Storytelling about PandoLogic with Jason Putnam
Welcome to the Use Case Podcast, episode 80. This week we have storytelling about PandoLogic with Jason Putnam. During this episode, Jason and I talk about how practitioners make the business case or the use case for purchasing PandoLogic.
Jason is an expert in all things programmatic job advertising. His passion to make sure you are putting your ads in the right place at the right time, for the right spend (to get the right candidates), really comes through during the podcast.
Give the show a listen and please let me know what you think.
Show length: 23 minutes
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Ladies and gentlemen, this is William Tincup. And you’re listening to the Use Case Podcast. Today we have Jason Putnam on from PandoLogic. And we’re gonna be talking about his firm, and the use case for PandoLogic. So without further ado, Jason, if you’ll do us a favor and introduce both yourself and introduce PandoLogic.
Happy to. Thanks for having me, William. Yeah, my name is Jason Putnam, the senior vice president here over at PandoLogic. I’ve been here along with several other members of the crew for going on about seven, eight months. Super excited to be here. I have been in the industry for a long time and was very excited to join joined with Pando. You know, big part of that, for me is, I know, this industry changes a great deal. But every 10 years, and there’s these waves that you can choose to be on the front end or the back end of and I’ve chosen to be on the front end of it, and happy to be here, excited to be here. And when we look at what we do, and the outcomes that we can drive, throughout this entire industry, very excited about it. I think of ourself is really that, that generation two of programmatic. Not just using AI to distribute to the network, but using AI to decision on those jobs, and really free up the the end user to do their job and get back to being human, and let the machines do what machines are really good at and let the humans do what humans are really good at.
So for folks that, you know, haven’t been down the path of programmatic or maybe don’t spend as much money in programmatic. I’ve always thought that it is okay, that you’re it’s the right place at the right time. You know, it’s it’s a part and parcel about budget and audience, getting the right candidate flow. How do you explain programmatic? Especially this version of programmatic that you all have? How do you explain programmatic to people.
Yeah. And the best way I like to say it is there’s a difference in how you want to explain things to people, depending on where they are in their level of the buying cycle and understanding a big change that we’ve made here. And I’ll come back to your to the to the question in a second is, we had a ton of success and very high growth, and we’re still continuing to grow. But early on, we sold to, you know, the other side of the chasm and sold to very much tech-focused early on adopters. As we’ve moved over to this side, we’ve really changed the entire pitch to do exactly what you’re talking about. And really not talk about programmatic and not talk about AI and not talk about algorithms. Those are all the means to the end. But really focus on what the outcome of programmatic can be for your organization. And then how you can use those outcomes to benefit the rest of the organization and potentially you personally. So if I boil it down to what programmatic is, is using machines using AI and machine learning to make sure you are putting your ads in the right place at the right time for the right spend. So you can get the right candidates. And I think of this very much as as a sales funnel. You’re focusing on what you want to come out of the funnel. So what, what typically isn’t done in a non-programmatic format is you don’t know the variable of x. So I know how many widgets I want. I typically know what my conversion rates are, but I don’t know how much budget to put against it, because the world is constantly changing dynamically. So with with our version of AI being able to do in real-time decisioning, we’re able to solve for that x element and tell you exactly what you should be spending for the outcome that you want. And if you want to ratchet up that outcome we’ll tell you exactly what you need to spend. And you know, the end result for the customer is the old adage that we’re all probably been long enough, around long enough to remember is 50% of advertising is wasted. We just knew we just wish we knew which 50%. Well, we know which 50% is being wasted in real-time. And we’re able to then reapply that efficiently and effectively in real time to the jobs that are working.
So dumb question. But if someone comes to you and says, Okay, I want to hire a data scientist, and they can be remote, obviously, at this point, they can be remote. Can you estimate for them and give them an idea of where they should start with their budget?
We can do more than that. So as we look at kind of what I would call V1 of programmatic that using that AI to decision where it goes, right we do that? That’s great. I think we do it incredibly effectively. Then there’s the part of how do I decision on it? So what you’re asking for is is you know, a crystal ball to say how do you predict the future? Or at least how do you predict what’s going on right now? What typical companies do, whether you’re doing it in house, whether you’re using an agency or another platform, and you have this concept of a day trader, who does AB testing to say, I’m going to put this job, this data scientists on Indeed for $1 a click and zip for 28 cents a click, I wait 10, 10 days, see what happens, then I make some adjustments. I may do some job expansions, I may do all that stuff. Because we’re able to do it all in real-time, we’re able to not just take a data scientist, we’re able, because our technology makes 7,000 adjustments per job per minute. We’re able in real-time to take an entire feed from a customer, put it into our machine and tell them exactly what their spend should be based on what they want the outcome to be. So not just the data scientist, but every single position you can give us, we’ll run that feed through the machine in almost in a presale format, and tell you with over 90% accuracy, exactly what your results can be. And then you can turn the knobs and dials to say I need more candidates, I need less candidates, I have more budget, I have less budget, and then we can drill down an individual job. One being a warehouse worker, one being a data scientist.
