Applicant Rank

Crosschq's Applicant Rank feature evaluates candidates based on how well their background aligns with a specific job requisition.

• Introduction
• Using Applicant Rank
• Common questions

Introduction

Crosschq’s Applicant Rank uses a proprietary scoring system that combines machine learning and intelligent parsing to match applications and resumes to job descriptions. Unlike traditional keyword-matching tools, our system evaluates context and relevance across three primary dimensions:

• Work Experience Alignment: How closely the candidate’s previous roles and responsibilities align with the open role.

• Skills Match: The overlap between skills listed in the candidate’s resume and those required in the job description.

• Educational Background: Comparison of the candidate’s academic history with any required or preferred educational qualifications.

The weighted result of these dimensions forms the match score for each application, which can be visualized from Crosschq's TalentWall app.

Using Applicant Rank

When enabled, Applicant Rank is available in TalentWall from the initial stage in your pipeline funnel. Hover over this stage for a job. A link will appear to view applications.

Once you click the link, a new window will appear with a table of the job's applicants and their match score visualized as a five-star rating. By default, the applications are sorted by highest to lowest match score.

Hover over each applicant to view the total numerical match score and the breakdown of alignment across education, work experience, and skills.

When you click the applicant's name, a window will appear with a detailed view of their resume.

Crosschq allows you to seamlessly advance or disposition candidates with in-app action buttons. These actions can also be performed in bulk by clicking the checkbox to the left of each applicant's match score.

Additional filters are supported including querying applicants by score, application question responses, title, and company.

Common Questions 

What technologies power Applicant Rank?

Applicant Rank uses LLMs to parse data and to create mathematical representations (embeddings) of the job description, application, and candidate's resume. We then use Machine Learning algorithms to generate our match score, which represents how similar the resume/job application is to the requirements listed on the requisition.

Do I need to be using TalentWall to be using Applicant Rank?

Currently, Applicant Rank is only supported within Crosschq's TalentWall app. In the future, we will support a standalone solution for customers that do not use TalentWall or have an ATS not supported by TalentWall.

What ATS's does Applicant Rank support?

Applicant Rank supports TalentWall integrations with Greenhouse, Workday, and we will continue to support additional integrations.

Can I tune, calibrate, or train the match rank model?

We recommend ensuring your job descriptions are an accurate reflection of your applicant criteria to optimize our model. You can make edits to your job descriptions to further fine tune the model. In the future, we will support user-level calibration within Crosschq.