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How to setup Usability Testing in Maze app

Before starting the preparation of Usability Testing setup in Maze app, make sure that you have prepared Clickable prototype in Invision, list of features/use cases to be tested, prepared scenarios and tasks descriptions and identified your targeted participants.

Steps to Setup Usability Testing in Maze App

Step 1 – Create clickable prototype in Invision and copy the public link.

Step 2 – Import your prototype in Maze by pasting the prototype public URL and add New project.

Step 3 – Create Missions (Imagine missions as tasks that end user will need to perform in Usability Testing). You can create a list of Usability Testing tasks for users and then define the success path/Optimal path. Make sure you provide proper clickable points in prototype and correct success page (where the task should get completed). The recommended Missions/tasks count is 5-7 per Usability Test Session per Person, but it always depends upon the task length as well. Do not overload participants with tasks, it may lead to mental fatigue and lead to errors/biases.

Step 4 – Once you have created all of your missions (tasks), now you have reached to a stage where you can make your testing (Maze) live. By clicking ‘Send Live’ button at top-right corner, your Maze will be ‘live’ and you may get Usability Testing URL.

Step 5 – Always try and explore the testing URL and test setup by yourself. For this just become a test participant and go through the test using testing URL. If you find any changes in flow or any errors, correct them before reaching to actual participants.

About Author,

Abhishek Jain
Lead UX Researcher

User Experience in Artificial Intelligence

Two years back, Toyota offered us a glimpse into their version of the future where surprisingly, driving is still fun. Concept-i is the star in the autonomous future where people are still driving. And in the case of Toyota, it's so much fun because they're cruising along with their buddy Yui, an AI personality that helps them navigate, communicate and even contributes in their discussions.

Yui is all over the car, controlling every function and even taking the wheel when required to. It's definitely an exciting future where the machine sounds and “feels” like a human, even exhibiting empathetic behaviour.

Related: Preparing for the Future of AI

That's the kind of future I'd imagine awaits user experience (UX) in the world of AI. A time when the human-AI connection is so deep that some experts say there will be “no interface.” But currently, UX does depend on an interface. It requires screens, for instance, and they don't do much justice to it. Integrating AI into the process will mean better experience all around.

From websites to homes and cars, here's how AI could help patch the holes and bring UX closer to maximum potential.

1. Complex data analysis.

Until now, to improve user engagement in their products, UX teams have turned to tools and metrics such as usability tests, A/B tests, heat maps and usage data. However, these methods are soon to be eclipsed by AI. It's not so much because AI can collect more data -- it's how much you can do with it.

Using AI, an ecommerce store can track user behaviour across various platforms to provide the owner with tips on how they can improve their purchasing experience, eventually leading to more sales. AI can be used to tailor the design to each user’s specifications, based on the analysis of the collected data.

All this is achieved through the application of deep learning that combines large data sets to make inferences. Additionally, these systems can learn from the data and adjust their behaviour accordingly, in real time. Thus, designers applying AI in their work are likely to create better UIs at a faster rate.

2. Deeper human connection.

By analysing the vast amount of data collected, AI systems can create a deeper connection with humans, enhancing their relationship. This is already happening in a couple of industries. When you think of Siri, you see a friendly-voiced (digital) personal assistant. When Amazon first introduced Alexa, it took the market by storm. But its usefulness could only be proven over time. And it was. Smart-home owners are using it to do a million things, including scouring the internet for recipes, schedule meetings and shop. It's also being used in ambulances. Even Netflix’s highly predictive algorithm is a case example of AI in use.

Toyota says Concept-i isn't just a car, but a partner. From the simulation video, you can see that Yui connects with the family on a level that current UX doesn't reach.

By using the function over and over, consumers end up establishing an interdependent relationship with the system. That's exactly how AI is designed to work. You use the system; it collects data; it uses it to learn; it becomes more useful; gives better user experience; you use it more as it collects data, learns and becomes more useful; and the cycle continues. You don't even see it coming -- and before you know it, you're deeply connected.

3. More control by the user. 

A common concern about the adoption of AI to everyday life is whether the machines might eventually rise and take over the world. In other words, users are concerned about losing control over the systems. It's a legitimate concern with the autonomous cars, robots guards and smart homes expected to become commonplace.

This lack of control is mirrored in the skepticism for the future, but it can also be seen in commerce and other areas where user experience is of great importance. For instance, a user will be more likely to enter their card information into a system if they feel they have control over when money is transferred, to whom it goes and that they can retrieve it in case something goes wrong.
As AI develops, users will gain more control over the system, gradually improving trust which will lead to more usage. 

In Which AI Could Enhance Your Company's UX 

UX design is about a designer trying to communicate a machine's model to the user. Meaning, the designer is trying to show the user how the machine works and the kind of benefits they can get from it, from the former's point of view. 

Traditionally, this involved following certain rules, and designers understood them very well. A designer knows how to create a web page by following certain rules that they can probably manipulate. With AI, however, the design is dependent on a complex analysis of data instead of following sets of rules. To be able to design using AI, designers will have to really understand the technology behind it. 

