Interview Transcript
Anthony: All right, so welcome to Founder Interviews, where I talk to amazing founders building amazing apps. And today I’m talking to the team at Evidenced. So tell me what, tell me about yourselves firstly.
Phil: I’m Phil, I’m the CEO.
Andy: And I’m Andy Clarke, CTO.
Anthony: And what’s the problem you’re solving?
Phil: So businesses all over the world are conducting millions of job interviews every day. And candidates are often successful or unsuccessful for sometimes arbitrary reasons.
And a big part of that is down to the fact that interviewers themselves, when conducting interviews, they’re going in unprepared or potentially don’t have sufficient training to do an effective job consistently every single time that they’re sat in front of a candidate.
So the problem that we’re trying to solve is how can we make interviews easy for interviewers to conduct whilst also making sure that they’re data-driven and evidence-based, hence the name.
Anthony: OK, so these days everything’s remote, so people would normally be using Zoom for interviews, but now they’re going to use Evidenced instead of Zoom for their interviews. So tell me how it works. I get the candidate and the person doing the interview in the app, they’re doing video, and now there are prompts. Tell me how it works.
Andy: So we replace Zoom, Google Meet, or Teams, and we listen to the interviewers as they’re taking the candidate through that very, very short time with that candidate.
We provide prompts, so we provide the structure upfront as well. So the interviewers are kind of guided through the interview so that regardless as to their level of experience, every candidate is getting a fair shot at the job.
Anthony: Okay, so I’m quite obsessed with the culture at SeedLegals. Our customers say our team are awesome, which I hope is the case.
But I still, even though we’re 160 people, will do and insist on doing the final interview with everyone so that the candidate knows about our culture values and I see that they are going to be a brilliant fit for the team. But of course the problem is that as businesses scale, it becomes more decentralized and you can’t do that. So how’s Evidenced going to help get fair, unbiased interviews that give candidates a shot that help put the company’s best foot forward. So of course these days you have to woo the candidates – it’s not just about the candidates wanting you. So how’s it going to help?
Phil: Well, so your first point about you sitting in on interviews is something that we see quite a lot. Even at very large scale businesses, there are senior execs that want the final say and often I say to those people, “We can’t scale you, right?” And that’s a really big challenge.
And so one of the ways that we do that is we enable you to run your interviews in the platform and then use that as training material for other people in your business to come in and potentially take over those things. And allow you to review a one hour interview in say 20 or 30 minutes, focusing on the key things that you are particularly interested in seeing without having to sit in on every single candidate and every single interview.
Anthony: Okay, so another challenge, I think, is that often the people doing the interviews, you know, the tech team will be doing tech team interviews, but their strong points are not management, you know, diversity, a range of other things. So they’re probably missing a whole bunch of things. I’m guessing Evidenced can help create that framework and prompts that will make sure that all interviews cover the sets of things that the business wants. Tell me more.
Andy: Even at a small scale, you start to build your company core values, your core culture, and you can build a competency framework around that and then build a question bank of questions that assess almost regardless as to what that role is. For example, I’m a software engineer. There’s a core kind of coding challenge that we’ll want to happen. That’s one part of it. The rest of it is very behavioural. And what we help is standardising that regardless as to what role you’re coming into.
So if you’re coming into a sales role, and we’re looking for customer empathy, well, that’s something that you want, but also you want that in your engineers as well.
Anthony: Okay. So what size companies are your target market?
Phil: Typically we’re trying to target mid-market or small/medium enterprise. As the organisations get bigger and bigger, effectively you end up dealing with multiple businesses, under one umbrella, it’s just you’re dealing with multiple businesses. And so for us, when we often go in, we’ll go into a business unit and help address the challenges that they’re having, use that as an exemplar and then scale that horizontally across the rest of the business.
Anthony: So you’d be targeting 100 plus, 500 plus, thousand people plus companies?
Phil: Probably thousand people plus is where we’d aim to try and target most. We do have smaller businesses using it, but those tend to be the people that are going through aggressive growth phases, rather than just hiring for churn at that low level because they’re just not hiring enough.
Anthony: Okay, and what’s the business model?
Phil: So we charge per user per month. And obviously for the larger enterprises, they like a little bit more predictable pricing. So we’ll price it based on organisation size after a certain level. But pricing starts at £399 for your first 10 users, just an easy way to get started with a single team, understand how it works, and then scale it from there.
Anthony: All right, sounds great. And what’s your traction so far?
Andy: So, we’re both software engineers and CTOs. And so we saw a lot of traction to begin with in kind of selling to our peers as CTOs. It’s where we had the most amount of empathy. But then the talent team started to get hold of it and asking us questions: okay, well, can we use it for the customer success team? Can we use it for the finance team? And so then suddenly we were able to sell to a whole organisation and not just an engineering department. But so we’ve started to kind of see small organisations roll it out fully. And now we’re seeing even at kind of 3000, 4000-people companies, Chief People Officers mandating the use globally, which is great. Like it’s kind of, they started in one team, one maybe small call centre that was having particular problems. And then the Chief People Officer can see that and then go, okay, no, I want this, I want this whole thing.
Anthony: So it sounds like you’re going to have amazing data because the problem with interviews is they’re conducted, you know, historically in a small room and only two people know about it, but there’s no, you know, spreading of the knowledge.
So how can you rate the interviewers and how can you show people what’s best of breed and so on? Tell me about the data side of things.
