Joe Leech

S1 E6 Christian Gonzalez YouTube

I’m joined by Christian Gonzalez. Christian leads a team of quantitative and qualitative User Experience Researchers at YouTube.

Christian has worked with various product teams at Google. He has a PHD in Human Factors and Applied Cognition and together we talk about how research drives product decision making at YouTube.


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Links, notes and transcript

Christian on LinkedIn

Joe: [00:00:00] [00:00:00] . How are you doing? 

[00:00:42] Christian: [00:00:42] Hey, Joe. I’m good. I’m good. 

[00:00:44]Joe: [00:00:44] tell me a little bit about you. 

[00:00:45]Christian: [00:00:45] so, my name is Christian. I’m currently a UX research manager at YouTube, working specifically on the creator side, of YouTube.

[00:00:55] So the people that upload videos, all the, all the tools that they use to do that, that [00:01:00] is what my, my team and I kind of focus on. but my. My background, how I got there. so my background is in psychology. I did, originally from the U S a I did my undergrad and grad training in psychology and in grad school, specifically I focus, in, human factors and applied cognition program, 

[00:01:18] it gave me a really good training in experimental design and. More than anything, just like using the scientific method to answer questions. And so , that was probably the most useful aspects of my PhD and psychology, 

[00:01:31] I had a few of my colleagues from George Mason that also went to Google. And so after I graduated, I had a connection there and I worked at Google or I said, I moved to California, started working at Google, originally on Google plus, when that existed and, Also, you know, kind of around that time.

[00:01:49] And when I started at Google, they were starting this, group within, within called area one 20, which is very much about, having the he’s kind of like small teams, like [00:02:00] spinning up an idea, getting a bit of runway to. Basically run a startup within, within Google. And so Google plus while that was kind of on the decline, a lot of the, the engineering and design and product bandwidth that was, kind of going away.

[00:02:13]we started playing around with it, this idea of having small teams come up with an idea and try to like very quickly and try to decide if it’s a good idea or a bad idea. and so like my first training as a. As a researcher and tech was kind of like working at a startup, but within the safety net of, of Google, which was kind of interesting.

[00:02:31] I mean, we were, we could move somewhat faster than a normal Google team, but we were still constrained by, you know, using Google’s architecture and those types of things. So, but my. but my, my training and stuff, like really kind of got more well rounded in terms of doing more like scrappy user research, much more qualitative research.

[00:02:50] I did actually did a lot of focus groups, and talking, with, with users, as like a discipline, And then yeah. Then I moved to [00:03:00] YouTube where I worked on YouTube music for about two years, launched the kind of combined version, of the YouTube and Google emerging together. I think that might be the first time that that has ever happened actually, where they combined Google play music and YouTube music into one product and then ship that, and.

[00:03:18] Then there was an opportunity to move to Switzerland, to move to Zurich, to work on the creator team. I thought it was a, well, I always wanted to live abroad and it seemed like a good time to take a break from the U S for awhile. And, yeah, that’s what got me here. And I’ve been here for two years. I started managing a small team now and yeah, that’s, that’s kind of the.

[00:03:41] The path, Oh, that wasn’t too, too long winded, but yeah, 

[00:03:46]Joe: [00:03:46] I love that some of that experience you’ve got there as well, especially kind of, you know, small, smaller startup style projects, right through to Epic infrastructure based, you know, so from the area one 20 spinning [00:04:00] up ideas through to, you know, that great combining of, of YouTube music and Google play music into once there’s some.

[00:04:06] Amazing range. And it’s the size and the scope of the projects you’ve worked on over the time at Google. So fascinating stuff. I’d like to talk about a couple of those ones. Then you mentioned this area one area, one 20 group to sort of, sort of small startups within, within, within Google itself. Can you, what would be interesting?

[00:04:21] Cause again, this, this pop, this podcast is about decision making. Really what. With that small group, where did the kind of way did the ideas come from? Why did it, why did the, the kernel of ideas come from, from the stuff you were working on in that group? 

