DEATH MATCH: AllyO's David Bernstein
Listen now to see how it went down for them.
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Chad: Welcome to Death Match, part one of four. This Chad and Cheese Death Match episode features David Bernstein of AllyO. The Death Match took place at TAtech on September 27th in New Orleans at 9:00 AM in the morning with a room full of TAtech practitioners loaded with mimosas, Bloody Marys, beer, and Chad and Cheese snack. Enjoy after a word from our sponsors. Okay, Joel, quick question.
Chad: What happens when your phone vibrates or you're texting alert goes off?
Joel: Dude, I pretty much check it immediately and I bet everyone listening is reaching to check their phones right now.
Chad: Yeah, I know, I call it our Pavlovian dog reflex to text messaging.
Joel: Yeah, that's probably why text messaging has a freaking 97% open rate.
Joel: We had a crazy high candidate response rate within the first hour alone.
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Chad: It's not long that you aren't able to remember, just go where you know, chadcheese.com and Nexxt with two Xs. All right, make sure you got that drink in hand. Anybody who wants a beer, if you would rather have a beer, we have beer up here at the judges table by the Stage.
Peter Weddle: Good morning everyone.
Chad: Good morning.
Peter Weddle: You can tell there's very few things that would bring a crowd like this out at 9:00 AM after a night on the town in New Orleans, so props to our good friends Chad and Cheese. Without further ado here's Chad and the Death Match.
Chad: Hello. Good morning, good morning. So today we're going to do our very first Death Match. So hopefully everything goes off without a hitch. If you've listened to the podcast, we do firing squad. This is kind of like an iteration, what's going to happen is we have four contestants, they're going to have two minutes to pitch. No PowerPoint presentations, they are going free falling. So no PowerPoint presentations, they are going to do two-minute pitch, and then after that the balance of their time, their 15 minutes is going to be Q&A by our American Idol judging panel. All right, next we have AllyO VP of everything, David Bernstein, bring it. Watch out, he's throwing shit.
Chad: Koozies galore sees all of you. Give Joel a koozie, he always bitches because he doesn't get any koozies. All right, bring it on up buddy.
Chad: All right, so Aman did pretty.
David Bernstein: He did.
David Bernstein: He did, and I'm not going to do karaoke this morning though.
Chad: You're not doing karaoke this morning, okay. Are you ready?
David Bernstein: I'm ready.
Chad: Let's do this.
David Bernstein: Let's box. Good morning New Orleans, how is everybody today? David Bernstein hear from AllyO. We are an end-to-end AI recruiting platform, we ... I'm going to make it really simple. We exist for three core reasons, our goal is to make recruiting delightful and efficient for all. Everything we do at AllyO is based on those three premises. Everything is all about what's going on today with the candidate. Our focus is actually to look beyond and focus on all the stakeholders. So at AllyO we think about what's going on for the recruiter, what's going on for the hiring manager, what's going on for the head of talent acquisition, and how do we bring all of that together to create a cohesive experience for everybody participating in the process?
David Bernstein: It's real simple, we do an AI conversation end-to-end using our own homegrown technologies to be able to provide an array of workflow capability throughout the process. Our conversational front-end manages the providing of data and the capture. Our workflow automation engine will be able to then capture that data and put that data in any source system and our analytics backbone will be able to provide the insights that come from all that data that's captured. We've got a pretty impressive array of customers so far in this early stage. We've been able to capture a pretty high percentage of the high volume recruiting market. We have one in five of the top five players in 16 industries as our current customers.
David Bernstein: We've been able to secure core backing from Google, from the AI perspective, Randstad from the sourcing background, sourcing and recruiting, and then we have Bain Capital who's also stood behind us in terms of helping us build the company. Our goal is to really make it, again, very simple. We really want to provide an end-to-end recruiting experience.
Chad: And that's it, Faith.
David Bernstein: All right.
Joel: Nice job.
Chad: Very good.
Joel: That's two minutes.
Chad: Hit it Faith.
Faith Rothberg: All right, thanks David, that was great. Now I may be mistaken here but I think that a lot of the data that you guys are using to support your platform is from LinkedIn, is that right?
David Bernstein: No.
Faith Rothberg: Okay, then I'm thinking another wrong thing. Now so then I'll just ask a different question.
David Bernstein: Sorry, no, no, so we capture the data coming in from the applicants or we can actually reengage from any candidate pool, so either way. But we're an engagement layer, we say we're a system of engagement or experience in a system of insights.
Faith Rothberg: So how do you integrate within those enterprise companies? With the ATS and things like that?
David Bernstein: You mean like from a technical perspective?
Faith Rothberg: Yeah.