And I’m sure on the analytic side, practitioners are asking about source of hire. Right? So this is this actually can give them some visibility into what’s working where.
Yes, and to me, a lot of this industry is very, very black boxish. We are not we have decided to err on the side of, let’s expose the data. Because we, we have a very distinct mission that we want to be. And I think we are based on, you know, some of that some of the stuff we hear in the industry and sharer voice and everything else, the best programmatic solution out there. And I want to be, we want to be as an executive team, not competing with other people in the market. But we want to be the programmatic platform for everyone who needs one. Whether you’re an agency or RPO, etc. So that’s the magic of what we want to put together here. And go back and I missed your question.
No, no, no, you you answered it. You did fine.
I want to make sure I answered it. Because I went on a tangent for a while.
No, you’re fine. Because again, that’s, that’s one of the things I love about the company, is your mission. Your mission is, is again, you could put everything behind the veil or in a black box. But you’re you’re trying to help people understand what’s working and what’s not working,
Yeah you should know where your money’s being spent and what’s working best for you.
Yeah. So and, and a lot of, again, for a lot of the TA folks, it’s driving, you know, quality candidate traffic. You know, that’s, that’s ultimately what they want, and they can turn the dial, or one way or the other, they can turn that dial. So let me, let me ask you a buying question. And, and the buying question is, what are questions that TA leaders should be should ask a programmatic vendor like yourself? What should they be asking?
That is a fantastic question. So here’s the problem. There’s, there’s a, there’s a huge lack of understanding from a technical perspective of what programmatic is. And again, not that that outcome-based, right. And I’ve heard you say, and that as, as vendors, we know how to sell and you’re asking the question of, hey, knowing that we know how to sell, how should somebody on the other side buy? And I will say, I want to flip that to answer your question slightly, because I don’t think every vendor knows how to sell. So we, you know, we go in, we go in and say, here’s our box, make, make your needs, your desires, and your outcomes fit our message in our box. And I think as as vendors throughout HR tech, we need to make sure that we’re meeting, we’re meeting our potential customers where they are. We’re we’re skating to where the puck is, as opposed to just beating them over the head constantly with messages that we think resonate. We do a very good job as a company to say, with a lot of data. Hey, what questions do you think you should be asking? Here’s how it relates. And then let’s equate that back around. So to me, if I, you know, if I invert this, and I’m sitting as a, as a potential customer of PandoLogic, I’ll tell you some of the questions we get, and then hopefully, maybe some of the questions we should be asking. And some of them are scary questions. Does that mean I lose control? Does that mean I need more budget? That’s all the questions that we’ve seen out there that are easily over, you know, easily addressed from an objection perspective. Because programmatic should be the easiest transition and the easiest sale in the HR tech space, because what we’re saying is just, you know, move your budget over to us, and we’re going to spend it more efficiently for you. So it’s around those questions that people should ask questions. What, what is the outcome that I think I can get from programmatic is a question they should ask. How is it going to affect my business? So not about budget, not about candidate quality? That’s all, to me, that’s all table stakes. But what’s the impact of you know, outside of this flow of candidates, what’s the impact on the organization and the business. So to me, you know, my my mantra I’ve always been, you know, even when I speak in the space is I think talent acquisition should be a strategic function and stop being administrative. So in order to be that strategic function, you have to have impact outside of your normal group that are going to affect the business. One of that is data, data integrity, and then how you move that data into analytics and report back on the business. So how is our data going to empower my organization to achieve that mission? That’s one question they should ask. What is the data? How do I get it? How accurate is it? Is it real-time? Another question I would ask is, you know, what is it going to do financially for me? If my budget’s a million dollars, am I going to save a million? I mean, I’m going to save 30%? Or am I going to get 30% you know, more more outcome from that? And then once I know what those answers are, I as, as the buyer of the product should already have in my mind what I want to do with those savings. So if my budget is a million dollars, and I can save $300,000 by just shifting my budget to a company like PandoLogic, I need to go kick that door in of my CFO, become more strategic and say, hey, those five initiatives that I wanted to do, that I didn’t have the money to do? I now have the money to do. Go ahead.
No, it’s okay. Let me ask you a workflow question.
As you advise prospects and customers, where in the workflow does programmatic does this PandoLogic? Where does it fit for sourcing to recruiters to hiring managers?
