Wow, I typed a lot!
Introducing the chatbot trend turned out to require quite a hefty piece of content.
Ready to start from the beginning? Here we go.
Get the Guide: The Marketer's Quick Introduction to Chatbots.
What are chatbots?
A chatbot is a program that communicates with you.
It is a layer on top of, or a gateway to, a service. Sometimes it is powered by machine learning (the chatbot gets smarter the more you interact with it). Or, more commonly, it is driven using intelligent rules (i.e. if the person says this, respond with that).
The services a chatbot can deliver are diverse. Important life-saving health messages, to check the weather forecast or to purchase a new pair of shoes, and anything else in between.
The term chatbot is synonymous with text conversation but is growing quickly through voice communication… “Alexa, what time is it?” (other voice-chatbots are available!)
The chatbot can talk to you through different channels; such as Facebook Messenger, Siri, WeChat, Telegram, SMS, Slack, Skype and many others.
Consumers spend lots of time using messaging applications (more than they spend on social media). Therefore, messaging applications are currently the most popular way companies deliver chatbot experiences to consumers.
Here is a video example of a Facebook Messenger chatbot, from David Marcus, VP Messaging at Facebook (starts around 7m19s).
Aside from buying shoes, here are a few more examples of companies using chatbots:
- Uber to book a taxi
- KLM to deliver flight information
- CNN to keep you up-to-date with news content
- TechCrunch to keep you up-to-date with techie content
- Pizza Hut to help you order a pizza
- Sephora to provide beauty tips and a shopping experience
- Bank of America to connect customers and their finances
The possibilities are (almost) limitless.
So, from where did chatbots come?
The history of chatbots
(For more illustrated content, get the Marketer's Quick Introduction to Chatbots.)
It would not be fair to talk about the history of chatbots without mentioning Alan Turing and Joseph Weizenbaum. These men imagined computers talking like humans and, in 1950, had the foresight to develop a test to see if a person could distinguish human from machine: the Turing Test.
In 1966 a computer program called ELIZA was invented by Weizenbaum. It imitated the language of a psychotherapist from only 200 lines of code. You can still talk with it here: Eliza.
The first move away from text chatbots occurred in 1988 when Rollo Carpenter started the Jabberwacky project – a voice operated entertainment AI chatbot.
In the year 2000, Robert Hoffer from ActiveBuddy Inc. co-created the SmarterChild chatbot that used AOL Instant Messenger and MSN Messenger to build a relationship with over 30 million users. The chatbot provided access to news, weather, movie times and acted as a personal assistant using natural language comprehension.
Microsoft Research has spent decades working on Natural Language Processing (NLP) to develop their XiaoIce chatbot. With millions of followers in China, the chatbot can discern topic, sentiment and more through back and forth conversation with its users.
Recent developments in technology have given chatbots more power in interpreting natural language and machine learning, to both understand better, and learn over time.
Huge companies like Facebook, Apple, Google and Microsoft are contributing significant resources to deliver interactions between consumers and machines with commercially-viable business models.
You can see an overview of the history of chatbots in this infographic from futurism.com
How do chatbots work?
There are broadly two variants of chatbots.
One follows a set of rules, flows, and triggers to respond to very specific commands. A simple example might be a chatbot that tells you the weather forecast for a location. A user might ask “weather forecast London” and the chatbot would find the answer and respond. This type of chatbot is only as smart as the developers who created it and thought of every eventuality of conversation.
The other variant uses machine learning to try to understand the sentiment and meaning of the language used, to not rely on pre-planned commands. A user might ask “what’s been happening in London lately?” and the chatbot might deliver the latest BBC News headlines for London. This type of chatbot learns from all the conversations it has had to improve accuracy and understanding over time.
Download the Marketer's Quick Introduction to Chatbots guide.
The use of natural, everyday language in their responses creates the illusion that chatbots are simple creatures, but that could not be more wrong.
The complicated algorithms, analytics, optimisations, APIs, routeing, UX and everything behind the scenes is a direct result of the hard work by thousands of individuals involved in computer programming for the last 50 years.
Why is now the time of the chatbot?
In early 2015, people started using messaging applications more than they use social networks.
This is a significant shift and a huge turning point in how consumers consume information. Up until 2015, to market a business online, you would use social networks – as this is where your consumers were. Now, there is a better place to concentrate resources (Tweet this).
Businesses that seize opportunity are the ones that follow consumers the fastest.
Think back to 5 or so year ago.
“There’s an app for that” – said everyone.
Now it is probably too late for a business to create an app, similar functionality can probably be better delivered elsewhere. I certainly do not think any sane person would form an app-building startup.
It is not just consumer trends.
Another contributing factor is the commercial opportunity, and therefore, interest from large (wealthy) companies. The platforms that enable the delivery of chatbot experiences are opening up to larger audiences and more innovative ways of creating an ROI and user interaction are being rapidly developed.
It is the culmination of the consumer behaviour (moving to messaging apps) and the technology being ready, along with a greater cultural shift in consumer behaviour.
People have been using messaging apps (and SMS) to talk with friends and family for long enough to feel confident in using the same practices to communicate with a business. This coincides with businesses now having the tools and technology to effectively communicate through the apps in a way consumers require.
The potential of chatbots
The near-future potential is quite apparent. No longer will consumers have to trawl through websites and search engines to find the information they need. Instead, they will be communicating with intelligent chatbots at every stage.
You – “Where is a good place to get coffee near me?
Search Chatbot – “There are three coffee shops near you rated five stars on xxx website”.
You – “Add the highest rated coffee shop chatbot to this chat”.
Coffee Chatbot – “Hello, this is xxx bot, what’s up?”
You – “Send directions to your shop and order a flat white”
Coffee Chatbot – “No problem, directions are in your xxx map, do you want to pay using your xxx wallet?
You – “Yes”
Coffee Chatbot – “Ok, 3.99 has been paid, see you in 12 minutes. We have some delicious muffins just out of the oven too…”
PA Chatbot – “Hi, I noticed you are going for coffee, it looks like it is raining outside, want me to order you a taxi rather than walk?”
You – “Yes, leaving in 2 minutes”
PA Chatbot – “Ok, your driver is called Sammy and the car registration is xxx, he will meet you outside.”
This type of chatbot interaction will be commonplace very soon.
Despite how impressive that sounds, it is done with technology that is still new. Communicating with chatbots will not just stop at businesses and brands.
Soon we will be using chatbots to communicate with other machines and connected devices. The internet of things (IoT) will connect everything to everything else. This is already happening with Amazon Echo and Google products.
Your PA chatbot will be connected to your fridge and will notify you that your wife used up all the milk, and you should get more on the way home from work, or offer to order it on Amazon for you.
Alternatively, perhaps your PA chatbot noticed it is raining, opened the garage door and had your autonomous car drive around the front to save you getting wet.
Chatbots, with the natural language and machine learning behind them, will lower our dependence on screens to receive feedback from a machine. Children of the very near future will joke about how we had screens on our phones and couldn’t just talk to the machines we use.
Chatbot technology will adapt to us, and creating personal chatbots will be as easy as changing the settings on your Facebook account, or adding an inbox filter to your email. It will know your surroundings, your personal history, your culture and language. It will become useful in ways we cannot yet comprehend or imagine.
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