Using Advanced Analytics

Advanced Analytics supports data-driven recruitment marketing. By tracking, measuring, and analyzing the effectiveness of recruiting efforts, recruitment marketing is turning talent acquisition into a data-driven function that consistently and predictably drives more qualified candidates into the hiring funnel.

We market jobs through many different channels, and we need to see which channels are effective at bringing qualified applicants to your Career Site Builder career site. Customers use the information from Advanced Analytics to understand candidate behavior, from first visit to final hire. You can leverage data about sites that drive traffic to your CSB career site to understand which sites result in the "best quality candidates." For example, if your career site gets a lot of visits from a particular source, but no hires, that tells us that you’re not getting interested and qualified candidates from that source. The goal is for visits to convert to actual hires.

Advanced Analytics is not part of SAP SuccessFactors Workforce Analytics. There are plans to eventually move this data to the SAP Analytics Cloud (SAC).

Advanced Analytics is embedded within SAP SuccessFactors Recruiting. When a permissioned user navigates to Recruiting→Advanced Analytics, the default view displays your sourcing data in an unfiltered state. You can customize your view of the data set by selecting the Time Period at the top, using the drill path on the left to filter the data, selecting the columns that you want to display from the Display options, and view the trends using the graphics icons at the far right. The data can also be exported to a csv file.

The fields that you would like to report on must be included on your job requisition template, populated on your requisitions, and mapped to Career Site Builder and Advanced Analytics. Some commonly used fields are shown in the screen capture below.

Customers often include fields such as Category, Department, Cost Center, Business Unit, Brand, Facility, and Recruiter. Please see the section Job Data Formatting and Job Distribution for more information about data fields to include and how they are mapped to Career Site Builder and Advanced Analytics. Note that if you see "Undefined" in your reports, that just means that the data is not related to a specific job requisition.

In the 2H 2020 release, Brand was added as a standard filter field for Advanced Analytics. If you already had a custom field for brand information in Advanced Analytics labeled Brand, the 2H 2020 update can result in two Advanced Analytics filters named Brand. Although both filters work correctly, you can avoid having two filters with the same label by submitting a ticket or working with a partner to rename your existing custom Brand field. If you choose not to change this, note the location of the new Brand filter, as it appears at the bottom of the filter list in Advanced Analytics.

The default report displays Source Type, which represents categories of sources, defined in the Key Source Type Definitions table later in this section. Many users prefer to filter by Source Engine, which is a listing of each specific source, such as LinkedIn, CareerBuilder, or Monster. A source engine can range from a large job board to a small local online newspaper. For example, to see what the source engine "RCM Invite to Apply" rolls up into, click on it and select Source Type, as shown below.

For this example, the Source Type is Email.

Change the drill path from the dropdown arrows. You can continue to filter the results, if desired.

For a Project Manager opening, am I seeing better candidates through my sourcing efforts or via my job postings on Indeed and LinkedIn? You can review sources for particular job roles.

It is often helpful to select a filter field, such as Job Title or Job City, and then further filter by Source Engine. So if you are opening a new Project Manager position, you can filter by the Job Title and then by Source Engine to see which sources brought in the best candidates the last time this job was posted.

Or it may be difficult to hire candidates in a particular location. First filter by city and then by Source Engine to see which sources have been most effective in the past.

And how do you know which universities you’re most effective at recruiting from? You can go back to last year’s data and see where you were most effective at recruiting for internship positions. Where did the most qualified candidates come from? Were they from a specific university? From a specific job board? From an email campaign?

Some customers report by recruiter or hiring manager. But remember that there can be a lot of other variables at play, so it’s best to look for recruiters who have a low drop-off rate and find out why candidates are completing those applications. Do these jobs use different job requisition and application templates with fewer questions? Or maybe the recruiters with low drop-off rates are posting to more effective job boards?

Remember that Advanced Analytics is tuned for source effectiveness. When measuring on other fields, such as Recruiters, remember that the tool wasn’t specifically designed for that purpose.

To view trending data, you can filter by Month or Quarter. When you see spikes, it’s a clue that there was something going on during that period. In this example, perhaps there was a Campaign during March.

