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Recruitment Analytics Software - Your Mission Control

This the ultimate recruitment analytics combo: AI, pre-built or fully bespoke. Houston, we no longer have a problem...

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Dominate. Or Be Dominated.

Isolate barriers to growth and identify the actions to take. Access a library of 50+ best-practice dashboards...or build your own.


Customize & Build Your Own Dashboards

With 150+ pre-connected data sources, build custom reports and create dashboards specifically tailored for your business.


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Activity, Goals, AI Forecasting & Fees

Obtain actionable insights from your recruitment CRM and enhance smarter decision making. Improve the performance of every individual and team.


Data is King

Based on data scoring set by you, Vincere analyzes & visualizes the health of your database, illuminating gaps and identifying duplicates. Incentivize data hygiene throughout your team and hold ‘Top Offenders’ accountable.

Remember- your ability to search (& scale) will only be as good as your data.


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Slice & Dice in Real-time

Apply filters to see what you need quickly. Drill down by brands, branches, teams and individual consultants. Slice by currency, job categories and custom dates.

Gamify Recruitment

Show your top billers on the big screen. Tap into recruiters' competitive nature and instill healthy competition within the team.

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Ready to meet your new Recruitment OS?

Vincere Core delivers you two essential tools: a centralised recruitment CRM and a recruitment ATS. Take your agency to new heights today!

Recruitment terms & glossary:

Recruitment analytics is defined as the application of data science in the recruitment field to enhance the efficiency of the recruitment cycle. It involves tracking, measuring, collating, and analyzing data to make better decisions.

For example:

  • You notice a recent rise in revenue - and wonder what is the reason behind that. You decide to analyze all activities to see which one has resulted in the most profits - and which ones should be omitted/optimized.
  • Recently, there has been a drop in the percentage of qualified candidates - which, coincidentally, occured around the same time as your company adopted a new recruitment operating system. You decide to find out if the latest move is to be blame for that.

At the basic level, data collected is mainly used for reports. Moving to a more advanced one, insights from such reports are invaluable assets that greatly help in planning and optimizing the recruitment process. This allows for a complete transformation of recruiting – from revolving around gut-feeling decisions to being based on real data and evidence.

Data science has left its footprints in a multitude of areas in the past decade, including recruiting. Recruitment analytics provide the basis for predictive analysis and insightful information that help skyrocket the efficiency of your sourcing, interviewing, selecting, and other staffing activities.

Recruitment analytics provide a plethora of data that act as basis for better decision making. By interpreting the information collected, recruiters have an improved chance of deducing if their business is being operated in the right way.

Enhance business efficiency

Data analytics in recruitment help staffing businesses spot opportunities to improve the recruiting process – as well as any problems that are hindering the team’s overall productivity. This allows for a reduction in the cost of total budget – as well as a potential improvement in time-to-hire.

Improve the allocation of budget

Identifying bottlenecks in the recruiting process is crucial to detecting ineffective channels – so that the team can allocate budget to more effective ones that bring in better qualified candidates.

Track performance of recruiting personnel

It is possible to assess each candidate's job quality by utilizing data science during the recruitment process. This enables staffing business owners to evaluate their team members' performance - and provide them with guidance on how to boost their own output.

According to the Future of Recruiting report by LinkedIn, leveraging data effectively is one of the top five priorities for recruiting over the next 5 years. Knowing which information to focus on may provide an enormous advantage for recruiters.

Here, we have compiled a list of the most crucial recruitment analytics metrics.

1. Source

Measuring the efficacy of your sourcing platforms is vital to the recruiting process. In order to save time and costs, your team must continually measure and find the most efficient channel. The time it takes for a platform to get the requisite number of applications, as well as the quality and quantity of those applicants, are all factors considered.

2. Time-to-fill

Time-to-fill refers to how long it takes to fill a position. This metric can give you information about the shortage of personnel for this position - as well as, somewhat, the effective level of the recruitment team. However, it is quite tricky to measure - as it ends when a candidate accepts a position. But when does it start? When the recruitment manager signs the document, or when the team uploads job postings?

