postup
Removing decision fatigue in finding a space to work
Project Overview
How might we make it easier for remote workers to find great public spaces to work from nearby? That was the challenge posed to me by PostUp for this solo, one-week design sprint.
By questioning assumptions, I reframed the problem beyond the smartphone screen. I drew inspiration from unexpected solutions ranging from Netflix to Amazon, built a prototype of a strategic design solution, and tested it with 5 remote workers.
The sprint resulted in a solution that minimized decision-making time and effort in usability tests, providing a starting point of a strategy for PostUp to launch a competitive, subscription-based app to lure remote workers from Google Maps and Yelp.
By questioning assumptions, I reframed the problem beyond the smartphone screen. I drew inspiration from unexpected solutions ranging from Netflix to Amazon, built a prototype of a strategic design solution, and tested it with 5 remote workers.
The sprint resulted in a solution that minimized decision-making time and effort in usability tests, providing a starting point of a strategy for PostUp to launch a competitive, subscription-based app to lure remote workers from Google Maps and Yelp.
The brief for this project came from BiteSize UX for educational purposes.
Role
I was the sole UX/UI Designer on this modified Google Ventures design sprint.
Methods
Problem framing
UX DESIGN
UX Testing
Device
User forums inspired a design sprint.
PostUp, a young startup where freelancers and remote workers share advice, noticed a lot of communication between users about finding public places to work from.
They wanted to explore launching a mobile app that helps freelancers find great public spaces to work from nearby, for a subscription of $5.99/mo.
I conducted a solo, one-week design sprint to design and test a possible solution.
They wanted to explore launching a mobile app that helps freelancers find great public spaces to work from nearby, for a subscription of $5.99/mo.
I conducted a solo, one-week design sprint to design and test a possible solution.
unpacking research
PostUp's research told a clear story, but not the whole story.
On Monday morning, I started by reviewing the research PostUp provided. It wasn't much. 8 user quotes, one persona, and one usability test with Google Maps. Here's what I noticed:
Users shared common needs: Available seats, WiFi, outlets, restrooms, low background noise, buffer space between neighbors, sustenance, and a work-friendly atmosphere.
But it's hard to tell if a public space will meet these needs with existing solutions like Google Maps or Yelp.
As a result, participants could spend more time looking for a place to work than actually working. Or arrive only to find something they need, like WiFi, isn't really there.
Users shared common needs: Available seats, WiFi, outlets, restrooms, low background noise, buffer space between neighbors, sustenance, and a work-friendly atmosphere.
But it's hard to tell if a public space will meet these needs with existing solutions like Google Maps or Yelp.
As a result, participants could spend more time looking for a place to work than actually working. Or arrive only to find something they need, like WiFi, isn't really there.
initial problem statement
Finding a great public space to work from nearby is time-consuming & unreliable.
initial design challenge
How might we make finding a great public space to work from nearby fast & reliable?
Most remote work shares common needs.
People often do a mix of work types in one session.
Usability Test with Google Maps
The participant struggled to assess if a public space would meet her needs.
Layout?
The test participant scrolled through 12 photos to see the seating layout, but they were mostly of food and drinks.
Wifi?
The test participant dug through reviews to find out if there's Wifi, but it's time-consuming and not always accurate.
Open seats?
The test participant looked at the "Popular Times" chart to assess her chances of finding an open seat. But the graph is based on the line to order food, which doesn't always translate to open seats.
questioning assumptions
The problem went beyond the smartphone.
PostUp's research suggested the reason why finding a great public space to work from nearby is hard is the design of current solutions like Google Maps. I applied Toyota's the five whys and Google Venture's start at the end to question assumptions.
In reality, remote work is a secondary use case of public spaces like libraries and coffees shops. Most public spaces and cities are not well-designed for remote work. Because remote work is a relatively new development, and infrastructure is slow to catch up.
Public WiFi, more outlets, larger commercial spaces, more ergonomic seating, and accessible public restrooms would do more solve remote worker's root problem than an app listing spaces that aren't designed for them.
Reframing the problem suggested a few important questions for my mobile app design.
In reality, remote work is a secondary use case of public spaces like libraries and coffees shops. Most public spaces and cities are not well-designed for remote work. Because remote work is a relatively new development, and infrastructure is slow to catch up.