[00:04:32]Christian: [00:04:32] That was a really interesting time because it was really, I felt it was like a very true to like Silicon Valley ethos, where we’re like, what is a good problem for us to solve.

[00:04:42] And there was a lot of, kind of like needs generation, like. Do you have a problem with like, you know, you don’t know who to, like, you don’t know who to share photos with or you have trouble getting together with friends. so one of the apps that I worked on was [00:05:00] specifically, about that was about getting together with friends and this sort of, friction, the initiation friction of like, Oh, well, I don’t want to invite people because maybe they’re not free or like I’m putting myself out there.

[00:05:13] And so, you know, we were really like mostly, you know, brainstorming, like thinking of basically just thinking of problems, but then trying to do as much kind of preliminary research. We used a lot of different, We use this tool called Google consumer surveys, which is a really useful tool basically instead of paying for a news article for exams, you’ll get a survey instead.

[00:05:38] So you get to see the article for free, but you have to answer a survey question. So this is, this is a really useful tool for getting kind of like internet population, feedback. And so we would use this tool to sort of gauge like. Is this a problem for you? How severe of this is this problem for you?

[00:05:54] How likely would you be to like download a, an app that would help you do this and the court, like the [00:06:00] absolute numbers? Of course, wouldn’t be that important. It’s all very hypothetical, but it was a way to sort of weed out different ideas, that we would sort of talk about. By trying to identify where, where there was the greatest interest or really the greatest need for like a problem worth solving.

[00:06:17]so that was, yeah. So I thought that was like a very, interesting, like a good, like principled way to approach, like making a decision as to what to build. but it is, you know, kind of like special case at Google where like, we are kind of specially sanctioned to do this type of thing at that, at that time, to try to generate, Sort of new, new product ideas and make a convincing case to our leadership.

[00:06:40] That it’s a product that’s it’s project that’s worth pursuing. It’s worth investing in. 

[00:06:44]Joe: [00:06:44] I liked that idea really of just sort of doing that kind of quite quick tactical research to see if an idea is worth pursuing or not. And using, I love that idea, that tool, the Google consumer survey, you mentioned there as well, which is a great way, I suppose, of getting reached and getting out there quite quickly.

[00:06:58] we’ve got some ideas. That’s just [00:07:00] ask people what they think and then just sort of help. Use that survey to narrow down our thinking into focuses a little bit more. I love that.

[00:07:07] Christian: [00:07:07] Yeah. I think it was really, it’s really helpful just because I think a lot of times, I mean, Google is a pretty democratic place, but you know, still  the most senior person in the room,  their idea kind of weighs more than your idea if you’re like a little person in the room.

[00:07:23]and so having something that was more data driven, Was really helpful equalizer. Whereas a as a researcher, you could just say  if everyone’s got an equal, everyone’s on equal footing here, right? Like we’re going to write down, like we can solve problem a or problem B or problem C.

[00:07:38] And we’ll just like, let, our users kind of help us understand what is the most meaningful problem. And oftentimes, you know, we, the like senior person in the room, like their ideas, wouldn’t be the ones that were the most, Preferred or well understood or, you know, cared about by users. And I think it was a helpful way to sort of address maybe [00:08:00] like power dynamics and decision making, by using a little bit of data to, to equalize and sort of.

[00:08:05] A priori kind of setting up, like, we all agree, like, you know, depending on the yeah. Output outcome of this survey result, we should like, you know, follow this data. didn’t know his work. I mean, sometimes people can just kind of ignore more information and go forward based on other things. I don’t think that, you know, a survey survey data doesn’t present like the whole complexity of like making a decision about a product, but, it definitely helped, I think, at certain early stages to give equal kind of.

[00:08:32] Voice to different ideas. 

[00:08:36]Joe: [00:08:36] I liked the way you talked about kind of democratizing almost the decision making process, letting the data help you make that decision sort of flattening the, almost the, the, the org, the org chart. So everybody’s ideas are equal when the data comes in. And I love that idea cause that sort of helps then.

