FIRING SQUAD: SquarePeg CEO Claire McTaggart


Back in the day matching - or shall we say - eHarmony wannbe sites really sucked. Now they're kinda good, thanks to AI and a bunch of available online profile data, which was NOT the case in 2006, for example. So here comes SquarePeg. Does this matching contender have what it takes, or are they gettin' the guns?

You'll have to checkout this Talroo exclusive to find out.

PODCAST TRANSCRIPTION sponsored by:

Disability Solutions helps companies strengthen their workforce and broaden their market reach by hiring talent in the disability community.

Joel: Hey, Joel.

Chad: What up?

Joel: Would you say that companies find it hard to attract the right candidates to apply for their jobs?

Chad: Well, Jobs2Careers thought so.

Joel: Jobs2Careers? You mean Talroo.

Chad: Talroo?

Joel: Yeah, Talroo. T-a-l-r-o-o.

Chad: What is that, like a cross between talent and a kangaroo?

Joel: No, it's a cross between talent and recruiting.

Chad: But-

Joel: Talroo was focused on predicting, optimizing, and delivering talent directly to your email or ATS.

Chad: Ah, okay. So it's totally data-driven talent attraction, which means the Talroo platform enables recruiters to reach the right talent at the right time and at the right price.

Joel: Okay, so that was weirdly intuitive, but yes. Guess that the best part is?

Chad: Let me take a shot here. You only pay for the candidates Talroo delivers?

Joel: Holy shit. So you've heard this before. So if you're out there listening in podcast land and you are attracting the wrong candidates and we know you are or you feel like you're in a recruiting hamster wheel and there's just nowhere to go, right? You can go to Talroo.com/attract. Again, that's Talroo.com/attract and learn how Talroo can get you better candidates for less cash.

Chad: Or just go to Chadcheese.com and click on the Talroo logo. I'm all about the simple.

Joel: You are a simple man.

Announcer: Like Shark Tank? Then, you'll love Firing Squad. Chad Sowash and Joel Cheesman are here to put the recruiting industry's bravest, ballsiest, baddest startups through the gauntlet to see if they've got what it takes to make it out alive. Dig fox hole and duck for cover, kids. The Chad & Cheese podcast is taking it to a whole other level.

Joel: Oh snap. After a holiday hiatus we are back and we are feisty

Chad: We back.

Joel: And ready to put a young, nubile startup through the Firing Squad and on that note, let me introduce Claire McTaggart from Square Pegs ... Is that right? Square Peg Hires.

Claire: Square Peg, yes.

Joel: How do you pitch yourself? Square Peg, Square Peg Hires?

Claire: Just Square Peg. We're just one peg.

Joel: Square Peg. All right, we'll go with that.

Joel: She's the Founder and CEO of that company. Claire, welcome to the show. Give us a quick elevator pitch about you.

Claire: Sure, so I'm the founder of Square Peg. My background's probably a little bit different from some of your guests in that I worked in Management Consulting, mostly doing strategy work for one of the big consulting firms. But during that time, I spent four years running a hiring team working at everything from campus recruiting to sourcing strategy to writing and delivering the infamous consulting case study interviews. And we were always just frustrated with the process. Put up a job post, receive hundreds of mostly unqualified applicants, whoever happens to be cruising the job board that week. And either use a ATS to pull out key words or a human to make five second decisions based on a little data. And just, we were kind of hoping to get results. That amount of guesswork and lack of analytics sort of astounded me so I left to go build a product I would have wanted to use. So that's sort of how Square Peg was born.

Joel: And what school did you attend, undergrad again?

Claire: I went to Michigan Undergrad and Georgetown for grad school.

Joel: Ooh, so you know this song because you're always getting your ass kicked by the Ohio State Buckeyes. There it is.

Claire: It's a sensitive subject.

Joel: It should be sensitive.

Claire: It's been sensitive for many years, especially this season it was especially sensitive. So, yeah, off to a good start here guys.

Joel: We like to get you off balance here at the Firing Squad. Play your rival's fight song before you go on.

Joel: Okay, Chad, tell her what she's won before we get to her pitch.

