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Privy helps users learn about the many ways that their data is being collected, and the reasons for it. A user would be able to see a personalized summary of their shared data, and in turn, take the appropriate action they feel comfortable with.

Project Timeline

8 weeks - March 2021

My Role

Independent - UX Researcher, Design Strategy, UI/UX Designer


Miro, Sketch, Figma, InVision, POP, Illustrator

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Hero image

Quick Summary

A Presentation Video

Problem Space Discovery

Rising concerns in Data Privacy

Most of the services and products we interact with today have become so integrated in our lives. We connect with others through social media, bank online, track our health with wearables, and shop online, among many more. This dependance on the online has grown tremendously with the pandemic, but the subject of privacy and data farming have seen a rising concern for better legislation, and action. The truth is, companies have deceived us time and again at keeping our information private. Whether intentionally by selling off data and turning their consumers into products that they can keep monetizing, or through immense data breaches that exposes millions, sometimes billions of people’s personal and identifiable data.

Landscape Mapping

Data Privacy over the years

In order to understand the ongoing trends, it’s helpful to revisit the past. This helps me understand the reasons why certain things are the way they are, and what could have led to certain sentiments, fears, and overall behaviours surrounding the space I’m exploring. I used Miro’s white boarding and sticky note functionality for that. This exercise was done in an hour, so it was not completed as much as I think it could be. I was also the first time doing this, but I do think I was able to capture some of the main trends and signals through the years. It is illustrated below.


Secondary Research 

Data privacy trends and developments

Generally, it’s the shady practices and the non-transparent ways that companies go about data collection that result in such backlash and distrust. Data leak scandals that expose big data operations only add fuel to the fire. With that said, we are currently seeing events in response to this overall sentiment:

  • Apple and Facebook are amidst a huge data privacy showdown. Apple is requiring developers to disclose the type of data their apps collect. This public disagreement is prompting elevated interest in privacy and user data.

  • Data breaches are happening at alarming rates since 2010, some of them exposing billions of user accounts, including personal, financial, health, and other sensitive data. This has affected lots of recognizable companies like Adobe, Equifax, Linkedin, Twitter, Marriott, eBay, Facebook, and Yahoo! to name only a few.

  • Privacy advocates and groups have voiced their opinions out loud, some exposing their governments, like Edward Snowden. Distrust has led to a growth in VPNs (software that allows users to mask their IP addresses, and to encrypt their online footprint from prying eyes like service providers) that shows no sign of slowing down. People are demanding more privacy, and are paying for it.

Quantitative Data

Key Statistics


Is the expected drop in Facebook’s revenue when Apple’s App Tracking Transparency is implemented


Users switched from WhatsApp to Signal, in less than four days due to privacy concerns


Of Facebook’s $20 Billion revenue depends on collecting user data for its targeted ads business


Is the increase in sensitive health data breaches between 2017 and 2019


Is the number of Yahoo! accounts that were breached, making it the largest hack of all time


Is the 2021 expected global cost for cybercrime prevention and remediation

statistics by CSO, Engadget, Forbes, Wikipedia.

User Interviews Insights

Understanding online users' goals and frustrations

In order to better understand what leads to some of the decisions people take when browsing the web online, I’ve interviewed five users of different age groups and genders. The goal is learn about the sentiment on their shared data. Interviews lasted about an hour on average, and below are some of their shared insights and frustrations:

Transparency & Disclosure 🤝

Transparency is becoming an important metric in which companies and brands are measured by, as users begin to value it when deciding where to put their trust.

Absence of Control 🕹 

Users feel beat-down and unable to do anything about being tracked, and some are concerned that their data will affect their outcomes and chances in life.

Confusion & Misinformation 🤷‍♀️ 

Users are left in the dark, as companies do not try to provide accessible, engaging, and clear ways of explaining the reasons and the methods they use to gather data.

“If we could build an app that's ethical by design instead of adding laws and rules, because there's a conflict of interest between what's good for the user and what's good for the company”

“I mean, there's no other way around it. So you kind of just accept it. There's nothing that you can do about it.”

“Nobody looks at the privacy policy because it’s way too long, too small, too confusing, and too technical…”

Persona & Experience Map

Keeping an online user's experience central to my design 

Using the gathered interview insights, I was able to proceed with crafting a persona and their experience map. This persona’s goals and frustrations will help guide my design decisions and strategy moving forward.


Looking into the persona and their experience map, it is clear that our user wants to be better informed so that they can take the proper data choices for themselves. Brandon’s ignorance on the ways his data is collected could lead him to take misinformed decisions that don’t work best for his needs.

With this in mind, we can declare our project's design question:

Design Question

How might we help users understand how their data is collected and utilized in order to better inform their privacy choices?

Task Selection

Informing users about their data collection as MVP

By using the HMW statement and considering the needs of the Brandon Trent persona, I was able to create a set of several user stories under three epics in order to define the function of my product. To create my minimum viable product, I chose the following epic and user stories by taking into consideration the core value proposition.