Public WiFi, more outlets, larger commercial spaces, more ergonomic seating, and accessible public restrooms would do more solve remote worker's root problem than an app listing spaces that aren't designed for them.
Reframing the problem suggested a few important questions for my mobile app design.
Some Critical Questions
Q: How often will a public space exist nearby that meets all of a user's criteria?
A: With some quick research (on Google Maps, of course) I found an average of 4-6 coffee shops within fifteen minutes, walking in NYC or driving in LA.
Given the limited supply, I determined two likely scenarios: (1) There's one clear standout for remote work nearby, or (2) the user will have to decide between imperfect options. In either case, the user may have to compromise one 0r more of their criteria.
Given the limited supply, I determined two likely scenarios: (1) There's one clear standout for remote work nearby, or (2) the user will have to decide between imperfect options. In either case, the user may have to compromise one 0r more of their criteria.
Q: Will the user always be looking for a space nearby and right now?
A: In theory, no. Other use cases could include doing research at home for a future occasion, or searching for place to stop along a route between points A and B.
For this sprint, I decided to focus on the primary use case indicated by PostUp's research: finding a public space to get some work done near your current location right now.
For this sprint, I decided to focus on the primary use case indicated by PostUp's research: finding a public space to get some work done near your current location right now.
How will PostUp provide enough value to keep users paying $5.99/mo instead of using free competitors like Google Maps?
Whether someone uses PostUp or Google Maps, the 4-6 coffee shops available nearby are the same. How can PostUp create a competitive edge?
How will PostUp collect the data that's relevant to remote workers (wifi, outlets, seating)?
PostUp could potentially do their own scouting to launch a beta in one or two cities. Or PostUp could prompt users while they're in a location to answer a question (in the name of helping other remote workers): How many seats are empty? How many outlets are there?
Mapping the current experience revealed pain points and opportunities.
With better context on the problem, I wanted to re-ground myself in the user's experience. I made a simplified Journey Map of the current experience of finding public space to work nearby. This helped me to identify pain points and opportunities throughout the journey.
A journey map helped me identify pain points and opportunities to improve the user's experience.
reframing the challenge
How might we help remote workers decide between what's nearby?
What started as an idealized goal of finding "great workspaces" transformed into a design challenge around decision fatigue.
How might we help remote workers make a quick, low-effort decision between the available public spaces to work from nearby, that leads to a productive and enjoyable work experience?
Given shared basic needs and limited supply (avg. 4-6 public spaces) within 15 minutes, I saw an opportunity to streamline the experience.
How might we help remote workers make a quick, low-effort decision between the available public spaces to work from nearby, that leads to a productive and enjoyable work experience?
Given shared basic needs and limited supply (avg. 4-6 public spaces) within 15 minutes, I saw an opportunity to streamline the experience.
My Solution Map
sketching solutions
I explored design solutions that help people make decisions.
On Tuesday, I found that my hard work understanding the problem on Monday paid off.
Reframing the problem around decisions allowed me to draw inspiration from a broad palette of design solutions that help users make a quick, successful decisions.
Decision fatigue is a thematic challenge across product design. Netflix helps users choose what to watch. Spotify helps users choose what to listen to. Amazon helps users choose which product to buy. The stakes are high: if a user can't make a decision, they leave.
I used "Lightning Demos" to extract a plethora of decision-assisting design solutions, old and new.
Reframing the problem around decisions allowed me to draw inspiration from a broad palette of design solutions that help users make a quick, successful decisions.
Decision fatigue is a thematic challenge across product design. Netflix helps users choose what to watch. Spotify helps users choose what to listen to. Amazon helps users choose which product to buy. The stakes are high: if a user can't make a decision, they leave.
I used "Lightning Demos" to extract a plethora of decision-assisting design solutions, old and new.
Lightning Demos
Sketching Iterations
These ideas were standing out to me
Netflix's One Big Feature
When a user lands at Netflix's home page, one trailer boldly fills the top 80% of the screen, chosen by Netflix's personalized recommendation engine. I saw potential to adapt this to my problem space.
