WARNER BROTHERS DISCOVERY - Vera Chien, Executive Director, Global Corporate Strategy and Research. Genuinely useful ways to integrate AI; optimizing corporate strategy for today and tomorrow; understanding need states; what stage is the metaverse at now?

Get an insider’s perspective on Warner Brothers Discovery's corporate strategy team, focusing on insights and analytics that drive business operations across movies, TV shows, streaming services, and games. Vera delves into the importance of consumer behavior and trends in optimizing current practices and identifies future opportunities in emerging technologies. 

Among other areas, in this episode we cover:

•  How AI can genuinely be useful
• Techniques used to evaluate emergent trends
• Tailoring presentations for left brain and right brain stakeholders
• Understanding need states
• Where the metaverse is now
• Differences between sectors and additional perspective from Vera’s time at Mattel, Del Monte and Microsoft Xbox
•  Do’s and don’ts for agencies

All episodes available at https://www.insightplatforms.com/podcasts/

Suggestions, thoughts etc to futureviewpod@gmail.com

Chapters

• 1:14 Guest intro
• 4:29 Vera's role within WB Discovery, optimizing for today and tomorrow....
• 8:21 Where is the metaverse now?
• 10:50 Understanding need states
• 14:02 Adding breadth to specialist department depth
• 18:26 Tools used for future looking analysis
• 23:05 Genuinely useful ways to apply AI
• 27:03 Differences between entertainment research & other sectors
• 31:32 Lessons from mentors
• 36:11 Do's and don'ts for agencies
• 45:01 Wrap up

Transcript

Vera Chien: 0:08

so I think yeah to your point, you know it's it's maybe it's it's more about knowing your audience and making sure you tailor the output for whatever screen, whatever um kind of approach. You know I've certainly presented to more right brain audiencesined audiences versus left-brained audiences. So obviously inherent in that you're going to present data to creatives much more differently than data to engineering or finance. So knowing your audience and I don't put that on necessarily the agency to know that necessarily, but to the degree they have had experience and can be thoughtful partners with me and understand that, is already a leg up. We don't have the volume and the structured development cycle of CPG, so I think that just then varies what we do do, because there's no point in, no need and no point in doing a conjoined for an upcoming movie, because the nature of the businesses, nature of the business models and nature of the content itself Welcome to FutureView.

Henry Piney: 1:15

This episode is brought to you by MXA Labs. Now we just heard a couple of clips from the fascinating Vera Chin of Warner Brothers Discovery. I loved having this conversation. Vera has an amazing role, supervising research on a strategic level, and she describes how she intersects with specialist business units, how she'd like to use AI where the metaverse is now Remember the metaverse as well as a host of other areas, including how entertainment research differs from other sectors, learning from great bosses and do's and don'ts for agencies. It's not often I get the chance to speak to someone who's able to incorporate so much perspective, not just from Vera's current role, but also from previous jobs at Microsoft, xbox, del Monte and Mattel.

Henry Piney: 1:56

Now, on the subject of M's, just a touch more detail on MXA Labs. I'd definitely check out this platform if you want to supercharge the back office research functions that can often be so frustrating. Mxa's platform is built for AI from the ground up, so the researchers at agencies and in-house departments can use tech to take care of all the time-consuming tasks like programming, link checking, running data, additional data queries you know the type of thing and they can apply their brains to what really matters If you want to turn tasks that used to take days into minutes. Then check out mx8labscom. Now on to the interview. So thanks so much for joining today. Now I wanted to get going with the traditional icebreaker, which was something about you that people generally wouldn't know. They might find surprising that you couldn't find just through a basic internet search.

Vera Chien: 2:50

Sure, sure. Well, I have to confess, first of all, I don't have anything probably worthy of like America's Got Talent or the Voice or anything like that. So well, one thing I will that might be interesting or surprising, or at least to me is funny, is I did play the organ for a few years growing up. And, mind you, we're not talking about like a cool church organ or anything like that, but a very, in my mind, cringy 80s electric organ with different color tabs where you know you press one and then it's yeah, yeah, you know, you press one and then it's Okay.

