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Make sure to fit the tone to the task at hand, as well as the brand your bot is representing.
Brands need to identify a place where a conversational UI can provide real value to users, and that may be within the confines of an app or website, and it may be outside of them.
Our job as an Experience Designer would be to predict the rate of change then anticipate the behaviour of user and how it might changewith the introduction of new revolutions (machines, voice interaction systems, conversational bots, BCI etc.) And, therefore, create groundbreaking products.
“Use” Users For UX
“Buy” Customers For CX or ServiceDesign For Customer eXperience or Service experience
Design For User eXperience or (Interactive) product experience
“Use” Users For UX
“Buy” Customers For CX or Service
“Talk” Player For PX(Playful eXperience)(Saying/Typing and Respond)
Design For Customer eXperience or Service experience
Design For User eXperience or (Interactive) product experience
Design For Player’s Playful eXperience(embodied (interactive) product experience and service experience)
“Use” Users For UX
“Buy” Customers For CX or Service
“Talk” Player For PX(Playful eXperience)(Saying/Typing and Respond)
“He has a magic lamp with a genie inside, who grants wishes.”
Design For Player’s Playful eXperience(embodied (interactive) product experience and service experience)
Design For Customer eXperience or Service experience
Design For User eXperience or (Interactive) product experience
“Talk” Player(Saying/Typing and Respond)
“He has a magic lamp with a genie inside, who grants wishes.”
For PX(Playful eXperience)
• Creating a magic lamp with a genie(Craft a Personality); Creating a genie-like UX
• Personalized god in a box; Era of IPA(Intelligent Personal assistant)
How broad is the understanding?Can the chatbot find any type of music studio and also any location in the world? Or just music studios in the United States? Or only music studios in Los Angeles?
How deep is the knowledge?Will the chatbot know of every music studio that’s on Studiotime? Or just the Top Line music studios? Will it share high quality photos of the studio if someone wants to see more photos?
Avoid nagging users with unhelpful or irrelevant messages
• Version 1.0* Every time a user typed “Dear . . . ,” Clippy would dutifully
propose, “I see you are writing a letter. Would you like some help?”—no matter how many times the user had rejected this offer in the past.
Clippy would give unhelpful answers to questions, and when the user rephrased the question, Clippy would give the same unhelpful answers again.Image source: http://bit.ly/1PDos4G
Scapegoating(Create a scapegoat; 죄를 뒤집어씌우는 전략) (1/2)
• Strategy* Social science literature to find simple tactics that unpopular
people use to make friends.
Without any fundamental change in the software, the right social strategy rescued Clippy from the list of Most Hated Software of All Time; creating a scapegoat bonded Clippy and the user against a common enemy.
Scapegoating(Create a scapegoat; 죄를 뒤집어씌우는 전략) (2/2)
• Version 2.0* After Clippy made a suggestion or answered a question, he
would ask, “Was that helpful?” and then present buttons for “yes” and “no.” If the user clicked “no,” Clippy would say, “That gets me really angry! Let’s tell Microsoft how bad their help system is.”
He would then pop up an e-mail to be sent to “Manager, Microsoft Support,” with the subject, “Your help system needs work!” After giving the user a couple of minutes to type a complaint, Clippy would say, “C’mon! You can be tougher than that. Let ’em have it!”
• 아내의 속도에 맞게 대화를!Our A.I. can type a thousand words per minute, but that’s not what people want from a
chat interface.
• 아내의 호흡(사용자의 특성)에 맞게 탄력적으로(학습을 통해) 대화를!We intentionally pace how fast a user receives our messages to make the experience feel
more natural; Pace messages at human reading speed. If your bot blurts out too much text instantaneously, this can be jarring for users to keep up with.
We’ve tested a lot of different levels of speed and found that adding a .02 second delayhelps with engagement.
We hope to create a feature that will analyze the way a user interacts with our system and adjust the pacing for each individual, and we already have enough data to appropriately adjust the pace by age.
• Engagement drops with every line of text over three lines, which we call the “glanceable tipping point.”
They need to be invested in the answer they are about to receive. If they ask for advice from a local doctor who accepts their insurance, they will take the time to read a long message because the information matters to them. We’ve also noticed that users don’t like receiving too many messages in a row without a break.
• We’ve now added a user input option after 4-5 messages to break up the text and give the user a few seconds to catch their breath. Even a simple response like “OK” or “cool” works to pace the influx of texts.