So the answer is it depends. And what again, I don’t want to build a box and say fit in our box. Right? I don’t think that’s that’s the right approach to do, right, you want to we want to go where it’s gonna be most impactful for the organization. So I’ll give you a kind of a typical flow. So what happens today is you may be an employer, and you have individual relationships with other job boards. And those could be happening, could the, the job distribution could be happening via an ATS on a recruiter basis, or it could be typically in a decentralized format. Or it could be happening, you know, at a corporate level. We, think of us as a vendor management platform. So you have all your vendors, and you’re doing individual distribution to those vendors. And you have individual data coming back from those vendors. Think of us as a hub that sits between you and those vendors. So in the procurement world, think of us almost like an Ariba. So the job flow is going to come in to us, we’re going to put it into the machine. We’re going to use AI and machine learning to determine where it should go for the breadth best price and quality and volume. And then how do we change? And how do we decision to get the same result. And then to the to the end applicant, they have no idea Pando is a thing. They’re going to go through their normal flow, they’re going to come through us and then end up where they where they need to belong, depending on whatever that that flow is, from the applicant flow perspective. The thing that is interesting is, you know, we can enable it on a per recruiter basis. But what we’re seeing more in the talent acquisition space is, we want it to be set it and forget it. We want it to be that self-driving car. We don’t want the recruiters to have to make a decision on where their jobs are going to be posted at what budgets. People are not good at that. And they don’t have the time to do that. So give us the jobs, tell us what you want the outcome to be, not what you want the budget to be. And then we’ll work backwards and make sure you’re getting the right candidates at the right price.
Because you mentioned price, quality, and volume. I can see customers and even prospects wrestling with the, those three. Because ultimately you’d like all three, right? It’s like, yeah. You want your husband to be good looking tall, intelligent. Rich, yeah. Okay, pick one. Anyhow. So, so how do when you –
My wife is 0 for four, so.
Yeah, mine is too. So, so how do they wrestle with that? Like, how do you get them over the the emotional kind of intellectual hurdle of dealing with the relationship between price, quality and volume?
Well, here’s what I find. Most people want things to be true. And then the reason they come up with objections is because it sounds too good to be true that they want to have an objection. So they don’t make a mistake. And that’s just that’s just human nature. Right? So if you think about that, let’s say those are the three elements and and the way we approach it, we can approach it with data. But data is just data and data is only interpreted by the lens by which you’re, you’re looking at it through. So I tend to do it in more in a story way and putting people in examples. So let’s say you are ABC Company, and you are spending $20,000 on a job board that we all know. And with that $20,000 you’re getting X amount of clicks, Y amount of candidates, Y amount of applicants and Z amount of hires. So somewhere in there is your interpretation of quality depending on where your funnel is. So if that ultimate outcome is let’s say 50 hires for your $20,000 making up numbers, of course. What were the way I would tell this story is Well, is 50 a good number for you that interprets quality irrespective of cost? And they may say, Yeah, I just need 50. Okay, we’re gonna get you 50 instead of $20,000 for $15,000. So that answers the question because we’re going to do the same things they’re doing today, on the same boards and sources they’re doing today and more, just cheaper and more effectively. So it’s not that we’re not, we’re not espousing that we’re gonna blow quality out of the water, we’re gonna get you comparable quality and potentially better quality, we can get you even better quality, if you want to turn, you know, turn the knobs to the right. But at the end of the day, if you’re spending a million dollars, and you’re getting an outcome that you’re happy with from quality, why not get that same outcome, but spend $700,000.
I love that.
We’re not going to do worse, because we’re already using the same sites. We’re going to, we should be doing significantly better, but we’re very much an under promise and over deliver type company,
Right. Because, again, the and the system gets smarter each each second, right. So, so ultimately, the spend is going to get smarter, as the, as the machine goes further in time, it’s just gonna get smarter and smarter about making these these decisions. Based on job class, job role.
You’re 100% right. So what’s interesting about that is theoretically barring, you know, macro change macroeconomic changes in the market, you know, affecting certain types of roles and jobs or geographies. The campaign should become more efficient as they go on individually for a particular campaign or a company. Because it’s its own data is feeding itself and making the machine learning is making itself smarter, making the AI smarter. But also now your data has been put into a larger data set. Which makes the entire dataset smarter, and the entire data sets can ultimately make your dataset smarter. So to your point, yeah it just continues the efficiency model of that.
So, three questions left, one is the role of the people that you know that that spend the majority of their time or whatever in in PandoLogic. I’m thinking that’s a recruiting operations person or recruitment marketing person, What do y’all, What are y’all finding in terms of who those folks are that are spending time there?
