Case study

Optimising user activation for a B2C flexible staffing app

I led the UX and product design for a project focused on optimising user activation for a B2C flexible staffing app. The company behind this app offers a dynamic shiftworking marketplace connecting hospitality venues with skilled staff, ensuring venues stay happy and profitable while connecting to a pool of flexible talent.

The project was focused on the worker app and its primary goal was to increase user activation and reduce initial drop-off rates, so that workers would be happier, the community would be more vibrant and the talent pool would become larger.

Key results 1 month from launch

17% increase in activation rates
31% decrease in drop-off rates
Increase in user satisfaction and engagement

Methods

User Research
Journey Mapping + User Flows
Visual Design + UI design
Usability Testing

Collaboration & Timeline

I collaborated closely with 2 Engineers, 2 people in the Activation Team and the CEO, who was the main stakeholder. This was part of a larger onboarding initiative and took around 3 weeks, with 1 week of design/research and 2 weeks of development, in 2019.

This case study has been anonymised for confidentiality purposes. The name of the company and product has been omitted while maintaining the integrity of the project outcomes.

The challenge

Satisfaction for active users was high, but we were experiencing 85% drop-off rates. Out of all app downloaders, 55% created an account, 47% of them initiated profile creation, but only 32% completed it and booked their first job.

What was happening?

From previous research, we observed that if a person booked a job within the first week after verification, they would then book 3 more jobs on average in their first month and would be more likely to stick with the app.

In order to support the key activation action of booking a job for the first time, we asked new users to verify their identity straight away, but they couldn't browse jobs until verification was complete.

This requirement led to a drop-off rate of 85% – the percentage of users who abandon a process before completing it – as people were unprepared for verification and frustrated by extended wait times, negatively impacting retention and conversion.

Our goals

⬇️ Reduce friction and drop-off rates

⚡️Increase user activation rates (by increasing the number of people who completed their profile and booked their first job)

⭐️ Set people up for success, making sure they could start using the app on day one

💎 Increase user retention rates

Key metric to measure success ⬇️
Percentage of first job bookings compared to app installs

Our users

Who were the people using the platform? We identified 3 main archetypes.

The student – Looking for a few shifts to help pay for education. Any type of work will do. More likely to hop between different venues. Often has a fallback.
“As a student, I want to find part-time flexible jobs so that I can help pay for my education and afford to do what I like.”
The skilled worker – Working hospitality full time. Highly skilled in their field. Likes to work in the same venues. Committed to their career and advancement.

“As a chef, I want to work a flexible full-time job so that I can earn and keep doing what I love, where I want.”
The side hustler – Has a main job (often within the arts) and wants to supplement their income. Likes to switch between roles. Doesn’t mind various venues. Likes to travel and take month-long breaks.

“As an artist, I want to find flexible jobs so that I can supplement my main income and afford to travel when I want.”

Research & pain points

To uncover key pain points and validate our initial assumptions related to the identity verification, I conducted moderated usability testing with 10 highly motivated new users – three students, four skilled hospitality workers and three side hustlers.

Observing them navigate the onboarding revealed that they were unprepared for identity verification, unclear on why it was required and frustrated by having to provide documents and having to wait for extended times.

The identity verification bottleneck

As we thought, the identity verification process was the main pain point, confirmed by some lightweight quantitative research as well (quicker verification times of 1-2 days led to higher happiness levels compared to longer durations of 4-5 days).

Not only was this a bottleneck, but we were not managing expectations properly. The manual verification process took 1-5 working days and created significant friction, contributing to drop-off rates.

Ideation & Design

After analysing the insights, I ran a whiteboard session with the team.

We decided to:

streamline the identity verification process and kickstart it only after users clicked to Apply for a job
expedite the onboarding (with possibility to skip sections and complete them later)
simplify the profile completion both from a UX and UI perspective

💡 We explored instant verification tools but had budget constraints, so we set a reasonable goal to manually verify users within 48 hours. Over the following three weeks, everyone would dedicate at least two hours per week to verifications, allowing us to measure metrics and assess the impact.

After this, I sketched the updated user journey and proceeded to design the new user interface, iterating along the way.

The updated funnel ⬇️

Step 1 ➡️ Users install app and create profile
Step 2 ➡️ Users browse jobs and click on Apply
Step 3 ➡️ Users upload verification docs
Step 4 ➡️ Ensure user verification within 48 hours
Step 5 ➡️ Verified users book their first job and get paid

The results

We transformed a complex identity verification process into a streamlined flow triggered when users were highly motivated.

Within one month from launch:

📈 Activation rates increased by 17%, from 8% to 25%

📉 Drop-off rates were reduced by 31%, from 85% to 54%

Making the onboarding flow more relevant, managing user expectations upfront, improving the overall UI and boosting job awareness were also key in the process.

Takeaways

⚡️ Instant verification was crucial to prevent user frustration and churn, highlighting the need to evaluate the cost-effectiveness of solutions like Onfido for the future.

✏️ The onboarding and profile creation were still long – we needed to iterate on it, making it more engaging, and always manage expectations.

👀 Continuously monitoring key metrics and gathering regular feedback were essential for maintaining user satisfaction and guiding future iterations.

Check out the UI designs 👇