decade as AI driven bots will accelerate their learning capabilities and their share in customer service.

Initially, creating a customer service bot was a complex, difficult experience. You would have to hire cutting-edge developers who had a deep understanding of language parsing, artificial intelligence, and customer interfaces. That’s changing.

Although some companies are still creating bespoke solutions, there is an influx of software businesses now offering premade, customizable bot solutions. These allow anyone to build their own chatbots.

Two types of solutions dominate the current market place:

  • Bot Frameworks — developer tools that accelerate the process of coding a chatbot.
  • Bot Platforms — these enable the development of bots with no coding experience.

For example, Chatfuel lets anyone build a chatbot in just ten minutes, with absolutely no coding experience. For developers with a little more time, the Microsoft Bot Framework provides extensive teaching on how to develop best-in-class bots. ChatScript, Pandorabots, and Botsify all let you create chatbots depending on your level of coding and customer service needs.

The process of creating chatbots is becoming more open and democratic — the great question is, what will the results of these experiments be? How human will they sound, how smart will they be, and what will they be capable of?

Most importantly how will consumer respond to them? Will consumers ever say we’d rather speak to a bot than a human?

Bots still a major target for tech giants

Even with this shift to demystify bots creation, leading technology companies like IBM and Facebook are still making major investments in the space wether creating bot platforms or developing their own consumer-facing, intelligent solutions. IBM’s “Watson” service enables businesses to experiment with Watson’s powerful algorithms and language parsing to develop optimized chatbot solutions. Facebook on the other hand is leading the way to the next level of chatbots with its own digital bot butler “M”.

Chatbots are Maturing

The way that we use chatbots, and the methods they use to respond to us, are changing. Initially, chatbots would parse language and provide a predetermined response to a question, based on an internal script. This is a fairly sophisticated process, but the applications are limited.

Deep learning and artificial intelligence algorithms mean that bots are able to learn from every interaction, and incorporate that feedback so they are continually improving. This lets us have richer interactions with these bots, that they then use to enhance their conversational responses further. This cycle of continual improvement means that bots are refining themselves over time, getting more effective the more they are used.

This can have major benefits for end users. For example, the virtual assistants like Amazon’s Alexa, Google Assistant, and Apple’s Siri. For example, Google Assistant can distinguish between users, understand the context of what it is being asked, and provide appropriate responses. Chatbots can also integrate with other applications, so it could understand when you were at work and change what you could do accordingly.

Another important task when it comes to helping customer service agents is data management. With multichannel service challenges and the Internet of Things, the amount of consumer data available to organizations is increasing exponentially — sifting through all of this information is very challenging.

One of the primary challenges for bots and AI is the ability to analyze this data quickly, learn from it, and translate it into relevant insights for consumers and customer service agents.

How will the Chatbot Marketplace Evolve?

Chatbots are here to stay. Business Insider says that 80% of companies will be using chatbots by 2020. Gartner says that chatbots are “entering the market rapidly” with businesses incorporating bots into customer service across desktop, phone, and mobile experiences.

Chatbots have so far corresponded with the earlier stages of the Gartner Hype Cycle. They went through the peak of expectations, the trough of disillusionments, and are slowly heading towards enlightenment and productivity.

The truth is that bots are slowly proving to be useful tools. The Facebook bot count hit 100,000 in April 2017 only a year after the initial Facebook bot announcement.

With so much human effort invested in the field and the accelerated evolution multiplied through the machine’s deep learning capabilities we’re sure to see big leaps in chatbot capabilities and capacity over the next few years. As they’re developed further, chatbots will be able to deal with more complex questions and situations.

In the journey towards mainstream adoption bots need to pass two primary tests:

  • Appealing to consumers.
  • Delivering clear ROI to businesses.

The statistics below show that bots are well on their way to accomplish these two tasks, and that it may happen faster than we think. (source):

  • 27% of consumers worldwide are very interested in artificial intelligence based tools.
  • 48% of consumers would rather connect with a company via live chat than any other mean of contact.
  • 40% of consumers do not care whether a chatbot or a real human helps them, as long as they are getting the help they need.
  • 21% of consumers see chatbots as the easiest way to contact a business.
  • 47% of consumers would buy items from a chatbot.
  • 45.8% of consumers would rather communicate with a business through a messaging app than email.
  • Chatbots could save businesses up to £6 billion per year across industries.
  • In 2016, the chatbot market was valued at $703 million. From now to 2021, the chatbot market is expected to grow by 35% a year.
  • By 2020, over 80% of businesses are expected to have some sort of chatbot automation implemented.

As you can see, organizations and consumers are embracing the chatbot. As it evolves, it will become a dominant way for consumers to interact with businesses, and for those businesses to provide the information, services, and support consumers need.

Hagai Shaham
Customer Service Marketing and Content Expert.background in film making script writing and more.


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