Vera Chien: 3:30

Okay, Exactly so. It simulates like a violin. And then you press another tab, it simulates the Samba or something. You know eighties like that, and that was the, I guess, instrument of choice for my parents at the time, and you know so.

Henry Piney: 3:41

Did you, did you get really good at it? I mean, can you go through grades and that type of thing?

Vera Chien: 3:46

I definitely not great at it, but I could probably fumble my way through. I mean with the tabs. You know, you just like hit a button and all of a sudden the keyboard belts out, you know whatever clarinet sounding.

Henry Piney: 4:01

That's probably about as far as I would be able to get in terms of musical instruments, that's probably about as far as I would be able to get in terms of musical instruments. I have to say, you know, giving an approximation of what I'm trying to do, and then hopefully the tech takes over and we're going to talk about a different type of tech actually today as well yeah, yeah, no, that would be amazing if if they can make the 80s electric organ cool I'm sure you did really make it cool.

Henry Piney: 4:22

but but should we, should we jump onto the present and just start with a bit of scene setting as well in terms of what you do now at Warner Brothers Discovery and it's a long title so Executive Director, global Corporate Strategy and Insights. So could you explain a little bit more about what that means and what you do?

Vera Chien: 4:46

what you do. Yes, definitely a mouthful, and something that I had unfortunately not that much control over, but essentially what we do, or the way I think about it is, first of all, we are the reason why corporate strategy is part of our title and our department is. We are literally embedded into the corporate strategy team at Warner Brothers Discovery, of course, and within that the insights and analytics side of that team is kind of focused on two main areas. One is to optimize the current businesses for today. So for us that is things like movies, tv shows, streaming services, games, things like that. So looking across all of these different types of businesses, how can we, either individually or collectively, optimize those kinds of businesses? So an example of that kind of work in that area would be looking at, for example, share of time or share of wallet of, you know, consumers across these different kind of categories, or even looking at kind of the journey of how someone goes from wanting to watch a TV show to finally picking and deciding which one to watch.

Vera Chien: 5:56

So that's part of my team's role. The other part of it, I think, is to me even more exciting. It's looking at, then optimize the future, or identifying, you know, opportunity areas for us to, you know, invest in experiment with things like that. And so you know they could be things like you know kind of metaverse type of experiences. You know something really. You know more down the line or more in the mid and long term future or there could be kind of closer in. So things like you know social media and social video platforms, you know what is kind of our role in that and you know, should we be applying more resources towards content on YouTube, tiktok, etc. So a bit of today, optimizing today and then looking at tomorrow is how I characterize kind of what my team does.

Henry Piney: 6:49

Yeah, it sounds really fascinating. And who are the stakeholders for that? I don't mean necessarily in terms of corporate structure, in terms of directly who you report into, but who's using your insights and the data that you're pulling together?

Vera Chien: 7:04

Yeah.

Vera Chien: 7:04

So of course you know the're part of our team corporate strategy, because what they will do is then take the information and then hopefully bake it in into short, mid and long term strategy for the company at large, which is why I really thrilled that you know this was a change, maybe about a year and a half ago, that we were, you know, a part of this group more formally Other teams, that, and sort of the beauty of what we do. You know, especially if we're talking about opportunities in the future, they're not necessarily wedded to a certain business unit or a line of business. You know we are looking at things at a broad level. So they could, for example, you know again just bringing back the metaverse, again the metaverse experiences, they could be applicable to marketing. They could be applicable to, you know, people who are creating content. They could be applicable to people on our max streaming service. So we really do try to uncover and research topics especially on that latter part, looking into the future that we think are applicable for multiple different functions and lines of businesses.

Henry Piney: 8:12

Yeah, got it, and I'll dip back in a moment in terms of how you intersect with the other departments, because obviously there are specialist departments across movies, games, whatever it might be, but the metaverse which we were chatting about beforehand. So is it still a thing? Because two years ago we were all talking about that, yeah, the metaverse, and then, as we said, ai has kind of supplanted it. But I suspect there are all sorts of initiatives still going on in the background.

