Bidding as a Pricing Model in Staffing Platforms: What Works, What Slows You Down
A few staffing companies asked us to test bidding for job pricing. Here’s what we learned — and how modern pricing strategies can fill more jobs, faster. Bidding gives jobseekers pricing control, but it often adds friction to staffing platforms. Learn what we discovered from testing bidding, why it impacts fill rates, and how smarter pricing tactics like client-driven rates, dynamic adjustments, and price recommendations deliver better results.
What we learned when a few staffing companies asked us to explore bidding as a pricing model
Over the past few years, we’ve helped launch and scale staffing platforms across healthcare, light industrial, education, and more. And while most platforms begin with some form of client-set pricing, a few have asked us something interesting:
“What if we let jobseekers bid on shifts or jobs?”
It’s a reasonable question. At first glance, bidding feels more flexible and fair — empowering jobseekers to say what they’d charge, and giving clients more pricing visibility and choice.
So we tested it.
What Bidding Means — and How It Works
In a bidding-based model, here’s what happens:
- A client posts a shift or job — sometimes with a suggested budget.
- Every jobseeker who applies must enter how much they want to earn for that specific job/shift.
- The client then reviews all the applicants and their requested rates before deciding who to hire.
In theory, this gives workers the power to set their value and gives clients a wider lens to choose from. It looks and sounds like a win-win.
But platforms don’t live on theory. They live on usage.
The Reality of Bidding in Practice
What we learned fairly quickly — and consistently — is this:
Bidding slows things down.
Not dramatically. But just enough to matter.
Workers are asked to enter a rate every time they apply. What should be a one-tap action becomes a micro-negotiation. Clients, in turn, must stop and evaluate pricing every time they want to fill a role — even if they just needed someone to show up on time. The consequences build over time. Jobseekers start dropping off. Engagement dips. Clients delay decisions. And gradually, the system fills fewer jobs — or fills them more slowly.
There’s also the pricing psychology. When workers are asked to set their rate, many shoot high. Not out of greed — but because why not ask for $200 if there’s a chance?
Even if they would’ve happily worked for $80, they end up getting filtered out. And now you’ve lost a match that was perfectly viable — just priced wrong.
Optional bidding doesn’t fix the issue either. If clients expect to see a rate, the optional field becomes functionally required. The result? Same friction. Just slightly more confusion.
The Goal Is Simple: More Jobs Filled. Faster.
Everything a labor marketplace does should orbit around one idea: reduce friction and increase fill rate — without compromising on quality or margin. And when we looked at the data, here’s what we saw: Bidding can sometimes increase fill rate — but marginally. In one test, we saw a 0.4%–0.5% gain in shifts filled. But to get that gain, 100% of users had to take extra steps.
That tradeoff rarely holds up. So instead, we focused on tactics that deliver better results — with less effort from both sides of the marketplace.
A Smarter Way to Price — And Fill More Jobs
Here’s what’s working better:
1. Client-Driven Pricing with Reinforcement
Let the client post a job with a fixed price. Simple. Fast. Familiar. But here’s the twist — if no one applies, the platform can proactively prompt the client with a nudge:
“We haven’t found candidates. You might want to raise your rate.”
Just that nudge increases fill velocity without any extra steps for jobseekers.
2. Dynamic Pricing Built Into the Platform
Rather than waiting for client action, the platform can adjust prices automatically. If a shift gets no applicants — or liquidity is low — the system quietly raises the pay. No friction. Just smart matching under the hood. This approach has led to up to 0.8% higher fill rates on some platforms — nearly double what we saw from bidding, with far less operational drag.
3. Smart Price Recommendations at the Moment of Posting
When a client posts a job, the system suggests a pay rate — based on role, location, day of the week, historical fill rates, and market availability. It’s not arbitrary. It’s based on real data from similar shifts that actually got filled. Clients feel guided. Workers get consistency. Everyone moves faster.
Bidding Isn’t Wrong — It’s Just Not the Smoothest Path
What we saw from testing is this: bidding isn’t broken — it just adds more weight than lift. In rare cases, it helps. But in the day-to-day world of shift-based staffing, it introduces just enough friction to slow things down. The goal is speed. Reliability. Efficiency. And that’s better achieved when workers don’t have to negotiate, and clients don’t have to overthink.
If you’re thinking through pricing models for your platform, we broke down the four major ones — and when each works best — in this guide:
👉 The Price Is (Not Always) Right
And if you want to go deeper — into dynamic pricing, smart recommendations, and how to get more shifts filled without overhauling your model — we’d love to help.
Book a call and we’ll walk you through what’s working now and how you can deploy it inside your platform.
