An app for finding the perfect gift.  Prezent: polish word for gift. 


Info: Class project for CS6755 HCI Foundations taught by Dr. Bruce Walker in the Fall 2017. 

Team Members: Meghan Galanif, Maria Wong, Ethan Graves, Nikhila Nyapathy

My Contributions: Ideation, Background Research, Survey Development, Survey Data Analysis, Sketches, Storyboards, Design of Evaluation Plan, User Testing Facilitator.

The Problem

People have a hard time deciding on a gift to purchase for a person when they have limited information about the person


The users of our system were identified as those who have limited knowledge about the person they are shopping for, but who still genuinely care about the purchasing a gift that match their preferences.  Examples of these types of users include:

  1. People who have newly joined a family.
  2. People who are new to a workplace and are purchasing a gift for a coworker.
  3. People who are busy and want a 'quick and dirty' way to select a good, meaningful gift.
  4. People who are not in close proximity to a friend, and are thus not aware of their current interests.
  5. People who are financially independent with disposable income.
  6. People comfortable with the idea of social media.

Discovery & Background Research

We performed 14 semi-structured interviews to find out how people shop for gifts.  We wanted to find out pain points and current methods. We also did on-site visits to store toy departments and surveyed websites for gift buying, such as, to see the current state of affairs.

We also designed and deployed a survey that had 215 respondents. 


Finding Insights into Gift Shopping

The team did an affinity mapping exercise to discover insights in our survey and interview data.


Insights From Qualitative Data

  • Common theme of gift attributes: wanting the item to be unique, sentimental and appropriate.
  • Common goals of gift giver: wanting gift to be useful, well liked or fun.
  • Decision making process and deciding factors that dictated whether they would purchase gift online or in-store.  We identified different buying approaches such as "buy now gift later."
  • People have methods of communication before and during the gift selection process in order to get information to support a gift buying decision, for example, contacting the parent of a child to ask for a gift suggestion. 
  • Gift givers leverage small bits of information about the giftee to support gift buying decisions. 

The Pivot

We started looking at people who do not have kids trying to purchase a gift for kids.  However, after some background research, we discovered that the problem of buying a gift with limited information can be applied to a more broad set of users and use cases than just kids.  Thus, we pivoted our scope to include people trying to purchase a gift for a person whom they have limited information about.


Task Analysis


Important Characteristics of the Problem

We identified the key elements of a successful gift shopping experience to be:

  1. The information pipeline between the gift giver and gift receiver.
  2. The identification of gifts that will fulfill the goals of the shopper.
  3. An easy process for gift shoppers to confidently identify and obtain gifts, either products or experiences, that fulfill both parties' requirements.

Functionality of the System

Our system design aimed to provide the following functionality:

  1. Provide the user information about the gift receiver's preferences.
  2. Allow the user to input information they already know about the gift receiver.
  3. Keep the user anonymous to the gift receiver.
  4. Assist users in making an informed decision.
  5. Aid the users in making a fast decision.

Preliminary Design Criteria

  1. Flexible: Fits multiple shopping styles and habits.
  2. Learnable: A user can complete a task in a reasonable amount of time, regardless of their technical background.
  3. Familiarity: Leverage the frequent use of mobile and web applications to reduce the amount of learning required, and use a familiar interface look and feel according to the system's purpose.
  4. Efficient: Reduce the amount of time users spend selecting a gift.
  5. Effective: Help reduce the stress of finding a gift for a person.

Initial Brainstorming

We met as a team and conducted a brainstorming session to come up with as many ideas as possible.  We then listed the ideas in a spreadsheet, and each team member picked their top five ideas with a checkmark.  We then chose the three ideas with the most checkmarks to continue with sketches and mockups.


Ideation Round 1

We got together as a team, and narrowed down to three ideas:

  1. Social Media Scanner - users could select a friend and which social media platforms to scan, and the system would automatically read and analyze all posts, pictures, and likes to generate gift suggestions.
  2. Anonymous Messaging - a social media application where users could make connections with one another in order to send anonymous messages regarding gifts to one another.  Users could also maintain an outward profile of likes and facts about themselves relevant to gifts, such as shoe size and birthday.
  3. Virtual Assistant - this idea ranged from an in-store kiosk where shoppers could look up gift suggestions and in-store locations, to an app that would tell users local locations and availability of a specific gift.

We started with a first round of sketches where each team member diverged and made a rough sketch of each idea.  We then got together to present our sketches, made critiques and further brainstorming, and synthesized our ideas into a second iteration of sketches. 


Ideation Round 2

We repeated the first round of ideation with a second round of sketches for each of the three ideas.  These sketches were meant to be more detailed than the first round, but still not refined sketches in order to decide on general layout and main functionality of each idea separately.


Refined Ideas

Next, we took our three ideas and fleshed them out more, creating storyboards around the use scenarios, and mocking up wire frames for each idea.  We then presented the wire frames and storyboards to potential users to get feedback on the ideas and main functionalities, and to see what potential users thought of each idea.