Chad: Well, Claire, on today's show you're going to have an opportunity for a two minute pitch of Square Peg. At the end of those two minutes you're going to hear the bell. Then, Joel and I are going to hit you up with rapid fire Q and A. If your answers start rambling, Joel's going to hit you with the crickets and we will move along. That's also the signal you need to make your shit more concise. At the end of Q and A, you're either going to receive a big applause. That means you knocked it out of the park, golf clap means you need to tighten up your game, or the firing squad. Hit the bricks, close up shop, pull out the drawing board because it pretty much sucks.

Claire: And that could also be the OSU fight song, right?

Chad: The only worse song would be the Michigan fight song.

Claire: Oh!

Chad: Yeah.

Chad: That's Firing Squad. Okay, Joel, let's slam this Square Peg into a round hole. You got that timer ready?

Joel: Slam it. I am ready. Claire, are you ready?

Claire: I am.

Joel: Two minutes starting.

Claire: Okay, so Square Peg is a data-driven hiring platform that helps employers source and match a curated batch of candidates to their jobs based on hundreds of indicators that fit, so not just resumes. We're also now starting to provide HR teams with insights and analytics to help them understand data behind who they're selecting and rejecting and help them improve over time.

Claire: So as you know, there are a lot of factors that make an employee thrive in a

particular job or environment that can't be found on a resume. And what those factors are actually differs depending on the company, the role, or the level of seniority. So Square Peg helps employers identify what skills, experience, personality traits and softer attributes are most important for a specific role in under ten minutes. And then, we source a batch of highly qualified applicants in just a few days. So all of the candidates on Square Peg's platform have been assessed across hundreds of indicators of fit before they're matched with a job. So our algorithms have a really rich data set to help identify top talent and invite those candidates to view the match and share their data.

Claire: So most of these pasts are pasts of candidates who aren't looking for job boards, but are open to the right position. So hiring managers or recruiters will receive a curated batch of interested candidates who might not otherwise had applied or who might have been filtered out. And they get a lot of data to help inform the section and interview process. And because we remove the bias of a human resume review and use alternative data sources, we actually help improve diversity outcomes, unlike your favorite Amazon case study you've been referencing.

Claire: So right now we focus specifically on corporate or business hires like marketing sales and customer experience, which are actually the hardest to get right and it's usually due to soft skills fit. So we launched a little over a year ago, paid plans starting this summer. We've assessed over 12,000 candidates and have 30 company clients, including a few Fortune 100s.

Joel: And dammit, Claire, where can we find more?

Claire: So you can find more at Square Peghires.com or you can email us info at Square Peghires.com.

Joel: Now, that was a tight pitch. That was a tight pitch, but if you've listened to Firing Squad, every single person who's pitched, every single CEO, founder, they always forget the end. Where do we find more?

Chad: They do. They do. It's amazing. They're so intimidated by us.

Claire: Hopefully, our IPO is just good enough that if you put Square Peg in we're somewhere near the top so.

Joel: Oh, that's a great question.

Chad: So let's go through that real quick. So why Square Peg because I understand the whole square peg in a round hole scenario, but the web is littered with just about everything Square Peg in every industry, TV, shows, sitcoms, Sarah Jessica Parker. I found so much about sitcoms looking for Square Peg. Did your team vet the name and SEO ability before actually taking the leap?

Claire: Yeah.

Joel: And what other names did you throw away?

Claire: To be honest, Square Peg was our first name and our only name. So we didn't go through that process of, you know, on a white board picking out a thousands names. And I definitely didn't want to spell it Square Peg with no vowels in it and have to explain to people what the site is. So we actually do decently well if you put Square Peg and then anything to do with hiring, recruiting, matching talent. We show up on top.

Chad: Well, there's even a Square Peg recruitment company and that's where I went first. And I was looking at it and I'm like there's no way in hell this is the thing. So I looked and I was looking at your email address and I'm like oh shit. This is not even the same one. So I mean that's somewhat confusing. I do like that Square Peg, very easy to spell, but you gotta get that "hires" in there and I think that was one of the things that Joel right out of the gate was like, "Is it Square Peg Hires?" That was a little bit harder, even for me just trying to research.

