One Platform, Many Minds: Designing for Digital Literacy, Culture, and the Real World.

Manthra Shriman Narayan at UXDX Community: Design for Everyone: Ethical AI and Inclusive UX. Video: https://youtu.be/RK1XQjuJxW8

Readable transcript: edited from the recording's captions for readability (fillers and false starts removed, punctuation and section headings added). Wording is the speaker's own. Timestamps are positions in the video. Names marked [?] could not be verified against the audio.

When the user is not system friendly

[00:00:00] Good morning, good afternoon, good evening to people joining from different parts of the world. I'm really happy to be here with UXDX to talk on this, one platform, many minds. This topic especially is very close to my heart, because this comes from a place of where things didn't go as planned and what we learned from them. We often loosely talk about a system not being user friendly, but I would like to talk about what happens when the user is not system friendly. I would not talk much about myself today, because I'm sure most of you here are people that I know, or you would have already seen the UXDX calendar. Otherwise you can just look me up on LinkedIn and just say hi.

[00:00:52] Moving on, this is roughly my agenda. I'll be starting by setting the context. I'll talk about how it is to design for conditions that are beyond what we know is ideal, and what are the varying digital literacy levels, and what happens when a good design fails. We often attach ourselves to good ideas and designs, and what happens when it fails. And then we'll talk about balancing trade-offs in UX, and culture and its impact on design, this is again something very close to my heart, and designing for real world environments.

[00:01:26] Let me just start by talking about an incident that happened about seven years back. I think it was seven years back, so this was pre-5G days. I was attending a cousin's wedding in some remote part of Bangalore, and I was also working on a pitch for a very prestigious client. Most of my work was done, but a little bit, like 10-15 percent of it, was left, which I had to complete, and I had connected my laptop to my mobile hotspot. This was, I think, roughly running on 3G, 4G or something. And you won't believe, every download, every site load was a harrowing experience. It took ages. The internet was working like it had some personal grudge against me. So at one point I even started hating loaders.

[00:02:27] That day I actually thanked my stars that this was not my everyday reality. We designers most often work in good conditions, in good air conditioned rooms with good wi-fi and a good laptop, maybe even sipping coffee. But how many of our designers, I mean sorry, how many of our users actually do that? Coming to think of it, our beautifully crafted flow, the users might be using it in scorching heat with two percent battery, or say on Edge. I know it is a thing of 2009, but then it still happens.

[00:03:04] So how many of our users are actually working in ideal conditions? If a system fails in those conditions, then it is not just inconvenience, but they will actually not be able to complete the task, be it filling up application forms, or if it's a contractor he might not be able to fill a walkout report or something like that. So a good system, a good design, is not just about it being very elegant or fancy, but it has to also work in real world conditions.

Four realities: diverse users and the myth of the perfect persona

[00:03:34] So what does this talk about? I've realized that over time a good design involves solving four different realities. The first one is diverse users. The second one is uneven digital literacy. The third one is unpredictable environment, and fourth is cultural context.

[00:03:47] So the first one, the myth of a perfect persona. We designers always love tidy personas. We create something like Sarah, 32, loves productivity apps. She always seems incredibly organized. But how many Sarahs do we actually know in real life? I've never met a Sarah in real life. A real platform can rarely have just one kind of user. It will have varying user bases. One person might have just started using mobile phones, or one person might actually be a hesitant user. So a good system should cater to every kind of persona. It cannot just be one very organized Sarah. That is the first lesson that we learn from real world users: they are messy. And UX is rarely about designing for just one persona, it is about designing for an entire ecosystem of users.

[00:04:47] The next one is digital literacy as a spectrum. Another assumption that we often make is that people are either tech savvy or they are not. But digital literacy is not binary. On one end you might have a user who might be hesitating to click on a button because they think they might just end up accidentally ordering something, or they might be paying for something that they didn't intend to, or they might be submitting an application form. And on the other end you have an expert user who might just want to finish the task a bit earlier, with a keyboard shortcut or something like that.

[00:05:30] So it is a spectrum. Digital literacy is a spectrum. You have hesitant users, you have beginners, you have confident users and you have power users. So a good system should cater to both beginner and expert user. If we design only for the middle of the spectrum then we are just going to frustrate both the beginner and the expert user. This is what a good system should do.

