TheLadders Blog

Since moving back to a free model for employers last October, we have made it easier for them to post jobs on TheLadders, yielding a 116% year-over-year increase in Q1 2013. One of the features we offer is the ability to rate the applicants either a “Fit” or a “No Fit,” which improves the matching experience on both sides.

In assessing this selection process, my team and I reviewed more than 100 jobs from this year’s first quarter and analyzed the 4,242 applications received for those positions. Typically, our jobs receive an average of 14 applications but for the purpose of our study, we selected jobs that received at least 15. We needed a large sample size to better understand and identify differences in behavior, and to ensure that the results were statistically significant. So, what did we learn?

• 17% of the applications received a “thumbs-up” rating, meaning they were a fit for the job
• 39% received a “thumbs-down” rating and, therefore, were not a fit for the job
• 44% of the applications were not rated at all

We studied 20 different variables for each job application in order to identify what caused an application to be rated a “thumbs-up” (a fit) or a “thumbs-down” (not a fit), which generated a fair amount of noise and inconclusiveness.

Ultimately, we were able to identify that the variables that best explain the ratings were:

• Time to apply
• Job Title
• Location
• Function

Shouldn’t Salary be a good indicator of “Fitness”?

Below are three different box plots that visually represent the salary distribution of the applicants to three different jobs. In two cases, we can see meaningful differences between “thumbs-up” and “thumbs-down,” but little difference with the non-rated candidates. In the third case, we observe hardly any difference between all three groups.

Across all 100 jobs, we did not see any evidence other than if an applicant’s salary is two standard deviations away from the average salary of the applicants rated a “thumbs-up” (a fit) than in those instances salary was a factor. In others words, for the outliers, salary was a factor that influenced the rating negatively (either low salary or high salary).

For example, with a marketing manager job where the average applicant earns $120K a year, if an SVP in marketing earning $220K were to apply to that job then, the high salary of that person would be the reason why this applicant would be rated not a fit.

The other reason why our data excludes compensation from being a negative factor is that we already control that factor in our user experience. At TheLadders, we have organized our candidates and jobs in five salary bands. The distribution is as follows:

• $40-60K
• $60-80K
• $80-100K
• $100-250K
• $250K+

Therefore, a professional earning $60K a year cannot apply to a job paying $150K and vice versa, a $200K Vice President cannot apply to a $75K associate job.

Location:

Example: Managing Consultant, Chicago IL

The location of the applicant impacts the candidate’s fitness for a job. This factor is specific to the preference of the employers performing the search. In some cases, the company is willing to relocate out-of-state candidates and, in other cases, the company is not. The maps below illustrate the case of a recruiter not wanting to relocate candidates. Applicants outside of Illinois were rated a no fit or simply not rated at all.

Job Title:

Example: IT Infrastructure Program Manager Windows 7

The data reveals that with most of the jobs, the applicant’s current title is a great variable to predict job fitness. In our example below, you can see that the applicants with titles such as CIO, VP of IT Services, Director IT, and Personnel Manager were rated not a fit or not rated at all. The recruiter behind this job is rejecting the over-qualified candidates who are applying to position below their levels (see graph below).

Function:

Example: Project Execution Consultant in Construction/Real Estate

Function was a less obvious variable that helps predict a candidate’s job fitness because we already control for function at TheLadders with our matching algorithms. However, with keyword search, we do not prevent candidates with a background in a particular function to view and apply to jobs in a different function. As you can see in the example below, the recruiters rejected candidates with a background in operations, general management or engineering. Only candidates with a background in real estate and construction received a “thumbs-up” from the employer.

Time to Apply:

Example: Division Finance Manager, Atlanta, GA

As we investigated 20 different variables such as function, salary, location of the candidate, and job titles, we found that one of the leading success indicators to be rated a fit was time to apply. What does time to apply mean? It is the number of days between the time the job was published on our site and the time (stamp) of the application.