Claire: Yeah, so you will know when we have raised a lot of money when we have bought the domain from that company. I think it's a small consulting firm in London and one day it shall be ours. But, you know we really just love the name Square Peg. It absolutely fits what we do. We look at just a lot of data on what makes a person thrive in a specific job and so we're not trying to fit someone who's just not going to be a good fit into a role. And so that helps for both the company side and the candidate side so the name just makes sense. And for some reason, also, I think it sounds familiar even if people haven't heard of it, maybe because of Squarespace or something else, but I know I've been to the bank before cashing a check and someone will say, "Oh, Square Peg, I love that company." And I'm like are you sure. But there is a nice ring to it so we're definitely going to keep the name and all we've gotta do is start buying up some other domains that lay in our path, but that's a long-term priority.

Joel: Fair enough. So SEO's not the only game in town. What other ways are you marketing the company?

Claire: Sure. So for employers right now it's pretty much a direct sales model and so either meet them at conferences or reach out personally to them and we get a lot of referrals so that's pretty much how we find employers. A lot of them have read articles about us online and signed up so the Fortune 100s that we have all came in through reading an article about us actually.

Claire: And then, on the job seeker side most of that we actually don't do any marketing at all. It just sort of grows on it's own. That's a lot referral base where people share. So for job seekers, they come onto Square Peg's platform, they take and in depth assessment, they get a free report with all of their results, and then we only bother them if we have a really high potential good job where we think they'd drive. And so they tell people about it and say, "Hey, you're not going to get these daily digests. They're only going to come to you when they have a really good match". So the job seeker side sort of grows organically and on the employer side it's really a direct sales model.

Chad: Okay, that sounds really nice, the job seekers find you organically, but that's just not very palpable, right? Are employers having them come to the site? There has to be some way that you're getting job seekers that you're matching with. How's that happening?

Claire: Yeah, so employers are not sending them. We source all of our candidates to our site and that's really important when differentiating us between an assessment company, for example, that's just going to take your existing candidates and give you their personality scores. We actually source all of our candidates. So again, we really don't do a lot right now to grow that. If we wanted to move from ... We've delivered 17,000 assessments. If we wanted to move that to three million, then yeah, we would probably have to do some rigorous advertising. We have done some advertising in markets where we're not big. So for example, we had a client that was looking to use Square Peg to grow their sales team actually in Carmel, Indiana and surprisingly, we did not have a lot of talent in the Carmel area.

Chad: That's Carmel. That' where Joel lives.

Claire: Okay, so we had to do a lot of advertising there to just say hey, if you take this assessment, you'll get a free report with your results and then, you can be a passive job seeker and we'll only inform you when you have something. And so they would do that and then, if they were a good match, then we would put them forward to this employer. So we have done some advertising and if we don't have it the right candidates, we'll always go source more through advertising, but right now it does grow at the rate that we need it to for our client base.

Chad: So does it work in a way that a company has a job opening and then, you guys ... Like let's say it's a PHP developer in Seattle. Do you have a team of people that will go source PHP developers in Seattle? Will you then, target marketing to PHP types in Seattle? How that does that work?

Claire: Well, we would never do that role because we don't do tech hires. That's one of the big differentiators between Square Peg and others. So you go to Square Peg for all of your corporate or business hires. So marketing, sales operations, customer experience.

Chad: Okay, my question changes to marketing manager in Seattle.

Claire: Okay, yeah so the first thing that we do, and where we always get our first batch of candidates, is usually just from our database. So right now we're the biggest in New York. All of our clients are in New York or California area, but we'll match them with candidates within our own database. And if we find that we don't have really high scoring matches, then we will go advertise to people with certain skills and backgrounds. And then, we will encourage them to take the assessments that we offer before they ever see their job description.

Chad: How big's your database?

Claire: So we've assessed 17,000. We've delivered 17,000 assessments.

Chad: And those are most organic?

Claire: Yeah, so again, people reading about us online. Right now we are a pretty new, small company and it is mostly organic or if you get your results you can share it online. You can invite other people to take the assessment. So we get most of our, I would say 90% come in just sort of by finding us online. We have a decent ranking for job matching or assessment. So that's how we're getting most people. I think as we grow, we'll have to start a more aggressive talent sourcing campaign, but what we are doing now is just trying to build an organic database where we have all these candidates with a really, really unique data set that you can't get anywhere else on each candidate.

Chad: Most power to you if you can do that.

