The Last Strategic Recruiting Frontier — Sourcing Using Consumer Data

Recruiting leaders are constantly looking for strategic opportunities, which admittedly are rare in this progressive field. There is only one big missed opportunity in strategic recruiting and that is … harnessing consumer data to direct source passive prospects. Unless you have adapted a big data approach to recruiting, you will undoubtedly be shocked to learn that the most accurate and useful profile that you can get on a potential recruiting prospect doesn’t come from LinkedIn or their resume.

Instead it can be gotten from data brokers who sell consumer data. Imagine the recruiting possibilities if you had a complete profile of literally every employed passive prospect in your area … and that this profile included their job title and company but also their income, ZIP Code, a list of behaviors that would indicate that they were a top performer, and best of all, that they are about to seek a new job.

This last strategic frontier in recruiting goes by several names, including consumer data, credit card data, and sales leads. Let me go on record by saying that consumer data is the most powerful direct sourcing tool that almost no one in the world of corporate recruiting is using.

Why Consumer Data Has Recently Become so Valuable

Consumer data/sales leads are certainly not new. What is new is the tremendous volume of information on literally every consumer around the world. The growth of Internet signups, credit cards, and customer loyalty programs means that you can now get a profile of almost everyone. In addition, the ability to customize and sort this data has increased dramatically so that it can now be effectively used to predict future behaviors. The incredible predictive value of consumer data has been proven in presidential elections and at retail marketing at firms like Target and Amazon.

Recently, using consumer data to monitor individuals and to predict future behavior has even entered into in healthcare. For example, Carolina’s HealthCare is using information on its patient’s consumer purchases to predict which patients are most likely to get sick because of their lifestyle. Executives on the business side have already learned how to use big consumer data, so recruiting is overdue in using it for sourcing prospects and for better selling candidates. With the right predictive algorithm, recruiting can now successfully identify and approach desirable individuals before they actively enter the job market and before every other firm begins to bid on them. To put it bluntly, there is no other source that covers every employable individual.

The Advantages of Recruiting From Consumer Data Profiles

The information provided from consumer data makes it a compelling sourcing tool. And before you start worrying about legal issues, remember that because these individuals are not technically applicants, you have more latitude in using demographic and psychographic data to identify them. Privacy is also not an issue because the information has been gained legally, and in any case, the use of consumer data does not have to be revealed to anyone. The recruiting prospect in particular does not need to know how you identified them. Some of the many advantages of using consumer data for identifying prospects include:

  • Coverage — unlike social media, where you have to sign up and fill out a profile, consumer data automatically covers every consumer.
  • Passive coverage — because it covers almost every consumer, it is particularly effective in identifying and assessing the so-called passive prospect, which includes the 80 percent of the working population that is not actively seeking a current opening. These non-lookers simply can’t be found using active sourcing approaches like job boards and corporate career pages. You can use it to find a wide range of individuals, including those who don’t want to be found on LinkedIn/social media. It can also be micro-targeted to find college students and women that have dropped out of the workforce.
  • Current occupation  most consumer data reveals a targets current and past job titles and the firms where they worked. You can buy consumer data that is targeted exclusively to any specific occupation.
  • Income — income information simply can’t be found on LinkedIn or even in resumes. However, because everyone lists their income when getting credit, it’s possible to figure out how much a target is currently getting paid and in many cases, their pay history. Income information is also useful. With it, recruiters can determine if your firm can afford to hire a particular prospect. It can also be used during salary negotiations with a candidate to determine their current pay level. However, you still have to consider total equity, which includes stock and bonuses.
  • Predictors of an upcoming job search — the best part of using consumer data is that you can use it to accurately predict future behavior. For example, if you put together an effective algorithm covering on average how long a target has been in a job (compared to previous jobs), their rate of income growth, and other factors, you can estimate the likelihood of them considering a new job or internal move in the immediate future.
  • Indicators of learning and a top performer — since most consumer data covers where individuals spend their money, you can spot indicators of whether they spend their money on learning and development. This information could include subscriptions, associations that they join, and conferences and seminars that they attend. You can also use frequent income increases as an indication that this individual is a top performer who is frequently rewarded by their current firm.
  • Where they live — because consumer data reveals the ZIP Code where prospects live, you can narrow your search to those who live within a reasonable commuting distance of the facility where you are hiring. Because the information includes the location of any second or vacation home, you may be able to convince some prospects to work for you at a location close to that second home.
  • Complete contact information — consumer data can provide almost every avenue that is available to contact a targeted individual.
  • New movers — consumer data reveals individuals who have recently moved into your recruiting area.
  • Education — consumer data profiles reveal not only education level but also current enrollment in technical courses.
  • Diversity — some consumer data even reveals whether the individual is diverse, for the cases where you want to proactively reach out to diverse individuals.
  • Dual usage — consumer data covering recruiting prospects may already be available in your firm’s consumer marketing division, so access to it may cost recruiting nothing. If it is not, its value increases if it can also be used by your firm to attract new customers.