1. Anonymous Messaging App


2. Social Media Scanner

Wireframes generated using Balsamiq (Nikhila Nyapathy)

Wireframes generated using Balsamiq (Nikhila Nyapathy)

3. Virtual Assistant

Storyboard by Maria Wong

Storyboard by Maria Wong


We again took our three designs to six different people who represented our users for feedback.  These potential users were asked the following questions in order to gauge usefulness and usability:

  • Would you use this system?
  • What do you like/dislike about this system?
  • Are there any particular features or functionality of this system that you would like or find useful?
  • Do the features of this system make sense to you?

As a team we presented our findings and looked for any themes and insights that stuck out based on the surveyed potential users.  We found the following key insights:

  • The social media scanner was found 'creepy' but potentially useful.
  • No one thought they would use the anonymous messaging - there was not enough incentive to do so, and some users thought it may be too much work.
  • The in-store kiosk was found to be clunky and unnecessary - users wondered why they could not just use their phones to find the same information.
  • Users liked the idea of keeping an outward profile of their likes, as long as it was easy and 'fun' to do.
  • Users liked the idea of knowing where to locally find a particular gift, especially if they were in a city they did not know very well.

Final Idea Synthesization

We discussed which elements of our findings were important to our system, and which elements were feasible, in terms of prototyping and evaluation.  We then made a preliminary synthesizing of our of our original three ideas, picking out the aspects of each that were found important based on the user feedback sessions.

Our first iteration took aspects of all three original ideas:

  • Social media aspect: a user could maintain an outward profile of likes.
  • Users can make connections and have a list of 'Giftees.'
  • Recommender: Users could get a gift suggestion for a friend based on either their outward like profile.
  • Input known information: User could input information they know, such as relationship to giftee and gift occasion. 
  • The system could suggest local stores carrying the gift item, and where in the store it was located, and its current price.

Prototype & Implementation

The screens were designed using Sketch and the prototype interactivity was implemented using Axure

Prototype screens (implemented in Sketch)

Usability Specifications

  • Users should find the app easy to use and navigate.
  • Users should be able to maintain a profile including their birthday, profile picture, shoe size, and other optional personal data.
  • Users should be able to create a database of their likes, in the form of picture tiles representing those likes, in a quick and easy manner. 
  • Users can edit, add and remove picture tiles of gift areas of interest.
  • Users can enter information they know about a potential giftee when prompted by the system after they indicate they would like to give a 'new gift.'
  • Users can tap a gift recommended by the system and see local stores that may carry that type of gift.


There were several types of data we wanted to collect during evaluation, both qualitative and quantitative:

  • Did users find system enjoyable and user-friendly?  Here we wanted to see if the buttons, labels and actions were clear to users, and if the steps to complete actions made sense.
  • Did users trust the system?  We wanted to know how users felt about gifts recommended by the system.  How much transparency does the system need about its recommendations? 
  • How useful is the system?  Here we wanted to know how likely people would be to use the system.  Do users think it would cut down on their time and stress looking for gifts?

In order to evaluate the prototype, we employed expert evaluations and usability tests.  For expert evaluations, we chose a heuristic evaluation in order to identify any issues in usability based on Nielsen and Normans 10 heuristics.  

Moderated Usability Testing

We recruited five potential users to take part in usability testing of the interactive prototype.  The structure was as follows:

  1. Introduce the app and allow participant to do a think aloud walkthrough of the prototype for a few minutes (roughly two minutes).  
  2. Explain context, introduce a potential friend, Sasha Sparkes, and ask participant to complete three tasks and answer a questionnaire set after each task to measure ease of completion, and trust with the system (for task 1 only):
    1. Task 1: Use the Prezent app to find a store location of one recommended gift for Sasha Sparkes. 
    2. Task 2: Locate the date of Sasha Sparke's birthday.
    3. Task 3: Add 'Yoga' as an interest to your profile.
  3. Participants were asked to respond to a set of Likert scale questions and a set of open response questions regarding their experience with the prototype.  We were trying to collect data regarding how the app compares to their current way of gifting, details about if they trust the system, how enjoyable the system was and how potentially useful they found the system.  
  4. We concluded with the System Usability Scale (SUS) in order to have a validated scale's measure on the usability of the system.


We synthesized the results of all of the usability tests to drill down to common themes that were found that could be improved upon on the next iteration of Prezent.

  1. The application needs to build trust with users. Users want more justification for the gift ideas before they feel confident enough to pick one.  One possible solution would be to provide some type of visualization or background information regarding the justification of the gift idea.   

Conclusion & Next Steps

The prototype does not include the algorithm for gift recommending, it only simulates it.  However, if the project were to be moved forward, what potential trust implications would we want to keep in mind when further developing the recommender algorithm.

Team Acme Redesign on poster presentation day!

Team Acme Redesign on poster presentation day!