A retail chain filled 40 seasonal openings through Paylocity Recruiting last fall. Most applicants who didn’t get an offer remain in their candidate profiles, which nobody revisits. When hiring season returns, store managers repost the same roles instead of checking who applied last time.
This practice costs money in a high-turnover business. Paylocity already has the resumes, application history, and contact details from the last hiring push. Reposting instead of revisiting means paying for job board listings a second time for the same candidates.
This expert guide explains what Paylocity Recruiting offers for finding qualified applicants already in your Paylocity account. It also highlights where that native toolset falls short and how an AI integration can fill these gaps.
What Is Candidate Rediscovery?
Candidate rediscovery means matching people already stored in your recruiting platform against a role that just opened. It covers applicants from filled positions, candidates who made it partway through a hiring process, and anyone whose resume sits in a candidate profile from a past posting.
Your candidate data becomes a real sourcing channel once those past applicants get checked against new openings automatically. Most recruiting platforms let a hiring team pull up old records by hand, if they remember to look. Rediscovery removes the "if" and does that check every time a role opens.
Does Paylocity Recruiting Provide Candidate Rediscovery?
No, Paylocity does not provide a candidate rediscovery feature or tool. It offers candidate profiles that centralize a person's resume, application history, and communication in one place, plus dynamic reports that hiring teams can customize to pull candidate data.
Neither of these features works as a search tool for the past applicant pool, and no keyword or Boolean search exists across historical candidates.
Paylocity is built for high-volume, high-turnover hiring in industries like retail, hospitality, and senior living, where the same seasonal or entry-level roles reopen again and again. Without a way to search past applicants against a live requisition, a hiring team's only option is to start sourcing from scratch for every hiring cycle.
How to Rediscover Candidates in Paylocity Recruiting
Since Paylocity Recruiting has no way to search or score qualified applicants in the database, teams integrate Skima AI to scan that candidate history automatically every time a role opens. Below is a 5-step workflow, from connecting your account to acting on results:
Step 1: Connect Your Paylocity Account With Skima AI
Generate OAuth2 credentials, a client ID and secret, from the Paylocity Developer Portal. This connection uses Paylocity's own APIs directly, with no middleware required. Skima AI requires both read and write access to function.
- Read access: Candidate, Job Requisition, and Application records, including resume attachments
- Write access: Candidate custom fields, tags, and activity notes
- Pulled data: candidate contact details, resumes, application status, and job requisition details for scoring context
- Event notifications: trigger scoring when an application is created or updated, a job status changes, or a resume is attached
If event notifications are not enabled, Skima AI falls back to safe polling for updates.
Step 2: Configure Custom Fields and Confirm the Connection
Create the candidate custom fields Skima AI writes to, or let Skima provision them during setup. These are Skima AI match score, a number from 0 to 100, and reasons explaining the fit. A SKIMA Screened tag gets added at the candidate level, so screened applicants stay filterable inside any Paylocity view your team already uses.
Optional HM Feedback and HM Comment fields capture manager responses once a shortlist goes out. If your Paylocity setup restricts custom fields, Skima AI falls back to writing an activity note or attaching a SKIMA_Evidence.pdf instead.
Before rolling this out further, test it on two or three open roles. Upload a resume, then confirm the match score and Reasons actually populate on that candidate's record.
Step 3: Launch Talent Rediscovery Against a Live Requisition
Open the job inside Skima AI, from the Jobs list or from within the job itself. Click the three-dot Actions menu and select Rediscover Candidates. A modal lets you scope the scan two ways. Limit it to a saved candidate segment, or leave it open to every synced Paylocity record.
Set the Candidate Created Date range next: All time, Last 6 months, Last 1 year, or a custom window, then click Apply. Skima AI scans the selected pool against this job's specific requirements and sends a notification once the scan finishes. Refresh the page to see the results.
Step 4: Review and Filter the Rediscovered Matches
Open the View Candidates tab to see a ranked list pulled from across your entire applicant history. Each candidate carries an AI match score and reason bullets explaining the fit. Filter by Industry, Work Mode, Experience Level, Notice Period, Location, and Salary Range.
Start broad and tighten the filters gradually. Narrowing too fast hides good candidates, especially in high-volume hiring where last season's near-miss often fits this season's opening.
Step 5: Shortlist and Sync Feedback Back to Paylocity
Build your shortlist from the ranked matches Skima AI surfaced. Generate a secure, no-login link and send it to the hiring manager. They can click a thumbs up, thumbs down, or maybe on each candidate, with an optional comment.
Skima AI writes that decision back into Paylocity through the same API connection for the audit trail. It updates the candidate custom fields and logs an activity note, so the feedback remains on the record without anyone needing to use a second tool.
What If Your Paylocity Database Is Messy, Duplicated, or Stale
Paylocity does not provide duplicate detection or a merge workflow for candidate records. For an employer with high turnover who posts the same seasonal jobs year after year, duplicate records can accumulate quickly. The same person may apply multiple times across different hiring cycles, each time generating a new candidate profile instead of updating the existing one.
Stale data compounds the problem further. A candidate profile from two hiring seasons ago carries a phone number that no longer connects and a resume that reflects a job the person left months ago. Nothing in Paylocity flags this automatically, so a recruiter only catches it by noticing the same name twice while scrolling through applicants manually.
Skima AI treats this as ongoing maintenance rather than a one-time project. It matches on email, phone, or LinkedIn URL first. It also checks for matches across name, location, and company as a backup signal.