On average we saw the following:

• 10.38 days for a “thumbs-up”
• 13.53 days for a “thumbs-down”
• 19.79 days for the not rated

The causality between that variable and the three other rating types became even more apparent when we looked into the median time (midpoint of the distribution):

• 2.81 days for a “thumbs-up”
• 4.32 days for a “thumbs-down”
• 13.95 days for the not rated

In other words, half of the applicants rated a fit for the job had applied to that same job within 72 hours of the jobs being published on our site. The median time for candidates rated “not a fit” was 50% higher and for the non-rated candidates, the median time was 400% higher. Below is the applicant distribution by time for a Division Finance Manager job in Altanta. The green bars represent the applicants rated “thumbs-up.”

Who is getting the job in the end?

The findings from this study teach us that the people who are getting the job cannot be explained by only one variable. It is usually a combination (one or many) of having the appropriate salary, the experience level, being from the appropriate function (marketing professional applying to a marketing job), having the required expertise (online marketing vs. public relations) and preferably being located near the job location (to avoid occurring relocation expenses).

However, the most eye-opening finding in our research was the following: regardless if one might be the perfect fit for a job, the later one applies to a job, then the less likely one is to get a call-back. That is the sad reality, even if that person was the purple squirrel that the company had been looking for all along.

Alex Douzet is CEO and Co-Founder of TheLadders. In this role, Alex is responsible for the company strategy, global business operations, and product development.

Happy Mother’s Day! In celebration of all the hard-working mothers out there, we recently conducted a study to see if the names they choose for their children could have possibly dictated their future success in the workplace. First, we analyzed data around first names from TheLadders’ nearly 6 million members against variables such as industry, salary level, and location. We wanted to prove the null hypothesis that what your mother names you makes a difference.

Second, we populated a few lists, hoping they would generate some additional questions. We started by aggregating and sorting names that were at the top of each list:

Top five C-level names, by gender, in ratio to their overall frequency:

Top five highest-paid names:

Both lists are normalized for frequency (not just absolute counts) giving a ratio of [C-level first names]/[all first names]. Here are a few quick takeaways:

• Christine was the only name that showed up on both the top five C-level and highest paid lists
• The top 10, highest-paid, C-level executive names earn, on average, 10% more than other names
• The top 25 most-popular names make about $7,000 more, on average, than the rest of the list
• Females make, on average, 22% less than their male counterparts in all comparisons

One point we noticed was that shorter names seemed to be higher ranked across all categories and metrics, so we investigated further. It turns out we were right, and there is a correlation between the number of letters in your name and the average salary:

Doing a simple linear regression, it looks like every additional letter added to your name accounts for a $3,600 drop in annual salary. One exception is names with seven letters, like Stephen, but closer inspection showed that seven-letter names lend themselves to males over females, so it’s higher paid males over-indexing and inflating the seven-letter bucket.

This surprising trend of shorter names led us to look at nicknames, and test whether Williams truly make less money than Bills. We looked at every abbreviation and nickname we could identify; here is a summary of results in the “Nickname versus Proper Name” head-to-head death match (gold stars for the winners):

All the shorter names earn more. Our test included 24 pairings, and in only one case (Lawrence vs. Larry) did the longer name win. Still not convinced? The definitive proof for this theory can be seen in Sara vs. Sarah, Michele vs. Michelle, or Philip vs. Phillip –  one letter less positively correlates with increased salary.

In conclusion, it DOES make a difference what your mother named you. So, to all prospective mothers, our advice is to keep Baby’s name short and sweet – your child will thank you when they’re raking in the money one day.

Thanks, Mom, for naming me Daniel but nicknaming me Dan. Happy Mother’s Day!

Daniel Cronyn is the director of consumer marketing at TheLadders. Besides a passion for creative direct-response campaigns and analysis, he spends his time tracking down obscure music events and even more obscure food choices across New York City.

Anyone who has ever looked for a job knows the drill: find job online, send resume, wait, and never hear back. If you’re sending out dozens of resumes, like most job seekers do, you’re likely familiar with this broken process — and frustrated when you don’t get a response. In the careers industry, this broken loop even has a notorious name: “The Black Hole.”

