UX Movement » Thinking http://uxmovement.com User Experience Movement Sun, 14 Jan 2018 02:59:05 +0000 en-US hourly 1 http://wordpress.org/?v=4.2.19 How Chatbots Can Help Your Users Without You Therehttp://uxmovement.com/thinking/how-chatbots-can-help-your-users-without-you-there/ http://uxmovement.com/thinking/how-chatbots-can-help-your-users-without-you-there/#comments Tue, 20 Dec 2016 13:25:53 +0000 http://uxmovement.com/?p=10051

2016 was the year of the Chatbot. Microsoft, Facebook, and Google have all released chatbots, demonstrating the importance of artificial intelligence on the web.

What is a chatbot and what can you use it for? “A chatbot is a service powered by rules that a user interacts with using a chat interface. The service can be any number of things, ranging from form to function and live in any major chat product” (Matt Schlicht, Chatbot Magazine).

Practical Uses for Chatbots


Scheduling a week can be one of the biggest pains for the planner-type of users. A chatbot coordinating with another person or bot can automate the calendar system. After coordination, the bot can send the user a plan of their week. Users can also block out busy times so chatbots can schedule around these timeframes.

An example of a scheduler is Meekan. Meekan can schedule lunches, check calendars, book conference rooms, or find flights. In Slack and on screen, Meekan seems like an ideal digital assistant.



Chatbots can simplify the introduction of a new user to an app or website. Chatbots provide a quicker response and better user experience by being “there”. Because the bot lives in the app, it can respond immediately without requiring a user to pick up a phone. This allows businesses to operate without requiring 24/7 customer support for onboarding.


Dolores Landingham is an employee onboarding bot in Slack for 18F. The bot was named after the West Wing character and is adapted to support users in different time zones. Users can subscribe to “benefits” or “legalstuff” and will not be flooded with excess information. With Dolores, employees no longer need hours of in-person training or mountains of paperwork when starting a new job.

Connecting users to websites

Because Chatbots live in a platform, they can track users’ behavior patterns. Chatbots may suggest potential partner websites or social networks as recommendations. As a recommendation source, chatbots make it easier for people to find similar sites.


Blair, a Singaporean voice-integrated chatbot, was designed on the Facebook Messenger platform as a restaurant recommender and booker. Blair is a personalized OpenTable and has potential to partner with wine bars, dessert parlors, or other hospitality services.


Advertising benefits from the rise of chatbots. Chatbots can identify users’ shopping patterns. From these behaviors, chatbots can suggest items the user may enjoy in the platform. The chatbot can even act as the user’s personal shopper.


Spring, a shopping startup, currently has a customer service bot that responds to users’ requests 24/7. The bot allows users to buy, save, or ask questions about items it recommends from brands that the user follows.


When trying to achieve a new goal, people like to be accountable or may never end up achieving the goal. Often, friends hold each other accountable for goals. Sometimes a person may find a goal embarrassing or want to keep their intentions private.

A chatbot can motivate by using personalized, conversational notifications to the user. The user can also set up reminders in intervals of user preference. The chatbot is always there for the user because it is personalized to the user and engages the user with personality.


I tested Opal, a motivational bot prototype on BOTTR. Opal has prepared responses I could click on, which she responded to. If I chatted saying that I was down, Opal would respond with a positive message. However, Opal was 1-dimensional and unable to motivate me to work out. Opal could motivate in terms of positivity, but not goals.

Chatbot Experience Essentials

Personalization Unpredictability

If bots are not personalized to the user, a usability problem arises. Chatbots should address the user –“Hey, Amelia!” and instead of asking generic questions, provide information the user wants to know. The bot should be able to respond to customized questions and responses.

MIT’s chatbot, Eliza first demonstrated this attention problem back in 1964. Eliza played a psychotherapist by asking standard questions and rephrasing answers as questions. If the user decided to be unpredictable and “go off script”, Eliza would break.