Further, a field comparison modal appears before anything merges, flagging exactly what differs across the two records. Missing details get filled in through contextual profile enrichment instead of staying incomplete. A dedicated Duplicates tab logs every resolved case for later audit, split across In Database, From Uploads, and Resolved sub-tabs.
5 Benefits of Candidate Rediscovery with Skima AI in Paylocity
Takent rediscovery with Skima AI changes what a Paylocity team can do with its own applicant history in 5 specific ways:
- Faster Time-to-Screen: Rediscovered candidates arrive already scored, so recruiters skip the raw resume pile entirely. In a documented 30-day Paylocity pilot, a team reduced time-to-screen by 58%.
- More Interviews From the Same Shortlist: The same pilot saw interviews from the top shortlist double compared to the prior process.
- Explainable Match Scores With an Audit Trail: Every rediscovered match carries reason bullets tied to skills and experience, plus a SKIMA Screened tag for instant filtering inside Paylocity.
- Hiring Manager Engagement Without a New Login: The shortlist feedback loop keeps managers responding through a link, no Paylocity credentials required. Manager satisfaction rose 24 points on NPS in that same pilot.
- Lower Cost Per Hire for High-Volume Employers: Rediscovered candidates were already sourced once, so filling a seasonal or repeat role this way needs zero new job board spend.
5 Best Practices to Rediscover Talent in Paylocity Recruiting
None of these benefits happen automatically inside Paylocity without a few deliberate habits. The 5 practices below cover search timing, data hygiene, and fitting rediscovery around a high-turnover hiring calendar:
- Scan Before Reposting Any Seasonal or Repeat Role: If your business rehires for the same positions every season, run Skima AI's Talent Rediscovery before reposting. Last season's applicant pool often has someone ready to return.
- Turn On Automatic Rediscovery for Every New Job: Skima AI's setting under Preferences and General starts a database scan the instant a new job is created. Enable it so no requisition slips through without a first look at your existing applicant pool.
- Use Reverse Search When a Strong Candidate Does Not Fit the Role They Applied For: A candidate who applied to one location or shift often fits an opening at another. Reverse Search starts from that one profile and returns every open job they match, ranked by score.
- Segment Scans With the Candidate Created Date Filter: Choose a 6-month or 1-year window when a role needs someone who was recently active. Widen to All time for a role where the qualified pool has always been thin.
- Review the Duplicates Tab After Every Hiring Push: High-volume postings generate duplicate applications fast, especially across seasonal cycles. Checking the In Database sub-tab right after a hiring push, rather than waiting for the next one, keeps the merge queue manageable.
Is Candidate Rediscovery Worth It for Your Recruitment Team?
The answer depends on how often you hire for the same positions. A business that rehires for the same roles each season or uses the same job postings in multiple locations has real value in its applicant history. On the other hand, a company that rarely reopens the same role has less to gain.
Setup effort matters too. Generating OAuth2 credentials, configuring custom fields, and testing on a few live roles all take some IT or admin time upfront.
A smaller employer that hires occasionally has less applicant history to revisit, and the extra cost may not be justified yet. Rediscovery becomes valuable when your hiring is repetitive enough that the same types of roles, and often the same candidates, keep reappearing.
Final Verdict: Pilot Candidate Rediscovery
For employers with recurring, high-volume hiring on Paylocity, a pilot with Skima AI can deliver high ROI. The right move isn't to switch every location or every job over at once. Start with a few live requisitions, ideally those tied to a role your business fills repeatedly.
Connect Skima AI, configure the custom candidate fields, and launch Talent Rediscovery on these roles. Skima AI's own Paylocity integration structures this as a 30-day pilot, with checkpoints along the way to track progress.
Track time-to-screen, how many rediscovered candidates reach an interview, and hiring manager response rates. Based on a documented 30-day Paylocity pilot, expect over a 58% drop in time-to-screen and twice the interviews from your shortlist. From there, expanding to more roles or locations becomes a decision backed by your own data, not a guess.
Frequently Asked Questions
1. Does Paylocity Recruiting have a built-in dedicated talent rediscovery feature?
No, Paylocity Recruiting does not have a built-in talent rediscovery feature or tool. It offers candidate profiles and dynamic reports for managing applicant data, but neither functions as a search tool across your historical applicant pool, and nothing scores a past applicant against a newly opened role.
2. How to conduct candidate rediscovery in Paylocity ATS?
To conduct candidate rediscovery in Paylocity, connect Skima AI through OAuth2 credentials from the Paylocity Developer Portal, configure candidate custom fields, then launch Talent Rediscovery on a live job. Skima AI scans your applicant history, ranks candidates, and syncs hiring manager feedback back automatically.
3. What are the benefits of Paylocity candidate rediscovery?
Rediscovered candidates arrive pre-scored, reducing screening time by over 58% in a documented 30-day pilot and doubling interviews from the top shortlist. Matches carry explainable reasons, a SKIMA Screened tag for filtering, and hiring manager feedback without a new login.
4. Is Skima AI safe to integrate with Paylocity for talent rediscovery?
Yes, Skima AI encrypts candidate data in transit and at rest, follows GDPR practices, and logs every AI decision and manager response for audit. Scores rely on resume-based evidence only, with no automatic rejections.
5. Is candidate rediscovery useful for Paylocity's customers?
Yes, especially for employers with recurring seasonal or high-turnover hiring, such as retail, hospitality, and senior living organizations. The value grows the more often the same roles, and often the same candidates, come back into play.
Yes, especially for employers with recurring seasonal or high-turnover hiring, such as retail, hospitality, and senior living organizations. The value grows the more often the same roles, and often the same candidates, come back into play.
