Database Matching allows teams to run automated checks by matching candidate responses against custom lists. When a candidate reaches a predefined stage, the system compares their information to a Google Sheets database and determines whether they pass or fail the check.
This feature is typically used for blacklist-style checks, academic validation, company restrictions, and other rule-based candidate screenings where responses need to be matched against a reference database. Common use cases include:
Running “blacklist”-style checks: Automatically flag candidates when their responses match entries in a restricted or do-not-proceed list.
Company checks: Compare a candidate’s current or previous employer against a list of restricted or excluded companies.
Academic checks: Match a candidate’s school, university, or qualification against an approved or restricted education list.
Location or residency checks: Validate candidate-provided location details against allowed or restricted geographic lists.
Vendor, partner, or referral checks: Screen candidates based on referral source, vendor name, or partner affiliation.
Duplicate or repeat application checks: Match candidate identifiers (such as email, phone number, or ID) against existing records or lists.
Each use case follows the same pattern: a candidate-provided value is matched against a database, and the system determines whether the candidate passes or fails the check.
How and When Checks Run
Database Matching is triggered when a candidate reaches the agreed workflow stage, and the corresponding result attribute is set to Pending. Setting an attribute to Pending queues the candidate for checking.
Once queued, the system compares the candidate’s response against the configured reference list and updates the result automatically:
Pending – The candidate is queued and waiting to be checked
Pass – No match was found, and the candidate can continue in the process
Fail – A match was found, and the candidate is flagged based on your rules
Checks run automatically on a scheduled interval. While the frequency can be adjusted, very short intervals are not recommended to avoid overlapping executions and processing delays.
Activating Database Matching
Database Matching is not configured through the Talkpush interface and requires external configuration. It is set up on a case-by-case basis and requires integration with external data sources such as Google Sheets.
To activate this feature, contact your Account Manager. They will work with you to define the candidate attributes to be checked, organize the reference lists, and configure the automation to match your workflow requirements.