Vera Chien: 8:41

Yeah, I mean, I think definitely there is. So I agreed that it's kind of in a quiet period, and one framework I personally love especially, you know, having worked in innovation and various different types of technology, even outside of the metaverse, of course. I really like the Gartner hype cycle, not, you know, not sure how you know, how familiar you are with it, but essentially it kind of is a framework of thinking about how, especially emerging technologies, a very kind of typical like cycle they might go through. So I think of that and I think the metaverse is one of those things that does fit. So it went through this like hype, as you said, very, very strong. You know everybody's talking about him. You know Facebook changed their name to Meta, all that kind of stuff happened. And then what we have seen since then is what Gartner calls the trough of disillusionment.

Henry Piney: 9:33

That's it, yeah, yeah.

Vera Chien: 9:34

That's it, the trough of disillusionment.

Henry Piney: 9:36

It's a great phrase, isn't it?

Vera Chien: 9:37

I know I love it, I love it. So we're kind of in that period, but I think we're getting kind of out, starting to get out of it and towards something optimistic. They call it. It's like slope of something, positivity or something, whatever it is, and then essentially it starts gaining back up and then plateauing and I do think the metaverse will, you know, follow some of that trajectory and partly the reason why I believe that is, you know, all the signals that you know we saw from the original. You know, yes, the pandemic especially magnified a lot of those drivers, but the signals are still there. You know, at least from my research and my team's research is, you know, the signals of people wanting more immersive experiences, more social experiences. Those are still kind of very universal kind of needs, and so this is leveraging technology to meet those needs in a newer kind of and more, I guess even more immersive way.

Henry Piney: 10:41

Yeah, it makes a lot of sense. I mean, I guess, in my view, I wondered in some ways, maybe not necessarily with the benefit of hindsight, because we're still along that journey, but whether it really needed to be called like the metaverse or Web 3.0, if it's actually just the next iteration of the web, continuing certain trends as you say that are more immersive of the web, continuing certain trends, as you say, that are more immersive, that enable you to interact and connect in different ways.

Vera Chien: 11:09

Yeah, I share that same kind of thinking too. It's not Web 3.0 with a capital W and a giant three, it's just the next instantiation of the web.

Henry Piney: 11:20

Yeah, and Vera, I warned you we might jump around a little bit, but you talked a little bit there around need states and that type of thing. Do you do that type of work in terms of looking at your consumers as a whole or your prospective audiences and thinking about? You know movies can provide this need state, certain types of streaming video games et cetera et cetera. So that's a big part of what you do, is it?

Vera Chien: 11:49

Yeah, yeah, so that falls in, you know, kind of, I guess, in between the two areas I described earlier. That is another area you know that can affect today also, can influence kind of how we think about tomorrow as well. It's one of those foundational types of research we do. So, yeah, so we have a framework that we fight where we've identified eight kind of semi or pretty universal needs consumers have for entertainment, not just TV shows, not just movies, but also gaming. You know podcasts, what have you. So it's been really kind of useful to use that as a grounding when we think about. You know why people do things and really ultimately the, the sort of third, fourth, fifth order. You know ultimate reasons why, what drives people to watch house of the dragon or succession, or, or you know any of our other shows or or play our games yeah, I'd love to know what the eight needs states are, but you probably can't tell me well.

Vera Chien: 12:43

Well, I mean they're not going to. I will say you could probably guess for just by looking at your own kind of and doing some introspective thinking, you know escape, for example, obviously a huge part, especially for TV shows, movies and games, a really big part of why people seek that. They want, want to escape from perhaps the stresses of the real world into other worlds, stories, and kind of immerse themselves into characters and storylines and real or fictional places.

Henry Piney: 13:20

So that's obviously a key one for entertainment and then how do you then intersect, taking that type of knowledge, with the various departments within warner brothers discovery, particularly the inside departments? Because you know, going back to the type of stuff I used to do, I know you know the movie department kind of like its own thing. Obviously that's blurred a lot with streaming and I'd imagine that they are still commissioning their own research. How do you intersect with those departments? Are you helping them inform what they do next in terms of going actually this type of content is likely to reach this segment of our audience and fulfill these needs and guiding them like that?