It’s so I want to answer a question two ways, because very few people actually do quote-unquote, spend time in Pando. But I’ll come back to that. It depends on the actual persona, depends on the organization. So if you’re looking at it at a, at an ad agency side, you know, with somebody there who’s running, you know, campaigns for their customers. If you look at it in the RPO and staffing side, again, it’s somebody comparable, who’s used to dealing with the boards. If you look at it on the employer side, you know, a large employer is going to be recruitment operations. You’re spot on. Some of the more sophisticated employers have somebody they’ve pulled over from marketing, who’s literally looking at this as a true marketing funnel. Same people you know, who are doing 95% programmatic in the typical marketing lead gen world, who they brought over here to optimize that. But very few of them are sitting in turning knobs and dials. That’s the beauty of us, it’s set and forget. Tell us where you want to be true. We use the example of self-driving Tesla, we’ve been using our decks in our pitch, it’s a you know, it’s when you first get into self-driving Tesla, you say I want to go home. You literally don’t have to do anything, it takes you home. If you’ve never done that, that can be scary the first time. But the second time is amazing. Now, at any point, if you want to grab the wheel and take over, you can do that. But at the end of the day, how much more efficient can you be when somebody else is doing the exact same thing with the exact same outcome, or a better outcome incredibly, more efficiently. So now those people who were spending time either interacting with the job boards, interacting with other solutions, be a programmatic or not working on bids, and doing that day trader function. We do that all for them. Of course, we have people here, we’re a big company. And we have campaign managers who can help. There’s a little bit of interaction they could do, as far as grabbing the wheel or tapping the brakes. But at the end of the day, go be a human and go do human things that humans are really good at. And let us handle the stuff that that machine should be doing.
Love it. So when you demo, and I’ve done a demo recently. But when when you demo the software to, to folks, what do they fall in love with?
Yeah, so it’s it’s a great question, because again, it depends on who they are. But let’s focus on the employer for a minute. There’s this there’s this kind of decision valley that I think of. And that there’s things that they want, that either they they lay their head down at night, and say I wish these things were true, but it doesn’t exist. And then they see some things that they’re like, oh, it does exist and they get very excited. So some of those things are, hey, I am a person or I have somebody reporting to me, who is literally logging into job boards, who is missing meals with their families, because they’re putting all this data together. Who’s managing contracts, I’ve got to deal with, you know POs from accounts for my accounting department to pay, you know, Careerbuilder invoice. Like all that goes away. So the first initial reaction is, from an efficiency perspective, that vendor management side is, Oh, you can do all this for me and I still get the, the goodness of having the vastness of a network and even bigger. Then when you get into the actual bits and bytes of the demo, what they love is how easy it is. It is just every piece of data at your fingertips, you can slice it and dice it, do it however you want. We are tracking against a goal that we told them we were going to hit. And they can see every minute in real-time exactly how we’re tracking against that goal. And to me, there’s this, and to them, there’s this gratification of it cuz everyone’s afraid to make a mistake. Here’s what you guys told me you would get, here’s what you’re getting me and everything’s trending well. And if you have additional needs, we can ratchet it up or ratchet it down and go from there. And then the other side of it is the outcome from being able to now make decisions as an organization based on the data that you’re seeing. So again, having talent acquisition be strategic. Being able to take the data, that’s the outcome and go back into the system and push on it is really what people fall in love with.
Alright, last question. I’m gonna hand you a magic wand. And I want you to eliminate a buying behavior from TA. So something that you’ve seen historically, or currently. A behavior that you’d just like to eradicate, and from all TA pros out there in the world, and you can do it with a wave of a wand. So what would that be?
So I’ve done a lot of these, this is my favorite question I’ve ever been asked. So kudos. To me, it’s fear. Right? So when your TA doesn’t have huge budgets, and they’re on the other side of a P&L, so you know, I’ve had I’ve had the blessed life where I can go, I’ve sold to both sides, or I’ve sold to VPS of salespeople who are revenue generators, and I’ve sold to people on the other side of the P&L. And, to me, the talent acquisition should be a profit center if it’s handled correctly. But there is fear there because they don’t have, typically don’t have the seat at the table, and they’re afraid of making a mistake. Whereas the VP of sales is going to quickly run some ads and go, Oh, that’s good enough, I can make it up with this and you’re showing me how to grow top line. To me, there’s this fear of, I’m afraid to make a mistake, because I already don’t have high budgets. I don’t feel like I have a seat at that table. And the fear is almost crippling that they don’t hear the actual outcome of how it’s going to allow them to be strategic and be better at their job.
Love. I think I’m gonna I’m gonna quote that from now on because I love that response. Jason, time flew. But I appreciate you carving out time to break everything down about PandoLogic. I love what y’all do. And thanks for everyone listening to the Use Case Podcast.
Thank you so much for having me. It’s been a pleasure. Anytime.