Consumer data can include much more information that you may or may not want to request, including age, marital status, hobbies, home ownership, and interests. You can also combine it with information that you obtain from LinkedIn profiles and resumes in order to get a complete picture of which passive prospects you should approach.

An Example of How You Can Use This Data

Let’s look at an example. If you are lucky and your targeted individual is on LinkedIn, you can already find out that Mary Smith is an engineer working at your competitor, the XYZ Company. What if you also got a consumer data profile that went further and also indicated that she made $10,000 less per year then you would pay her and that she lived within commuting distance of your facility? But what if analytics could tell you that there was a 90 percent chance that she would begin looking for a new job in the next six months? The consumer data profile could also indicate that she was likely a top performer at her firm because of her pattern of income increases. The profile could also tell you what publications she paid for, what books she purchased, what associations she was a member of, and even what conferences she has attended.

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In short, consumer data has the capability of providing almost everything you need in direct sourcing in order to convince currently top-performing employed individuals (who are relatively happy where they are) that they should consider the one and only other opportunity that they are aware of, and that is the opportunity to work at your firm.

Final Thoughts

I have long been an advocate of what I call “parallel benchmarking,” where recruiting learns about successful business processes (i.e. supply chain and CRM) and then adapts them to recruiting. Well, the time has come for recruiting to reach across the aisle to learn from marketing and sales, who are experts in using consumer data and sales leads. They can help you find out how to better understand and reach out to high-value prospects and then how to better sell them as candidates once they have applied.

If you’re worried about managing this direct sourcing database, fear not. You can buy this data relatively inexpensively from data brokers, and fortunately they do all the data management in sorting work for you, so you don’t have to manage and update the data. There are many different sources for this data including and If money is an issue, some data brokers even offer free trials.

You may choose to pass up this amazing opportunity, but I predict that the use of consumer data in recruiting will become commonplace within as few as three years from now. It covers every consumer around the globe, it provides valuable income information, and finally because big data alone allows you to predict future job search actions.

Dr. John Sullivan, professor, author, corporate speaker, and advisor, is an internationally known HR thought-leader from the Silicon Valley who specializes in providing bold and high-business-impact talent management solutions.

He’s a prolific author with over 900 articles and 10 books covering all areas of talent management. He has written over a dozen white papers, conducted over 50 webinars, dozens of workshops, and he has been featured in over 35 videos. He is an engaging corporate speaker who has excited audiences at over 300 corporations/ organizations in 30 countries on all six continents. His ideas have appeared in every major business source including the Wall Street Journal, Fortune, BusinessWeek, Fast Company, CFO, Inc., NY Times, SmartMoney, USA Today, HBR, and the Financial Times. In addition, he writes for the WSJ Experts column. He has been interviewed on CNN and the CBS and ABC nightly news, NPR, as well many local TV and radio outlets. Fast Company called him the "Michael Jordan of Hiring," called him “the father of HR metrics,” and SHRM called him “One of the industry's most respected strategists." He was selected among HR’s “Top 10 Leading Thinkers” and he was ranked No. 8 among the top 25 online influencers in talent management. He served as the Chief Talent Officer of Agilent Technologies, the HP spinoff with 43,000 employees, and he was the CEO of the Business Development Center, a minority business consulting firm in Bakersfield, California. He is currently a Professor of Management at San Francisco State (1982 – present). His articles can be found all over the Internet and on his popular website and on He lives in Pacifica, California.