Mixing UX and AI as we can have played with “AIBO” 

Artificial intelligence
Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks - as, for example, discovering proofs for mathematical theorems or playing chess - with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.

What Is Intelligence?

All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is never taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger waspSphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced.

Fixing the AI in real time

Problem solving, particularly in artificial intelligence, may be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution. Problem-solving methods divide into special purpose and general purpose. A special-purpose method is tailor-made for a particular problem and often exploits very specific features of the situation in which the problem is embedded. In contrast, a general-purpose method is applicable to a wide variety of problems. One general-purpose technique used in AI is means-end analysis—a step-by-step, or incremental, reduction of the difference between the current state and the final goal. The program selects actions from a list of means—in the case of a simple robot this might consist of PICKUP, PUTDOWN, MOVEFORWARD, MOVEBACK, MOVELEFT, and MOVERIGHT—until the goal is reached.

Many diverse problems have been solved by artificial intelligence programs. Some examples are finding the winning move (or sequence of moves) in a board game, devising mathematical proofs, and manipulating “virtual objects” in a computer-generated world.
About Author
Jagannathan Kannan
UX Lead Designer @ Verizon wireless



Top UX Trainings & Certifications in India

Crd Sorting, design thinking


Institute - HFI  - Human Factors International 

Institute - HFI  - Human Factors International 

Institute - IDC, IIT Mumbai

Institute - Imagine XP

Institute - Design Incubator

Institute - Umber Learning Facility

Institute- Design Mortals Academy 

Institute - UX Mint

Institute - BrigdeUX

Institute - Design Errs

Share your feedback & more suggestions on team@uxness.in 

Getting started with Maze tool for Usability Testing

Maze tool

About Maze Tool

Analytics for Prototypes -  Maze is an online Usability Testing tool which can use high fidelity (Clickable) prototypes to prepare Usability Testing/Remote UT environment setup. Discover how real users interact with your prototype: define missions, collect actionable insights and analyze how your design performed, with 0 lines of code. 


Key Features of Maze

1. Direct Success
2. Indirect Success
3. Bounce Rate
4. Average Duration
5. Mis-click rate
6. Heat Map & Click Trail
7. Individual User Session Data

Lets Look at Maze tool

Direct Success, Bounce Rate, Misclick rate

User session data, Heat map, Click Trail

About Author
Abhishek Jain
Lead UX Researcher 

7 best Card Sorting tools

What is Card Sorting?

Card sorting is a method used to help design or evaluate the information architecture of a site. In a card sorting session, participants organize topics into categories that make sense to them and they may also help you label these groups. Card sorting helps us gain valuable insight about the structure of data.

Types of Card Sorting –

Open - In open card sorting, each participant is given a stack of cards. The participant is then asked to group those cards together any way they want. Then they make labels for the groups they created.

Close - In closed card sorting, the researchers create the labels for the groups. Participants are given a stack of cards and are asked and are asked to put each card into a group.

Best Tools for card sorting

1. Optimal Sort

Optimal Sort

Type of card sort – Both (Open, Close)
Remote card sort – Yes
Report & Analysis – Yes

2. User Zoom

User Zoom

Type of card sort – Both (Open, Close)
Remote card sort – Yes
Report & Analysis – Yes

3. Usability Tools (UXSuite)

Usability Tools UXsuite

Type of card sort – Both (Open, Close)
Remote card sort – Yes
Report & Analysis – Yes

4. UX Sort

UX Sort

Type of card sort – Both (Open, Close)
Remote card sort – NA
Report & Analysis – Yes

5. xSort


Type of card sort – Both (Open, Close)
Remote card sort – NA
Report & Analysis – Yes

6. UsabilitiTest Card Sorting    

Usabilititest Card Sorting

Type of card sort – Both (Open, Close)
Remote card sort – Yes
Report & Analysis – Yes

7. Simple card Sort

Simple Card Sort

Type of card sort – Both (Open, Close)
Remote card sort – Yes
Report & Analysis – Yes

15 Top Design Schools in India

Top design college of India, NID, MIT, SID, IIT, JJ School of arts

If you are a design enthusiast, then this post will be helpful in knowing some top design schools & institutes in India for your bachelor & master’s degree course in design.
Note: This list is not in order from 1 to 15 or vice-versa. 

Top Design Schools

1. National Institute of Design

City: Ahmedabad

2. Industrial Design Center (IDC) – IIT Bombay

City: Mumbai

3. IDDC, IIT-Delhi

City: Delhi

4. Centre for Product Design and Manufacturing (CPDM), IISc

City: Bangalore

5. Department of Design- IIT Guwahati

City: Guwahati

6. MAEER’s MIT Institute of Design

City: Pune

7. Srishti School of Design

City: Bangalore

8. DSK International School of Design

City: Pune


City: Pune

10. Raffles Millennium International

City: Delhi

11. Symbiosis Centre of Design

City: Pune

12. Pearl Academy

City: Jaipur, Mumbai, Noida, Delhi

13. GD Goenka School of Fashion & Design

City: Sohna

14. JJ School of arts

City: Mumbai

15. D J Academy of Design

City: Coimbatore