Joel: On the site it says, "Take all assessments in under an hour", which made me almost lose my lunch.

Claire: Yeah, it's actually 12 minutes.

Joel: Well, in a market with such low employment, how do you get candidates to invest even two minutes, let alone 20 or whatever it takes. How do you get those candidates to really invest that amount of time, especially in the kind of era that we are right now in a quick ... I mean the anticipation and the expectation of people is instant.

Chad: Yeah. Can't I just swipe right?

Claire: So we're actually the opposite of the Tinder swipe right model. And we see less than ten percent of users dropping off during the assessment part of onboarding and the reason is because, I think, today's job seeker, although they want instant gratification. They are willing to exchange more personal data for a better personalized product and experience. And so when they go through the Square Peg assessment, they learn about themselves. Are you highly detail-oriented? How do you compare to other job seekers? How do you compare in certain environments? And so as they take these assessments, they learn about themselves and then, they get this report. And I think especially today's job seeker are really interested in learning about themselves and getting curated, personalized sort of insights about themselves. This is why you see so many people taking Buzzfeed quizzes on which Harry Potter character you are, but this is actually real, psychoactive data that's valuable and reliable and so they are willing to exchange data. And what we do in return is we say, one, we'll give you this rich report, but also we're not going to spam you. We're not going to bother you. We're actually just going to reach out when we say, "Hey, you are highly detail-oriented and adaptable. You'll work well in a fast-paced entrepreneurial environment that's really mission-driven and we've got a perfect position for you that's within your salary range". And so we'll give them that instead of here's the daily digest of 30 irrelevant jobs.

Joel: We've heard this before and we've heard this for years. It sounds like it at least. It's called eHarmony for jobs. So it is different from Tinder. Tinder is the instant gratification, you swipe.

Claire: Yeah.

Joel: And eHarmony, that whole process, methodology, it sounds very similar to what you're talking about. You're talking about in depth assessments in matching. So even eHarmony couldn't make that work. What makes you guys think you can make it work?

Claire: Yeah, so a lot of I think what some of the other companies who've worked on this, that they do is they have a hypothesis that it is one thing that makes a person thrive in a job. So you've had guests on that say it's all skills or somebody else that will say no, it's all personality and culture fit. And what we say is actually we don't know because it's going to be different for every company, every team, and every role. And so what we do is we build for all of that. And so what that means is we do look at resume data, we look at skills, we look at job role, we look at experience, we look at education, everything, industry background, and ask a lot of questions about the resume, and then, we also ha ea psychometric assessment where we look at 20 different workplace personality types and then we also look at preferences, things like what actually makes you want to perform better. We have these assessments for both job seekers and for employers.

Claire: And then, what we'll do is over time, I'll algorithms personalize. So we'll say okay, for this entry level sales role, actually personality plays a really big part. You know you want persevering, motivated, highly people-oriented candidates that have a really good work ethic and that actually matters more than whether they know sales force, but for this brand marketer of SEO marketer, actually skills play a much bigger role than personality does. So we start to curate over time and that's how our sort of algorithms work is that we aren't going to come out there and tell you this is what works. We're going to say we're collecting data across the board and we're going to measure success over time and we have a lot of data on what makes success at various roles, at various seniority levels and at different types of companies.

Joel: Well, success changes from company to company though because hiring mangers do, right? So their though process around what a perfect candidate looks like changes from one sales manager to the next sales manager. So do the sales managers, do the employees actually have to take these tests as well to ensure that the match is what they're looking for? And when turnover happens, how do you continually go through that process of assessing all these new hiring managers.

Claire: Yeah, so that's a great question. So there are two options that we have. One, which we tend to do a little bit more with enterprises, where we can have your entire sales team take the assessment and we can identify what is in common with your top performers and then, we can source candidates based on that. And we do collect all diversity and demographic data so we ensure that, on average, we provide a pipeline that's around 60 percent women, 25 percent diverse candidates.