Recently, TheLadders conducted a study on job-seeker behavior using “eye-tracking” technology to determine how we could help close The Black Hole while leading job seekers to their perfect job. We analyzed how job seekers view job postings, what they actually saw, what they concentrated on, and what they totally missed.

If you’re unfamiliar with eye tracking, it’s a way to record and analyze where someone focuses on a page, and in what order they do it (see cool visualizations above).

So, what did we find out?

Job seekers assume The Black Hole exists because employers do not take the time to respond, which is only partially true. What we found from our behavioral analysis was that job seekers also played their part in The Black Hole, which can be statistically proven through our eye-tracking study.

The fundamental conclusion of our study relies on sensitivity and specificity, two really important statistics terms. Sensitivity, in this study, was the ability of job seekers to correctly determine a good job “fit” for them, while specificity was the same job seeker’s ability to determine a job “not a fit.” Basically, we were on a mission to find out if job seekers were applying to the right jobs, and avoiding applying for jobs that were not right for them.

Surprisingly, the results of those two pieces of analysis showed us that job seekers were unable to determine good jobs, only picking good fits at a rate of 38%, but were able to tell bad fits at a rate nearly twice that. For further clarification, this means that out of every 10 jobs an average job seeker applies to, six of them will be bad fits. Additionally, this means that out of every 10 job postings viewed, the job seeker overlooks at least two that are good fits.

Our primary assumption for why this happens is due to the time spent reading and assessing the positions. Sixty-five percent of our study participants self-reported spending up to ten minutes reading job postings before applying; however, our study findings show that, on average, job seekers spend less than a minute per job posting – even less when they determine it’s not a fit.

What can TheLadders do to help job seekers make better decisions in the job sourcing and application process? We have to make the application process more precise, so that job seekers can better identify the right opportunities and avoid getting stuck in The Black Hole. This is why we recently introduced TheLadders Scout, a competitive-analysis tool that provides job seekers with an anonymous overview of who else applied for that same role.

To determine the effectiveness of TheLadders Scout, the second part of our study tested how participants viewed the competitive data provided, and whether it influenced their ability to identify good fits.

The results were equally surprising, in that job seekers eyes were heavily drawn to the new feature on the page, and spent on average 12 incremental seconds viewing the competitive data.

Additionally, participants viewing job descriptions with TheLadders Scout were able to determine good fits at a 35% higher rate than job descriptions without Scout. With 12 seconds of viewing time being devoted to TheLadders Scout, we expected the overall viewing time of postings with TheLadders Scout to increase, but we were proven wrong. Job seekers spent 24% less time finding fits with TheLadders Scout.

Looking at these “heat maps,” you can see that job postings without Scout data on them (pictured on the left) drew job-seeker attention primarily to the title, company description at the top, and then the first line of the first couple of paragraphs. The majority of information (such as job requirements) was skimmed, or went completely unnoticed. In the Scout version, not only was more information read, but 12 seconds were spent reviewing the competitive information and determining based on other applicants if the position was truly a fit.

For us at TheLadders, the study provided valuable information, not only on why The Black Hole exists, and why employers and job seekers have equal roles in contributing to it, but also on how we can provide features and tools to help close The Black Hole.

Download the full research study. 

 Daniel Cronyn is the director of consumer marketing at TheLadders. Besides a passion for creative direct-response campaigns and analysis, he spends his time tracking down obscure music events and even more obscure food choices across New York City.

Spring is upon us! For most of us, spring evokes familiar images of Easter eggs, flowers, and longer, warmer days to come. However, according to our members, spring is also the time of year when you’re happiest with your job.

Across the country, employees report the biggest increase in job satisfaction when winter weather gives way to spring, boosting overall job happiness by 13 percent. Are you ready to be 13 percent happier?

While overall job satisfaction increases across the country from winter to spring, the variance of the increase was also dependent on things like regional climate, and a person’s job industry and salary. In colder American job markets, like Boston, New York, and Chicago, working professionals are 30 percent happier to see spring come than their counterparts in warmer markets like Los Angeles, Houston, and Miami. Makes sense right? If your winter is colder, then of course you’ll be happier to see spring than someone in a warmer climate.

