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Fight Recruiting Spam Through Measurement and Modeling

Fight Recruiting Spam Through Measurement and Modeling
From Recruiter - December 2, 2016

Recently, Ninh Tran and I had a discussion on the topic of recruiting spam. The struggle is real, folksnot just in our industry, but for the whole business landscape.

We cannot fix the problemwith other industries, but we have to try in ours. The conversation Tran and I had brought us to the conclusion that we could use big data to take on the challenge of spam. If youre interested in this mission as well, please join us.

Lets start by first defining what spam is. We are not talking about the tasty, salty treat that you ate with eggs as a kid, but the email clogging up your inboxand, if you are like me, draining your phones battery life. The definition of spamming, according to Wikipedia, is the use of electronic messaging systems to send an unsolicited message (spam), especially advertising, as well as sending messages repeatedly on the same site.

The key component of that statement is unsolicited message. The major problem of spam is that we did not ask to be emailed but still are. Sometimes, people sign up for a hosted webinar about a particular topic, and by doing so, they aresaying that theywould be okay with beingemailed product announcements from the vendor that hosted the conversation. I just wanted to clear that up, as earned interest is one of the requirements that makes a message solicited.

Spam accounts for 14.5 billion messages globally per day, and it makes up roughly45 percent of all emails. If you are surprised by these numbers, you dont check your spam box very much.

Ironically, were still producing spam emails every day, intentionally or not. We dont have the statistics on how much spam is generated byrecruiters specifically, but we do know that recruiting spam has been a serious problem in our community. Just look at the#FightSpam group on Facebook run by Steve Levy.

As recruiters, we should look at the data in a new way so that we can learn from our own best practices.

But enough from me let us hear from the COO and cofounder of Hiretual, Ninh Tran.This is going to be cerebral, so Aaron Lintz, Glen Cathey, Stacey Zapar, etc. get to geek out. Me, I am taking a nap.

FromNinh Tran:

Before we can come up with any solutions, we should dig deeply into the reasons why recruiting spam happens. Derek Zeller summarized the hard truth about recruiting spam in this article. The most insightful part to me is the statement, If someone doesnt realize they have a problem, they will never even try to fix it.

The problems of spam are often attributed to having a wrong mindset like spam works or a mixed bag of lack of training, bad leadership, or people just being lazy, as presented by Allison Kruse and Glen Cathey at SourceCon.

When I dig a bit deeper, I find that those who spam often dont have to deal with the repercussions of spamming, like a damaged employer brand or an angry mob of people (Google recruiters are to see how people feel about the profession). Imagine if every spam message we sent would cost us a couple minutes of our liveswould we spend a little time personalizing our messages? I would.

Fortunately and unfortunately, thats just my imagination.

What I have found is that people are not fighting spam because they are not asking the right questions or not questioning their methods at all. I get itspam is a complex problem, and complex problems dont have simple and clear answers. But that shouldnt stop us from trying to ask the right questionswhich just might do the trick and point us to many viable solutions.

Most of the time, we all totally agree that we should fight spam. However, we rarelyknow if our own recruiting has been spammy or not. We have no standards by which to measure our email recruiting performance beyond the uninsightful response, acceptance, open, and click rates. How do you measure your spamminess? Do you actually mark down how many unsubscribes or angry responses you get? Does that lead to visible changes in our recruiting processes?

A fundamental approach to solving our spam problem involves addressing the lack of insightful measurements and effective models to guide us. What follows is a deep analysis of email recruiting strategies. The model I propose is general and practical tomeasure the performance of email recruiting. My hope is it could be helpful to our recruiting community.

Measuring the Impact of Email Recruiting

Here are some variable we should define first:

The goal of our email recruiting is to maximize profit (W). We knowthat profit is the difference between benefits and costs. Therefore,

Equation 1: W = YZ

To simplify the model, lets assume two things:

First, that the benefits (Y) linearly depend on the numberof emails sent (X).



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