How I Lowered Applicant Rates by 25%, Leading to 38% Faster Talent Matching
- Hching Lin
- Apr 17
- 3 min read
Updated: Jun 22
Key results ✦ 38% faster matching due to a 25% rate decrease ✦ 64% of users updated their rate within 2 weeks
Some context before we start
Arc is a platform that connects companies with top freelance talent. When someone signs up, we ask them to set a default hourly rate—kind of like saying, “Here’s what I usually charge.”
That number gets reused when they apply to jobs, and recruiters also lean on it to find the right match. But we started to realize… this setup wasn’t working so well anymore.
When “set it and forget it” backfires
Here’s what we were seeing:
Freelancers often picked a high rate during onboarding—sometimes too high. That made it hard to match them with jobs.
They rarely updated their rate later, even when their expectations changed.
Many applied to jobs at much higher rates than their default, which confused clients and hurt their chances of getting interviews.
So the “default rate” was starting to feel more like a dead weight than a helpful signal.
How could I make it easier for them to set and update their rate?
After defining the problem, I had two clear goals:
1. Achieve faster talent matching by pushing users to update their default rate regularly 2. Increase interviews/hires by lowering applicants' hourly rates
I had a few hypotheses I wanted to try and validate:
Users are filling in random (often way too high) numbers as their default rate because they have no idea what most jobs are paying.
Users might update their default rate more often if they can always see what their current rate is.
Users might be more motivated to update their default rate when they're actively applying for a job.
Small tweaks, big impact
With the hypotheses in mind, I rolled out a series of changes to the product.
More information in user onboarding
First, I added a graph in the onboarding step to show what most jobs with requirements that fit the users' profile were paying.
To avoid psychological reactance, my strategy was not to "tell" users how much they should set their hourly rate, but to instead provide a reference as to how much made the most sense.
The recommended rate would change based on the user's region, seniority, and skillset. For example, a senior front-end developer would see a higher recommended rate range than a junior iOS developer.
Show their default rate in a prominent position
As the saying goes: "Out of sight, out of mind." So, to remind users to update their default rate regularly, I added a side column to their dashboard showing crucial information such as their default rate, availability, job search status, and job types they're open to.
Every time users logged in to Arc, they would see their settings on the right. And if they ever want to update their rate, they could do so by simply clicking on the edit icon.
If the user had never set a default rate before, they'd see a more visible call to action prompting them to update their settings.
A small nudge before applying
I noticed that some users would apply to jobs at the highest possible rate, regardless of their own default rate. However, companies were significantly less likely to interview these applicants because of budget concerns.
To avoid these types of applications, I added a simple tip at the top: “Applicants with similar profiles usually apply for less than {$50}/hr.” The amount shown in the tip would always be $5 lower than the job's maximum rate.
Fast update with a simple checkbox
Since the user's default rate is always pre-filled when applying for a job, I designed a checkbox that only appeared whenever the user applied to a job at a different rate.
This meant that whenever there's a rate change, I can prompt users to update it as their new default rate.
But that's not all. I also made it so that the checkbox would always be checked by default if the user had just lowered their rate, but would be unchecked if the user increased their rate instead.
This way, we could encourage users to lower their default rate as much as possible, and as a result, increase their chances at getting interviews from hiring companies.
The proof’s in the numbers
We released the series of changes and saw significant results within 2 weeks:
64% of users updated their default rate while applying
12.5% drop in median apply rate
25% drop in median default rate
37.8% faster job matching thanks to more competitive rates
These changes made default rates way more useful—for users and recruiters alike—and helped job seekers land opportunities faster.