[00:08:52] Like you say, because again, you know, we all come in with biases in terms of what we do in terms of what we should build and how we should build it. But I liked the way that you’ve you used the data there to [00:09:00] kind of level that playing field and let the data make the decision for you. Really? I do like that.

[00:09:04] Fantastic. Okay. And so let’s talk about some of the stuff perhaps you’ve worked on most recently, or it was something you watched in your career. We talked about sort of smaller decisions there in terms of the kind of startup you’re working with. Start world, you’re working with an area one 20 within Google.

[00:09:18] Can you think of any sort of more larger decisions and that you’ve, you’ve been involved in, in making for the products you’ve worked in over the years? 

[00:09:26]Christian: [00:09:26] I mean, I can think,  I was, I was thinking a bit about this and I, I feel like the types of, of decisions that we often are making are kind of like either additive or some trip, like most of the time it’s like attitude.

[00:09:38] Like we want to build some new thing where we’re trying to figure out, like, you know, should we build something like this? Or should we build version a or version B or like, is this something that has built well, and I feel like those are different, like levels of. Of kind of decision. So it’s a recent one that, I think was really, thinking about [00:10:00] what should we build.

[00:10:01]next year this was like a very tangible, we have, we have 50 ideas of things that we might want to build, in the following year. So this is specifically for. The YouTube studio product. This is, this sort of internal tool that creators use to upload videos to check their analytics, to kind of like be a content management system, as well as a creative hub for, for YouTube creators and, We were really thinking of like, what do you know?

[00:10:30] There’s many things that we can do to improve the experience for YouTube creators. So what, what should we build? And, we. Again, kind of like the sources of that decision making can come from, like our, the way it came to me. And my team was like, we are thinking of doing these 10 things. We want to help, generally speaking, we want to do these three or four.

[00:10:55] We want to do these four or five things to, help creators, choose better sort of like [00:11:00] videos and improve the quality of their, their videos. and. I think that how I approach that was like, well, why, like, why those five things? Why not another five? Like why not these other ideas? And I think very quickly, like through that line of questioning, it’s like, I kind of heard this, or like there’s some anecdotal, like I’ve seen this before or like we get this input, like there’s a lot of like passive inputs that kind of get into specifically to like product leaders.

[00:11:29] And I think that that’s natural. Like we’re just, again, human and like, we just rely on memory and you know, if you see enough tweets complaining about feature X, then you’re like, that’s what we’re going to, that’s what we’re going to fix. And I wanted to sort of help that process. Again, trying to like approach it from being as helpful as possible.

[00:11:49] And I think that sometimes there can be like an adversarial, like nature between research and product where it’s , we’re telling people that their ideas are good or bad and , you know, [00:12:00] it can be, it can be tough like that. I think that tension is good. I think that there’s checks and balances there, but.

[00:12:05]when it came to , what should we build next year? It felt like we should feel really confident in that. Like, when we say like, why we did this over that, like, we should have a better, we should have a really good data-driven reason. I guess there’s a theme there. but we, what I did is my team and I would work together and.

[00:12:22] We kind of, again, surveyed, creators, asking them, you know, one of the top things that we should improve, versus the top new things that you’d like to see. So that was, I think, another kind of big decision point that wasn’t really that clear in terms of. You know, it’s, it’s obviously exciting to work on new features, new product areas, but oftentimes like your users are like, yeah, like the new stuff is great, but like this thing that I use every single day, it still sucks.

[00:12:51] Can you please make that better before you do anything else? and.  that’s, that’s kind of, we wanted to make sure that we could capture that. I think that was a, that was a concern of ours that, you know, we’re, we’re [00:13:00] missing out on, you know, existing experiences that, that could really be improved on for creators.