Claire: So we can asses your top performers and say we'll take the attributes that with low standard deviation are really in common with your top performers and we'll find you more people like that while also taking care of the diversity issues. And then, we work with startups as well as Fortune 100s so you might have startup wanting to hire their first head of marketing and they don't have a team to take an assessment. And so then, what we do is we have a questionnaire for that, for whoever's the hiring manager and what matters to you, what will this person be working on, some questions, and then, we have a lot of data that we spend a lot of time and research doing on what makes a successful, mid-level marketer at this type of role. So we will pre-fill some of the psychometric data. So we'll say, for example, for this operations role logical thinking is probably really important, moreso than intuitive thinking. And so we can pre-fill some of that information.

Claire: Then, I think the most important thing that we do is you mentioned turnover and hiring managers coming and leaving. The most important thing is right now if you work with recruiters internal or external, whatever it is they're using to make decisions on who to sect and who not to select, you're not collecting data on that.

Chad: I'm curious. What does the ideal customer look like for you and are there any scaling issues with your business? Cause you mentioned a strength in New York. Is this sort of a regional rollout? Talk about that.

Claire: Yeah, so we are a small team. We are primarily New York bases and other sort of major cities. And what are some of the issues to scale? We're a very small team right now and so on our roadmap, there's some things that we haven't done yet like a lot of ATS integration, which we probably need to do, but the reality is because we get such a small, curated batch of candidates, it's not been a highly requested feature. And our ideal employer is usually like a Fortune 500, but we have a bunch of clients right now who are 10 to 12 person startups. So I would say we tried to market to larger companies because they can make so much more use of all the data, but we do work with small companies as well.

Joel: So when most vendors, today, are trying to pull data from social data warehouses and anywhere they can actually build profiles, you guys are going the old-fashioned route, right? Because that's all we're hearing today is AI, machine learning, I mean all this stuff. And you guys, really, you're saying no, we're not going to step down that path. We're going to go down the build your personalized profile so that we can fit you better into a role. That's not the most popular path. Why are you guys going down that path?

Claire: So we are open to any sorts of data as long as we can prove that it works. And so I haven't seen a lot of compelling evidence that knowing somebody's Twitter feed is going to help you hire them. And I also think that there are some issues about your private life versus your work life and so what we want to do is anything where we can prove that that data actually has an impact on hiring, that's what we want to use. So it's not that we're old school, it's just we want to use something that we know is valid and reliable.

Claire: And we do use machine learning algorithms so the way that we use that is as an employer, you receive your candidates and you say I'm interested in this one, I'm not in this one, connect pass, connect pass. As you connect and pass, we start to show your more candidates that are similar to the ones you connected it and less candidates that are similar to the ones you passed on and then, we give you data on who you connected with and passed on. So we might say you're connecting with people mainly because of skills. Here are the skills that you're connecting with. And then, we want to see that those people end up being your top performers. If you end up hiring them and they leave after three months, which has never happened with one of our candidates, but if it did happen we might go back and say, "Okay, well what were you basing your decisions off of?" It was skills. Well, now we need to know that that should be weighted less when you make a decision, maybe it should be something else.

Joel: Can you also see if there are bias against gender or anything else?

Claire: Absolutely. That's a huge part of what we do. So we've worked with a lot of financial services companies who simply don't have a diverse pipeline that includes a lot of women and they're wondering why and we don't think it's a pipeline issues. We'll just say okay, let's look at what you need to be a top performer and then, let's get people in and then we can feed them back that data. Okay, we gave you a pipeline of people that are qualified. Here's all the data on how they're qualified and here's who you selected. We aggregate all of that.

Joel: Okay.

Claire: At the individual level, but we feed that back and then, we can help them improve. So we might say you're putting too much emphasis on what school they went to and not to preventing you from getting enough hires in this particular role so let's actually weight that a little bit less and get more women or diverse candidates into the role and see how that impacts outcomes.

Joel: What is the company look like in, let's say three to five years? You sort of mentioned raising money. What does it look like, both from a features perspective as well as a company at large perspective?

Claire: Yeah, so I think in three to five years what we are moving into will be sort of what we'll call the smart analytics or smart insights category, which is how do we help hiring teams use all of the data on a day-to-day basis that they use in section to get smarter over time. So that they are becoming strategic players and informing the rest of the company about what is working and what is not. If people are your more important assets, they will be the experts on all of the traits and aspects of what people are performing well in what roles. So we're going to move and we'll always do sourcing and matching, but I think we're also going to move to build a really robust analytics tool. That's definitely in our two to three year pipeline. And as far as other features, we're a small company so there's a lot that we can still do to build out.