12 Comments on “The Last Strategic Recruiting Frontier — Sourcing Using Consumer Data

  1. Excellent article on a very interesting subject. Thank you. My company has been taking a hard look at the “consumer” data sources you reference and I was actually considering writing on this topic myself. As per this article, this is an area of great untapped potential. However, there are two things I wanted to point out. First of all, these data sources can, in many cases, provide a lot of very detailed information. But, generally speaking, NOT much detail regarding specific skills. To use your example, the fact that someone is an “engineer” in today’s world is a pretty useless data point as is their current employer. Engineering, science, and technology continue to become more and more specialized and details regarding specific skills and experience are really necessary for a recruiter or hiring manager to determine qualification for an open position. I’d argue that the same is true in other areas including finance, legal, etc. So, for many sorts of needs, the data you write about is best used as an addition to other more skill centric data points. But not necessarily a profile (the whole point being, to some extent, to find candidates without detailed profiles or resumes available on line). For instance, a couple of technical publications by an engineer or scientist along with consumer data can be put together to build a really excellent profile. Again, I absolutely do think there is a role for this data. But my second point is I think you have to be careful about brushing aside compliance issues. The fact that the research might be targeted at prospects and not candidates does NOT just excuse everything from a compliance perspective. There are potential problems even if your prospects never become candidates (and there would be absolutely no point in that). In fact, I think the compliance issues for this kind of “big data” or “deep data” work probably warrant a separate article. And there is ambiguity in this area because the approach is so new with little or no legal precedent. Plus there is a “spooky” factor to this approach that needs to be considered for employer branding reasons if no other. So setting up procedures and processes to manage this data would be essential. But I do agree with your fundamental point that this is a powerful new approach that demands attention. Thanks again.

    Doug Friedman
    LinkedIn Profile

  2. Thought-provoking piece but whoever pioneers this is in for some data
    privacy pain, since you’re combining two big areas of personal data (and
    Logan Meece’s half-joking comment implies the slippery slope — it
    would get messy if any medical data were inadvertently included). It
    would be great to hear about some employers pioneering this, beyond your brief hypothetical example (John – I’m guessing some of your clients
    do; can you get them to present at a recruiting conference and/or post a
    follow up article?). Or maybe commenter Timothy Graves can share? But
    it won’t become big in recruiting until a vendor combines all the
    available data — likely by one of the big data people profile
    aggregators (Dice OpenWeb, Entelo, HiringSolved, SwoopTalent, TalentBin, Yatedo, ZoomInfo, etc.) that have a robust mix of professional and personal social network data, partnering with one of those consumer data sources, looking for a way to eclipse LinkedIn.

  3. Thanks, Dr. Sullivan. This seems like it might be useful for the 0.1% of companies who have the time, money, bandwidth, and organizational support to go after the types of people who might be found this (and no easier) way. Furthermore, most of the time FINDING people is not the problem, RECRUITING them is, so instead of spending *large amounts of resources on boondogglish plans to get people that wouldn’t likely be interested anyway, IMHO it would make more sense to determine what type of people a company can REALISTICALLY hire (, and then asking their own recruiters and sourcers how best to source and recruit them.
    *In 2013, I investigated using a data broker to do just as you suggest, and it seems that the data costs thousands or tens of thousands of dollars.Ifg someone knows miuch more-affordavle alternatives, please let me know.,

    1. When recruiting Silicon Valley engineers, “thousands or tens of thousands” isn’t a barrier. At a $30-40k recruiter fee per hire, the data costs you reference, amortized across dozens or hundreds of hires over time, is a rounding error. However, IMO, the BigData approach will be applied differently. It won’t be individual companies or recruiters licensing the data and trying to figure out how to make sense of it. A startup will offer this as a scalable SaaS solution for an amount that you won’t be able to afford not to pay. Yes, you’ll still have to make successful recruiting calls, but they’ll be far better informed, making the critical first 15 seconds of each call much more relevant and effective.