[00:13:05] So, That’s , so we, we kind of got the, like a broad universe of possible ideas from YouTube creators. We collated that into a subset of existing things to improve new things, versus new things to build, and. If I can get slightly method nerdy, on like how we did this, we, we use like these, a particular survey question, a constant, some type of question where we’re basically like here’s a hundred points allocate these hundred points based on which idea, which thing would be most valuable to you, as a, as a creator across those different categories.

[00:13:38] And, obviously there’s some flaws. .  the ideas are only as good as the like question string that we’ve written. but you know, it really helped us. Get a better sense of what was most. Most valuable, not only like in a stock rug sense, but like the level of magnitude. So we can say like, actually this feature is five times more, more valuable to creators than this other feature.

[00:13:59] So we have a [00:14:00] much better reason for doing this, you know, to pursue this next year, rather than this idea. And, and oftentimes it’s like we say that we’re going to do five, which really means that we’re going to do three. And then at the end of the day, we ended up doing like two. so it’s really helpful to know.

[00:14:15] at the, at the beginning of the year, that those two that really actually are going to happen are well aligned with like, you know, what are the things that creators really are our users really want to see improved on and what are the new things that are going to deliver value. And so that we don’t end up at the end of the year, kind of like going whittling down through that process.

[00:14:33] And then we’re, we’re still, there’s a huge gap in between, what users really need and what we’ve. Been working on over the last year. So this was, you know, trying to set us up. The decision making was really, you know, what, what do we work on next year? And then how do we set that up? So that we’re confident that at the end of the year, we’ve, we’ve built the best thing.

[00:14:51] We’ve tried to, you know, canvas the universe of possible inputs, at least from our users. certainly not the universe of all possibilities, still a lot of [00:15:00] unknown unknowns out there, but from the best we could gather, we can feel confident that we know why we chose to do. One, build one feature over, over another.

[00:15:10]Joe: [00:15:10] I liked that way. The concept you talked to those two  types of things, you look to build the idea of that improvement or the additive of new staff as well. And you sort of put those into the same, that same research idea of this, you know, of this, the user’s kind of this constant.

[00:15:24] So you gave the users a hundred points. Now they haven’t had to allocate the points to the things that they wanted the most, I guess that, I guess that gave you the, the granularity to know that which one was going to. You know, going to give that user perceive more value from that user than anything else.

[00:15:36] So I love that idea of again, using the research to help you decide what to build next and what order to build it. And I really love that idea, I guess, like you said, as well, I like that idea. You came up with that and you mentioned that it also gives you the confidence that you’ve made a better decision.

[00:15:50] So you’ve got some data to say, well, we, you know, this gives us great confidence that these are the three or the five things that we should build next year. I like that. And it has the data behind it. [00:16:00] and so, We’re doing that, then that, I mean, that sounds fantastic. And I’m guessing some of those features were successful, but I think in any, any, any leader in any, any person in working in product, digital product these days, some things are successful and some things are not.

[00:16:16] Can you talk anything about any, any decisions that have been made where things haven’t gone so well? 

[00:16:23]Christian: [00:16:23] this is a, maybe an interesting example because I was thinking of  a, you know, that’s like an additive example, right? Like we want to build new things or improve new things, but sometimes the decision is to deprecate a feature.

[00:16:36] And I feel like that is a really interesting question that we. Don’t talk about as much. And that happened kind of recently, that this is public so we can talk about it. So YouTube deprecated, a, captioning feature that allowed people to, sort of like crowd source captions for their videos. This is mainly due to, I mean, the driving rationale behind [00:17:00] it was more of a technical one.

[00:17:01]but you know, that was an interesting example, of.  we technically, it was difficult to migrate this into a new tech stack. and so we thought that we’ll, we’ll get rid of it. and there was some, you know, research questions around like, well, what is going to happen if we do that? and.

[00:17:23] basically what we saw is we kind of decided just looking at some numbers , well, how many people really use this? Is it this common? not, not as common, not as often used, so like, we’ll get rid of it. But then, you know, what we see from the community is that lots of people really realize that, you know, even though it’s a small number of the absolute, the people that did really use this and cared about it, I heard about it a lot.