Eliza’s problem is still prevalent today. Opal the motivational bot was only able to respond to prepared responses. The bot could not handle unpredictability and broke when I asked a 2-dimensional question about motivation. The bot could only handle happiness quotient. It could not understand both happiness and goal setting.

Current bots’ increased personalization are creating better user experiences. Blair is able to suggest restaurants and book dinner for users. In the future, Blair will be able to book other hospitality and service partnerships and anticipate users’ wants. Similarly, Spring can anticipate shoppers’ likes and become each user’s personal digital shopper.

Bots can also help with professional goals. Because Dolores Landingham is personalized to an employee, the bot can guide the employee in HR and paperwork questions. In the future, Dolores can automate timesheets, checking in, benefits, and other “busy paperwork” to save time and increase employee productivity.

Solution: Personalize with Conversation

To personalize a chatbot, conversational design is essential. Designing conversation responses involves intention and figuring out linguistic patterns, tone, and interactions. Examples of conversational design include drafting scripts or language mapping.

chatbot_conversationWhat exactly is a language map? Language maps are conversations broken down by sentences and words. The most common type of language maps are Syntax Analysis. Syntax Analysis breaks up strings of words to determine syntactical relationships.

With syntax maps, the user can form different types of responses and meanings from a statement. If desired, the user can create multiple responses, duplicate the idea, scale to a broader meaning, or focus on a specific generalization.


For chatbot use, syntax maps are very helpful because they can allow users to predict responses and create alternatives for the bot to chat if the user goes off-script. Although hard to predict for user error, the chatbot has potential alternative response paths it can take and will not break.

Engagement Loss

Attention must be maintained from the beginning of the chatbot experience. Once the user’s attention is lost, the chatbot’s game is up. Engagement has to happen throughout the experience.

An example of engagement loss is Meekan. Meekan has to gain permission to a user’s calendar through a sign-up link. The sign-up link causes friction and takes the user out of Slack, into a separate page. Although I clicked the link, Meekan lost me after two or three clicks that did not allow me to give the bot permission. After testing out Meekan for 4 minutes, I gave up using it because I could not get past the permissions page.

Engagement loss also occured when I tested Opal. Once Opal was unable to answer my two-dimensional question, I stopped paying attention to the bot and exited BOTTR. The immediate response was, “Oh, Opal doesn’t work.”

Solution: Engage with Visuals

The chatbot has to be eye-catching, but not a real person. Designers must use visuals or conversation to communicate that a chatbot is a robot. When testing the CARL bot, I discovered that users liked the image of the bot as an illustration. Many users expressed their uncomfortable feelings of a bot with a human image.


Users automatically associate chatbots with people or users they know. Users create and impose an identity onto the chatbot. An IDEO study analyzed women’s responses to a “coach” chatbot. Female users projected a pushy, male coach identity onto the chatbot. The “coach” was actually a female human controlling the bot. Even without intention, people humanize bots to connect bots with what is familiar.

Future Potentials

Chatbots have the potential to create better user experiences. They are quick, responsive, and always available. Currently, chatbots play the role of digital assistants. No longer do people need a provider to find house cleaners, laundry cleaners, or physical assistant to schedule appointments.

As technology further develops, chatbots can provide an increasingly personalized level of service and remove the in-person assistants’ roles completely to make users’ lives easier at no price. Further chatbot potentials may include more voice integration, personalization, and memory storage to address a user’s current needs.

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How to Turn User Research into Usable Datahttp://uxmovement.com/thinking/how-to-turn-user-research-into-usable-data/ http://uxmovement.com/thinking/how-to-turn-user-research-into-usable-data/#comments Tue, 24 May 2016 14:15:27 +0000 http://uxmovement.com/?p=9447

Why do some sites captivate us in ways others can’t? The technology used to develop a site plays a role in the experience, but it takes a back seat to content and design.

