TechXperts — A Tech Support App Case Study

An app that connects novice technology users to expert technology users in order to solve technology related issues.

The Problem

There is a need for technology assistance for tech-impaired people and an equal need for others to share their technology knowledge while getting paid for it. Many older or less technologically experienced people often need assistance with everyday tasks regarding technology but don’t have readily available access to someone who can help.

The Solution

My partner and I believe that creating a technology support app will solve this problem and benefit two kinds of people: Novice technology users and expert technology users. The novice users will gain either tech knowledge or support from tech supporters. The expert users will gain tech experience or a freelance opportunity from those receiving tech support.

The Team and Their Rolls

Allison: UX Designer & Researcher for the “Novice” side of the application.

Courtney (me): UX Designer & Researcher for the “Expert” side of the application.

Competitor Research

Through researching the competing tech support applications observed that other competitors aren’t easy to use or unliked by the general public because of long wait times and non-reliable service. Due to the creation of the Gig economy, which is a labor market characterized by the prevalence of short-term contracts or freelance work as opposed to permanent jobs, apps like Uber and GrubHub have grown exponentially and there is an untapped market for tech support using the Gig economy model.

We found that other products that solve a similar problem are mainly web applications as opposed to mobile. Uber and Airbnb are both apps that rely on the gig economy model. Both companies are excelling over their competition because of their ease of use and transparent design. Uber was the most helpful in creating a model for our TechXperts app. We noticed that the success of Uber relied heavily on transparency. When you open the Uber app and request a ride, you can see the price of the ride, where your ride is coming from, when they will arrive, and how long it will take for you to get to your destination. This is successful because its is so simple for the user. There are no questions needing to be asked. All the information you need is right in front of you and not only that, that app is fast.

User Interviews

Other companies are using a Gig economy model, but there is an untapped market in freelance tech support. This is causing novice tech users to either ask their friends/family or give up and causing expert tech users missed opportunities to make money. How might we create our technology support app so that our customers are successful based on receiving and giving tech support?

We conducted audience research and found our two ideal users: novice users which consist of the Silent & Boomer generations and expert users which consist of Gen X, Xennials, & Millennials. We conducted research for both sides of the app separately, with two sets of interview questions. The first five questions of the surveys were the same and bases on the fifth question (Would you consider yourself tech savvy?) we split the interview into either novice user or expert user. While we conducting street interviews, we came across an interesting note. There seems to also be a third group of people who may use the app: an in-between users. This helped us in deciding to create a way for users to toggle between modes.

Web Research

The most important research we conducted was looking into the increase in tech usage among older generations. We found that usage has quadrupled according to Pew Research, meaning that not only do older generation need help with understanding tech, there is also a growing market for tech support in this area.

The solution was to connect these two types of people using a gig economy model. We need the app to be easy, clear, and concise. Our research showed that not only was there a gap in the ability of older generations to use technology, but also that tech usage among those generation is on the rise. In finding this, we concluded that tech support is a growing market.

User Pesonas


In the ideation phase, we used the I like, I want, and What If method to ideate. We struggled with the “What If” section because we were focused on what we already knew and we needed to think out of the box. We took the best ideas and simplified them into 7 features. We ended up implementing 4 features: connect novices with experts to solve tech problems, profiles for tech support, simple on boarding for novice users, and job sorting for tech support.

User Flow Map

We started mapping out our user flow by putting both users in the same flow but that did not work as it entangled a crazy web. So, we ended up breaking the user flow into 2 user flows: 1 for novice users and 1 for expert users.

Sketches and Lo-Fi Prototypes

In the lo-fi paper prototypes, we empathized with our users to create an easy experience. However, what we found through user testing of the paper prototypes was that the chat feature was too complicated for our users to understand because they were not chatting in real-time and a confusion of chat prompts. see out first iteration below:


After simplifying the app in out first round of testing, our second round of testing told us that we needed to be more clear. We researched a bit more about terminology used in this industry sand inserted out own terminology when needed.

Final Conclusions

Our main focus when iterating our prototypes was on simplicity and clarity. From the beginning we knew we would have to succeed at both because of the nature of our users. We modeled the functionality of TechXperts based on other gig economy applications. They are successful in their transparency and easy of use so we knew our app would need to accomplish both.

The most challenging part of creating this app was honing in on simplicity in order to accommodate our older user group. Our immediate solution for the complexity of this app was to create an “App Guidelines” page for both users. In the future, we would like to eliminate the need for this as we feel it is too much reading and not enough intuitive design. We would like to replace this with AI functionality so that the app automatically prompts its users instead of them needing to manually enter in each function.

We would also like to implement a few interesting features that we also came up with in the ideation phase of this project. Expert users can export their profile for their resume or portfolio, gifting money to other TechXpert user accounts to get them started with using the app or if you just want them to stop asking you for tech advice, and classes hosted by expert users from TechXpert to give in-person tech demonstrations to novice and intermediate users.

I’m a multidisciplinary designer with experience in UX design, UI design, traditional graphic design, and video production.

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