Frequent Questions

We collect basic account information (name, email, and password) when you register, plus support communications if you contact us. We also collect standard technical data like IP addresses and page visit logs for security and performance monitoring.

No. We use a self-hosted analytics tool called Umami, which is cookieless and does not track you personally or across other sites. It only collects aggregated, anonymized data like page views and general device type to help us improve the platform.

Never. We do not sell your data. The only third party we share limited information with is Stripe, and only what's necessary to process your payment (such as transaction status).

Yes. You can update your account information directly in your account settings at any time.

The reports include insights and visualizations, but specific recommendations are left to the discretion of the client and/or organization.

The number of bins in the histogram is set using the larger value between two statistical rules: Sturges' Rule and the Freedman-Diaconis Rule. These rules help determine the best number of bins to display the data effectively.

Once the number of bins is decided, the score values are divided into equal ranges (or "chunks") across those bins. For example, if there are 9 bins, the data is split into 9 equal groups based on the minimum and maximum values. The numbers shown (e.g., 89) represent the starting point of a specific bin—meaning any score within that range falls into that category.

A referent group is the baseline group used for comparison when evaluating selection rates, particularly under the 80% rule for adverse impact.

While often called the "unprotected class" for simplicity, this is not technically accurate — all races, ethnicities, and genders are legally protected under U.S. law. The term simply reflects that the referent group is usually the one least likely to experience discrimination and is used as the benchmark for fairness evaluations.

 Adverse impact and mean differences are reviewed at each stage to ensure compliance with standard selection procedures and to identify any potential biases early in the process, ensuring fairness and equity throughout.

The purpose of the Adverse Impact report is to help organizations assess the fairness and compliance of their selection and assessment processes. The report will analyze whether there are any disparities in how different demographic groups (e.g., race, gender, age) are affected by the assessment process. This is particularly important for ensuring that the selection methods do not unintentionally discriminate against protected groups, thus violating anti-discrimination laws such as Title VII of the Civil Rights Act.

Yes, the report will vary depending on the type and complexity of data provided by the user.

The software is regularly updated to ensure compliance with the latest industry standards and regulations.

No, it is used by HR teams, compliance officers, recruiters, and legal teams for workforce analytics and selection fairness evaluation.

Statistical significance shows whether a result is likely real or just due to chance. If the p-value is below 0.05, it's generally considered significant, meaning there's a low probability (less than 5%) that the outcome happened randomly. However, significance doesn’t always mean the result is meaningful or causal.

Industrial-Organizational (I/O) Psychology is the study of human behavior in the workplace. It focuses on improving employee performance, well-being, and organizational effectiveness through research and applied psychology.

Yes. We understand that every organization's selection process is unique. If you need something tailored, whether it's a specific report format, workflow adjustment, or data configuration, reach out to us and we'll work with you directly.

TalenTrack is built and supported directly by its creators. You're not dealing with a generic help desk. If you run into an issue or have a question, you're hearing from the people who built the software.

You can reach us through the Support tab within the platform. We're here to help you get the most out of TalenTrack and will respond within 24 hours.

We use several technical security measures to protect against unauthorized access, data modification, and corruption. These include firewalls to control network traffic, automatic system security updates to patch vulnerabilities, and anti-virus software to detect and remove malicious code. Additionally, we are implementing multifactor authentication (MFA) for email accounts to enhance account access security.

The de-identified dataset uploaded to our software will be retained for 10 days, after which it will be automatically deleted by the system.

No, sensitive data is never stored. Once you upload your sheet and select the columns to use, only the necessary data is imported. All other data, including unused columns, will be automatically deleted to ensure your information remains secure.

Payments are processed through Stripe, a PCI-DSS compliant payment provider. We never see or store your full credit card details — Stripe handles all sensitive payment data directly.

The individual components do not include a pass/fail or Selected/Not Selected threshold because, in a compensatory approach, each component is not designed to stand alone with its own decision point. In this model, overall performance across all components determines selection outcomes. To evaluate Adverse Impact, please refer to the Overall Report. The individual component or assessment reports are useful for examining mean differences (e.g., through ANOVA analyses), but they are not intended for independent pass/fail decisions.

NaN means “not a number,” and in a correlation matrix it simply means the correlation cannot be computed.
This usually happens when there are not enough people with scores on both assessments (for example, in a multi‑hurdle process where many candidates never reach later hurdles), so the software has no valid data pair to correlate.

Processing time depends on the size and complexity of the dataset, but optimizations are in place to ensure efficiency. Generation time should take no more than 90 seconds.

There is no limit, however, the larger the dataset, the longer it will take for the report to generate.

The "Traditional Adverse Impact Selection Ratio" is selected by default because historically, most lawsuits have noted the assessment and selection procedures favored the traditional group (White, males, under 40). If you wish to modify this selection, you can adjust it by clicking on the report wizard.

The software supports Excel (.xlsx), and CSV

Yes, the software includes basic data validation checks to flag missing values or formatting issues.

Yes! If your selection approach uses a compensatory selection system or a multiple hurdle selection battery containing multiple assessments and/or steps, all of that data can be uploaded together in a single spreadsheet for seamless analysis.