[00:17:47]and so there was significant. Backlash, in these channels. So it’s like, it just made me think of the interesting decision making of , when we, when we’re making a active decision, we look at the data and the whole ecosystem, and we, we [00:18:00] kind of make a decision based on cold numbers and then.

[00:18:02] When we’re reacting, it’s like, Oh wow. We’re getting like a lot of tweets and negative feedback coming through these different channels. And then all of a sudden we’re like, well, what can we do to address this, this kind of negative feedback, which is very different, kind of like mental calculus.

[00:18:17] So that decision to deprecate, I guess it’s hard to say if it was the right. Or the wrong one, but certainly there was a lot of users that were negatively impacted by that, those that, that relied on it. And I think it’s maybe an example of where we didn’t, you know, we made a decision kind of one lens, which was, you know, how often does this get used?

[00:18:41] If it doesn’t get used more than X percent, then it’s, you know, not a candidate for us to. Technically migrate this over to some other, you know, some other tech stack, just takes too much time. but you know, based on, you know, our thinking that’s going on now, which is like, okay, how do we now kind of.

[00:18:59] Build something [00:19:00] that’s a compromise or, you know, something that will fill that gap that we created ourselves. it’s it’s like we’re on our back foot. And I think that’s an example of like, we could have been more on our, on our front foot with, with these types of. Decisions of, of taking something away, people are upset and it’s either like you accept that this is going to be a, this is just an unpleasant decision and we can’t do anything about it.

[00:19:25] Or, you, are going to have some kind of way to mitigate that. and I think. Like decisions can go, can go wrong. When, when you don’t have that sort of plan in mind of like, what’s really going to happen. And what are you going to care about once, once this change is made, like what are the sources that you’re going to be basing your, your, your future decisions on.

[00:19:50] Does that make sense? 

[00:19:52]Joe: [00:19:52] you’re right. This deprecating features is something that isn’t talked about, much turning things off is that we know that when things are successful, we should [00:20:00] turn them off and get rid of them. But we never really think about that too much. I liked your concept there, of the lens where you often, we see these decisions through our lens, which is, well, technically this is difficult to do.

[00:20:11] Not many people are using it, you know, a small percentage, but obviously in YouTube terms, that’s a lot of people and. You know, seeing it through a different lens can help you reframe that decision a little bit. And obviously with hindsight, it’s easy to see, Oh, we should have done that. You know, that the backlash was obviously going to happen, but like you say that when then you’re on the, on that back foot, straight away when people are reacting to it.

[00:20:33] And I’m guessing as well, because you work with YouTube creators. They’re not quiet people are, they, they’re not gonna suffer in silence with this that they will let you know when something. Yeah. You’ve, you’ve upset them in some way. So I can understand that it’s, it’s a real challenge to have to kind of do that stuff.

[00:20:49]and so can I ask you, where are you now with that? Well, you know, so this, this has obviously been deprecated, this feature. 

[00:20:54]Christian: [00:20:54] I probably can’t say, well, the real truth is that we’re, we’re working on something [00:21:00] hopefully better.

[00:21:01]but you know, the timing of that, isn’t quite, you know, a transition, right?  ideally you deprecate something and then you, you know, have some kind of solution that’s. Already there. And so in the interim, we don’t really have, we don’t really have much. So that, that kind of there’s that gap, that’s left there, but for now, I mean, I think we are, we better understand the needs of those users.

[00:21:25]and we understand that they are valuable, to YouTube, regardless of, you know, the absolute kind of numbers here, which as you said, you know, small percentages at YouTube are still many, many. Many many creative creators and users, and it really is about the community as well. So this is kind of an interesting feature that sits in the, in between like a viewer, consumer of YouTube and a creator, because this is really the community that is contributing to, to, creators, To translation and really helps the sort of reach and, visibility, an audience, of [00:22:00] a particular video.