The content is what keeps users coming back. But it’s the design that’ll capture their attention from the get-go. User research is a critical component of the design process. Without it, you’re just shooting in the dark.

Choosing a User Research Method

Before you can collect data and implement it into your designs, you need to decide how you’ll be collecting the data.

Codal’s ideal user research process includes surveys, interviews, personas, onsite observations, and usability testing. A healthy cocktail of techniques that’ll give you insight into the needs, gripes, and opinions of real users.


Surveys are the first logical step when conducting user research. They allow you to establish a ‘baseline of insight’ by asking the average user the most basic questions.

They’re especially beneficial when trying to reach a broad audience while gathering quantitative data. Surveys generally come at the beginning, when lots of basic information is helpful.


Surveys need to have clearly defined goals in order for them to have the greatest effect. They’re used to validate ideas and assumptions, or even confirm data from other findings.

You can distribute your survey via social media, websites (as a link), or by paying for responses. At Codal, we use a healthy combination of all three. For many of our clients, we place a link to a survey on their current website, as well as in their newsletter.


Interviews offer more focus to the problem you’re trying to solve. Unlike surveys, interviews allow you to ask follow-up questions. If you have questions after users complete a survey, they will often go unanswered.

Interviews can be structured however the researcher sees fit. Just make sure you leave enough time for follow-up questions to add context. The hardest part is actually finding people to interview.

Interviewees can be found by reaching out to existing customers. They’ll be more likely to respond because the future of their experience is affected by these interviews.


Another strategy is to request that users include their contact information on the surveys you send out. This way you can reach out to them for an interview.

Alternatively, you could use what we like to call “guerrilla” tactics. Guerrilla interviews are where you go to a public location and ask friendly strangers to talk to you. You should only use guerilla interviews when you cannot get enough interviews with your ideal user candidates.

Keep in mind that you cannot conduct this type of interview in a random location. We like to conduct guerilla interviews in locations that have plenty of relevant users such as startup incubators. Make sure that you have a wide variety of demographics, experiences, and prior knowledge in your group.

Contextual Inquiry

You have the option of contextual inquiry where you make observations in the natural environment of the user. This could be as simple as going to an on-site location and seeing how users do things.

This can be a difficult type of research to perform because you have to be in someone’s way while they’re doing something. But it can also give you valuable data because you’re observing natural user behavior.


Contextual inquiries give you the best sense of a user’s real choices and actions in a given context. For example, rather than assuming users will prefer a certain layout, you can observe and document their choices in a real scenario.

This presents a huge advantage over surveys and interviews, as you are not forced to trust what the interviewee has said on the matter.

Usability Testing

Usability testing is the process by which researchers devise tasks and scenarios for users to complete. How they go about completing the task is the focus of analysis. You can do this at any stage of the process on high/low fidelity wireframes, UI mockups, even on a pencil-and-paper sketch.


For example: “find a toy for a ten-year-old girl who is into Disney”, or “use this app to find the highest rated Chinese restaurants within a mile of your location”.

Usability testing provides two important pieces of data:

  1. Was the task completed successfully?
  2. Did the user go about the task in the way that you intended?

The latter is an important metric because it tells you whether your interpretation of surveys match the path a user will take. In essence, usability testing serves as an assumption validation technique.

The answers to the above questions will either validate your assumptions or contradict them. Should a set of usability tests contradict your research or designs, you know that you need take a step back and make changes.

From Raw Data to Usable Data

As you conclude your research, your desk may be covered with post-it notes, documents, and usability test cases. This is the raw data. Raw data is good, but it’s useless until it’s compiled into a usable format.

The keyword here is usable. That means going beyond the act of compiling the things we see and drawing conclusions. So, how do we separate the things we see from the things we know? Analysis and Synthesis.

Analysis refers to the act of defining and categorizing the data you’ve gathered. Ideally, you should conduct analysis in conjunction with synthesis.

Synthesis refers to the act of taking data a step further by generating insights that you can use to predict the needs of your target user.