Core Value Proposition

To inform users about their collected data and help them understand it

Core Epic

Confusion & Misinformation

User Stories

The above chart shows 10 user stories under this epic. Highlighted are the main ones I chose to move forward with.

I’ve decided to proceed with the task that felt most necessary to people first. Before we can provide users full control and expect companies to be more willing to be transparent, we may want to ensure that our users are informed first and foremost. Through our selected user stories, we can see tasks beginning to emerge: viewing and searching a library full of privacy terms explanations and definitions, as well as watching a short video that explains the basics of a certain tracker type.


I can now start thinking about the interaction process, summarized into the main task flow below. It depicts a user wanting to learn about what cookies mean, access the cookies page, and watches a video about them.

Task Flow

Sketching & Wireframes

Exploring quick ideas with pen and paper

I started ideating some interface elements and screens, with the goal of keeping the app extremely simple and intuitive. Users are already overwhelmed with a topic they know little about, so the app shouldn’t deter them from learning about data privacy.


Usability Testing: 2 Rounds

Testing the low fidelity prototype

I've decided to start my first round of testing with my wireframe sketches with the help of the Marvel POP app. Photos of my sketches were rendered interactive and testable. This iteration of the prototype was tested with five (5) users, with the presented task being to “use the app’s library to learn about cookies. Watch a short video about them, and explore their benefits and drawbacks”.

Notable Changes

All 5 subtasks that led to the completion of the presented task were successfully performed by all 5 users, but some of the very minor hiccups were limitations of the lack of any proper context in the paper prototype. However, no user got stuck on any of the tasks, which pointed to a positive start. One user did ask how they could save a page for later reviewing.

Changes for the Mid Fidelity Prototype

With positive reviews throughout, we can refine our prototype with a higher level of mid fidelity, by combining envisioned UI with grid systems right away. We will also include the ability to bookmark a certain page a user would like to revisit later.

Notable Changes

5 new users tested the app with successful task completion throughout, again. This means there isn’t a need to change any major components of functionality. However, useful feedback was provided, mainly the ability to sort through privacy categories, as well as modifying the confusing non-affordance that the “+” symbols implied. Mostly a UI element intended to provide extra context on what constitutes a benefit.


Also, one user mentioned that the wording of “advantages” implies that there should automatically be a “disadvantage”. The same user asked if there could be an option to learn more if one so chooses.


Finally one last user highlighted it could be beneficial to have users access these data tracker terms based on the relevance to the user, ie. through their history. When a user sees the data that’s been collected about them, they are more likely to explore what that specific type of tracker was, and read up about it.

Changes for the High Fidelity Prototype

1. Adding the ability to sort through privacy categories

2. Rewording "Advantages" to "Benefits"

3. Ensuring we don't use symbols that imply false affordances

4. Including a link allowing users to learn more about a selected topic

5. Attempting to include another main flow that serves the same MVP purpose, accessed through a user’s summary, making it more relevant. Though significant, this change could be added in a future iteration due to time constraints.

Brand Identity & Design Language

Colour & Typography

In order to bring the Privy brand to life, I utilized a mood board and a UI inspiration board. Some of the words that stood out were trust, transparency, and literacy. I therefore utilized colours that help portray trust and wisdom, so blue and purple felt most natural. Below are the colours used for the Privy brand.

Colour & Type

Logo & Wordmark

Inspired by the colours and the brand identity, the logo and wordmark came naturally. After sketching some modern designs, the final logo was created from scratch, and so was the wordmark. The wordmark was inspired by the “Rubik” font, but I later decided to build it from scratch, for greater editing and creative control over the font.



Icons were created from scratch. I find myself often doing so as it allows me to have elevated control on dimensions, line weight, colour, and proportions. This helps me ensure that icons feel like they are from the same family. Below are all icons used throughout the Privy app.


Next Steps

What's next for Privy?

If anyone is wondering how the Privy app can actually recognize the trackers in order to showcase them to users in their summary tab, it’s because I haven’t gone in depth on how users could use Privy on several devices. My next step would be to explore the entire user’s journey outside of the app!


To give you a quick idea of my thought process, Privy, as mentioned right above, can be installed on several devices. In theory, it would operate similarly to a VPN, but will ensure it can monitor what is being tracked from your device, in order to relay that information to the user, through the iPhone app. iOS and iPadOS apps will act primarily as a learning and informative hub for users to review their collected data. The desktop version will consist of a browser extension which can monitor trackers as well, all of which can be viewed later on. The addition of an Apple Watch could be useful in order to inform users in a timely manner of when they were tracked at any given point, but remains conceptual, as I do not want to imbue paranoia into users, when they get notifications every few seconds. Maybe it can flag particularly problematic, suspicious trackers communicating with untrusted sources? All this will be considered in later stages.

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