[Whitepaper] Recruitment Analytics in a Programmatic Sourcing Era

in a Programmatic Sourcing Era
Recruitment Analytics

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About the Author
Allan Schweyer
Allan Schweyer is the Founder of TMLU, Inc. in which he develops
and delivers curriculum and conducts human capital management related
research for a wide variety of clients including multiple government
agencies, the Incentive Research Foundation, Lockheed Martin, and many
others.
Allan is a recognized subject matter expert in human capital management.
Prior roles include Staffing Subject Matter Expert at HR.com, President
and Executive Director of the Human Capital Institute (HCI) and partner
at the Center for Human Capital Innovation.
Allan is the author of the books, Talent Management Systems (Wiley & Sons,
2004) and Talent Management Technologies (HCI Press, 2009) and co-author
of the Enterprise Engagement Textbook (2014). Over the past twenty years,
he has published extensive articles and white papers in dozens of popular
media and industry-specific publications worldwide, including Inc. and
The Economist Magazines. Allan has been recognized as among the “100
Most Influential People in HR and Talent Management.”
Recruitment Analytics in a Programmatic Sourcing Era

Contents
Introduction
Part One: Rethinking Recruitment Advertising
The Data Imperative
A Renaissance for Recruiters
The Future is Now, but the Metrics Aren’t
Figure One: Programmatic Recruitment Advertising Feedback and Learning Loop
Part Two: The New Recruitment Advertising Metrics
Table One: Programmatic Recruitment Advertising KPIs
Conclusions
Footnotes
References
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Introduction
The world of recruitment advertising has changed remarkably in just the past few decades.
Only twenty-five years ago jobs were posted on physical bulletin boards at job centers, and listed
in newspapers. Today, through real-time, automated bidding engines, algorithms negotiate
behind the scenes to determine who will see which job ads, and where and when they will see
them. In milliseconds, countless factors are considered, prices negotiated and ads displayed.
This occurs every day – thousands of times each minute – across the web. Welcome to the age
of programmatic recruitment advertising.
Despite great changes in the way we advertise jobs, however, recruitment, (aka, “sourcing”)
remains the process of generating suitable applicants for job openings. It starts with finding and
attracting candidates and ends when those involved in the selection process receive sufficient
qualified applicants.1
In sourcing candidates, recruiters rely enormously on recruitment advertising, a big and growing
business.2
Conservatively, employers worldwide post about 3.3 million jobs each month 3
contributing to a worldwide annual recruitment marketing spend of at least $10 billion, 4
including approximately $6 billion in the US alone.5
The recruitment advertising market will likely remain a high growth industry for the foreseeable
future. The US unemployment rate has stayed at or under 5 percent over the past ten
consecutive months according to the US Bureau of Labor Statistics 6
and employers are once
again citing skills shortages among their chief concerns.7
Yet, even though the employment market may already favor job seekers,8
few organizations will
pour money into recruitment advertising without evidence of returns. Rigid budgetary discipline,
a necessity for most organizations during the Great Recession, continues, despite
the recovery.9
Today, decision-makers demand data and evidence of results.10
To furnish this
evidence, recruiters should understand and adopt carefully chosen metrics relevant to
the current recruitment advertising landscape and where it is headed.
While a range of staffing and HR metrics inform and influence recruitment advertising,
the measures of its effectiveness should align to its own key objectives and be within recruiters’
span of control. Recruitment advertising supports two key objectives: to deliver qualified
applicants to a specific job opening (or to fill a talent pool) and to present the organization in
a positive light in order to protect and strengthen the employer brand.11
In just the past five
years, the metrics, benchmarks, and KPIs used to measure recruitment advertising effectiveness
have shifted. This paper explores those changes and recommends a mix of revised and new
measures based on the changing landscape of recruitment advertising.

