Users are a big part of User-Experience design and so, getting to know your users is extremely important. Without a proper research about your users, half of your efforts to create anything — are meaningless. Doesn’t matter how beautiful your interface is, if your functionality is flawed, it cannot retain users for long!
So — how do you make sure you know your users? Through interviews? Surveys? Well maybe. But do you think you would be 100% true in an interview or during a survey? Think about it for a minute. Would you be genuine and would all your answers be 100% true? There’s a chance that maybe out of ten questions, you give 1 wrong answer and 9 right, isn’t it?
Now that creates a BIG PROBLEM when we are talking about a research that includes 30–40 participants or even more. One wrong answer from each participant’s questionnaire would mean around 40 wrong responses, which means — a recipe for disaster. And this isn’t something that I am claiming out of thin air. But this is something that I observed during one of the research sessions that we conducted with some local drivers for a multinational on-call cab-servicing company (I was working with a really cool design and research agency in Bangalore, and I was a behind-the-scenes moderator in that session, which means a person who works behind the scenes while someone else takes the interview). And during my time working with them we conducted numerous researches using various methodologies and it was an excellent learning experience for me to be honest!
But let me share our observations during the study. Now, the company wanted to conduct a research upon whether to allow drivers to take ‘cash’ trips or not. The control would be with their partners (people who have rented out multiple cars, and those cars were driven by different drivers on a monthly salary).
The partners often filed complaints that drivers ran away with the cash money and it was hard to track them and their earnings since they did not report back to them that often. Some drivers, who would make more money (in cash) in a week than their monthly salary, would often run away with it seeking another job. This was back in 2017 that this study was being conducted for Indian subcontinent, and I’m not sure whether the company added any feature that allowed partners to ‘control which drivers get cash trips and which do not’, but the results from that study were really surprising!
Some background about drivers — coming from low income backgrounds, not educated properly, not able to understand, read or even write English, but using drivers app every single day, which was primarily in English language. While translation options were available, but some drivers didn’t even know how to translate the language on their phones! Many of them did not understand basic stuff about operating an app, let alone running a business).
Now these people had little knowledge about what we were doing, and why. They were conscious, as they thought that we were going to complain about them to the company and close their accounts. Then we asked a Kannada (common language in Bangalore) speaking moderator who explained the purpose of study to them and then they relaxed a bit!
After they gained some trust on us, we began asking them general questions, just to know how familiar they were with options in the app. Surprisingly, they were mostly using only a couple of options, that they recognised through signs and icons. Since they couldn’t read English, most of the words and sentences were meaningless to them. The more we asked them about their familiarity with the app, the more shocking it was to know how little they knew about an application that they were using as primary source of their income!
After half an hour into the interview with every single driver, they would come out clean and say ‘Madam, I don’t know what this does…’ or something similar for a feature or an action in the app. When we told them to share their thoughts about ‘limiting cash trips for drivers’, they panicked thinking that the company is going to do that and they thought their income will be affected the most! The ones who were on a monthly salary said that they don’t care as long as their wages are paid on time, while those who earned through incentives were worried. Many opposed this move with full force and thought that they will start getting less trips, rather than thinking the other way round — that more people would have to use cashless options to secure a cab early, if cash trips were limited, and hence — more transparency and visibility.
The interview went on and on, but the major takeaway from this session was that — people are not honest if they think they’re being judged.
This takeaway was really effective, as it helped in all future researches, to understand people ‘beyond’ their own words. Their expressions and emotions play an important role in helping the other person understand whether they’re lying or not, and many people come with such a straight face that it becomes even tougher to judge them and believe their words.
Suppose you’re running a user-research session for a food website, there will be many people who will say that they like every item on the menu that you think you will have — but once you launch the restaurant (product), only then you will actually find out if they are going to order every dish in the menu or not, and surprisingly —
Not a lot of people are ‘as open to changes’ as they claim to be. Doesn’t matter how much I express my interest towards trying Japanese food in a chic restaurant, but mostly I will end up ordering my desi Indian food wherever I go, because that’s what I am ‘comfortable in’. Experimenting is cool, but what if something goes wrong? What if my stomach can’t digest the Japanese food? Let me stick to what I know will work best for me, rather than experimenting, and so, let me order my regular Indian Punjabi food that I know I can digest.