  4. Besides thinking one’s consumer information as it relates to their ability to do a job successfully is irrelevant, the effort and education it would take to gather/integrate/sync the consumer data with recruitment data is huge. With, in my opinion, little to show in the end.

    So few companies have sourcing tools/applications, even those with a robust one..I don’t see this working. Matching and merging data from multiple sources into one is not for the faint hearted…it can be done…but you really need to know what you are doing.

    If you start pulling in non work related information that is not provided by the talent themselves…good luck with syncing your data. You’d be surprised how many guys are named Rob Mcintosh and if you don’t have the right key data in hand…you are going to get a dirty database real quick duplicate and “un-matching” data.

    This isn’t a great opportunity, it’s only a chance to waste time and money.

    Look…a shiny object…chase it.

  5. Once again, I think this may be a possibly erroneous path to take (assuming that the most detailed data will give you the best hires).
    I’ll do a “thought experiment”:
    1) Let’s assume you’re a recruiter and you and you alone have the same kind of detailed data that the NSA has right now on anyone/everyone you could ever possibly want to recruit, it’s in an incredibly easy-to-use form, and you knew how best to use it. You would be Emperor/Empress of the Recruiting World!
    2) Now let’s assume that you were one of 1000 recruiters worldwide who had the same thing. You could still do incredibly well, but you’d no longer be “Emperor/Empress”
    3) Finally, assume that you are but one of 1,000,000 recruiters, sourcers, sales reps, lead generators, marketing drones, etc. Now, your competitive advantage is GONE.

    MY POINT: The great majority of people who get hired can be found quite *easily RIGHT NOW, so unless you have a very specialized niche of nearly invisible people, you don’t need to concentrate on the latest ways of finding people (which others can easily duplicate), you need to concentrate on having non-duplicatable opportunities/offers for the (realistically hirable) people you do go after.


    *Furthermore, what makes anybody think if that someone is extremely hard to find, they’ll be any easier to recruit once you’ve found them?

    1. Keith – You make some great points. I often find myself agreeing with your “common sense” comments and I like the way you stay focused on what works for most companies as opposed to just the top one percent or so of employers. But you, and others on this thread, might want to reconsider the possible value of these data sources. To give an example, let’s say you have a job to fill that requires some proactive sourcing. It could be a real tough fill or just one where your postings, etc. aren’t working well for whatever reason. So you put together or get a sourcer to put together a list of qualified candidates off of LinkedIn or wherever and start calling or emailing them. Wouldn’t it be much more efficient if that list only included people making less than your open job pays? Why contact people who you can’t get because they make too much? This is a big time suck and a point of frustration for most recruiters. And this is the practical deliverable that this kind of data has the potential to offer. Not 100% accurate (we’re not talking about IRS data) but really pretty darn good. Now, as I point out in my first post, I think the compliance issues are nothing to sneeze at and I also agree with others here that the data integration and integrity issues are big. But definitely not insurmountable. Other industries (think financial services and retail) use this data across much, much larger information pools than any recruiter would ever need. Also, I’m using the salary angle because it is the most straight forward. But there really are other things, lots of other things, that this kind of data could help with. So I think the potential value isn’t just for purple squirrel stuff. I mean, how much more confident would you be on a first recruiting call if you knew going in that your company could offer more money or a better health plan for a new baby on the way, etc. Yeah, I DO think it is a bit spooky. But also inevitable. Why? Because very few people seem to really care that this kind of data is used. It’s going on all over the place. How many unfilled “data scientist” reqs are there right now? Why have statisticians suddenly become a super hot commodity? Because HR is compliance oriented, we haven’t seen it in our world yet. But I think it will happen. Anyway, it’s interesting food for thought if nothing else.

      Doug Friedman
      LinkedIn Profile

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