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Part One
Rethinking
Recruitment
Advertising
1 / 244 / 22Recruitment Analytics in a Programmatic Sourcing Era

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The marketing industry has undergone sweeping change since the advent of the world wide web
in the 1990s. Recruiters, to their credit, discovered the internet as a medium for advertising
before most others. Today, more than 80 percent of recruitment advertising is placed online,
making it the largest single component of the digital advertising industry.12
Consumer advertising, by contrast, still utilizes television as its largest advertising medium
(online, digital advertising is set to exceed it by 2018).13
Nonetheless, marketers have moved
quickly to understand the programmatic and analytical advantages of digital advertising.
Already, as of 2016, automated systems place the majority of digital advertising; 14
a process by
which software and algorithms instantly process massive amounts of data to determine what ad
content should go where, when, and to whom – and at the best price – to achieve maximum
Return on Investment (ROI).15
Not surprisingly, growing numbers of recruiters are embracing programmatic ad placement, and
the rich world of data and analytics it makes possible. First movers and fast followers are
discovering the advantages inherent in reducing time spent on manual ad placement and in
reaching active and passive candidates across thousands of channels; all the while controlling
their budgets by paying only for applications received rather than impressions, clicks, or the
duration of the posting.16
There is little doubt that recruitment advertising will follow consumer advertising in its rapid
elimination of manual ad buying and placement over the next few years.17
With this shift comes
the need to re-examine recruitment and sourcing metrics to determine which measures remain
relevant and what new metrics, benchmarks, and KPIs recruiters should adopt as they evolve
toward a more programmatic, predictive and personalized era of recruitment advertising.

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The Data Imperative
In a 2015 article in Forbes Magazine, HR thought leader Josh Bersin remarked: “Today, for
the first time in the fifteen years I’ve been an analyst, human resources departments are getting
serious about analytics. And I mean serious.” 18
There is little choice. Fewer operations today are allowed to run on experience and instinct alone.
Leaders have woken up to the fact that even “expert” opinion is only, at best, informed opinion.
In 2005, the results of a two-decade-long experiment involving hundreds of experts across
dozens of domains revealed that their predictions – concerning events in their own fields – were
no better on average than that of the person in the street.19
This reality is illustrated in Michael Lewis’ best-selling book, “Moneyball.” In telling the story of
the Oakland Athletics (A’s) baseball team and its analytical approach to the 2002 draft, Lewis
demonstrates the dramatic improvement that evidence and data make in sourcing talent.
The team’s expert scouts failed (like every other scout in baseball had for at least a century)
to spot available, low cost talent... talent that data analysis helped identify very quickly.
By combining baseball wisdom with data-driven decision making, the A’s, with the third lowest
payroll costs in major league baseball that year, made the playoffs.20
More remarkably perhaps,
the A’s tied the New York Yankees – the highest paid team in baseball – for the most wins
in baseball that season.21
Today, virtually every Major League baseball team, and many teams
in other professional sports, use a similar data-driven approach to sourcing and evaluating
talent.22
In advertising as in baseball, analytics and data-driven decision-making are fast becoming
the way business is done. In 2013, 67 percent of the respondents to a 2014 advertising executive
survey said that more than half of their digital efforts are driven by data.23
A 2014 survey
involving more than 3,000 marketers revealed that almost everyone anticipates a greater role for
data in their advertising efforts in the future and more than two-thirds already consider their
marketing operations to be data-driven.24
Where recruiters are concerned, a 2016 survey by Jibe
(a recruiting technology provider) found that almost three quarters of recruiters believe analytics
are a high priority.25
Of course, much in the world of business, sports and recruiting is subjective and difficult
to measure, data analytics offers no panacea for eliminating uncertainty and ambiguity.
For recruiters and others, the most insightful and desirable metrics are often the most difficult
to measure because they lack precision and definition – case in point, “quality of hire.”
Yet, in the real world, measurement isn’t about getting the absolute, right and precise answer.
Such absolutes are exceedingly rare outside of controlled, laboratory environments. The goal
of measurement, whether in sports, business or recruiting, is to reduce uncertainty and thereby
improve decision-making.26