You can continue to drill in to Source Engine to see where those visits were coming from.

What if a candidate is forwarded to a requisition and then invited to apply: what source is tracked when they apply? The source will vary depending on the way the candidate is forwarded/directed to apply. When a candidate is forwarded to a requisition, the leading practice is to invite them to apply. So the source would depend on whichever source is used to direct them to apply; it could be email, through SAP SuccessFactors Recruiting functionality, and so on.

Campaign tags are an excellent way to filter reports in Advanced Analytics. This allows you to segment data coming from a particular source, for example, activity from LinkedIn. For this example you would start filtering on Source Engine (LinkedIn), and continue to filter using the Campaign tag.

Generating reports using Campaign tags provides customers with a great tool to track your recruitment marketing effectiveness. Campaign tags can also be created for Data Capture Forms, enabled through Candidate Relationship Management, which is a feature set within SAP SuccessFactors Recruiting. Note that for Data Capture Forms, Advanced Analytics will only track the initial visit.

Remember that Campaign tags are created from the Source Tracker tool. See the section Applying Source Tracking for details.

As you will see in the next section about implementing Advanced Analytics, the candidate statuses in SAP SuccessFactors Recruiting are mapped to five statuses in Advanced Analytics: Applications Completed, Qualified, Interviews, Offers, and Hires.

These are the standard columns for a Browse report in Advanced Analytics:

Visits, Subscriptions and Applications Started are captured from activities on the CSB career site. These are also available to view from Source Reports, under Recruiting→Source Tracking.

Applications Completed, Qualified, Interviews, Offers, and Hires relate to candidate statuses in the SAP SuccessFactors Recruiting applicant tracking system (ATS). These Advanced Analytics statuses are populated when the Recruiting data is synced on the schedule defined by you.

Visits Conversion displays the percentage of visitors that began applying for a job (clicked the Apply Now button). A Visits Conversion of 8-9% is a great benchmark to strive for, but will depend on industry and job type. Visits Conversion benchmarks will vary by Source Type. For example, a strong conversion rate on CareerBuilder would be 30-40%, as those candidates are actively looking for jobs on a job board like that. Whereas Facebook tends to have a much lower Visits Conversion rate, as candidates may find jobs on Facebook, but may not be actively looking for new opportunities while on a social network site like Facebook. Before posting a job, remember to look at where the applications came from the last time that job was open.

Application Completion Conversion displays the percentage of Applications Started that were converted to Applications Completed. For example, if 10 visitors start an application and 7 complete it, the apply conversion is 70%. (Subtract that from 100 to get the drop-off rate, in this case, 30%.) An Application Completion Conversion of 70-80% is a common benchmark for customers. Conversion rates in that range or above are considered a strong application conversion rate.

If the Application Completion Conversion rate is low, look at the specific Job Title or Category or other filter to understand the results. For example, is there a Department that works closely with the government and requires a lot of specific fields to be completed on the application? Or is there a job application that is really long? Or could it be that the candidates for that type of position are less motivated?

Be aware that, in addition to viewing all of these data measures by Source Type, you can view their averages by selecting Display options ＞ Show averages (see below). This provides you with averages for each column, rather than by source type, and lets you see the average number of visits per hire, application starts per hire, application completions per hire, qualified persons per hire, interviews per hire, offers per hire, and hires per hire. Knowing what these averages look like is important because not all sources are created equal, and the average column shows you the averages across all dimensions.

From Display Options, you can also select Show browser default columns (shown in the screen capture from Report Columns above) or Customize (select which columns you would like to see on the report).

• Track recruitment marketing effectiveness by analyzing candidate sources, from initial visit through hire, to optimize sourcing strategies.
• Filter reports using drill paths like Source Type, Source Engine, Job Title, and Campaign tags to identify top-performing recruitment channels.
• Monitor key metrics including Visits Conversion (8-9% benchmark) and Application Completion Conversion (70-80% benchmark) to improve candidate experience.
• Analyze source cost data and conversion rates to determine which job boards and campaigns deliver the most qualified candidates cost-effectively.
• Export customizable reports to identify trends by time period, location, recruiter, or job category for data-driven hiring decisions.