The result of your analysis and synthesis need to be communicated to your team in a usable way. This is where user personas, user journeys, and affinity maps come into play.

User Personas

User personas are a tool that depicts the goals, frustrations of fictitious but representative users.

Professional opinion on personas varies. There are two schools of thought: for, and against. Some people would argue that personas are not a valuable tool because they’re not technically real users.

Personas are only valuable if they are a true representation of your data. Therefore, they should come in after all data has been collected, organized and synthesized.

Not every project will use personas because not every project needs them. The project dictates the process, not the other way around.


Any assumptions that you make about your users or customers can easily be invalid. If you are using those assumptions to build personas, you may completely misrepresent the needs of your audience. Once a design is implemented, the design team can ‘test’ it by pairing a scenario with a persona.

The real trick is actually using them during the design process. Keep your personas handy. Print them out and keep them nearby at all times.

For every design decision you make as a designer, refer to each of your personas. In the above example, Anita—and ask yourself how does this help Anita solve her problem? If it doesn’t help any of your targeted users, the feature is likely unnecessary.

User Journeys

Personas describe the average desires, frustrations, and motivations of a particular user type. But User Journeys describe common scenarios or tasks, and paths taken by users to fulfill them.


User Journeys can be used to achieve two different outcomes:

  1. Illustrate the current way of completing a task
  2. Illustrate a new preferred way of completing a task

This is useful not only as a point of reference during the design process but also when justifying design decisions to stakeholders.

As a designer, your intuition and research are far more likely to contribute to the design than the whims of the stakeholders. Unfortunately, stakeholders are ultimately the decision-makers. As such, the insight you provide them is critical if you want your design decisions to make it into the final product.

Much like user personas, user journeys are all about referencing hard and often. This means that user journeys are not intended for one-time use. Once you’ve made them, they become a permanent aspect of the design process.

That is, you have to refer to it all the time, and make as many or as little as makes sense. Each design decision has to fit into a particular part of the journey. If it doesn’t, then you didn’t make enough journeys for the decision you’re making.

Affinity Maps

Affinity mapping is the process of organizing ideas into common relationships. They are a great way to synthesize data that comes from contextual inquiries and surveys.


When you categorize data, patterns tend to emerge, even when you don’t expect them to. You can then use these patterns can to generate unique insights.

One of the most common mistakes is ignoring the need to reorganize their maps. Not all affinities are as deep as they appear. Sometimes you need to scrap your analysis and get new results.

The more themes you can identify and attribute to causal factors, the better your affinity maps will be. Sometimes it can take quite a few different reorganizations of the affinity map to find trends that make sense. Don’t be afraid to do this.

Usable Data Means Usable Design

Personas, user journeys, and affinity maps are strategic and goal-driven tools for designers. They allow them to focus on the user to make and defend their design decisions during the design process.

Spending time on research and analysis can help you measure the effectiveness of your design and ensure a better end product. Once you get a wealth of usable data, you can pass it on to the rest of the team.

The rest of the team can use the results from the analysis & synthesis phase to develop design guidelines and techniques. When they incorporate them into the design of the product, that’s when you know your work has paid off.

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Why Circular Profile Pictures Accentuate Faceshttp://uxmovement.com/thinking/why-circular-profile-pictures-accentuate-faces/ http://uxmovement.com/thinking/why-circular-profile-pictures-accentuate-faces/#comments Tue, 23 Feb 2016 15:57:18 +0000 http://uxmovement.com/?p=9032

What shape are your app’s profile pictures? Chances are they’re square. A square isn’t the best shape to use because it makes it hard to visually process faces. A circular profile picture works better because it accentuates faces.

Corner Brightness

One reason square profile pictures are harder to process is because of its sharp corners. Sharp corners make shapes appear brighter. This brightness can interfere with facial processing in profile pictures.

