As we closed 2016, we might say that 2016 was an excellent year that bots, A.I. systems and apps, human assistants have been growing rapidly. Since we’re following all the news on either VentureBeat’s bot channel, or Facebook Bots groups, a lot has changed. However, we wanted to discuss about how we started these technological developments in the first place. Why do people adapt to these A.I. related systems and chatbots? We would like to dig into the behavioral phases of these adaption.
Since we are on the analytics side of the story, our work is more about observing the people’s behaviors and prompting meaningful actions based on the facts of triggers, engagement, and habits. Wall Street Journal best selling author Nir Eyal has a lot to say about this breakthrough we’re experiencing. Let’s summarize what we extract some points from his articles that stand out nowadays.
What is the behavioral motivation to use chatbots now and will be in the future?
The motivation is so obvious that people use verbal and non-verbal communication since the beginning. As the technology is developing, we witness human nature stays constant, but it’s adjusting to what the technology brings. It’s same for bots and A.I. systems. They can talk to you in a voice or text, however they are still designed to have same psychological patterns connecting to the humans.
Nowadays, people are comfortable with the texting much more rather than voice, as we observe. The reason can be its convenience, of course. It’s really quick to send a message in a meeting than a voice recording. Thus, motivations of using chatbots are convenience through texts, and having their problems solved in an easy way.
When we look into what brought us to these days from Nir’s articles, he mentions:
”Of all the ways humans communicate, texting might be the most direct. Text carries less superfluous information than other ways of sending information. With text, there are no voice intonations to decipher or accents to understand, no facial gestures to interpret, and no body language to translate. Text is something computers can understand and process quickly and it’s why messaging is a great place for humans and A.I. to work together to serve customer needs.”
The future will not be different, though. Behavioral motivation will stay as people want to solve their problems in quick and easy way.
Nir points out in one of his articles: ”The power of the conversational interface is that it shields the end user from having to learn anything new. We already know how to chat, so making requests is easy. An assistant-as-app leverages well-trained humans to use complex technology behind the scenes. The assistant can process requests that would otherwise require several steps, time-consuming analysis, or pro tools the layperson is unlikely to have the knowledge or patience to use.”
When we think about habits and triggers, how do you think bot makers can increase the engagement of their bots?
In order to specify this topic, we shall say that triggers and habits are psychological concepts we need to explain their meanings first. Triggers for the users can be loneliness, eagerness, satisfaction, uncertainty, or curiosity. Also habits comes from the repeating actions from the mental experiences. It’s about the feelings in the end. Therefore, bot makers or A.I. system designers should think where the feelings should be put into the system and extract data from the people’s behaviors. Observation and empathy are the most needed skills for designing the system of the bot, basically. Furthermore, after designing the system, increasing the engagement lies within the feelings and behaviors, too. Why do people even feel positive about a system? The answer should be written down in big fonts in front of the desk.
According to that, bot makers can increase the engagement of their bots or A.I. systems by thinking the back end so well based on the psychological effects, thus people who use their products do not even suspect about the the rest. No one would love the idea of getting betrayed or getting annoyed. Everyone would want to trust and enjoy the moment.
In one of Nir’s articles, he mentions:
”If communicating with CUIs is going to be as simple as talking to a good friend, we should design them as such. William Rawlins, a professor of Interpersonal Communication at Ohio University who studies friendship, says a friend has three qualities: they’re easy to talk to, enjoyable, and dependable. We form routines around turning to important people in our lives in the same way we build habits with our technologies.”
Increasing engagement is similar to meeting a new person and getting him/her into your life and getting to know better and trusting him/her slowly. If we think chatbots in this way, we can say that bots should be considered as friends while increasing engagement, such as caring like a friend, listening to their problem like a friend, or helping out him/her as a friend does.
”The future of enterprise software won’t be about complicated dashboards and mind-numbing amounts of big data; it will be about well-designed interfaces that make work a pleasure. Software should be like a good friend—ask and ye shall receive.”
How do you think a bot can create a value or can it change the image of a brand in people’s mind?
By making people let bots into their lives! But how? We might say ”like a real person”. Nir gives a perfect example about it. Imagine two friends talking in a coffee shop. He mentions: ”If the other party wants to talk about something else, it would be rude to stubbornly insist on only talking about one thing. However, that’s exactly what today’s software does.” This is not creating a value in people’s mind. Creating a value means creating something for the user which he/she cannot give up on. Think Facebook, Instagram, Whatsapp. They’re connecting us to the loved ones or things. These habit-forming technologies create a big value for their users, so people have positive images about these brands. Brands which create values for their customers win in the end.
”A conversational interface however, can do something no ordinary dashboard can do; it listens and learns. By noting the user’s response to the discrete piece of information presented, the software remembers whether the insight was valuable. If the user continues the conversation about this information, the system learns the importance and raises similar concerns in the future. But if they don’t write back, great, that’s one less notification the app needs to send and one fewer interruption to the user’s day.”
Nir Eyal
This is a perfect graph of value and usage by Nir Eyal
Lastly, how should bot makers design their bots considering human psychology?
Human psychology is a complex thing to talk about for many centuries. However, there are some tricks that bot makers can think of while designing a conversational user interface. Bot and A.I. system designers can hack the human nature by some situations or feelings. Nir Eyal gives mostly needed situations for designing a system to consider.
”-An assistant-as-app works best in certain situations:
When a user wants to accomplish a singular goal but has too many options.
A user does not enjoy browsing through the options.
Data entry is easy but processing and analysis is hard.
The traditional screen interface is too complicated or small.
A trusted relationship helps.
A request does not have to be completed immediately.”
All these are common people behaviors that mostly everyone tend to do. Do not forget to use empathy and research for your personas while designing and mind-mapping your conversational user interfaces.
”By designing services that are enjoyable, dependable, and easy to talk to, companies can build products that feel familiar even when we are using them for the first time.” Nir Eyal
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