David Bernstein: Yeah, so it's real simple, we can either do that through a flat-file integration or through API. We're able to either buy directionally with pull data and we're able to push data back. We also have a centralized platform, so customers who ... What we find is that actually like store managers, district managers, infrequent users like to use our casual user interface, and then we'll have the power user or the recruiter use the back of what they've already been trained on it in terms of their to AllyO, their Isms, their Greenhouse, whatever that would be.
Deb: My question to you, I know that there was conversation at HR Tech where a lot of people were questioning the end-to-end. I'd like to hear you walk us through a used case from start to finish.
Chad: Where are the ends, is that what you're asking?
Deb Andrychuk: Yeah.
Chad: Where is-
Deb Andrychuk: Am I right on that?
Chad: Yeah, no, no, I was clarifying for myself.
David Bernstein: So to keep it simple again, that's been our whole premise is we say from hello to higher and beyond, that's the way that we think about things. So everything from providing a Walmart style greeter at the front of your website to be able to greet every candidate that comes and be able to help them get directed to the right job opportunities through that conversation. And be able to get them pre-screened and qualified, get those qualified candidates into the interview scheduling. We manage all that deep interview scheduling right into the calendar with Office 365, G Suite, and Iron Outlook, and then beyond. We're into the whole kind of reminder process, the background checking on boarding, and we actually also do a 30, 60, and 90 day check in with all the new hires. Throughout that process, it's all conversational, it's in a Q%A fashion, we can provide assessments.
David Bernstein: Either provide the customer with their ability to do any in-house tool, any kind of in-house questions that they may be asking candidates, or we can tap in directly into their vended solutions. So whether they're doing skill tests or psychometric types of assessments, we can actually deep-link and pull those in and provide those direct links to the candidate directly.
Chad: So Chatbot chat Chatbot, we hear Chatbots all ...
David Bernstein: We talk about Chatbots all the time.
Joel: All the time.
Chad: Yes, so how do you, knowing that there are a sea of Chatbots out there, how do you distinguish yourself and get away from all of the Chatbot noise? Because there's so much Chatbot noise right now.
David Bernstein: Great question, we actually think a lot about this. One of the things that we firmly believe is by 2020 we believe the Chatbot industry is just going to become a commodity. So to distinguish ourselves, we really have focused on four or five key areas. One of those is that we believe in the end-to-end automation experience is critical. We're deeply doubling down in the technology investments relative to automating that end-to-end, and it's really about the art of the possible. If you abstract up what we do at a key conversational level, we're actually capturing data and providing information.
David Bernstein: We'll actually be able to do that through audio, video, or text. We'll be able to do that on any platform, and be able to then do that scheduling, employee referrals, reminders, and be able to do the reminders through email, through text, through even phone reminders. It's an end-to-end conversation that will really distinguish us from just being a point solution as a Chatbot.
Joel: First off, I'd like to compliment your shoes. It takes a real man to pull off the moccasin loafer.
David Bernstein: Rocker man, yeah, you like that?
Joel: From even talking to some of your competitors, one of the main challenges I see with the Chatbot business is scale. Most that I've talked to, you have to call the customer, what are the questions you want to ask, or there's some sort of interaction that takes place to know what the questioning is for a candidate in the automation process. My question is do you agree, and if so how are you tackling that problem or is it just going to be a scaling issue for all Chatbots going forward?
David Bernstein: Well, I don't want to give away all of our secret sauce, but look we've managed millions of conversations today and we've learned a lot through that. I can say that between the machine learning and our team of experienced customer success team focus, we've really automated the process itself. What we're really doing is so we took a large customer last week live at Marathon Oil, we brought them live in 10 days. Again, it's because we understand the nuances of being able to do this. What we've also found in this early adopter stage is that a lot of customers aren't ... So we have a buffet of capability but the customers are typically piloting in key areas where they can see most immediate return. So we're able to take them in the bite size transformational going live.
Joel: Let me interrupt you, you said 10 days as if you were proud of that and that stuff we're not turnkey I think you would agree. Will that 10 days become a day at some point or will it always be a 10-day turnaround to get a new customer up and running?
David Bernstein: No, you're right, so it's a journey down from some other numbers. So our goal though obviously is to be able to make this something that's very different than their system-wide implementation experience. Again, I think anything that's going to be a challenge for any technology vendor is the adoption of this and how to best deal with the transformation issues. But in terms of just the deployment ready capability within 10 days and be able to manage that process has gone down from less than a two-week number down to about 10 days. And being able to continue to scale that down as we automate more and more of the process to bring candidates and customers on board.
Faith Rothberg: My question is around scale, so clearly you've had a lot of conversations already, and so you've learned how to or hopefully are learning how to scale as far as conversations go. But what about scaling as far as for the recruiter and the thousands of candidates that they have to go through for high volume hiring in these enterprise companies?