Claire: Fundraising is something that we need to do to get there, but it's not a goal in and of itself, I'd say. I'd rather have happy, paying clients than VCs, but it's something we are probably going to look to fundraise in the next few months.

Joel: So being a small business and looking to try to find the cash quickly, right? Because I mean it's all about that direct sale at this point. So what type of of partnerships, business development partnerships have you started to cultivate and put in play to be able to make an impact on driving revenue?

Claire: There are things that we have done early on to help drive revenue like build out some custom assessments or do things that help us become an expert in our field that we can charge for just to get revenue in the door early on. And then, in terms of partnerships that we are going to grow into, I think an ATS partnership is a great way of helping us with business development. The problem is we are never just going to show resume data. We have to have a custom integration because we provide rich data and so that will be a longer process than most people's ATS integration, but that's sort of a natural progression.

Claire: And then, there will be, I think from a product perspective, offering our product on other sites might be something that we look into. So for example, if you're reading on The Muse about what career should you go into next, maybe you can have a Square Peg assessment integrated into that article and you can take that assessment and get feedback on exactly where you might want to go and then, get a report and then The Muse might be able to tailor articles to you. So you know there are a lot of sort of product integrations, but I would say we have too much low-hanging fruit until we get into some of those larger partnerships.

Joel: From a business development standpoint, once again, there's a lot of low-hanging fruit. How big is your sales team?

Claire: So my sales team is myself and one other person. It's very small. We are a team of five people right now. So we have a machine learning data scientist. We have our Chief Science Officer. He's not an employee. He's one of the premiere experts in the US on industrial organizational psychology. So he wrote the textbook on personnel assessment selection that's used in most PhD programs. So we have a lot of technical experts on IO Psych side and machine learning data science side and we are minimal on sales and marketing, but I think that's okay in the beginning because it allows us to serve our clients and then, as we start to generate more revenue, then we'll invest much more in sort of our sales and business development side.

Joel: What's your pricing breakdown for people who want to use the product as a subscription based model? Like how do you guys structure pricing as well as what is that pricing?

Claire: Sure. So we structure it per month per role and so if you put a role with us if you only do one, it's $1,000, which I know sounds very expensive, but we guarantee that you'll want to interview 40 percent of the candidates that we give you.

Claire: So if you go to a job board, you'll probably want to interview two percent maybe and you'll have to look through hundred of irrelevant candidates. So with us you're going to get 12 to 20 candidates. You'll want 40 percent. We'll guarantee that you want to interview and if not we'll continue to work for free until we get you that 40 percent. So it's $1,000, but the more roles that you buy with us the more you get a discount. So if you're buying large packages of roles, it can be $500 per role so the more you buy, the cheaper.

Joel: All right, Claire, that's the bell meaning that our time here is done.

Claire: Yeah.

Joel: So you know how this works Shark Tank style? Chad and I are both going to comment on what we've heard and give you a final grade. Are you ready?

Claire: I don't know. Am I?

Joel: I don't know, okay. I'm going to go ahead and start this off Chad, if you don't mind. I've got a trigger finger that's itchy after such a long layoff.

Joel: Okay, Claire, I couldn't help but listen to your pitch and think that I had been transported back to 2008. Chad mentioned a lot of this stuff. He mentioned eHarmony, but he and I both know names like Climber, Jobster, it's big. Companies where job seekers had to feel about very lengthy questionnaires, companies had to fill out a similar questionnaire, and then this magic matching thing happened. It's, in theory, a great business model. Unfortunately, none of those companies are around anymore and I think that's maybe a fairly telling thing for your business. You may have a secret sauce that I'm not seeing. That's certainly an option that I'm willing to explore.

Joel: I'm having a hard time with the organic job seekers are just finding us thing and I would've loved to have hear some sort of a marketing strategy whether that was just PR or going on to stupid podcasts and getting shot down by idiots like us. So I would've loved to have heard something around that. I think you do have scaling issues. I think you're going to have a hard time getting a lot of companies to buy into the sort of manual approach because automation is such a big trend right now and not very many people are betting against automation and AI and getting job seekers and employers together. So from that standpoint, I

think you're very challenged.