Phil: There’s a couple of different ways that we slice it up, but fundamentally, the people that are conducting the interviews themselves are very often in most businesses, they don’t have strong incentives to do a good job because it’s very difficult to measure how effective they are. So one of the key areas is helping to quantify the impact that your interviewers are having on decision-making, candidate experience. So things like, are they asking all the questions they’re supposed to? Are they filling in the necessary fields? Are they turning up on time? It’s a very common problem, as you might expect.
And then things like the questions that you’re actually asking interviews, but have a whole load of data about how well they are predicting candidate success or failure to help you iteratively refine what you’re asking your candidates and make sure you’re spending that very little time that you have with them on asking the most important questions. And not on asking the ones that aren’t gonna help you make a decision.
Anthony: So one of the problems when you interview candidates is you have a hundred people applying for a job and you can only hire one or a few. How do you tell the others they didn’t get the job in a way that doesn’t create problems, leave you open to discrimination or other things if there was an objective way of doing that? Is that something Evidenced helps with?
Phil: It’s very easy to tell somebody they got the job and very often people don’t even give feedback. They just say you did well, congratulations, you’re on to the next stage or, or something pleasant, but rejecting people is really difficult. And even candidates that say that they would like feedback very often don’t take it well. And so it’s a very tricky minefield to traverse. And this is something that we work really closely with our customers with because we have some customers who have said we want to give feedback 100% of the time, which is a massive objective and really difficult to achieve.
But I think the way that they’re able to do that with Evidenced is primarily they have captured the entire interview. You’re not relying on recollection from your interviewers. You have a lot of data in order to give very specific feedback.
There’s two pieces of advice that I often give out. And one is: your interviewer should treat an interview like it’s their job to prove that this candidate is right for the job rather than relying on the candidate to prove that they’re right. It’s very difficult for a candidate to know exactly what you’re looking for.
And the second piece is: when giving that feedback after you’ve been a detective and you’ve got all of the information when you’re giving it, try and be as specific as possible because if the feedback that you’re giving is vague, it’s very easy for the candidate to start filling in those gaps in negative ways. And then that’s when the relationship after you’ve given that feedback can deteriorate.
Anthony: So in the VC investor space, one of the problems that founders when they go to VCs, they’re always complaining that VCs just say, “Love what you’re doing, come back later.” And then they ask for feedback and VCs don’t like giving feedback. And it seems exactly analogous.
And the reason is as soon as VCs give feedback, they’re then dragged into, you know, why did you not like my total addressable market or you didn’t understand the proposition and so on. So VCs just come up with the lame, “You’re too early.” And it annoys founders greatly. But VCs have learned, they got burned by trying to give more feedback. And maybe companies are like that as well, which is they’ll just say, sorry, didn’t get the job. And the occasional candidate will then grill them on that. And then they’ll have to have more. So if you can provide a better way of doing that, that doesn’t plunge you into panic when somebody asks, that sounds fantastic.
Phil: So yeah, so we give you a summary of how the candidate performed across a number of dimensions and use that as a foundation for your talent team to pick out specific observations that were made, if they want to.
Now, like you said, a lot of businesses find that minefield too tricky to traverse and just go with, we’re sorry you are unsuccessful. But in the case where they do want to do it, and there are very often cases where candidates will do very well, but maybe they are too early, right? And they should come back in six, 12 months when they’ve got a little bit more experience or they’ve learned the skills necessary. That critical feedback for them can be the difference between having to go out and source other candidates in six months or getting that person back in when they are ready.
Anthony: Great point. So how does Evidenced help your team become better interviewers?
Phil: So, well, fundamentally, we take away a lot of the burden of the logistics of an interview. So things like remembering what to ask, keeping track of the time, because you only got 45 minutes, making sure that you’ve covered all the points that you’re supposed to cover, and not having to document it. We take care all of that so that your interviewers can just focus on the important bits, which is getting through the things you have to in the time given and giving a great candidate experience.
Anthony: Okay, great. And I’m assuming that these questions you come up with can also then be collaboratively created by the team who want to do the hiring so that each member of the team gets the same set of agreed questions.
Phil: Exactly. A big frustration for talent teams is seeing multiple interviews conducted and the same question asked by different interviewers. This is surprisingly widespread. And so that’s one simple thing that our tool can do is make sure we flag you’ve asked this question, you’ve got this question in a different interview, you may want to replace it with a different one, those kinds of things.
Anthony: So what got you out of bed one morning and went, we’ve got it great, we need an app for this?
Phil: If you ask him, he’ll probably say that it’s quite hard to get me out of bed in the morning. But I tend to work late. I’m a late start, late worker.
But I think ultimately, the problem that we’re talking about at the beginning is something that we’ve both experienced. We’ve been working together for six, seven years now. When I left one of my full-time employee jobs, a long time ago, I went into consulting, teaching people how to interview. And I started to see patterns emerging of the same kinds of problems, the same traps that people were falling into and wanted to build something that I would use myself to run my own interviews. And that’s when he and I talked and I showed him what I was thinking up and he was like, I’d use this.
Anthony: All right, that sounds fantastic. So if you’re a company, large or small, and you want to help your hiring team and your team hire more effectively and more wisely, where do people go to find out more?
Andy: If you head over to evidenced.app, you can sign up, book in a demo, and I’m quite happy to give anyone a tour, show them what the platform’s all about.
Anthony: All right, so you’ll interview them and see if they get the job as a customer. Amazing.
Great talking. This is an area, as I mentioned, I’m super passionate about, and I love to see technology helping to change and improve that. Thank you.
Phil: Thanks.
Andy: Thanks.
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