3. Interview-to-placement ratio

This recruitment analytics metric measures the proportion of interviewed applicants that receive offers. It is a very strong signal of how well your recruiting is performing - specifically, how efficient and effective their sourcing and screening activities are. To cut down on costs - and save time for clients, recruiters should constantly evaluate their interview-to-placement ratios - so as to determine any impeding loohoples in the process, and any ideas for improvement.

4. Diversity

Diversity indicates the variety of your candidates. There are many reasons for staffing businesses to pay attention to this factor. Diversity of the workforce enhances productivity, innovation, and financial performance – which is all what your clients desire.

5. Cost per candidate

Cost per candidate refers to the amount of money you spend on one applicant. This number will help you allocate reasonable costs for each step in the recruiting cycle.

6. Applicants per job

This recruitment analytics metric could indicate how effective the recruiting team is, or a problem your job description might have (for example, too vague). Adjusting the number (and quality) of applicants can save you time at the screening step.

7. Quality of candidate

Quality of candidate is measured by a combination of metrics. Essentially, it tells recruiters if they have chosen the right applicant for their clients. In order to decide if a candidate is qualified, you need to assess various aspects - staring from the pre-hire phase:

  • Does the applicant possess necessary skills to perform the required jobs?
  • How long does it take to get them onboard?
  • What is the percentage of first-offer acceptance
  • How satisfied are your clients with your candidate pool?

As well as the post-hire stage:

  • How long does it take for qualified candidates to get used to - and contribute to - your clients’ business?
  • How engaged are they to your clients’ corporate culture?
  • What is the retention/ turnover rate?

8. Candidate experience

Whether online or offline, optimizing and measuring the candidate experience is extremely important. An applicant with good experience will be open to leaving good reviews – as well as more willing to contribute to your clients. This, in turn, is a great stepping stone to establishing yourself as a trustworthy recruiter.

Below, we have compiled some of the best practices to optimize your recruitment process with data analysis:

Make use of the right data

According to the Future of Recruiting report by LinkedIn, the most valuable recruitment analytics metrics are being overlooked. Quality of hire is in the top 1. While 88% of recruiters agree this metric will be the most useful in the near future, only 48% actually use it. Other overlooked metrics include sourcing channel effectiveness, hiring time, and cost per hire.

Different levels require focus on different metrics. For example, entry-level jobs need to recruit people regularly, but management-level positions have less selection and opportunities. Measuring applicants-per-hire for fresher positions makes more sense, while management positions focus on quality-of-hire.

Visualize your data

Visualizing data helps recruiters detect trends from the data, thereby recognizing areas for improvement in the recruiting process. When working with huge volumes of data, using a recruitment dashboard to keep track of your metrics can help reduce the time - and obtain more accurate results.

Platforms like Vincere are designed with a wide variety of templates and customized metrics for you to choose from.

Implement insights into the recruiting process

The ultimate goal of recruitment analytics is to uncover meaning from the data - and make changes to optimize the recruiting process.
For example, if your candidates per hire are low, your job description could be overly imprecise, or your platforms are unsuitable.

Towards a data-driven planning

Data analytics are not only used to evaluate past or present activities; they can be used to predict the future too. Using data to plan for the future can help allocate businesses budgets, predict opportunities, and anticipate potential risks. Get a detailed overview of data-driven recruitment strategies.

To apply recruitment analytics, staffing businesses need to find the right software for themselves. Vincere is an all-in-one recruitment agency software that integrates tons of features to help the recruitment team monitor the hiring process – as well as to keep track of the team’s performance. Our analytics tool – Vincere Intelligence – comes with a library of 50+ dashboards, 150+ data sources for custom reports, and various pre-built features for recruiters to acquire practical insights – so that they can improve their decision-making capability.

Start using Vincere today!