4 Lessons Talent Acquisition Teams Can Steal from Marketers

For decades, marketers have been in overdrive to keep up with fast-paced innovations in marketing technology. In the beginning, an impersonal email blast to cold leads might have brought marketers results. However, consumers evolved and so did marketing technology. Prospects, bombarded with digital advertising, wanted more personalized communications and thus, marketing automation was born. It allowed marketers to migrate from an impersonal “one-to-many” strategy to a personalized “one-to-one” approach, without devoting more time to the effort.

Talent acquisition professionals now find themselves in a similar position. In the competitive talent marketplace, candidates expect personalized, authentic communication — not generic email blasts and one-size-fits-all messages. So how can talent acquisition teams rework their strategy and their tech stack?

Luckily, we don’t have to reinvent the wheel for talent acquisition. We can borrow a few pages from marketers’ playbook.

Personas Help You Personalize

It is all about personalization today, right? But you cannot begin to deliver personalized messages if you don’t really know your audience. Marketers develop buyer personas to help guide them.

What is a persona? The simplest definition is a semi-fictional representation of your ideal customer. One way that marketers develop personas is by gathering feedback from their sales team. The sales team understands the buyer better than anyone else in the organization. They know what drives them, what interests them and, most importantly, what questions they regularly ask.

How to apply this to talent acquisition: TA professionals can build “candidate personas.” For each persona, try to uncover what is important to them when it comes to their job, their strongest skills, how would they describe their personality, what groups they belong to on LinkedIn, and anything else that will help you develop personalized messaging and communications to the right target audience.

Consider Content

Before diving into any marketing automation program, marketers typically segment their prospects to deliver highly relevant content. A marketing best practice in developing content is to create pieces for each point of the buyer journey. For example, content for the top of the funnel should help raise brand awareness. The middle of the funnel content should help convert a prospect to a lead. Marketers often “gate” this type of content, meaning someone has to fill out a form before they can access it. Once those leads are captured, nurturing campaigns (drip marketing) can begin.

How this applies to talent acquisition: It’s no secret that candidates expect a personalized experience today. So, as you develop your pipeline for specific job families or hard to fill roles, consider what type of content makes sense for each stage of the candidate journey.

Nurture, Nurture and Nurture Some More

Marketers work really had to develop a strategy that will bring in leads. The last thing they want to do is lose those leads! Once leads have been captured they need to be “warmed up” and handed off to the sales team to further develop. That’s when the aforementioned email nurturing campaigns come into play. Yes, email. According to an Adobe 2017 survey, email is the preferred method of communication (61%) over other channels.

How this applies to talent acquisition: Once you have segmented your talent pipelines, think about how you want to keep these candidates engaged. What information can you include in your emails that will be of interest and what’s the best cadence? Maybe a company email newsletter, blog or video with the latest happenings at your company? Be sure not to send two emails to the same person in a week and keep this stat in mind: An engaged user only commits 8 seconds to reading an email. Always keep it short and sweet and enticing.

Measure Everything

Although many marketing tactics can be very tough to measure, marketing automation is not. And that is by design. After all, automation is supposed to make everything easier, and that includes reporting and measurement. With marketing automation, marketers can view stats from a very high level — open rates, click-through rates, etc. — or drill down to the finite details like which web pages were visited, how long the visitor stayed on each page, and session replays.

How to apply this to talent acquisition: Data drives decisions. The most effective recruiting enterprises thrive on rich, timely, and actionable information. Understand your lead sources, which pipeline needs more action, and how long it takes to fill those hard-to-fills in order to set benchmarks and goals for success.

Speaking of goals, I’m ending this blog post with what should always be the beginning — a strategy. Marketers never proceed without setting goals and mapping out a strategy to obtain them. Perhaps a talent CRM is just the tool you need in your recruitment toolbelt. Not only can it help you to source and nurture candidates, but it can also help you build pipelines, improve time-to-hire, personalize the candidate experience and automate the entire process. Go ahead. Steal a page from marketing automation’s playbook and start winning.

This post is sponsored by gr8 People.

Will a Robot Take Your Marketing Job

Are you panicked yet that artificial intelligence (AI) will soon put you out of work? Could a robot take your marketing job? Some of the brightest minds in Silicon Valley are warning of massive job displacement across the economy in the next decade.

But there remain good reasons not to be terribly alarmed. At least, not for a while.

First, the bad news: according to, “Between 9 percent and 47 percent of jobs are in danger of being made irrelevant due to technological change (in the next 15 years), with the worst threats falling among the less educated.”

Some panelists at SXSW this spring were even more apocalyptic. Bill Gates said, “AI is the biggest threat to the human race. I can’t believe more people are not worried about this.” Steve Wozniak added, “Fast machines will eventually get rid of slow humans.”