Innovation versus familiarity: killing a favorite idea

[00:05:49] The next one is innovation versus familiarity. This is one of my favorite topics, where I had to kill one of my favorite ideas because it was not familiar enough. We designers often suffer from what we call falling in love with our own ideas, and also we will defend it like our reputation depends on it.

[00:06:19] So I had a requirement coming in saying that a contractor has to build a certain form with certain elements that will go as part of a contract. The requirement was very simple. They already had an existing table. So I wanted to scrap off the table, because I thought it was old-fashioned and everything. So I built a very elegant list builder where the user could move the stuff around, they could add whatever they wanted or remove. I was very proud of the design. This was something that anyone would look at and say, this is going as part of my portfolio and everything.

[00:06:52] Another thing that made me overconfident about this design was I had already tested this with another set of users for a different client. Those set of users were policy makers. They were ministry level officials who were sitting in the comfort of their offices to build this list. And here in the current scenario I was designing for users from a different context. They were contractors who would come back from a long day at work, or they would be in the middle of a highway filling up something. So the context was completely different, but I gave both of them the same interface thinking it would work.

[00:07:33] Then we went for usability testing. What happened was very fascinating. The users kept moving stuff around. They tried to click on things that they thought were call to actions but were not. But not one of them could complete the task. At that point I thought there were either three things that would have happened: either the users were confused, the interface was confusing, or usability testing itself was fundamentally flawed as a concept.

[00:08:00] So eventually one of the participants then asked me, can we just not have a table? I was a bit shocked. And then I asked him, sorry, a table? And then I tried to also convince him, saying this list builder is more modern and elegant. What he told me was very interesting. He said, right now they already have a table format offline, so that's how they fill up the system. Rows, columns, neat structures and everything. And at the end of a long day, innovation is not what they need. Familiarity is what they needed.

[00:08:37] So we ended up doing a table and that worked really well, and we had a lot of completion rate as well. The lesson that we learned from this was that users prefer familiar structures when completing real work. Innovation is valuable, but familiarity often beats novelty when it comes to task heavy systems.

Trade-offs: the job portal

[00:09:03] The next one: trade-offs are part of design. Where to find the middle ground between competing needs. This is often a dilemma that we face. We were designing a job portal, and the job portal had to serve both the applicants and HR. As an applicant, for so many years, whenever I've applied for a job, one thing that I always found frustrating was you upload a resume and then you end up telling the same thing in the form as well. And even now, even with the parsers and stuff, either the fields are incorrect or they are incomplete.

[00:09:42] So long forms are something that always frustrates, and we also found that a lot of applicants were dropping out. So we went for a different technique. We gave them short forms, and the completion rate improved dramatically. And there was another issue here. The HR found it painful to actually go through hundreds of resumes to filter them, and the questions that we were asking were not enough. Although a lot of candidates were able to complete the form, the HR had a very difficult task at hand.

[00:10:12] So instead, after a lot of brainstorming, what we did was, first, for each job posting we would have customized questions. So we would give them a form with just questions that were customized for that job posting. This satisfied both the HR and the applicant. We would ask them to upload all the forms and everything, the certificates and everything, once they have gone past the first level. So this really worked between both the HR and the applicants. One lesson that we learned from this was that good UX is often about balancing competing needs. It's not about perfect solutions, it's about thoughtful trade-offs.

Culture: translation, localization, and two famous failures

[00:11:00] So the next one is culture. Culture, interestingly, shapes how people perceive and use technology. This can be approached in two ways. One is translation, the other one is localization. Translation is quite simple, where only the interface language changes. The structure, the layout and all the experience remains the same. Whereas in localization, the product itself is adapted to the culture: the visual design, the content strategy, the interaction, everything changes for different cultural contexts.

[00:11:34] So I will just share two case studies about what happens when there is a lack of cultural awareness. These two are very famous, you can even look it up. Gerber. Gerber is known for their product packaging with that cute baby face on the cartons. When they entered the African market, they had the same packaging. And what happened was, in most parts of Africa where the literacy level is a bit low, they have this practice of adding a picture of the content of the product on the face of the carton. So if you have porridge, the picture of porridge will be on the face of the carton. Or if it's chicken, it will be on the face of the carton.

