Carousell

Design Challenge: UX Personalization

Carousell is the LetGo of Singapore and Asian-Pacific. They are a mobile and web C2C platform for the buying and selling of new and secondhand goods.

My Role

I was approached by the team to conduct a design challenge.

I spent eight days going through my design process to come up with a proposed redesign of their iOS app to solve the problem provided.

Explore the Problem

Before diving into the design process, I studied the information provided to me to extrapolate goals and additional assumptions. I moved forward with a couple of new assumptions as I believed the user behavior observed may have been influenced by other factors.

Goals

  1. Better the user experience by providing a more relevant and personalized browsing experience
  2. Make it easier for users to discover and find items of interest

New Assumptions

  1. A significant portion of users who reach the homepage have the intention of buying specific items
  2. Users with specific items in mind to be purchased will usually opt to use the search bar

Research

Existing Research

I researched and found existing studies that would validate (or invalidate) the assumptions, as the validity would influence the design decisions made to address the needs of the user.

Assumption #1

 A significant portion of users who reach the homescreen have the intention of buying specific items

Research findings:

Researched data suggests that millennials make up a majority of purchase intenders, and roughly half of millenials do not browse online for entertainment-shopping. Assuming this is true of Carousell users, then it is likely that a significant portion of users landing on the homescreen have intent to purchase specific item(s).

See research data below:

Assumption #2

 Users with specific items in mind to be purchased will usually opt to use the search bar

Research findings:

In a research performed by Stanford University and Pinterest personnel around almost 3 million Pinterest users and their browsing/ purchasing behavior, it was found that users with built-up purchase intent exhibit more searching and click-through behavior at the expense of browsing and content saving

Usability Tests + User Interviews

Without access to the Carousell user-base, I opted to further validate my assumptions by usability testing and interviewing a comparative demographic: millenial, online-shoppers who are users of C2C platforms such as Letgo, Craigslist, and Mercari.

Assumption #1

A significant portion of users who reach the homescreen have the intention of buying specific items

Answers collected support the assumption that there is a significant portion of users who shop online only when they have purchase-intent for specific item(s):

Assumption #2

Users with specific items in mind to be purchased will opt to use the search bar


Users' behavior in response to the below scenarios further validate assumption #2, as users with purchase-intent used "search" significantly more than "browse".

Assumption #3

Content on the Homescreen lacks personalization and relevance

I ran users through scenarios that encourage browsing during testing and followed up with questions around relevance of content presented on the homescreen:

According to usability testing, there is room for improvement in terms of personalization of homescreen content.

Research Summary

  1. Assumption #1 and Assumption #2 are supported by both online research and usability testing/ interviews. This suggests that most buyers may be using the search bar more often than exploring because they have purchase-intent for specific items
  2. We also have some qualitative feedback from usability testing for Assumption #3 that suggests the homescreen content can be more relevant and personalized

Additional Findings

Empathize

USMO to Job Stories

After research, I had a better understanding of shoppers and their behaviors.

I did used the USMO and job story framework to get into the mindset of the users and see what the ultimate desired outcome would be for a shopper on Carousell.

User Journey Map

Leveraging my understanding of user behaviors from research and empathy, I created a journey map

depicting common behavior exhibited by e-commerce shoppers. Doing so helped me visualize which areas were in need of improvement so that I could map potential solutions to them.

Ideate + Create

Hi-Fi Mockups

Research validated that users were probably not browsing the homescreen because they had specific-item purchase intent. As such, in order to achieve the ultimate goal of providing a personalized and relevant user experience, my proposed solutions branched out from simply personalizing the homescreen.

The app has a wealth of demographic and behavioral data that was not being utilized effectively. I tried to leverage such data to personalize the user experience in my designed solutions:

Home Page

* - Behavioral data may not directly suggest that a user would enjoy items related to gardening, but if other Carousell users who exhibit similar behavior also typically look at gardening items, then there is a higher likelihood that this specific user would also be interested in this content. The same extrapolations could be made at the listing-level to curate a "For You" section that pushes relevant and personalized items to users.

Listing Details Page

Likes Page

Validation Plan

Prioritization

I used a 2x2 matrix and made some assumptions around cost of implementation and impact of feature on KPIs in order to prioritize the features

1. Sub Navbar – (in place of carousel)

2. Customized Homescreen Layout

3. Similar Listings” – (on Listing Details page)

4. “You May Also Like…” – (on My Likes page)

5. “For You” – (recommendation tab on new sub navbar)

Feature Flags

The impact of my designs on the user experience would have to tested and measured through controlled AB testing in order to obtain statistically significant results.

I would elect to AB test and roll out the features via feature flags, which are often used by e-commerce apps to display customized layouts and content to users based on user data. It further allows for the ability to roll out and test in a controlled environment while reserving the capability of turning off the features completely at any time.

AB Test Plan

I wrote out a high-level test plan for my design complete with hypotheses, KPIs considered, expectations, and risks for each of the features designed:

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