But hold on, after further analysis, we discovered that people in colder markets report an average job satisfaction level 28 percent higher all year long than warmer markets (even those toughing it through famously cold Boston winters). Let’s look into why…

• Warmer job markets have a higher percentage of sales professionals
• Regardless of location, season,  AND salary, sales professionals generally report higher levels of dissatisfaction
• Colder weather markets have a more even distribution of professions across their top job types

Basically, more sales employees with a less diverse job market means that no matter how beautiful it is outside, that market is relatively less happy with their jobs.

TheLadders unearthed lots of other interesting trends; here are some highlights:

• Happiest Job Market: Washington, DC,
• Unhappiest Job Markets: Sacramento
• Happiest Professions: Law, Tech, and Accounting & Finance
• Unhappiest Professions: Real Estate, Sales, and Education

One more interesting trend showed that the axiom, “mo’ money mo’ problems” is actually true. Professionals making or “about to make” $100k proved to be the happiest, meaning there is a psychological factor in starting to make six figures (something employers could leverage in raises/bonus considerations), even though the difference between $90k and $100k is nominal in your take-home pay.

Additionally, the trend data shows quickly diminishing returns on incremental salary as employees near the $200k mark. Across all industries, professionals reported being less happy the more money they made after $170,000 per year. Think about that: on average, professionals making $240,000 a year reported being slightly unhappier than those making $40,000.

So who is the prototypical happiest worker in the country? Drumroll please…our analysis shows that a city-dwelling techie, who works in the northeast during the spring months, and makes six figures (but under $200k) is the happiest employee in the country. Conversely, if you find yourself working a sales job in Sacramento, perhaps this research will persuade you to pack your bags and take a cross-country road trip this spring.

* This study analyzed the behavior of more than 390,000 TheLadders members over the past two years.”

Daniel Cronyn is the director of consumer marketing at TheLadders. Besides a passion for creative direct-response campaigns and analysis, he spends his time tracking down obscure music events and even more obscure food choices across New York City.

TheLadders has predominantly operated with the goal to make the job hunt shorter, less painful, and more efficient for job seekers and recruiters. We’ve had our successes, but of course we’re always trying to get better.

One of our initiatives was to partner with professors from seven leading universities to research and understand various aspects of the job search and recruitment process. We conducted an in-depth study of job-search challenges, in partnership with Connie Wanberg, from the University of Minnesota, an internationally recognized expert on the topic. The study,  “Navigating the black hole: Explicating layers of job search context and adaptational responses,” has been published in the Personnel Psychology journal.

For this particular study, we had semi-structured phone interviews with more than 70 job seekers that lasted anywhere between 30 and 60 minutes. These calls were transcribed and analyzed to identify common challenges across all job seekers.

For me, hearing our job seekers’ personal stories was insightful. Frustrations with the current economic climate, the lack of human touch or feedback, the technology-driven application processes – all came to the forefront in the form of real stories. Day-to-day challenges of managing the time and effort needed to find and apply to the right jobs, as well as the discouragement one often faces in the process, compound the stress related to finances and life-changing decisions that a job search can bring about. While it can be a learning opportunity, most people viewed the job search experience negatively and understandably so.

Our research here at TheLadders allows us the luxury to be curious. We strive to know more about the job search and how it works, and predict events and human behavior that drive job seekers and recruiters. Teaming up with world-class experts, we’ve been able to look at our customers’ pain points through a new lens, and we look forward to continuously improving our offerings to alleviate these struggles for our customers.

A white paper, commissioned by TheLadders, can be downloaded here, and a video interview with lead author Connie Wanberg can be viewed here.

Archana Agrawal is the Vice President of Strategy at TheLadders. In this role, Archana is responsible for managing the planning and analytics function, including product utilization, marketing analytics, and financial planning and analysis.

Every day, I provide advice to job seekers on ways to improve their job search. Some clients are looking to get promoted at their current companies, whereas others want to change employers and will accept a lateral move in the same industry. That said, many are seeking something completely different. Apart from the advice and resources I offer, I motivate job seekers to step out of their comfort zones to look for possible job opportunities.