[00:12:23] So now, when Nestlé entered the market with this baby face on the carton, people thought it was actually baby meat inside the product, inside the carton. So this was a big failure. The product was not an issue, but the lack of understanding of cultural context here was the issue.

[00:12:43] And secondly, the McDonald's ad in China. They ran a very famous commercial where there's this employee who's kneeling and begging a McDonald's employee to accept an expired coupon. The intention of the ad was to be humorous, but this didn't go well at all in China, because kneeling and begging is considered insulting. They would never do that. So this ad was a big failure in China. Even if the intention was humor, if you don't understand the cultural context, your product is never going to make it in that space.

[00:13:20] There are many frameworks that can help you understand how these cultural contexts work in different countries. Hofstede's cultural indexes is one. If you look at culturefactor.com, they can help you with rating how each of these scale in different indices. So I was trying to look up how Hong Kong and the United Kingdom score. If you see, Hong Kong rates very high in power distance index and also in long term orientation, whereas the UK scores very high in individualism, motivation towards achievement and success, and uncertainty avoidance index.

[00:14:05] Let me just show you how this works in a digital platform. On the left, the Chinese University of Hong Kong, and on the right you see University of London. Because the power distance index is very high, if you see, the Chinese University of Hong Kong has images of authoritative figures on their carousel, whereas University of London will have more of students, student life, something that projects or exudes individualism, success and on those lines. Whereas your Chinese University of Hong Kong will show you mostly about how community works and everything. So this is how these cultural factors will also be incorporated in digital spaces.

Designing for the real world

[00:14:56] So moving on, designing for the real world. Time and again, in different parts of my experiences, I always notice that these three things keep coming back. Designing for ecosystems and not personas. Familiarity often beats innovation. Context is part of the interface. If we don't stick to these three, then the system actually fails in the real world.

[00:15:23] The future of UX is not about designing for the average user, because this average user does not exist. These real platforms actually serve a first time internet user, an experienced power user, or people working in different cultures and people working in unpredictable environments. The challenge is simply not designing beautiful interfaces, it is designing systems that will work for real humans and the real world. And sometimes that means having the humility to actually step back and listen to users and kill your favorite idea where it is not helping them succeed. Because good UX is not just about making designers happy, it is also about making your users successful. So the real challenge isn't designing for users like us, it is designing for realities that they may never fully understand. Thank you very much for this opportunity again. If any of you have any questions, please feel free to ask.

Q&A

[00:16:25] Host: Excellent, thank you very much, Manthra. Those are really nice examples. I like how you made it very relatable by using the examples throughout. It definitely helped me to picture exactly what you were sharing. And again, just to remind everybody, if you have any questions please write them in on whichever platform you're watching this on and we can put those questions through to Manthra.

[00:16:47] Host: My first question, just going back to the digital literacy example that you gave. I love the concept of meeting people where they are versus where you expect them to be. But some of that also is efficiency, because the more modern patterns potentially are more efficient. So is there any concept of helping guide people as well? So maybe we meet them where they are right now, but we look at ways to guide them towards more digital literacy.

[00:17:19] Manthra: I'm sorry, I didn't get the last part. Could you please repeat?

[00:17:24] Host: So your example was, instead of the list, to have the table, because that's just what they were more familiar with. But I'm just wondering, because I can think of examples where, yes, something might be more familiar but maybe it's not as efficient, and that's why we want people to use the more efficient modern approach. So are there any patterns for, yes, we meet people where they are today, but is there a way that we can try to improve their literacy over time to get to that more modern, potentially, hopefully more efficient way of working?

[00:17:58] Manthra: Absolutely. There are two approaches to this that we have actually tried and tested. A few years back when I was working with Network Rail UK, what we used to do was to just get people up to speed. We used to release some tutorial videos, quick videos on different modules that would help them understand how things work. But we should also be able to give them that kind of time to adapt to that system. If the users are going to be a bit resistant about new systems, then you can't just push the new ideas immediately. You need to give them some time and let them warm up to the idea of a new system or a more elegant system, and probably give them some of these tutorial videos and conduct workshops to help them understand how this would benefit them. So these could be two approaches. The idea is to just give them some time to warm up to that idea.