That’s what most people do anyway. It’s a psychological fact that losing your comfort zone isn’t something that anyone will do easily unless prompted/forced/motivated to. It acts as a big bias in your research that skews the results and deviates your product outcome too.
Observing behaviour is more important than ‘listening’ to what they’re saying. Observations give you deeper and richer insights into the minds and lifestyles of users.
LONG STORY SHORT (How Nestlé targeted toddlers and small kids to launch their coffee shops twenty years in future in Japan!)— Nestlé ran a research campaign in Japan to understand whether their coffee will work in a Tea-loving country or not. Everyone loved coffee during research sessions, the taste was peculiar and research went positively well! They launched more than a dozen stores in Japan, and within six months to a year, all stores had to be shut down because of low footfall and people’s continuing love for tea.
Now, when the research went well and results were positive, why did the product fail? Answer — COMFORT. People didn’t like to experiment, they were more comfortable drinking tea. Then, Nestlé launched coffee-based products for Japanese kids, candies and toffees in coffee flavours, and twenty years later, they again launched coffee shops, and they were a massive success! Why? Because all those kids who had grown up eating coffee flavoured candies, loved the taste of coffee even in their adulthood. This teaches us that people are not willing or ready to leave their comfort-zones. Research results might vary very strongly, but comfort is what is deeply ingrained in the psychology of people.
But how do you translate user behaviour-observations to tangible products?
User behaviour is peculiar. Not every user will behave alike in similar situation, and everyone might have a different approach towards a same problem. That is why we have user-personas but even personas are not 100% reliable, and that is why there are user-groups. User groups are one methodology that we can use to translate user-behaviour into tangible products.
What are user groups?
We classify a particular group of people who have similar lifestyle, similar income background, similar patterns throughout the day and group them up. For example — let’s consider that you’re designing a food and nutrition app where you give different diet plans for people who have different lifestyle. What will you ask your users while on-boarding them on the app?
- Their age group (to understand the kind of lifestyle they might have).
- Their marital status (usually single people lead a different life compared to those who are married or are with kids).
- Their activity level throughout the day (to understand their metabolism rate).
- Their sleeping pattern and schedule (to recommend them best possible diet, for example — new mothers might have a totally wrecked up sleeping schedule)
- If your user is a female, you might even want to ask more questions (like if they are expecting a child or not, if they have recently had a baby, or if they’re breastfeeding their kid at this point or not, if their menstrual cycle is normal or not, if they have PCOS or not, and so on).
Basically, your set of questions is not linear, but nested — it is dependent upon previous answer of the user, based upon which your questions are bound to change.
As you can observe here, this is a tiny user group chart, with a lot of scope for expansion. Here, I have only considered the sub-groups created under the category ‘Females’, relating to the status of their pregnancy. A diet chart may vary greatly when it comes to status of someone’s pregnancy and similarly you can create sub-groups based upon every category and sub-category.
This will give you a high-level and detailed view of your users, and will help you precisely know their lifestyles and patterns. This exercise will not only remove a lot of ambiguity from your research and perception but will also enable you to create well-defined personas with EXTREME NEEDS.
What are extreme user personas or corner-case user personas?
User personas are what everyone knows and understands, but extreme user personas are those who are at the edge of the spectrum. The personas that can greatly deviate the usage of a product and the persona that many researchers or designers might ‘ignore’ because they are not a lot in numbers.
As discussed above, there are many user groups that have similar habits and lifestyle, but then there are some peculiar users who have distinct lifestyles and varying patterns throughout the day. Are you considering those fringe users in your study? Are you weaving a story on their lives and building a product for them?
Let’s consider the food and nutrition app (the one we were discussing above). Can you find out 10 extreme user personas from it? Without reading the answer below, try to come up with 10 different personas who are on extreme edges of spectrum, they are like those tiny percentages of people who have a super-power, and you’re allowed to design for that super-power! Let’s discuss them one by one, considering the problems they might face and what solutions we can implement to keep them happy!