Joel: The silver lining in some of this is that I think you're a smart person. I think you probably have a good team. You're a small team, as you said. You haven't taken a bunch of money so there's not a lot of pressure to do things the way that you have outlined it so I would expect to see a pivot at some point in your business to maybe something that is more feasible for success. But for me at this point right now, Claire, I'm sorry but it's guns. And it has nothing to do with your Michigan degree FYI.

Chad: Ha. I wouldn't believe that if i were you. Okay, my turn. I believe the only way forward for employers is intelligent matching systems period. I mean I've been waiting for this for years. It's probably my favorite tech in the recruitment sector right now even more than chat bots, believe it or not.

Joel: Lies.

Chad: We've come so far so fast thanks to technology. Namely because we're getting closer and closer to kind of a loose definition of AI. I mean it's not sentient. We know that, but we're getting closer to what that actually means and being able to pull data together. It's my favorite so I am most cynical about this area because I want it to happen so badly. So in a market where unemployment is low and you cannot hope that candidates are going to spend nearly and hour, half an hour.

Claire: No, it's 12 minutes, 12 minutes. And for employers it's eight so yeah.

Chad: Still adoption is hard, right? Adoption is hard, especially on the employer side. You might be able to have companies spend time because they need talent so badly, although when the market flips and it will those same employers are not going to spend the time to update their profiles. And obviously the newly evolved jobs are going to be the updated information that you need to be able to make those great matches because you're going se deep into the heads of these HR managers or these hiring managers and also candidates. So you know at the end of the day because of some of the things that Joel mentioned, not to mention here recently we've seen a company much like, not exactly, but Hirevisor, kind of pitch the same thing and not get the traction because adoption is the hardest thing and everybody's looking for that quick and easy make it happen kind of scenario. I've got to go the way of the firing squad.

Joel: We still love you Claire. It's done out of love.

Claire: Can I say one thing real quick?

Joel: Of course.

Claire: So I guess one thing, maybe, I didn't make clear is how quick and automated this can be. So for employers, they can add a job, it can be done in under two minutes. So this isn't a process that's old school where people are taking very long assessments and for job seekers we have ways of them updating this in a quick, automated way that takes less than two seconds and their data lasts for two years so it actually is quite quick on both sides, which maybe I didn't get to and the matching makes it an entirely sort of automated process. So just wanted to be clear that this is not spending an hour on onboarding. This is really in a matter of minutes and it's mobile.

Joel: Look, if your challenge is the messaging, then that's an easy thing to fix. And we could rewind the clock and our reviews would be different, but from what we heard you know that was our grades and you learn from that and change your message up a little bit if that's-

Claire: Yeah, no I just didn't want anyone listening to think that this is a very long onboarding process because we put a lot of time and energy into making sure this is quick and automated as fast as we can.

Joel: And last, but not least, here's the thing that you're going to have to obviously fight from an adoption standpoint. There are companies that are out there that are taking feeds and pulling data and tweaking algorithms and having tremendous success right now. I mean we're seeing that. I'm working with companies who are having tremendous success with really little onboarding time so that's a big, steep hill you're going to have to ... and we hope that you get there.

Claire: Yeah, and I think it differs a little bit depending on the role. We do VP roles, director roles, manager roles really in the soft scale intensive niches. So we're not doing tech hiring where you know just knowing someone has two years of job is enough to hire them. So I think for the area where we play this is sort of a strategic decision on using this type of data and this amount of data because fit is so important. But I think for if you're looking at filling a call center or you're looking at filling some developers, then something like a better or Stellar Employee will work for those options. But we're really trying to build something specific for the niche we're going after.

Joel: All right, Claire. Where can we find out more about you and do you have a deal for our listeners?

Claire: Yes. So you can Square Peghires.com or send an email to info@Square Peghires.com and we will offer anybody who's listening to this podcast ten percent off of any package of roles. So just send us an email with Chad and Cheese referenced in the email and

we will offer you ten percent off.

Joel: Right on. Chad, we out.

Chad: We out.

Announcer: This has been the Firing Squad. Be sure to subscribe to the Chad and Cheese podcast so you don't miss an episode. And if you're a startup who wants to face the firing squad contact the boys at Chadcheese.com today. That's www.chadcheese.com.

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