Redesigning onboarding for a new user segment
Summary
Instawork is an on-demand staffing platform used by blue-collared workers to find flexible work (gigs).
When the onboarding flow for this mobile app stopped working after expanding to a different industry, I helped redefine the user segments, redesigned the onboarding flow to make it work across the industries, and increased the conversion by 400%.
My role
As the lead designer for the project, my responsibilities included:
Company
Instawork
Team
1 Designer,
1 Product Manager,
1 User Researcher (mentee),
A team of developers
Timeline
Q2-Q3 2021 (3 months)
Context
Project background
Before the Pandemic, Instawork was an on-demand staffing platform focused in the hospitality industry. Due to the pandemic, the focus changed to a new industry — Warehousing.
As a consequence, the onboarding flow for professionals (workers) — that used to work well in hospitality — started seeing huge drop-offs.
Problem statement
- The current growth rate of supply — i.e. professionals available for working gigs — is not enough for the projected peak season demand.
- The onboarding funnel has massive drop offs, thus losing a lot of great professionals in the pipeline.
Deep-dive & Hypothesis
As a first step, I teamed up with the Product Manager, and took a closer look at the funnel. And we were able to quickly narrow down the problem to the later part of onboarding - i.e. the part where the user applies for a “position”.
Initial hypothesis
Based on anecdotal evidences like support tickets, app store reviews, etc., the product team had a hypothesis that:
The drop-offs were happening because of a “lack of trust”, since the product was not as known among the warehouse workers as it was in hospitality.
And this had even influenced the roadmap for that quarter.
Digging deeper with User Research
While it was a valid hypothesis, I wanted to conduct more research, to:
- validate if lack of trust is indeed the biggest reason for drop-offs, and discover any other reasons
- identify the underlying reasons for lack of trust, and thus our biggest opportunities to build trust
Interviewing dropped-off users
From my previous experience with onboarding-related changes, I knew that conventional user interviews wouldn’t work for new user experiences.
Because, users who abandoned the app without even completing the onboarding are very unlikely to respond to requests for user interviews.
So I seeked help from the “Supply Ops” team, that used to call up the dropped off users to nudge them to complete onboarding and to help them with any questions.
Usability testing
While the interviews gave a high-level understanding of what the users were looking for, I wanted to dig a little deeper into the specific pain points.
A usability study would be perfect for this. But like any other first-time user experience, this should ideally be tested with a new set of users who haven’t experienced the flow already.
So I used an unmoderated usability testing tool called Userbob, to test the live app with a set of potential users.
Learnings
Seeing opportunities upfront builds trust
Letting users see the available gigs before asking for personal details can go a long way in building trust. This can help in both the old and new industries.
Lack of clarity on current status & next steps
Users want to know when they can start working a gig and how to get there quickly. But, UI and the terminology made it hard to understand the current status and next steps (e.g. “positions” were misunderstood as specific roles rather than categories).
Friction with entry-level requirements
Some of the required details like work experience are perceived as “too much” for working entry level gigs. These details are also tedious to complete.
Redefining user segments
With the above learnings, some of our shared assumptions about professionals started to break, and new personas started to emerge. I evolved this understanding by conducting additional (secondary) research. Here are a few examples of the sources I used.
- “Working/Shadowing a Gig” notes from colleagues in the US
- A large-scale survey conducted by Marketing to understand the new userbase
- My past surveys related to worker profiles and work experience
- Intent questions from onboarding
For the scope of this project, I identified these four segements in particular:
Skilled hospitality professionals
Entry-level hospitality professionals
Warehouse professionals
Newbies
Realigning the roadmap
Now that I had these solid findings from the user research, it was time to revisit the roadmap and adjust the priorities.
First, I discussed these learnings with my PM, and we came up with the updated roadmap, which focused more on getting the professionals to realize value sooner and simplifying the journey to their first gig.