• Humans expect computers to act as though they were people and get annoyed when technology fails to respond in socially appropriate ways.(컴퓨터가 사람처럼행동하길 기대하고, 기술이 인간적인 방식으로 반응하지 않는 것에 불만을 가짐)
Show that people treat computers as if they were real people(컴퓨터와 미디어를사람처럼 대하는 사람들의 성향 관련 연구) Nass, C., and Brave, S. B. (2005). Wired for speech: How voice activates and
enhances the human computer relationship. Cambridge, MA: MIT Press. Reeves, B., and Nass, C. (1996). The media equation: How people treat
computers, television, and new media like real people and places. New York: Cambridge University Press.
• This is a reproduction of one of the most famous of the Tiffany stained-glass pieces—the colors are absolutely sensational! This first-class, handmade copper-foiled stained-glass shade is over six and one-half inches in diameter and over five inches tall. I am sure that this gorgeous lamp will accent any environment and bring a classic touch of the past to a stylish present. It is guaranteed to be in excellent condition! I very highly recommend it.
• This is a reproduction of a Tiffany stained-glass piece. The colors are quite rich. The handmade copper-foiled stained-glass shade is about six and one-half inches in diameter and five inches tall.
• You should definitely select option A instead of option B. There are at least six reasons why this is the right option. I am 90 percent confident of this assessment.
• Perhaps you should select option A instead of option B? It seems like there are reasons why this might be the right choice. I am 40 percent confident of this assessment.
• Similarity-attraction affects people to such a degree that they feel positive toward not only similar people but also anything associated with those similar people. For example, in the experiment, not only did participants like the sellers who were similar to themselves, they also felt more positive about the items associated with the similar sellers.(유사성-매력 효과는 긍정적 감정 뿐만 아니라 유대감 유발. 심지어성격이 비슷한 판매자가 경매에 올린 제품까지 선호)
• 외향성 음성과 내향성 음성 동일 적용; 음량, 음역, 음성 속도; 성격과 음성의 일관성중요하게 판단함
• When the introduction to a computer-based “Entertainment Guide” matched users’ personalities, users found the recommended music to be significantly better, even though the recommendations themselves were identical.(동일 음악을 추천하여도서비스 도입부가 자신의 성격에 부합하면 선호 발생)
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* Source: Clifford Nass & Corina Yen, 2010
Reference: Dormehl, Luke (2014-04-03). The Formula: How Algorithms Solve all our Problems … and Create More. Ebury Publishing.
Quantified Self movementSelf-knowledge through numbers
(숫자를 통한 자기 이해)
Based upon speech patterns, the particular words they used, and even details as seemingly trivial as whether they said “um” or “err” – and then utilise these insights to put them through to the agent best suited for dealing with their emotional needs?
(Chicago’s Mattersight Corporation does exactly that. Based on custom algorithms, Mattersight calls its business “predictive behavioral routing”.)
Quantified Self movementSelf-knowledge through numbers
(숫자를 통한 자기 이해)
Based upon speech patterns, the particular words they used, and even details as seemingly trivial as whether they said “um” or“err” – and then utilise these insights to put them through to the agent best suited for dealing with their emotional needs?(Chicago’s Mattersight Corporation does exactly that. Based on custom algorithms, Mattersight calls its business “predictive behavioral routing”.)
The man behind Mattersight’s behavioural models is a clinical psychologist named Dr Taibi Kahler. Kahler is the creator of a type of psychological behavioural profiling called Process Communication.
What Kahler noticed was that certain predictable signs precede particular incidents of distress, and that these distress signs are linked to specific speech patterns. These, in turn, led to him developing profiles on the six different personality types he saw recurring.
Reference: Dormehl, Luke (2014-04-03). The Formula: How Algorithms Solve all our Problems … and Create More. Ebury Publishing.
Quantified Self movementSelf-knowledge through numbers
(숫자를 통한 자기 이해)
Based upon speech patterns, the particular words they used, and even details as seemingly trivial as whether they said “um” or“err” – and then utilise these insights to put them through to the agent best suited for dealing with their emotional needs?(Chicago’s Mattersight Corporation does exactly that. Based on custom algorithms, Mattersight calls its business “predictive behavioral routing”.)
The man behind Mattersight’s behavioural models is a clinical psychologist named Dr Taibi Kahler. Kahler is the creator of a type of psychological behavioural profiling called Process Communication. What Kahler noticed was that certain predictable signs precede particular incidents of distress, and that these distress signs are linked to specific speech patterns. These, in turn, led to him developing profiles on the six different personality types he saw recurring.