There’s no question the nature of work will continue to change, of course. Automation has been gradually displacing human labor since before the industrial revolution. And AI will expand the range of tasks machines can perform, through “smart” automation.

Yet the future for workers may not be so bleak after all, particularly in skilled trades and in creative professions like marketing. Here’s why.

Robots Can’t Make It Alone—Even in Manufacturing

Robots have been used in manufacturing since 1959. And it’s true, automation in general, and robots in particular, have had a significant impact on factory employment. The number of U.S. workers employed in manufacturing fell 39 percent from its peak in 1977 to 2012. Five million factory jobs have disappeared since 2000, partly due to trade but primarily due to automation.

However, those trends don’t quite tell the whole story. The U.S. has actually added one million manufacturing jobs since employment in the sector bottomed out in 2010. And growth is continuing. According to the latest figures from the Bureau of Labor Statistics (BLS):

“In February (2017), employment in manufacturing rose by 28,000. The manufacturing diffusion index increased from 50.0 in January to 65.4, its highest level since November 2014. A value above 50 indicates that more component industries gained jobs than lost them.”

Factories are having trouble finding workers—at least finding those with the right skills. In Minnesota, for example, “nearly 5,000 manufacturing jobs are unfilled — a number that will likely grow as more and more employees move into retirement.” And nationwide, Bloomberg projects, “Over the next decade, 3.4 million manufacturing jobs are expected to become available as baby boomers retire and economic growth spurs work opportunities… but a skills gap could result in 2 million of those jobs staying unfilled.”

How is it possible that employment may grow and factories may face (human) worker shortages even as robotics and AI technologies advance? Simple: Automation increases productivity (which increases societal wealth) and makes the U.S. more competitive globally. We’ll need more workers and more robots.

Driverless Vehicles Roll Forward Slowly

A recent U.S. government report—Artificial Intelligence, Automation, and Economy—predicts driverless automated vehicle (AV) technology may eliminate 2.2 to 3.1 million existing U.S. jobs. But any such job losses that occur won’t happen immediately or abruptly. They will be spread out over time.

Further, the report concedes that certain types of drivers (e.g., long-haul truckers transporting goods) are more likely to be replaced than others (school bus drivers transporting children, for example). The study also notes, “New jobs will also likely be created, both in existing occupations—cheaper transportation costs will lower prices and increase demand for goods and all the related occupations such as service and fulfillment—and in new occupations not currently foreseeable.”

And those projected job losses assume AV technology will become reliable and trusted. Though great progress has been made (driverless vehicles are being tested in several cities beyond San Francisco, Detroit, and Pittsburgh), some of the hardest work remains. As the expression among software developers goes, the first 90 percent of a project takes 90 percent of the time; and the last 10 percent of the project takes the other 90 percent.

AV technology will need to work nearly flawlessly before adoption becomes widespread. Business Insider has reported that lawyers are “salivating” over self-driving cars because they are “going to get a whole host of new defendants,” with deep pockets, in the event of any crashes.

Development of AV technology that works dependably regardless of weather, daylight, and other conditions remains challenging. As Gary Marcus, a best-selling author, entrepreneur, and professor of psychology at NYU, pointed out in TechCrunch regarding AI, “look for example at a driverless car, that’s a form of intelligence, modest intelligence, the average 16-year-old can do it as long as they’re sober, with a couple of months of training. Yet Google has worked on it for seven years and their car still can only drive —  as far as I can tell, since they don’t publish the data —  like on sunny days, without too much traffic.”

Still, robots and AI already have displaced some workers and will continue to expand into new jobs, particularly those that deal with things rather than people. It will likely be a long time before robots are trusted to care for children, or adults with special needs, but they’ve already been running warehouses for years.

Public policy will need to address those job losses, for example with displacement assistance and retraining programs. But standing in the way of AI and robotic progress would be counterproductive (literally); by increasing productivity, they raise living standards across society. Schemes like a robot tax are a bad idea.

So, Robots Can Weld and They Can Drive—But Can They Market?

Technology has eliminated wide swaths of employment in the past, from telephone operators and electric typewriter repairers, to photo technicians and video rental store cashiers. It’s now threatening various types of clerks, professional drivers, even insurance underwriters and appraisers.

But AI is more likely to change how marketers work than to replace them. It will supplement the efforts of human workers rather than take their jobs. Why?

First, consider one type technology already in wide use: marketing automation software. Despite the label, these applications don’t “automate” marketing; they merely enable marketing professionals to set up sequences of email messages which are then automatically sent out using (human) defined sequences and branches.