However, in order to quickly test out the original hypothesis around lack of trust, we planned these “quick wins” to build trust:
- Surfacing up “People you may know”
- Social proof (testimonials, app reviews, etc.)
- Quick-glance view of the demand
- Personalized flow for high-intent pros
- Collecting “intent” to help prioritize follow-up calls
Scenario mapping
Before taking this updated roadmap to the leadership and other stakeholders, I worked with the PM to hash out the high-level plan on how the different scenarios (based on a combination of user preferences and the demand in the market) will be handled.
Then I visualized this into simpler user flows to communicate to a wider audience.
Green signal
Through a series of discussions (thanks to Zoom and Slack), using the above findings and visualizations, and with the help of the PM, I was able to get a go-ahead from the leadership for the new roadmap. But we agreed it was important to keep these in mind:
- Quality of the professionals is important for all the positions, but it’s non-compromisable for the “skilled” ones.
- The proposed solution has to be signed off by the Supply ops team - who was also part of this discussion on the new roadmap
- This might require changes to some fundamental assumptions in code, so the solution should be discussed with engineering as early as possible.
Solution exploration
Design goals
Inspiration
Before I start exploring design solutions, I often spend some time looking at other apps (not necessarily competitors) for inspiration. Here are a few of the apps I looked at for this project, and the takeaways from each of them.
Design concepts (lo-fi)
Before I start exploring design solutions, I often spend some time looking at other apps (not necessarily competitors) for inspiration. Here are a few of the apps I looked at for this project, and the takeaways from each of them.
Stakeholder inputs & final direction
Supply ops
Supply ops team owned all the backend processes for the supply - reviewing applications, activating professionals, handling ad-hoc communications and many more. So it was crucial that they’re aligned with any changes we were making to the onboarding process. I also wanted to get their inputs on the pros and cons of the different approaches.
Thanks to the detailed scenario mapping I had done in the previous step, it was straight forward to evaluate the solutions against the different market scenarios and user preferences.
The team’s major concern was that auto-activation (letting professionals book a gig without a manual review) could be risky and might lead to bad experience for customers. After discussing the trade-offs, we came to an agreement that
- auto-activation should only be applied to entry-level work
- even the existing process for entry-level involved bulk-activating anyone who had filled in some basic profile information, so this wouldn’t be a problem
- but the team would continue to asynchronously review the profiles for red flags like inappropriate profile photo
- showing gigs before activation could backfire in markets with low no. of gigs, so the design should handle this scenario carefully
- removing work-experience requirement for entry-level might be ok, but we should roll this out in a controlled manner and check for any impact on worker quality
Engineering
Besides getting a feedback on the overall solutions, I particularly wanted to check the feasibility of showing gigs before activation, because I knew it would require a major change in the “dispatch logic” — the part of the code that determined how a newly posted gig gets dispatched (made available) to the different tiers of professionals.
I learned that the answer is a mix of yes and no. i.e. Letting users see a list of gigs before activation would be straight forward, but letting them see the details page would require major code changes and would delay the release.
But it was super helpful to find this out early on, as I was able to design the MVP accordingly (more on that later).
Design critique
It was a usual practice at Instawork for the designers to present their work (often WIP) to the whole product team of PMs and designers, and sometimes people from the leadership team. I used this opportunity to get inputs on the high-level concepts to narrow down the direction.
Design-approach document
In parallel, I summarized the context and thought process so far in a document and shared it with a wider audience across the organization, seeking feedback
This is a practice I established along with another designer, inspired by the “Technical Approach Documents” from Engineering. The idea was to make the thought process behind the designs transparent to the whole organization, and encourage feedback from anyone.
This also helped with getting asynchronous feedback from stakeholders across timezones.
Final direction
From all the stakeholder and user inputs, it became clear that concept #1 fared better than others, because it
- most clearly communicated the whole range of opportunities (entry-level to skilled) for all user segments
- addressed the immediate need for entry-level workers, but also scaled well for future scenarios and edge cases
- lends itself to iterative rollouts and controlled experimentation (A/B tests)
Task Prioritization
After collating the inputs from all the stakeholders and the learnings from the research, I worked with the PM to identify the different tasks in the project and prioritize them using RICE framework as shown below.

UI design
Exploring new components
There were clear usability issues identified from the user research, so some of the existing UI components had to be rethought. Also, showing the entry-level gigs upfront required a new section.
In order to explore a breadth of design possibilities, I took a modular approach and tried to visualize each of the modules in multiple ways, and then combined the best options to create the final UI.
Revisiting Terminology
Confusing terminology was a recurring theme in the usability issues identified.
In order to explore a breadth of design possibilities, I took a modular approach and tried to visualize each of the modules in multiple ways, and then combined the best options to create the final UI.
- For instance, we had been using the term “position” to refer to a job category (e.g. “Bartender position” would mean all the Bartending jobs on the platform), but most users understood it as a specific job opening.
- There were associated terms like “Apply to a position”, which also added to the confusion - Also, the term “gigs” had come to have a slightly negative connotation due to the negative PR associated with other “gig” apps, and this was a good opportunity to rethink the term.
In order to explore a breadth of design possibilities, I took a modular approach and tried to visualize each of the modules in multiple ways, and then combined the best options to create the final UI.
- replacing “Gigs” with “Shifts”
- replacing “Positions” with “Roles”
- replacing “Apply to position” with “Get activated to work gigs“
Prototype testing
Before finalizing the design, I set up a Figma prototype to validate them with users, especially:
- Does it convey the range of opportunities available on the platform?
- Do people get excited by the opportunities?
- Do people understand what the next step is?
- How do the above things compare for Hospitality workers vs Warehouse workers?
Since a vast majority of the gigs at that time were entry-level gigs, we focused on optimizing the end-to-end experience for these user segments. From the end-to-end design I had made earlier, I picked the relevant parts for MVP and created a new design.
Testing with different user segments
I ran two quick studies (thanks to Userbob again) with two cohorts of users from Hospitality and Warehouse industries.

Final design
Here’s the final design, based on the user research insights, prototype test results, inputs from stakeholders and UI explorations.
Planning incremental rollouts
Though we had prioritized the tasks using RICE framework already, we wanted to be really conscious of the timeline as were approaching the peak season. Using the 80-20 principle, we wanted to identity the 20% changes that would give us the 80% results.
MVP: Showing entry-level gigs upfront
I worked with the engineering team and the PM to identify the MVP that would
- have the highest ROI (using an 80-20 principle), but also lay the foundation for subsequent changes
- validate the hypotheses and nullify major risks
Since a vast majority of the gigs at that time were entry-level gigs, we focused on optimizing the end-to-end experience for these user segments. From the end-to-end design I had made earlier, I picked the relevant parts for MVP and created a new design.
Results
The changes were rolled out with an A/B test — starting with a small % of users seeing the new design, and then ramping up this percentage. I kept a close watch on the data over the next few weeks, and started seeing the conversion rate being significantly higher for the cohort that saw the new design.
The end-to-end conversion (from signup to working the first gig) improved by more than 400%.





