A person patched through to an individual with a similar personality type to their own will have an average conversation length of five minutes, with a 92 percent problem-resolution rate. A caller paired up to a conflicting personality type, on the other hand, will see their call length double to ten minutes – while the problem-resolution rate tumbles to 47 percent.
Reference: Dormehl, Luke (2014-04-03). The Formula: How Algorithms Solve all our Problems … and Create More. Ebury Publishing.
Personality type Personality traits How common?
“Thinkers”Thinkers view the world through data. Their primary way of dealing with situations is based upon logical analysis of a situation. They have the potential to become humourless and controlling.
1 in 4 people
“Rebels”Rebels interact with the world based on reactions. They either love things orhate them. Many innovators come from this group. Under pressure they can be negative and blameful.
1 in 5 people
“Persisters”Persisters filter everything through their opinions. Everything is measured upagainst their world view. This describes the majority of politicians.
1 in 10 people
“Harmonisers”Harmonisers deal with everything in terms of emotions and relationships. Tight situations make this group overreactive.
3 in 10 people
“Promoters”Promoters view everything through action. These are the salesmen of the world, always looking to close a deal. They can be irrational and impulsive.
1 in 20 people
“Imaginers”Imaginers deal in unfocused thought and reflection. These people operate in vivid internal worlds and are likely to spot patterns where others cannot.
1 in 10 people
Dr Taibi Kahler’s the six different personality types
Reference: Dormehl, Luke (2014-04-03). The Formula: How Algorithms Solve all our Problems … and Create More. Ebury Publishing.
• I’ve even heard that comedy writers are becoming the next hot UX hires in the hopes of making copy more engaging.
• We often use humor to lighten up a situation and smooth over our mistakes. We might consider using this tactic when the bot encounters a limitation or needs to give
an error message.
• To succeed with humor, consider what type of personality your users would find engaging. Make sure to fit the tone to the task at hand, as well as the brand your bot is representing. For example, if you’re building a banking bot, avoid flippantly humorous error messages
when a user’s balance can’t be retrieved. This is a very important place to check in with our User Personas to get a feel for their
• We did learn to only use emojis in positive affirmation responses and to introduce them later in the onboarding process.
• We use templated responses for many interactions that the user inputs, and one thing we learned is that people don’t like being “forced” to send emojis back to a bot. Our responses tend to be fairly generic because people need to connect to the things we are allowing them to say.
• First impressions really do make or break an interaction, so we should consider our greeting carefully.
It’s often helpful to explain what our bot can do in the first interaction,
But it can be jarring for the user to get a huge chunk of text before exchanging a greeting.
Like it or not, your first-time users are essentially talking with a stranger, which in the range of enjoyable life activities ranks right up there with surprise dental emergencies.
They may grow to love your bot at some point, but in the first engagement, your bot is essentially the guy on the subway who just started asking them questions.
Natural Flow and Cadence: Don’t Be A Broken Record
You: What is your name?Mitsuku: My name is Mitsuku.
You: What is your name?Mitsuku: You just asked me that. It’s still Mitsuku. It hasn’t changed in the last 10
secs.
• Nobody likes being told the same thing over and over again, So why do chatbots keep doing it? Bots should detect when they’re about to repeat a
previously given answer and switch strategies.
As an egregious example, I ran into a bug with the 1–800-Flowers chatbot on Facebook Messenger. This chatbot presents categories and subcategories of bouquets you can choose from, but if you go into a subcategory card menu, the previous menus become deactivated and there’s no obvious way to go back to them. Pretty silly, eh?
• Our audience comes from a huge cross-section of society. We sell our product directly to employers of a highly educated workforce as well as to people who didn’t finish high school. We’ve found that, regardless of the audience, making your scripts as simple as possible results in the greatest level of engagement.
• You can use the Flesch-Kincaid Grade Level feature in Microsoft Word or an app like Hemingwayapp.com to figure out the present grade level of your scripts. I don’t think there is a hard and fast rule of what grade level you want to write to, but in general, the lower the better.
Typing "@uber from Penn Station to LaGuardia Airport" would order a car to pick you up to drop you at the airport.
Typing "@nest 73" and Prompt will turn up your heat if you have a Nest thermostat.
Typing "@flightstats AA21" would get you the status for American Airlines flight 21
Typing "@hue" will turn on and off your Philips Hue bulbs
Typing "@showtimes" will tell you what movies are playing near you, and so on.
• Just like the command line, though, Prompt's biggest barrier to entry is syntax.That's especially frustrating on smartphones, where on-screen keyboards and autocorrect can wreak havoc with Prompt's super-specific vocabulary.