There are marketing professionals, agencies, and consultants who specialize in optimizing the use of marketing automation systems. In the words of Marketing Week, marketing automation platforms “don’t destroy jobs, they just change what jobs are needed.”

Second, there are several distinctly human characteristics essential to marketing that will likely prove vexing to reduce to mimic with silicon.

Interpretation: An AI-based tool like PaveAI can evaluate 16 million possible correlations within Google Analytics then produce a report showing the most significant findings. But it still requires a human to interpret the results.

For example, knowing that the highest conversion rate correlates with visitors who land on your home page on a weekday during business hours is about as unsurprising as any data point could be to a B2B marketer. But discovering the lowest conversion rate associated with a particular section of your website visitors often reach through organic search is far more interesting, and actionable.

Sentiment analysis presents another type of problem. Words like bomb, sick, mad, bad, and beast are generally considered negative terms to associate with your brand; yet all have, within recent memory, had a positive connotation in slang. People get that (hopefully). Machines will likely struggle.

Creativity: Marketing is an almost uniquely left brain and right brain profession. Data analysis, where AI can help, is of course vital.

But emotion plays a significant role in every considered purchase process, impacting both consumer and B2B buying decisions.

The creative side of marketing appeals to our emotions, and that side requires distinctly human creativity. It’s difficult to imagine, for example, even the most sophisticated AI systems coming up with something like E*TRADE’s invest in vests commercial.

Originality:  AI can help marketers optimize current channels, but it won’t develop radically new ideas. For example, AI can help optimize and personalize email content—but AI never would have come up with the idea of using email for marketing in the first place (that was Gary Thuerk of Digital Equipment Corporation).

AI may help with optimizing messaging and timing on social networks. But it couldn’t have spontaneously computed Oreo’s famous dunk-in-the-dark tweet… Or suggested creating a profile for KFC’s famous founder on LinkedIn. And it certainly wouldn’t have invented a sporting event to support brand content marketing, as Red Bull has done with Crashed Ice.

Perspective: Not every question, in any realm of life, has a clear-cut answer. Even when looking at the same underlying data, reasonable and intelligent people can disagree, based on their beliefs, assumptions, experiences, and definitions—in short, based on their perspective.

For example, is it possible to accurately measure the ROI of social media marketing efforts? AI could provide an answer—and with the right data sources, even perform the calculations—but it couldn’t provide the perspective on the answer that a human thought leader provides.

In marketing content, it’s often the perspective that’s as interesting as the answer. It’s difficult to imagine an AI system weaving a narrative from a unique or interesting perspective. It’s even harder to imagine AI writing this post.

Persuasiveness: Great marketing in any form—text, visual, video—combines logic with emotion to move buyers to act. AI has logic literally at its core, but trying to teach AI to understand human emotions has so far been an enormous challenge.

Robots: The New Job Creators?

An analysis by The Economist on the impact of robots and AI on employment suggests not only that the fear of massive job losses is likely overblown, but that in some cases automation may actually increase the number of jobs for humans. A study of the American job market from 1982 to 2012 found that:

“Employment grew significantly faster in occupations (for example, graphic design) that made more use of computers, as automation sped up one aspect of a job, enabling workers to do the other parts better. The net effect was that more computer-intensive jobs within an industry displaced less computer-intensive ones. Computers thus reallocate rather than displace jobs, requiring workers to learn new skills. This is true of a wide range of occupations…

“So far, the same seems to be true of fields where AI is being deployed. For example, the introduction of software capable of analyzing large volumes of legal documents might have been expected to reduce the number of legal clerks and paralegals, who act as human search engines during the ‘discovery’ phase of a case; in fact, automation has reduced the cost of discovery and increased demand for it. Judges are more willing to allow discovery now, because it’s cheaper and easier… The number of legal clerks in America increased by 1.1% a year between 2000 and 2013.”

The analysis also reiterates that almost every new wave of technology in the past has raised the specter of mass unemployment, only to end up creating more jobs than were destroyed. The term “technological unemployment” sounds like a concept Gates or Wozniak may have devised. The phrase was in fact coined by economist John Maynard Keynes in the 1930s. The total U.S. labor force more than doubled in the following five decades.

In marketing, AI will take over routine and data analysis-intensive tasks, but also create new opportunities for human employees—for example, in training and teaching AI systems. AI is already being used in areas like personalizing product recommendations and more granularly targeting advertising.

But AI requires human training, testing, and teaching both during the implementation phase and on an ongoing basis. Both human testing and human judgment are needed up front in terms of preparing AI platforms for the real world and determining when they are ready to go live.

Harvard Business Review article points out the level at which AI systems are “good enough” varies widely by application; a mistake by Alexa or Siri in understanding speech and ordering the wrong item is annoying. A mistake by a self-driving vehicle may be fatal.