A circular profile picture would not have corner brightness because it has no corners. This allows users to view faces without visual noise.


Center Focus

Most faces are at the center of a profile picture. When looking at a face in a square profile picture, users will spend longer focusing on it. This is because the distance from the center of a square to each corner is longer than the distance to the sides. Users have to move their eyes along the diagonals to see everything.


When looking at a face in a circular profile picture, users can see everything by looking at the center. This is because the distance from the center of a circle to every edge is equidistant. Users will spend less time focusing on it because they don’t need to move their eyes around.

Background Area

The most important part of a profile picture is the face. The less background area there is, the more users can focus on the face. A square profile picture displays more background area than a circular one. A circular profile picture cuts the background area at the corners.


Non-Facial Pictures

A circular shape for profile pictures work well because it accentuates the face. But it isn’t as effective for non-facial pictures. The background of a non-facial picture may contain content users want to see. Cutting the corners off could also cut depth and detail.


Shaping the Experience

Circular profile pictures accentuate faces more than square ones. Accentuating faces helps users identify their peers easier and distinguish usernames from content. If a simple change can shape the user experience this way, it’s a change worth making.

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The Art of Questioning as a UX Skillhttp://uxmovement.com/thinking/the-art-of-questioning-as-a-ux-skill/ http://uxmovement.com/thinking/the-art-of-questioning-as-a-ux-skill/#comments Tue, 17 Feb 2015 13:56:08 +0000 http://uxmovement.com/?p=7683

When starting any design project, you need to ask a lot of questions. The perceived problem and actual problem may not be the same. So how can you get better at asking the right questions?

I decided to brush up on my questioning skills by reading A More Beautiful Question by Warren Berger. Berger illustrates how questioning is an inherent skill we’re quite adept at during childhood. He notes that children haven’t developed a “mental model” of the world, so they question everything. But as we go through standardized education, we begin to suppress our curiosity.


As adults, it’s frowned upon to ask too many questions in the workplace. On the flip side, we’re often embarrassed when we don’t have immediate answers. But Berger claims the ability to admit you don’t have all the answers, but can ask better questions, is a superior skillset.

By analyzing innovative figures, Berger identified three common types of questions that lead to breakthroughs.

3 Types of Questions


Why does something have to be the way it is? Has everybody else missed something obvious? Are we basing our understanding on assumptions? Asking ‘why’ questions is about challenging assumptions and the status quo. A famous example of a ‘why’ question is when Edwin Land’s son asked, “Why do we have to wait to see our pictures?” Land answered that question by creating the Polaroid instant camera.

What if…?

This is where you mash up ideas, go against common logic, or add/remove factors that make the challenge more interesting. Sky’s the limit here as each wild idea often yields a workable element. This thought process is sometimes referred to as “divergent thinking.” Thank the candy gods that one day H.B. Reese, inventor of Reese’s Peanut Butter Cups asked, “What if you put peanut butter and chocolate together?”


This is where the rubber meets the road. Propose solutions, create testable hypotheses, perform a bunch of tests to gain insight. This is typically the “prototyping” stage where you have to see what elements of your ideas are compatible with reality. A near legendary example of the rapid prototyping is the story of the Google Glass team creating a working though ugly prototype of Glass in just 45 minutes.

Questioning in the Context of UX Design

So now that you know the basic framework for asking better questions, what questions should you ask and what assumptions should you challenge? As a UX designer and strategist, I often encounter clients who are in need of better problem framing and deeper insight before embarking on a design project.

A better understanding of the problem inevitably yields better solutions. Here are three statements I often hear from clients that are great opportunities for reframing through questioning.

Ex. 1 – We already know what our customers are like so we don’t need research or user testing.

Put more simply, clients often assume that they are exactly like their customers. An easy technique to challenge this assumption is inverting the statement. “We know our customers want to do XYZ…” becomes “How do we know our customers want to do XYZ? Why are they coming here in the first place?” When you invert your assumption statements, you can start the “Why” portion of the framework and challenge existing paradigms. Your goal is to derive solutions from a solid knowledge of underlying factors. From my experience, the “Why” is least clear to most clients and the most overlooked.

