-Craigslist Mobile App-
UX IA - Growing Revenue on Mobile
Evolving Craigslist's Mobile App
Information Architecture 5-Step Design-Process
UX Design & Research Specialist
My UX Information Architecture team at UC Berkeley-x chose Craigslist Mobile for Case Study re-Design - an Information Architecture challenge with deep category dependencies (on a small form-factor).
But Mobile offers Craigslist the Business Value they need—more traffic and easier high-value transactions, on the devices Users' prefer and use most.
So we optimized the IA of CL's Mobile App with UX design by,
analyzing the current IA
better-understanding Users' mental models through research
testing alternate abstract IAs
honoring CL's values with intentional restraint
optimizing revenue-producing tasks:
move Users from 'Seeking' to 'Doing' (faster value 4 business & user)
surface 'actions' (every 'task' has an 'action')
'actions' signify categories, aid Users (ex: volunteer = non-profit)
Design Strategy: Make it easier (more intuitive) and faster (more task-direct) for Users to get Tasks (highest $CL revenue) done on Mobile.
Results: Saw very good find-ability improvement on Tree Test (across the board)
I created an 'Actions' toolbar for faster task-completion - with very good initial effect, needs testing and further wire framing
Recommend: More tests on 'Actions' Tool
UC Berkeley-x UX-IA Team: Margaret Seymour, Claudia Benitez, Noynica Ahuja
Tools: Figma, Miro, PowerMapper Cloud, Optimal Sort, Balsamiq, Google Sheets & Slides, Microsoft PowerPoint
Source: process templates - Rakesh Patwari
1) Conduct Initial Research
Identify Business Value & Key Tasks
Research informed the strategy
The growth of Social Selling on Facebook (and others) significantly increases competitive pressure for Craigslist. Total user traffic in '21 for CL did not reach pre-pandemic levels, although revenue per transaction is up.
We chose to focus on Craigslist's Mobile App information architecture. This was a challenge with 100s of items on a small form factor. But Mobile can increase Business Value for Craigslist best, with new traffic and by enabling easier high-revenue transactions (on devices people use most).
Make high-revenue Tasks on Craigslist easier for Users to Find and Do
Make it easier (more-intuitive) and faster (more-direct) for Users to get tasks (with high CL $revenue) done on Craigslist Mobile
Honor and maintain the values-first simplicity of Craigslist, while updating for more profitable traffic and mobile usage
To respect CL's values-1st mission make it simpler and easier for CL Users to transact with each other in ways that are:
Communal: as 'Seekers' or 'Doers'
Grow traffic by optimizing more profitable and new usage scenarios (Mobile)
Move Users from 'Seeking' to 'Doing' faster
Innovate mobile to 'get things done'
Do UX User Research for inherent needs / mental model
Should we enable new modes of contactless-trusted transactions? Ex.
Optimize community self-regulation
Maximize community ownership
Increase traffic and organic growth
Trusted peer - to - peer
Community - NOT a global Social Media brand
Created 25 common Tasks
Then Created 2 Personas for Most Desired Tasks: Buying & Finding Work
Provided info for User context, goals, needs, pain points
Helped create Tasks in next step - Card Sorting
Highest revenue per transaction for Craigslist?
Most in-demand by Users?
2) Gap Analysis and Tree Testing
Next, we performed gap analysis for the Tasks identified in research
Looked for key insights from our analysis
Important tasks that do not have matching pages?
Included screenshots of the gap analysis spreadsheet
We conducted online Tree Tests with 18 Users, using Optimal Workshop
Used top 10 tasks we identified in research
Analyzed and presented results
Tree Test Results for Top 10 Tasks
3) Synthesize - From Analysis to Sitemap
Planned and performed card sorting, in person and online
Analyzed the results of card sorting
Identified the relationship between card sorting and mental models in an Abstract IA
Created a 1st site map
Created script, finalized tasks, input to Optimal Worship, recruited participants, sent-out
Evaluated 100s of results,
Normalized across 3 different native-language speakers (real-world in The Bay) for 'optimum' label results
-Craigslist has LOTS of CATEGORIES
Confirmed Prior Observations
User mental model of 'Gigs' is confused
Overwhelmingly chose 'Jobs' or 'Services' or 'Volunteer'
Starting with 'Nouns' made sense to Every User
Selling procedure unclear - but Category is not
AND Users went to 'For Sale' (VERB?) to sell an item
Created draft Abstract IA and Site Map
using Mental Models from Card Sort
4)Refine, Validate & Design
From Sitemap to Navigation
Considered different classification schemes and organization structures
Suggested more effective navigation ideas
Evaluated and scored 100's of labels
Using the new labels we updated the abstract IA
And created 2 new Navigation Options
Then performed another round of tree testing with new abstract IA
Note tasks for this second round of tree testing must remain the same
Used same number and many but not all same participants (not necessary)
Compared Tree Testing results - observed how the results varied
Success - which would have been greater
IF 'Actions' had been also a 'correct' choice
5) Design - From Navigation to Wireframes
Considered different navigation models across form factors
Selected optimal navigation options
Created low-fidelity wireframes with Balsamiq