So, let’s try this exercise here and come up with some extreme personas. Note that extreme personas are those who are not your common/usual user-groups, people who are very less (or negligible in numbers) —
- People who have some kind of sight defect — Those who may not be able to read light text or dark text on dark background on your app. They might be ones who have either complete colour-blindness or partial colour-blindness.
SOLUTION: For such people, you can always keep a separate panel in which you can allow them to change the colours of the app as per their requirements.
- People who are below 25, married and with kids below age 2— They have high energy level (because of a relatively young age), but their energy is drained, because they have small kids who need more attention than school/college going children.
SOLUTION: You can provide them flexible and easy to cook options in meal plans, something like a meal prep for a week, so that they don’t have to spend too much time cooking!
- People who are below 25 but with less than 7 hours of sleep and no activity level — These people are packed with energy, but they aren’t using that energy because of lack of sleep and activity.
SOLUTION: You can give them meditation exercises to calm them down and help them get better sleep, and then motivate them to pick up some easy and interesting activities so that they actually see the result by using your app.
- Pregnant women who are in third trimester — Such women need more nutrition and rest as they’re in final stages of pregnancy.
SOLUTION: You can suggest them to rest and meditate. Calm them down with breathing exercises and present them facts about what to expect when they are in third trimester.
- Pregnant women in first trimester but with complications — Such women don’t need that much rest as the baby is of a significantly small size at this stage, but then again, pregnancies vary and if there are complications, you might ask them to refrain from certain activities.
SOLUTION: Ask them to avoid lifting heavy objects, motivate them to eat more fibre and greens and so on.
- Women who have never been pregnant but trying to be — Such women might need foods that help them with fertility and conception.
SOLUTION: Suggest them a diet that enhances their fertility and helps them conceive a child.
- Women who have kids and are experiencing menopause now — Menopause is a state where a lot of women might experience rush of emotions and hormones, such women might need to control on their sugar cravings and keep at bay from stress.
SOLUTION: Such women might need special diet that keeps them full and supplies proper nutrients in their bodies.
- People who are suffering from clinical depression — Such people don’t exactly form a fringe/extreme user group, as there might be many, because weight gain is a common problem in depressed people.
SOLUTION: Don’t suggest only weight-loss diets and tips to them, but also suggest positive messages, tips to help them socialise and curb depression.
- People who are going through insomnia and are living in cold, hilly areas — Demography plays an important role in lifestyle and habits of people. You can’t suggest same diet to someone who lives in extremely cold areas, as you can suggest to someone who lives in a coastal/tropical area.
SOLUTION: To such people, you can suggest a diet that keeps them warm, helps them boost metabolism and keeps them energetic and not lazy.
- Transgender people who are going through a hormonal transition and are on heavy medications — There might be people who are transitioning from male to female and vice-versa, and they might be taking a lot of hormones as a part of transitioning medication.
SOLUTION: Such people might require a special diet that helps them through an easy transition.
There can be hundreds of extreme cases, but exploring only some of these cases can help a designer to diversify the user-research and come up with solutions that benefit not one, but all! Such a thinking, if promoted across all products, can make it easy for all kinds of users to use the app and make it a part of their daily lives!
Although they say that you only need 5 users to do an extensive user research, in my opinion, along with those 5 users, you also need a critical thinking and a design-thinking mindset, that can help you explore many other corner-case scenarios, and maybe you add one such feature for one such corner-case user that changes the future of the app entirely!
I know it was a long post, and it took me almost two weeks to draft it, but I’m sure you had some new insights to take away from here. Let’s make the UX Design community an awesome one to be a part of!
That’s all for now folks, I am writing the tenth and last part of this series in parallel and I want it to be a really good one, so that might take some more time, but look out for it in the same space.
Thanks a lot for reading, please share your love 💖 and add your comments for a healthy discussion! 😊 😎
You can read the previous parts in the series here —