[00:22:00] So there’s definitely so obviously value in captions and value in having the community kind of connect there. So I think the idea is, that we will have something in the future, and we are investing more in this area. But it will be a longer timescale probably then than users would, would want.

[00:22:21]Joe: [00:22:21] so back to   the decision making you talked about there, you talked about some of the inputs. Is there kind of a, a prescribed process that you have. That you do to, to make decisions or kind of across the teams, say at YouTube, do you all sort of follow a same decision making process and anything like 

[00:22:36] Christian: [00:22:36] that?

[00:22:37] Yeah, I, I wish, I wish there was a process, but not, not really. I mean, I think that it’s, it depends. Well, I think decisions are being made by people, and these people are in a different context. and so I view my, the role or my team’s role as trying to, you know, we are [00:23:00] customizing our support in decision making, based on what.

[00:23:03] The, you know, the individual and, and the context of that are there like legal mandates that are going on? Is there a massive technical constraint and all of these things? So I think, the risk, because sometimes I think that I see with. Research is that we can really focus on having a really good, the structured research process, that generates insights and draws conclusions, but that can sometimes maybe miss the broader context.

[00:23:30] Like, yes, it would be great to, to build feature X, but like, We are also under legal mandate to build feature wise. So like how have we squared those things away? So I think in terms of process, I feel like what’s most important is really understanding your, your stakeholders, what they care about, what they think about, what their, what their own sort of biases that they bring are, how do they, how do they view research, for example, how do they view user data?

[00:23:56] I think. There’s definitely a broad range of like, [00:24:00] you know, I know what’s best for users as a, as an individual decision maker versus like the users, you know, no, no best and you know, all sorts of shades in between. So I think just gauging a sense of, how much the sort of user. Input is going to be a factor in decision making, is really important for, for our team.

[00:24:22] And then based on that, it’s really trying to get at the heart of like, what are the core questions that need to be answered for us to move forward for us to make a decision. Because oftentimes there’s lots of lots and lots of, around, you know, should we, should we build this feature? Should we deprecate this feature?

[00:24:40] Should we build feature a versus B? but oftentimes there’s like a much more narrow question that is, At the, at the heart of it, like, is this a good enough, like this thing we should, we could build a, or B, B is 10 times more technically difficult. So how much better is Bay B versus a, and then trying to under [00:25:00] understand, those types of questions, is, is kind of.

[00:25:03] Part of that, of that process. I feel like it’s the most important part is really talking with, with the stakeholders and the decision makers figure out where in that, like where they’re at and where can we provide the most value as a, as an insights, team. Cause I think that the UX research, at least at YouTube, I think is moving to be really just part of, an insights group.

[00:25:24] And we. Rely on certain types of methods to generate insights about users. but you know, we’re not that different from like data science or market research insights or other teams. we’re just using things in different ways. We sort of sit on in, in different, layers and the organization, but ultimately we’re trying to, we’re all trying to influence decision making mainly based on user data.

[00:25:46] It’s just where you get it and how you call yourself. But the most part it’s there, they’re very 

[00:25:50] Joe: [00:25:50] similar.  I like your thinking there about these kinds of the core questions you need to answer to move this forward. So what are the core questions? [00:26:00] Research can help you answer to input to this decision making.

[00:26:02] So what, you know, and I liked also the way you talk there about the types of stakeholders, understanding who they are, what they care about, so that then you can, I guess, formulate your insights in a way that’s going to help them make those decisions better themselves. So that’s a really interesting way of thinking about it really, that you can use.

[00:26:20] Research to make the decision making process easier and better from a kind of bottom up point of view. I really like that, that way of thinking about it. 

[00:26:28]Christian: [00:26:28] to just add a bit more to that, as I mentioned it before, like confidence, I think it’s really hard to just say like, this idea is good and this idea is bad.

[00:26:39] I think it’s one it’s really hard  to make  absolute distinctions there and oftentimes like, You won’t have a full picture, like, you know, relying on user data, is, is helpful, but it’s not the end all be all of like, this is, this is a good idea versus a bad idea. But I do think that, so, so most of the time, this decision makers, aren’t [00:27:00] quite looking for that.