[00:18:56] Host: No, a great example. I guess it's trying to handle, somebody gave it to me as learning anxiety. When somebody is new around something, they have learning anxiety: I can't do this, I can't figure it out. So I guess trying to reduce that.

[00:19:08] Manthra: And also for them, this system that we are giving them is only a part of their daily work. We are trying to help them speed up their work, we are trying to make them more efficient. So if they think that this is going to bring their speed down, then it is counterproductive.

[00:19:32] Host: Excellent. I want to move on to the localization piece, because I love the examples that you gave there. It's interesting because it's so ingrained in you, all of your biases, that it can be difficult to think through the biases of other people. And what would you say? The universities are quite good, because I guess they're localized a little bit, but potentially let's say London University wanted to attract overseas students. What's the best way? Is it trying to come up with a one size fits all, or is it trying to detect browser locations and serving them different things? What are the examples that people could take away right now for how they could improve the localization of their apps when you're looking at a global audience, so not just very market dependent?

[00:20:29] Manthra: Sure. One way to look at it would be if the university wants to project the culture of the country, their existing cultural context, or if they want to be more global. If they want to satiate the other ethnicities as well, people coming from other cultural contexts. So that is something that we need to understand from the university. If the university is, say, a client, we need to understand where they are coming from, what is their grounding. Depending on that, we will be trying to do a little bit of research and come up with some solutions for that. But again, most of the universities try to only project their cultural context. I've not seen something that tries to attract other countries, other cultural contexts as well.

[00:21:34] Host: And if we're looking at something like the McDonald's example, but let's just say rather than the ads, their homepage, because their homepage, McDonalds.com. Is it that you get a McDonalds.in, do you get one for each country, or do you try and make it so that the McDonalds.com fits for everything?

[00:21:54] Manthra: I don't think McDonald's can afford to have a single website that would cater to different countries, different cultural contexts. It has to be for that specific context. For instance, in a place where beef is banned, they cannot be having a homepage with beef on it. So they'll have to be very culturally aware of what is allowed where. A classic example was the humor not going down very well in China. So it has to be different for different contexts, especially given the size and scale of a McDonald's.

[00:22:39] Host: And I guess on that size and scale, a company like McDonald's can well afford it, they can afford to get teams in all of these different locations. Would you recommend leaning on AI, or what would be your recommendation for those smaller companies that potentially don't have the resources? They don't have the resources to have a different website in every different geography.

[00:23:06] Manthra: So they might have to just customize it to different geographies, in the sense of not having a separate domain, but they'll have to have some kind of sensitivity towards different cultural contexts. It has to be more generic. They cannot afford to have something that might not go down well in some part of the world.

[00:23:27] Host: Okay.

[00:23:29] Manthra: Sorry, these days you have a lot of personal customizations. Even e-commerce has it. I go and look up some toys, the next time I go, I'm seeing a list of all different kinds of toys. So those kinds of customizations can actually help for different contexts.

[00:23:49] Host: Okay, so lean on the tools that are existing in the marketplace. I guess it is 2026, so I have to ask the question: how are you using AI, to tie in with our first conversation? Are you seeing it as a tool to help with those points that you've mentioned throughout your talk? Or where do you see AI filling in, or is it all down to the human still?

[00:24:15] Manthra: It is still mostly human, because like Shreya had rightly pointed out in the previous talk, not all of the content that you get, especially when we're dealing with real people, not all the content that you get is real. So we cannot afford to make that mistake. We still have to talk to people and understand and be sensitive to each one's context. So I don't think AI has fully taken over. AI can be used maybe like certain tools we use for rough prototyping, to just quickly turn around a few things and turn ideas into some prototypes. So that we can use, but in terms of research and trying to come up with personas and things like that, I don't think we can rely on AI as much right now.

[00:25:06] Host: Yeah, no, it's probably a good take. There's a lot of movement towards these digital personas and things like that, or synthetic users, but I think it's dangerous. It's a risky proposition at this point.

[00:25:19] Manthra: Maybe in future it'll be foolproof, but at this point I don't think AI can completely take over understanding our real users. It's going to be very risky.