The Shopping Cart
This is no shopping app, but I was interested in the shopping cart as a temporary repository for items users are thinking about buying. Maybe I could adapt this model to help remote workers set aside and compare their final options.
Category Tags
Category tags have become a popular way to learn user's preferences in mobile onboarding flows (especially for apps with all kinds of content, like TikTok) because they are easy to scan and tap-friendly.
Pros and Cons
A classic for a reason. People have been using pros and cons lists to make decisions since 1772, when it was allegedly invented by Ben Franklin himself. This could be a familiar mental model to help users compare multiple, less-then-ideal options.
the solution
One Big Feature
PostUp does the work for the user and recommends the best option for remote work nearby, using a combination of GPS and a personalized recommendation algorithm. PostUp's algorithm uses a range of data to present the best option: proximity, confirmed amenities, likelihood of available seating, reviews, plus the specific user's preferences, previous choices, and feedback.
Providing more photos of a public space's layout, clear indicators of amenities like wifi, outlets, bathrooms, and a prediction of open seats (if technically possible) were also easy wins.
Providing more photos of a public space's layout, clear indicators of amenities like wifi, outlets, bathrooms, and a prediction of open seats (if technically possible) were also easy wins.
Solution Storyboard
With my solution decided, I sketched a storyboard of the main screens in preparation for building a prototype.
building a prototype
I built a rapid prototype to test my solution of "One Big Feature"
On Thursday, I built a rapid prototype to test with users. This step was exciting. But the central role of location, photos, and decisions in this solution presented unique prototyping challenges.
Stock photos needed to create realistic distinctions between spaces, without giving one an unfair advantage. I was testing the design, the not the photos. At the same time, the space the algorithm chooses to feature should, in theory, be the best space.
And of course, the time constraint of prototyping in one day required some sacrifices.
Stock photos needed to create realistic distinctions between spaces, without giving one an unfair advantage. I was testing the design, the not the photos. At the same time, the space the algorithm chooses to feature should, in theory, be the best space.
And of course, the time constraint of prototyping in one day required some sacrifices.
Alternate Views
As a control, I decided to include some other solutions to see if participants would use or prefer them. Would users prefer seeing a map to visualize the relative distance of their options? Would they use a filter to make their results more specific? Or use a shortlist to organize their top choices?
Getting Ready to Test
I can't say the prototype was perfect. But testing with it did provide valuable new insights, so it achieved its purpose.
TESTING THE SOLUTION
User testing indicated that users need more context to build understanding & trust
It was time to test how users respond to my solution. Earlier in the week, I'd set up usability tests with 5 remote workers in varying professional fields.
The Task
"Imagine you have a few hours between meetings, and you are looking for public place to do some work. What would you do?"
What Worked Well
Participants found the design easily scannable due to amenity icons, spatial photos, pro and con lists, and seating types diagram.
Participants made a decision in under 5 minutes, and felt it was easy.
Participants made a decision in under 5 minutes, and felt it was easy.
What Needs Improvement
The "One Big Feature" solution needed more context for users to understand it, and this limited its success.
- Location uncertainty | 4/5 participants asked, "So this is near me? at the home screen
- Ad mental model | 3/5 participants thought the one big feature was an ad, at first, then later decided it wasn't)
- Hidden logic | 3/5 participants wanted to know how the featured suggestion was chosen
Did the solution succeed?
Overall, the "One Big Feature" solution showed potential. 3/5 users ultimately chose the featured option. 2 participants chose one of the 4 other options. All participants made a decision in under 5 minutes.
next steps
A strategy & insights in one week
With the one-week sprint complete, my next steps would be to create more context and trust though an onboarding sequence and design changes in the primary screens.
I judge the effectiveness and value of usability testing by how much I learn. It's normal for usability testing to feel humbling. The goal of this step is learn something of value, test your assumptions, and improve the product.
A Design Sprint is a great methodology to get to these insights faster, so you can debunk assumptions and iterate to better solutions.
I judge the effectiveness and value of usability testing by how much I learn. It's normal for usability testing to feel humbling. The goal of this step is learn something of value, test your assumptions, and improve the product.
A Design Sprint is a great methodology to get to these insights faster, so you can debunk assumptions and iterate to better solutions.
Let's connect
I encourage you to reach out to me about a project, role, or just to say hi
