Sift

Sift Size Assistant

Finding the right size is hard. Don’t worry, Sift has you covered!

The Sift size assistant is introduced in the initial on boarding. Users follow the measuring prompts on each screen and input their corresponding measurements. The size assistant is not only a way to mimic in person shopping interactions with a store associate, but also allow Sift to better personalize your sifted items based on your fit preferences. All measurements can be changed in the profile tab of the app.

3D Clothing Search

The entire mall in the palm of your hand!

Using Maxon Cinema 4D I created a 3-dimensional clothing rack. This interaction allows the user to interact with Sift in a way that mimics the in-person shopping experience. The rack is filled with the items that make up your filtered search. By using a 3-dimensional interaction Sift is able to tap into the hedonic needs when shopping online.

Problem Statement - The birth of the problem statement derived from my team's shared experiences with e-commerce shopping difficulties. This project took place at the beginning of the Covid-19 pandemic when the nation went on lock down, which made the e-commerce industry a vital source of daily entertainment and interaction.

Research - We conducted two weeks of various user research methods. Through these methods we managed to understand behaviors, draw user insights & findings, all to create our design framework.

Prototyping -We began by developing wire frames which we then evolved into our low-fi, mid-fi and high-fi screens that were then prototyped.

Evaluation - Finally, we conducted user testing to evaluate and evolve our design ultimately creating the altri ecosystem.

In summary...

Our first research method was a survey. We received 211 responses. The goal of our survey was to collect quantitative data about the connotations between physical and online shopping.

As a team we each conducted user interviews, in total we interviewed 16 different users. This was a semi-structured interview with prepared questions and talking points. To keep these interviews more conversational and natural we used these questions more as a guide. Our goal for these interviews was to find out what parts of shopping are enjoyable, and what parts can be improved. We wanted to understand the general motivators behind leisure shopping.

We then wanted to dive into the user's assumptions and perceptions. We conducted a sensory cue and asked users to assess the differences between the assumed quality, textures, and sizes of products from photos to their actual physical qualities. We did this by first showing the image of the item followed by handing them the physical clothing item.

To find patterns in how users use online shopping websites we conducted a cultural probe. With this method, we aimed to assess the most and least used features within e-commerce. We also wanted to find similarities in ‘enjoyable’ sites from various participants.

Key Take-aways

User Personas
Informed by our research, we created two personas to represent our main users, their needs, frustrations and goals.

User Journey Maps
Informed again by our research and our understanding of our personas we created two journey maps to represent our users.

Ideation
With a core understanding of our problem space and user desires, we as a team began our ideation process. We spent lots of hours formulating concepts and directions and eventually formed the concept Sift!

Wire frames
Our wireframing process was a key phase in our development. We focused a lot on developing the user flow and creating a solid information architecture.

Low - Fi
Once confident in our wireframes I then moved along to create a low-fidelity prototype.

Key Take-aways

1. We must be able to differentiate our product from existing products on the market already.


2. We must provide a useful and concise product without excess features to avoid overwhelming the users.


3. We need to be aware as to not alter the shopping process too much making it unenjoyable for our target audience.

Mid- Fi
Evolving from our low-fidelity and the feedback we as a team received we began creating our mid-fidelity prototyped which we then user-tested on a large scale.

Key Take-aways

What does work...

1. The concise understandable on-boarding process


2. 3-Dimensional clothing rack compared to 2-Dimensional swiping


3. Overall usability and information architecture of the design


4. Comparing items between brands


5. The universal aggregation of products


6. Emphasis on transparency through product reviews

What does NOT work...

1. Needs to be closer to the in-person shopping experience, really no need for something 2- dimensional.


2. More experimental interactions when exploring through items.


3. More emphasis on the personalization of sizing


4. The flow for beginning a hunt needs to be more direct and clear.

High- Fi
Based on our user testing we created a game plan to easily transition into our high-fidelity prototype development.

Key Changes

1. Define a more clear user flow from landing page to creating a Sift.


2. Create a more clear process to identify personalized sizing measurements and preferences.


3. Overall usability and information architecture of the design

Sift Interface
The idea for the Sift interface was to design something that aligned with our 3-dimensional theme of mimicking real-world counterparts of in-store shopping in both how they appear and how the user interacts with them. To convey this feeling for the user we created a Skeuomorphism / Neomorphism interface. Skeuomorphism makes the interface objects familiar to users mental models by using concepts they recognize.

Sift Branding
The aim for Sift’s branding is to keep it clean and fun. Typeface Open Sans and poppins both reflect the idea of Sift by providing a consistent, legible, and friendly typographic voice. The colors remain accessible and friendly, promoting enjoyment and the efficiency of the fashion hunt.

To read more in depth about each step of the creation of Sift visit our process book!