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A Renaissance for Recruiters
Automated recruitment switches the focus from clicks to applicants, thereby more closely
aligning key financial metrics with recruitment advertising goals. This aids recruiters in generating
the evidence they need to demonstrate value for the money they spend. Real-time, precise
tracking allows organizations to instantly shift budget from vacancies that have enough
applicants to those that don’t. Moreover, automatic controls that stop the process once the
desired number of applicants is reached leave nothing to chance and relieve recruiters from
the burden of regularly checking click volume and worrying about their exposure to unexpected
costs.
Programmatic recruitment advertising shouldn’t concern recruiters with respect to job security.
Only computers, algorithms, and software can process the millions of decision points at play
in optimizing ad placement, but only skilled recruiters can create the messages that make ads
effective. As the laborious, manual work of ad placement and tracking is reduced, recruiters gain
time to focus on creative work. More than ever, relationships and trust are key – tailored
messages, well-crafted job titles, creative descriptions and thoughtful blogs, articles and posts
build rapport and reputation; they give firms an edge in recruiting.27
Recruiters should expand their branding activities by composing and posting to social media
sites, monitoring responses, engaging in conversation and building networks.28
These activities –
and tracking employee/candidate sentiment on sites like Glassdoor – add value. Again,
recruitment advertising and marketing generates applicants for job openings; building
the employer brand and reputation makes it easier to attract top talent and desirable applicants.

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The Future is Now, but the Metrics Aren’t
In the early years of the world wide web, job ads were posted for a duration of time at a fixed
price. Gradually, job boards proliferated and were joined by aggregators (who distribute one post
to many sites) and social media, which gave recruiters another place to seek candidates and
advertise jobs online. As technology became available to track users and their actions on job
boards and web pages, duration-based pricing gave way to pay-for-performance models such as
cost-per-impressions (eyeballs) and then cost-per-click.
These models better satisfied recruiters’ need to distribute their jobs and demonstrate value
for their investments. It also gave them new recruitment advertising metrics, such as
cost-per-impression, click-through rate, and cost-per-click, while adding to the intricacy of
existing staffing measures and benchmarks, such as source effectiveness.
Today, web and social media users, including active and passive job candidates, experience
a wide array of online advertising – not only by type but in the personalized manner ads are
increasingly presented. Consider that as you move through web pages, auctions involving
hundreds or thousands of players occur in real time behind the scenes. In just microseconds,
the winner – the highest bidder – earns the right to place an ad in front of you.
According to senior marketing manager, Paul Kluge, “Getting the right message to the right
consumer at the right time in the right context to drive a conversion at the lowest price is
the goal of every marketer …” 29
From the perspective of the advertiser, the ad delivered, is
(ideally) the right ad, presented at just the right time to get the prospect’s attention and cause
them to take the next step in becoming a customer – or, in the case of recruitment advertising,
an applicant.
Though programmatic ad buying and predictive analytics don’t yet accomplish this perfectly, they
do so more effectively than any person could hope to. The algorithms and software used to place
ads learn constantly, and they never forget. As ads are placed, prospects attracted, and
applications received, the system receives constant feedback. Algorithms improve, and the
predictive abilities of the software deepen.
This is the new age of programmatic ad placement – powered by big data and predictive analytics
(See Figure One). And it’s not just the future, it’s the present. Recruitment advertising metrics
need to catch up.

1 2 3 4
Set your budget and
application volume target
Software uses data to ﬁnd
where your target candidates
live, work, and play on the web
Your ads are placed across
the web at the right place & time
to engage the best candidates
You receive quality
applicants
10,000+ sites
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Programmatic Recruitment Advertising Feedback
and Learning Loop
Figure One:

Part Two
The New
Recruitment
Advertising
Metrics

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As programmatic recruitment advertising ushers in a new era in staffing, new metrics and KPIs to
measure its effectiveness are needed. While some legacy metrics remain relevant, others are
needed to bridge the gaps.
The essential recruitment advertising metrics are those that track closely with the supply of
applicants and the strength of the employer brand. Programmatic ad buying changes the game
such that metrics including click volume, click through rate, cost-per-click, and – to a degree –
even source of hire, become less important. Meanwhile, cost-per-applicant (CPA),
cost-per-quality-applicant (CPQA) and other related metrics, such as source of quality
applications, application conversion rate, and “bounce rate” come to the forefront.
In measuring recruitment advertising effectiveness in programmatic ad buying, organizations will
become less concerned about the volume of people who see their ads, the number of
click-throughs and where their ads are placed, because fees are not calculated against any of
these factors. What recruiters will care about are applicants; the volume of applicants first –
because programmatic services currently charge by the applicant – and the quality of applicants
because, ultimately, that is how sourcing and recruiting effectiveness is assessed.
Even quality of hire metrics are only peripheral to the assessment of recruitment advertising
(whether programmatic or not). Again, sourcing ends when those responsible for hiring receive
sufficient qualified applicants. The sourcing process can’t impact the hiring process directly.
Who gets hired, who gets an interview and whether anyone is hired at all, are subject to a myriad
of factors – beyond the control of the recruiter – that may have little or nothing to do with
recruitment advertising.
Programmatic ad buying changes the game... metrics including click
volume, click through rate, cost-per-click, and – to a degree – even source
of hire, become less important. Meanwhile, cost-per-applicant,
cost-per-quality-applicant and other related metrics, such as source of
quality applications, application conversion rate, and “bounce rate” come
to the forefront.
“
“

Applicants-per-Hire
(APH)
How many applicants, on average, are
required to fill each position? Collect data for
this metric by job and job type. Knowing how
many applicants you need, on average, to fill
various positions will help you set the right
parameters in your programmatic spend (i.e.,
set the right cut-offs for applicants) so that
you don’t overspend.
Using historical data where available, simply
divide the number of hires per position by
the number of applicants considered for
the jobs.
Time to Applicants
(TTA)
Though quality trumps time, you should know
how long it takes from job advertisement to
the supply of sufficient applicants. Remember
that requisitions can be put on hold and
vacancies left open, these decisions are often
made outside the recruiter's control. Account
for those factors to determine a reliable
measure of how long it takes to generate
sufficient applicants for specific jobs and job
types. Note: if recruiting controls the time
between receiving a requisition and placing
advertisements, track this metric separately.
This is a gauge of recruiter or recruitment
process efficiency but is not relevant in
assessing programmatic advertising efficiency.
Track the time a position is advertised to the
point at which enough applicants have been
submitted to cause the advertisement to be
closed or suspended. Determine averages by
job and job type.
Volume of
Applicants by
Source (ABS)
Though the source of your applicants is less
important in a programmatic environment,
you should still develop an understanding of
where your applicants are originating if only
so that you can eventually construct a more
important measure, Source of Quality
Applications (see below).
Your programmatic sourcing leads prospects
to your career webpage to apply. Do your web
statistics tell you where your prospects came
from when they clicked through to your page?
If so, search your web stats by name of the
applicant to determine the source (this can be
automated). Alternatively, this metric might
come from reports supplied by your program-
matic vendor. Request a breakdown of where
the applicants you paid for originated (i.e. the
specific job board, social media site or web
page).
Supporting Metrics Description & Rationale How to Measure
Table One: Programmatic Recruitment Advertising KPIs
Cost-per-Applicant
(CPA)
This is what you’re currently paying for in
the programmatic model, so it is a very
important metric by default. As more
programmatic platforms come on stream, this
will be among the most important measures
by which you will choose your supplier.
Measuring CPA in programmatic recruitment
is straight-forward. Calculate and convert
to dollars the time spent by recruiters and any
others involved (greatly diminished in
the programmatic approach) plus fees paid
to your programmatic vendor, divided by
number of applicants received.
Key Metric
(Applicants)
Description & Rationale How to Measure
Table One below suggests the current and near future metrics that recruiters should include
among their KPIs:

Cost-per-Quality-
Applicant (CPQA)
Ultimately, you should measure what you’re
really aiming for – quality applicants. Even
though CPA represents a significant improve-
ment over duration, impression-based and
even click through metrics, it remains flawed
because it measures quantity rather than
quality.
First, define “quality.” Remember, a key
ingredient of a good metric is one that
measures what is within the control of those
whose efforts will be assessed using
the measure. Thus “quality of applicant”
should be defined as those applicants who
pass a threshold that moves them along in
the hiring process. This might mean, for
example, those who pass the initial screening:
either automated ATS type “knock-out”
questions, or a telephone screening interview.
Be careful not to include factors that involve
artificial limits. For example, you might have
a rule that only four applicants per job are
interviewed in-person. If so, being put forward
for an in-person interview cannot drive your
applicant quality metric.
The best measure of applicant quality may be
those who qualify for an eligible pool of talent
(for a specific job or others like it). Organiza-
tions that maintain eligible talent pools (an
important “best practice”) are selective in who
qualifies and they don’t restrict numbers (the
more, the better). As such, this becomes an
excellent means to define “quality of
applicant” for recruitment advertising
purposes.
When you have your definition, calculate your
CPQA by dividing the total of what you spent
on applicants by the number of quality
applicants received. Do this by position and
position type as well.
Time to Quality
Applicants (TQA)
See TTA above. For this metric, use your
definition of Quality Applicant as a substitute
for Applicant.
Track the time a position is advertised to
the point at which enough quality applicants
have submitted to cause the advertisement to
close. If ads are suspended because enough
applicants were received, but re-opened due
to a lack of quality applicants, include
the intervening time in your calculation.
Determine averages by job and job type.
Key Metric Description & Rationale How to Measure

Source
Effectiveness
In the programmatic recruitment era, source
effectiveness remains important but is aimed
at programmatic platform providers
themselves rather than the thousands of job
boards, social media and websites where they
place your ads.
Think of programmatic advertising vendors as
providers of “recruitment advertising
as-a-service.” As more vendors enter the
market, the question of source effectiveness
switches from the places your ads are served
to the service that places them. This brings
the benefit of greatly simplifying the tradition-
al “source effectiveness” measure that many
recruiters use today.
Compare CPQA and TQA among programmat-
ic and platform vendors. Choose the vendor
with the best combination of CPQA and TQA
weighting each accordingly.
Admittedly, this is a near-future metric, not
a current one. At present, there are too few
recruitment advertising programmatic
platform vendors to offer a robust compari-
son. Nonetheless, by registering for free trials
and conducting assessments on current
vendors, you may be able to compare CPQA
and TQA among existing suppliers.
In the future, as more providers enter the
market, buyers guides and published rankings
of vendors – presumably by CPQA, TQA, and
other factors – will emerge. Granted, this may
be months or even a year or more away.
Key Metric Description & Rationale How to Measure
Bounce Rate Even though your main concern might be
number of applicants, you should also track
the ratio of prospects (those who land on
your career site) to applicants (those who
apply to a position or join your talent pool).
Your bounce rate is a good indicator of the
effectiveness of your site. For example, do
prospects land immediately on a lengthy
ATS-driven application (which might be a turn
off) or are they given additional compelling
information about the organization to
encourage the next step? Your Bounce Rate
helps gauge the impact of adjustments to
your site and the funnel it represents.
Simply divide the number of unique site
visitors by applications received to jobs and/or
to your talent pool.
“Social Media
Multiplier” (SMM)
While still difficult to measure, word-of-mouth
is more visible today because so much of it
occurs in the social media. “Likes,” re-tweets,
blogs, “friending” on Facebook and many
other social media activities have become
important sources for referrals and traffic to
career websites. Some social media sites offer
analytic tools for those concerned with their
brand and the reputation of their organiza-
tion, and/or the effectiveness of their
recruitment marketing.
The Social Media Multiplier offers a rough
gauge of word-of-mouth about your organiza-
tion by tracking the number of people who
visit your career page from various social
media sites.
To measure, query your career website stats
to include a report on how many visitors came
to you from social media sites, including
Facebook, LinkedIn, Twitter, Pinterest, and
others.
Key Metric (Branding) Description & Rationale How to Measure