Once live, AI platforms—just like a human graduating from college and entering the workforce—need continued training over time to increase their capabilities and stay current with changing tastes and technology.  And that means people, as explained in VentureBeat: “AI’s advancement up the value chain is only possible with the aid of human intelligence.”

Historically, technological advancements have always ended up creating more jobs than they destroyed. Today may prove to be different, but for now, it appears robots are more likely to be workplace assistants rather than job terminators. As a marketer, you probably don’t have to worry about robots or AI taking your job. But you will need to be prepared to work with these technologies to do your job better.

Photo Credit: The Adventurist and MOCIST Flickr via Compfight cc

This article was first published on V3Broadsuite.

Talent Acquisition Has a Marketing Problem

My previous two posts in this series, Why We Don’t Need to Reinvent the ATS and Talent Acquisition Technology: Reinvention and Innovation, discussed the state of the talent acquisition marketplace and the current machinations of the ATS product category.  Justifiably, this asked: “Should we try and reinvent the ATS?” or “Should we look for another way forward?”

To me, the answer is clear: the ATS by itself is not enough. That doesn’t mean, however, that the ATS isn’t part of the solution. Rather, other systems are emerging that can help make the ATS better―ones purposely built for the coming realities our industry will be facing.

The Consumerization Of The Candidate Experience

Five to 10 years ago, getting access to the right talent was much easier. Job boards reigned supreme, and the competitive noise was at acceptable levels. With these channels, you reached the audience you needed to reach. Fast-forward to today where nearly every organization uses job boards in some form or fashion, but the results vary (and in most cases have reduced in effectiveness).

It’s not that job boards can’t be a useful part of a successful strategy.―the real problem is that we have not evolved how we use these channels to communicate our organization’s value and differentiate our opportunities. We are still stuck in the Stone Age of job ads, still stuck with selling job positions vs. selling our employer brands, employee stories and true value as an organization. Talent acquisition is not faced with an HR problem; we are faced with a marketing problem.

Candidates, especially the top ones, are used to being consumers. They are used to being catered to by companies; consistently receiving personalized and useful content and messaging from brands; researching and comparing companies and products; and are increasingly more informed about making purchasing decisions.

Candidates fully expect a similar experience in their career search, and, more importantly, don’t differentiate between organizations’ marketing brand and employment brand. Candidates are wholeheartedly embracing their alter ego―the consumer―when they look for their next career opportunity. Talent acquisition organizations need to adjust by not just being recruiters, but by also being recruitment marketers.

Learning From The Marketing & Sales Technology Blueprint

With the influx of readily available information online, data aggregation to help consumers easily compare options and user-generated content providing context to inform purchasing decisions, the consumer has gained control of the sales process.

This consumer revolution has made companies rethink how they interact with prospects and customers, and in many cases, necessitated the development of new skills, processes and tools to effectively reach the right consumers. One such example is the use of specialized technology to enable marketing and sales organizations to better reach modern consumers.

As marketing and sales organizations have matured, they have focused on modernizing their respective areas of the sales funnel:

  • Marketing is focused on generating qualified leads for the organization in the top half of the funnel. To do this, they execute and evaluate a diverse strategy of content, campaigns and channels to get consumers to convert into qualified leads for the sales team. In the end, the main goal is generating the most Marketing Qualified Leads (MQLs).
  • Sales is focused on converting these qualified leads into customers in the bottom half of the funnel. It’s their job to convince prospects of the value proposition of the product or service and influence the selection process. In the end, the main goal is generating revenue through sales.

It’s taken years for marketing and sales to find the right balance with each other and, in turn, each has figured out the key responsibilities and technologies it needs to be successful in its own pursuits.

Sales CRM tools such as Salesforce rose up to provide order to the chaos of tracking sales contacts. It provided structure around the sales process, helped the sales team better stay in touch with prospects, and most importantly, allowed for reporting on the sales funnel and process to ensure the sales model and practices actually worked. These systems provided huge value at the time, and still do so today.

As marketing evolved, they began using the same system as sales, but realized the limitations in terms of functionality for their needs. They needed a system that was less about process and more about engagement―one that enabled better emailing capabilities, targeted landing pages for content and stronger metrics to track the multiple touchpoints that potential leads interacted with before converting through CTAs or the website. These needs led to the birth of Marketing Automation Systems.

As you look at the technology space today, Marketing Automation Systems and Sales CRMs work in concert with one another to provide an integrated experience and view into the full marketing and sales funnel. They’ve addressed the unique needs of the professionals for the two distinct disciplines they were built for―and both disciplines are better off for it.

Look for my next post on how these technologies align with the way forward in talent acquisition software. 



Smashfly is a client of TalentCulture and has sponsored this post.