Looking at the results from our summer job-search survey, which are illustrated in our awesome infographic below, I cringe at the discovery that only 31% of respondents say that they network more during the summer. Summertime activities present a unique opportunity to network with loads of new people. Whether at the beach or at a baseball game, you should make it a point to strike up a conversation with someone you don’t already know. People are generally more relaxed during the summer, making it easier to grow your professional network while celebrating your social life.

However, seeing that 71% of respondents believe employers are less responsive during the summer was not surprising to me. Whether they’re taking an extended weekend at the beach or enjoying shortened summer hours, employers tend to be away from their desks more during the warmer months than other times of the year. Nevertheless, this doesn’t mean that hiring slows down during the summer, so it’s imperative to remain persistent.

While the summer may seem like a slow period for job seekers, there is typically less competition during these months, so it’s actually an ideal time to get out there, network, and seize the opportunity. For additional information, check out these tips to help job seekers stay motivated during the summer months, from Job Search Expert Amanda Augustine.

Click here to download a PDF version of the Summer Job Search Infographic.

Diana DeClemente is a Certified Professional Career Coach, CPCC, for TheLadders. She uses her savvy people skills to help job seekers set and achieve realistic goals and loves motivating them to find their next role. Outside work, Diana enjoys sitting on the beach and watching International House Hunters (separately, of course)!

The weekend before last, I had the pleasure of participating in the inaugural EMC Data Science Global Hackathon. The event, orchestrated by kaggle as part of Big Data Week, involved teams around the world competing to build better, more accurate predictive models of metropolitan air pollution. Air pollution threatens millions of people around the globe suffering from asthma and other respiratory diseases each day, and predictive models like these can provide an early warning system to alert the public regarding dangerous levels of pollutants on an hourly basis.

There was a global competition, in which teams from London, New York, Boston, Chicago, San Francisco, Melbourne, Canberra, Sydney, and Turku, Finland (as well as independent entrants from around the web), battled for 24 hours straight to top the leaderboard by building the most accurate prediction models. The NYC event also included a Data Visualization competition: who could transform the competition data into the most effective and impactful visual form.

My team focused on this Data Visualization competition. Lo and behold: we won! Team CornerOffice (comprised of Frederic de Sibert, Gregory Gorin, and myself) “out-visualized” the other teams competing in the 28^th floor offices at Bloomberg to take the top prize. Our submission leveraged a data analysis and visualization tool called Tableau to create customized, interactive dashboards providing insight (and some animation) around the time, location, season, weather, wind, and other factors affecting pollution levels in the Chicago metro area.

Frederic de Sibert and Gregory Gorin, Noah's partners in the hackathon

Several other competitors boasted impressive visualizations as well – including a simulated public website for accessing pollution prediction information, and another interactive dashboard showing how changing the ranges of any attribute in the data set affected the distribution of all other factors. Thus we were in good company as the esteemed panel of judges – Cathy O’Neil (Intent Media, Mathbabe.org), Chris Wiggins (Columbia University, HackNY), and Jake Porway (NYTimes, DataKind) – chose our entry for the win.

Visualization of poisonous winds in the Chicago area

Having unfortunately elected to take a cruise to the Bahamas last December (ok I’ll admit, probably not the most accurate use of the word “unfortunately”), I missed last year’s annual TheLadders Hackathon, and thus last Saturday marked my first time participating in this kind of event. I was glad to get the W, but even more so to learn a great deal, meet a bunch of great people (especially my teammates Greg and Freddie), and finally see what all this “hackathon fuss” was about. Many thanks must go as well to Matt Turck and Shivon Zilis of Bloomberg for providing the impressive venue and supporting the NYC arm of this global competition. Though this was my first hackathon, it certainly won’t be my last!

Noah Goldenberg is “The Data Guy” (aka Research Analyst) at TheLadders. He’s a New Jersey native, but also spent time as a Virginian and occasionally still says “y’all”. When he’s not wrangling data or winning hackathons, he likes to take it easy and run marathons.