Net Promoter Score
(NPS)
The Net Promoter Score, a widely used
measure of customer and employee
sentiment, can also be used to gauge broad
attitudes about your organization as an
employer by asking prospects just one
question.
Using your career website, your corporate
Facebook page, LinkedIn networks, etc., ask
prospects how likely they are to recommend
your organization to others as a potential
employer based on what they know about
the organization. Alternatively, “likes” on
Facebook might offer a similar, though cruder
metric. Similarly, depending on the size of
your organization, Glassdoor.com (see below)
surveys employees and ex-employees on their
likelihood of referring your organization to a
friend.
Glassdoor Rating For large organizations especially, Glassdoor
ratings and reviews might yield valuable data
and insights for recruiters. As an anonymous,
third party site, Glassdoor data is likely to be
less biased than an internal survey, particular-
ly where raw employee sentiment is sought,
and it is also effortless – you don’t need to
construct, distribute, collect and analyze a
survey.
Though Glassdoor ratings and reviews come
from current and past employees, not
prospects, it has become the premier place
for talent seeking information about organiza-
tions they might be interested in working for.
As such, recruiters should monitor Glassdoor
to track overall ratings and to review
comments, which might also guide recruiters
in the development of recruitment advertising
and marketing content. Moreover, recruiters
can and should craft compelling company
overviews on Glassdoor and respond to
negative and positive reviews. Increasingly,
Glassdoor ratings and reviews impact
organizations’ employer brands.
Visit Glassdoor.com, enter your organization’s
name and receive your aggregate/average
rating to date.
More advanced analytical features are
available to employers by subscription, but
you can access full reviews and see your
overall ratings at no cost. You can also view
aggregate metrics such as the percentage
who would refer your organization to a friend
– a variation of the NPS metric described
above.
PwC consulting, for example, is currently rated
and reviewed 11,000 times, offering
a treasure trove of information without
the need for surveying.
Key Metric (Branding) Description & Rationale How to Measure
Return on Invest-
ment (ROI) or
Return on Ad
Dollars Spent (ROA)
Like ROI (Return on Investment) ROA is a
bottom line metric that estimates the
efficiency of spending in recruitment advertis-
ing. If recruitment (or sourcing) were
concerned only with forwarding quality
applicants, CPQA might suffice. But because
recruiting also entails branding, a broader
measure is needed to assess the ROI on
overall recruiter activity.
Key Metric (Other) Description & Rationale How to Measure
Divide Net Benefits by Total Costs and
multiply by 100 to get percentage ROI or ROA,
Total Benefits – Total Costs
(Net Benefits)
______________________________ x 100 = % ROI
Total Costs

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Conclusions
In recruiting and most everywhere else, the emphasis on data and automation brings constant
change. Undoubtedly, experience still matters in recruiting because it informs the questions we
ask, the data we collect and store, and the way we interpret the results of analysis. Moreover,
the new freedoms that programmatic recruitment advertising oﬀers, means that recruiters can
spend more time thinking strategically and in creative pursuits that build the organization’s
reputation and attract top talent to its doors.
The measures above, while not comprehensive, should aid recruiters as they adopt
programmatic recruitment advertising and begin to shift the focus of their work to branding,
social media monitoring and networking.

17 / 22
Footnotes
1
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ResearchAndMarkets. (2016). 2016 Recruitment Annual Report.
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5
Borrell. (2014). 2014 Recruitment Advertising Outlook: The Long, Gray Line. Borrell Associates.
Borrell Associates; Trefis. (2013, January 18). Forbes. Retrieved August 2016, from Forbes
Investing: http://www.forbes.com/forbes/welcome/#723c4d7d6054
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11
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12
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15
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