Off-platform Reputation & Budget Signaling

Understand the Talent Manager's process for finding and vetting talent, to locate their pain points.

Take their process and simplify it into an intuitive user-centric flow, so freelancers can manually input their data.

Interviewing 10 high-value clients, showed what experience they wanted to see from experienced freelancers ranging from backend to front end, so I iterated low-fidelity wireframes to do user testing on 8 experienced freelancers to see if they saw value in going through different flows to be more visible to high-value clients.

What we found from user testing was… • High-value clients were looking for other examples of work/experience in other apps • Experienced freelancers were interested in going through an application flow, as long as it didn't take too long

Pre-screen freelancers to go through our assessment process so our Talent Managers can fast-track them to become Expert-Vetted. I designed an MVP with a front door in job search for freelancers to enter their minimal off-platform work experience as a demand test.

In user testing, users wanted to learn more about the benefits and process, so I added a welcome screen, steps screen, and more options to share their experience in other apps.

Once we met critical mass of user engagement, I added years of experience, review, and step counter.

Hiring rate of high-quality freelancers increased from 4.2% to 23%, leading to higher revenue for Upwork.

Problem: As a client that's posting a job, I see that the budget section is directly linked to the expertise level. Because of this, it's difficult to make tradeoffs between dollar amounts and the expertise needed for a particular job, because it's so ambiguous.

UX Challenge: Provide better rate guidance to clients, so they can make a more informed decision between their budget and the experience level they're looking for. Research: In past research, we saw that clients often start with a rate in mind, but make tradeoffs in price when presented a freelancer with the right skills and experience, after they posted a job. This led us to the hypothesis that we need to do a better job informing the client before posting a job, to get the best results.

For this project we asked 10 hiring managers (5 users, 5 non-users) some key questions: • What is their process and expectations when deciding an hourly range? • How well do they understand the expertise tiers? • Do they understand that the specific inputs cause the suggested range to go up and down? • How helpful is a suggested price range?

After distilling the research, we concluded that clients wanted more guidance and autonomy when choosing a budget. So we did usability testing on this design that showed a histogram that suggested an hourly range based on their previous inputs, with handles to give them complete control, as well as tabs to toggle between each expertise tier. 8 out of 10 users didn't know that the graph changed when they tapped through the tabs, and 8 out of 10 users did notice the dynamic fields below the graph change.

So we went back to the whiteboard and simplified things a bit, by eliminating the tabs and separating each section. Once we felt confident in the moderated testing, we switched to non-moderated to confirm this was the best solution. The result after a 60-day A/B test was an 8% lift in invitation acceptance rate, 10% lift in spend per job, and 15% lift in fill rate.

My Part: Designed the end-to-end experience from research and usability testing to prototyping, working with PM and Engineers. Result: First Job Post (which is a very big metric) went up 9%, and client spend went up 5%. This was initially rolled out in the U.S., but because of its success, we are rolling it out globally and using the histogram in other parts of our product.