David Bernstein: Yeah, so what we see is that 80% of what these recruiting teams are doing is something that can be automated, and so as long as we can dive in and manage that and be able to capture those conversations that they'd be having, but how do we then use the AI and the NLP to be able to then replicate that. It's one and done and then we set that up and it's on its way, so the scaling and then obviously we bring the learnings from past customers up to the new customer base. It really transforms the whole on boarding process.
Deb Andrychuk: You were talking about the fact that clients can buy pieces of the solution or they can buy the full suite, and I was just curious so out of all of your clients today, what's the percentage of those that are using all of the capabilities?
David Bernstein: Great, the pilot is showing us where customers are zeroing in most, and so what we often see is it's around prescreen and qualifying schedule is where the heavy proponents of that is. But we do have a number of customers, you can go to Hilton, jobs.hilton.com. For example, if you want to see AllyO in action, you can go to Sprouts, you can go to Marciano's, you can ... Five Guys. You can go around the Internet and see where some of our customers are ... Pitney Bowes, Pitney Bowes, has decided to deploy us not just in English but English and Spanish, and they've decided to create a user experience that actually weaves together these Lego building blocks of capability that we have. Where they're actually doing FAQ with the job search and the prescreening qualify all under one cohesive candidate experience.
David Bernstein: I have other customers that say, "You know what, let's let them go naturally through the application process, through the ATS," but have AllyO pick up tomorrow and say, "Hey there, how are you today? Thanks for your interest in what we're doing here at XYZ company and we have a few following questions." Be able to manage at all process and those that get qualified then move into the interview scheduling component, and those that don't get packed and be able to be moved into some other category and/or will be redirected which is another one of our features. Is you're not necessarily a fit for this one but here's some other jobs that we think you might want to take a look at. So very some interesting ways to be able to handle the whole candidate experience.
Chad: So not only Chatbot, Chatbot, Chatbot, but now AI. You're using all of the buzz words necessary to try to get into somebody's top of mind, right? My question is, is this really AI? Help me understand because it really seems like RPA. It's really process automation, which is awesome and necessary, tell us why it's AI instead of more RPA?
David Bernstein: The intelligence around understanding intent of candidate conversation is probably one of the biggest components there. Whether it's just the candidate or understanding the recruiter but it's really being able to process just words on the page into something meaningful. The intelligence kicks in there, then the machine learning goes with it to see the patterns and be able to then figure out how to act next.
Chad: So they're not just standard responses, these are responses that are being pulled together by the AI to be able to have a response that's different in custom for every type of conversation?
David Bernstein: Yeah, and not to be able to do ... So to be able to do that in multiple languages but also be able to do that in multiple voices. If a customer has two jobs, they might have one job here in New Orleans and the same an HR job in New York and then an HR job in New Orleans and the conversation would be, "Hey chat, how y'all doing today?" From the New Orleans position and the same for the same company but the interaction because we know the location of the job and the language and the voice and will be more particular to New York, "Hello, how are you?" For example, right? It's a real deep human-like conversation that we're driving for.
Chad: In New York wouldn't it be like, "Hello, what do you want?"
David Bernstein: Yeah, really. What the F?
Chad: What are you?
Joel: I'm going to push back on the human touch, I feel like in all this technology, a lot of the human element is lost and I want to ask you about branding. So there's a human to human or at least a perceived human to human connection and communication, but what are you guys doing to help companies build their corporate brand whether it be through videos, pictures, what we're doing as a company, etc.
David Bernstein: That's really not in our category, so it's really on the company and where that deployment mechanism for communicating how they would like to convey themselves. Out of the box, we do have a natural language that we would propose on how to interact in that human-like way. But really we're relying on our customers to know how they'd like to brand themselves, and AllyO becomes the agent and to be able to converse that. Think of it like you hire AllyO to join your team, AllyO is a digital assistant that joins your team to manage a certain amount of their process. We see something like 60, 63, anyway some high 60% of the candidates at the end of the conversation with AllyO will actually say, "Thank you." That real even though they understand they're talking to a machine, to say thank you is that indicator and the trust that they're engendering with that experience, then we'll feedback into their experience with that employer.
Chad: So with the last 30-ish seconds, where ... You get the first question next time. Where can we find out more about AllyO?
David Bernstein: Besides allyo.com?
David Bernstein: Yeah, firstname.lastname@example.org, our Twitter account, we're running webinars, I'm going to be at SIA next week talking about things. We are connected and I'm going to be doing more and more work with the job board industry, the staffing industry, RPAs. Yeah, moving all around. Thank you.
Chad: Thank you. Hey, those are some pretty hot loafers by the way. Yeah, I like them.
David Bernstein: Thank you.
Chad: Thank you very much. Everybody, AllyO. The Steven Seagal of the recruiting industry. Good looking man.
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