[00:27:01] I think they’re looking for. For confidence more than they’re looking for, like an absolute answer sometimes, maybe. Yes. But most of the time, I think it’s about a degree of confidence and I feel like research can, can provide that and it’s really run counter to a decision maker expectations. Then we’ve kind of already got our foot in the door that they can, you know, relied more on these insights and maybe, you know, and then in the long run, you know, we kind of.

[00:27:30] Make that shift, but I think if you approach it from , I want to help you make it, I want to help you feel more confident in your decision. I feel like that is always met or warmly than like, I want to, you know, Decide, whether I want to basically, you know, rigorously decide whether your idea or your suggestion is better or worse than some other, some other things like that.

[00:27:52] Again, maybe it’s like too much going through the front door and, I think it’s helpful to really just. [00:28:00] Be in this sort of mindset of like I’m here to help provide confidence and support. And eventually, like we work together, to come to, you know, these longer term decisions and it’s more of a conversation.

[00:28:11]so, so that I think is less of a process, but maybe more of an attitude, when it comes to supporting decision-making, that I have found to be the most effective. 

[00:28:25]Joe: [00:28:25] The two concepts you taught there about as well, you’re looking to show the confidence in an idea, not an absolute yes.

[00:28:31] It’s a good one though. This one’s better. You give the confidence a confidence score almost to the people, making the decision to help them make that choice. 

[00:28:38]  earlier on you talked  about the process of decision making, you talked about inputs and user research being one of the inputs that you, you, you have. To the decision making process. So YouTube, what are the kinds of other inputs? I mean, obviously Google is quite famous for being quite data driven.

[00:28:53] Is, is YouTube a similar way? Do you, does data help you make the choices to, 

[00:28:59]Christian: [00:28:59] I think that [00:29:00] the data, I think that user research provides one type of, of data, but I do think that, , the hard numbers, are oftentimes like the. A really important input, but still not the only one, because oftentimes you have data, but, in the case of YouTube, we have to balance, different types of users and needs.

[00:29:24] So we have data on creators, but also viewers also advertisers also content owners. Sony that provides lots of music. So we have, certainly we have data from all these different inputs, but we still have to figure out what’s the right balance. Between these, these different forces. So I think, you know, YouTube probably like many other places is, is, there are many of different types of users with very potentially competing interests for advertisers might not be best for viewers or for creators.

[00:29:54] there is a bit of , Philosophy and subjectivity that comes into making the really [00:30:00] big sort of ecosystem level decisions. The data is, is helpful, but I think what really defines the direction of the product is, is the philosophy of how, you know, the teams are trying to, to operate. And, and so I feel like that’s where having a mission and having like a clear set of.

[00:30:22] Of longterm goals can, can really influence the, those bigger decisions, about, about YouTube overall. So, so data. Yeah. So data does, does play a major role, a major role in that, but it is an input to a more, a much more complicated, ecosystem. I think. 

[00:30:43] Joe: [00:30:43] I really like that idea , that data is helpful.

[00:30:45]but what  defines direction is the , the philosophy, the mission, the direction that kind of longterm goal planning, data inputs to that, but doesn’t necessarily direct it. So I realized that that concept in the idea. Great. Well, we’re almost out of time there, Christian. [00:31:00] Thank you very much for your time.

[00:31:00] I’ve learned so much today from chatting to you. It’s been fantastic. So thank you , for talking to us today. Is there anywhere that people can go find more about you? Where’s the best place for people to find out a bit more about you? 

[00:31:12] Christian: [00:31:12] Yeah, I think the easiest would probably just be on LinkedIn.

[00:31:15]that is where, yeah, that’s probably the easiest place to find me. You could just search Christian Gonzales, Google or YouTube. And you’ll, you’ll find me there. Joe, but, that’s, that’s probably the easiest way to get, get in touch with me.

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