Ex. 2 – We think our customers need an app and we just need to partner with you to design it.

Before starting with a predetermined solution, teams should explore and exhaust the “What if” scenarios first. By removing constraints, teams can break out of their current paradigm and discover a more effective direction than the initial one. The “What if” phase is usually scary for established companies. But scrappy startups who are apt to try things that fly in the face of conventional wisdom have popularized the buzzwords “innovation,” and “disruption.”

Ex. 3 – Now that we’ve figured out the problem, we need to write detailed requirements and spend 3 months to build a beta.

After you determine a workable solution in the “What if” stage, the mindset of a team tends to latch onto a single solution. But the result of the “What if” stage is only a hypothesis, which still needs to be tested before committing resources. In the “How” stage, the team needs to maintain flexibility while focusing on creating shareable prototypes. Prototypes should be relatively cheap to create and thrown out quickly. A mantra of the lean startup movement is “fail faster.” It’s better to find the holes in your plan before doubling down.

Questioning in Business Culture

While most modern enterprise companies use buzzwords like “out of the box thinking”, they seem to rather question averse. Instead, they’ve created a culture which rewards employees on measures of efficiency, while punishing those who ask too many questions.

Enterprise software design treats the Lean method more as a process than a mindset. It’s used to move a project from concept to creation, but not to iterate and discover. In a true spirit of Lean, a team needs to be ready to try many approaches and fail. A strong culture of questioning is essential to achieving innovative results.

UX and product designers must adopt a questioning mindset. Skilled questioning leads to better outcomes and paradigm changes within organizations. You may stir the pot a little bit, but you may also help shape a new direction and encourage others to move forward.

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How the Hermann Grid Illusion Affects What Users Seehttp://uxmovement.com/thinking/how-the-hermann-grid-illusion-affects-what-users-see/ http://uxmovement.com/thinking/how-the-hermann-grid-illusion-affects-what-users-see/#comments Tue, 10 Jun 2014 13:36:26 +0000 http://uxmovement.com/?p=6874

Imagine looking at a grid of images and gray ghostlike blobs appear on your screen. This isn’t a hallucination, it’s what users see when the hermann grid illusion takes effect. It occurs when a grid of images have equal margins of more than 2 pixels. Users will see gray ghostlike blobs at the intersections of the grid. But when they focus on the intersection, they won’t see anything.

At the intersections, white light floods most of the retina’s receptive field. This causes strong lateral inhibition which results in an area that appears gray. Looking directly at an intersection activates the fovea. It causes little lateral inhibition because it has the smallest receptive fields and the highest number of photoreceptor cells. [source]

Better Ways to Align Images in a Grid

It’s common for websites to align images in a grid with 10 pixel margins or more. But this creates the hermann grid illusion, which can annoy users when they’re scanning images. The gray blobs aren’t easy on the eyes, but here are a few ways you can make them disappear.

2 Pixel Margins

Aligning the images in a 2 pixel margin grid is one way to make the gray blobs disappear. Some other benefits are that it saves space and the margins become thin, subtle lines.

Ragged Margins

Another approach is to align images with different sized widths or heights together. This creates ragged margins that make the gray blobs disappear.

Larger Row Margins

Making the row margins larger than the column margins also make the gray blobs disappear. Doing this guides the user’s eyes to scan the images row by row.

Colored Background

Instead of changing the size of the margins, you could change the grid’s background color. Any colored background can make the gray blobs disappear.

Final Thoughts

It’s interesting how the human eye plays tricks on us. The hermann grid illusion deceives the user’s vision and distracts them from their task. But through proper image alignment you can decrease the visual noise. Image grids are a common layout choice for websites. Next time you decide to use one, remember what users could see.

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