Vera Chien: 14:08

Yeah, I mean. So, first of all, you're spot on with, like obviously there's many different teams across our company that work on, you know, inside analytics around, you know kind of whether it's consumer or you know first party data, things like that. And so my mental model is, you know, we have a couple of research teams that are more about depth. You know, as you kind of alluded to already, we have a team that's focused around researching our movies, researching our TV shows, researching our games, streaming services, et cetera, et cetera. And then we have a couple of research teams that kind of more sit across, slightly more breadth, I would call them, and really just because they cover multiple different business units or types of content. So we, of course, are an example of that, because our purview is quite broad and can cover multiple different of these businesses and these types of entertainment.

Vera Chien: 15:03

We have other teams like advertising, ad sales. That also touches multiple different forms of entertainment, especially movies and TV shows and networks, things like that. So, and basically, I think we, I think we have great relationships with, with many of these teams, most of these teams, and really do try our best to collaborate and share knowledge, you know, when it's appropriate, you know, for example, if we did kind of a deep dive around Gen Z, for example, obviously that's going to cut across, you know, multiple of these, not only breadth kind of other teams, like at sales, but also depth teams, because nearly all of our businesses touch Gen Z in some way. So that's kind of an example of how we might work together and you know we might get their input on the questionnaire or something like that, but we definitely, at the very minimum, would you know, would be sharing our findings with them.

Henry Piney: 15:58

Yeah, it sounds like a really smart approach. I mean in terms of dipping into their expertise, as you say, because they're going to be or this movie, but big picture, we believe the real value for Warner Brothers Discovery is around this type of streaming or.

Vera Chien: 16:34

Absolutely, I think, and we are probably the core team where that's their responsibility to identify, scan and monitor and identify not only what's happening in the landscape but also what we are hearing the pulse of the consumers to, to kind of bring forth. You know, hey, maybe we should be looking at true, more true prime content because that seems to be resonating. Or, hey, there's this new kind of e-commerce live streaming phenomena happening in China. Maybe we need to understand it more and see if there's application for us. So, yeah, definitely, and that is I got to say. To me the most rewarding parts of it is to really try and be kind of have a pulse on consumers today, but also be looking at what might be coming through in the near term, future, so that we can either develop strategies or or even just directly start implementing and actioning on them.

Henry Piney: 17:37

Yeah, I mean that sounds brilliant, like an amazing, amazing, amazing job. Everyone listening to this podcast probably wants your job right now. I'm sure there are frustrations.

Vera Chien: 17:46

I'm probably glossing over a lot of things that need to happen before they say okay, vera says double down on true crime, we're going to invest. I mean a lot of things need to happen and it's not for sure not that straightforward.

Henry Piney: 18:00

Are you saying we should blame you for the endless true crime podcasts?

Vera Chien: 18:06

You know true crime. It's got its following for sure.

Henry Piney: 18:10

I mean clearly. I think the proof is in the pudding, to use a very British phrase. I mean, they're everywhere, and I guess there's a good reason why that's the case. Yeah, yeah yeah, so what tools do you use to inform your analysis, then, and so particularly the future looking stuff? I mean that's you know very hard, a little bit of crystal ball gazing. How'd you go about it?

Vera Chien: 18:34

Yeah, yeah, yeah. So I mean I'd say our toolbox is very, not probably too dissimilar to any other you know researchers kind of toolbox. We obviously do a lot of primary research around you know specific topics once they're identified, and then of course we rely on you know, syndicated research and syndicated data too, for just other general, maybe more general topics or sometimes specific topics, and then social listening we also take advantage of. You know when, where it's appropriate, and then you know just the full suite of quant techniques, qual techniques, when it comes to primary research. That's it's. It's probably you name it, we've probably done it and have been doing it or trying it, I guess.

Henry Piney: 19:22

And to what extent do you do that internally in terms of insourcing, or to what extent do you rely on external agencies?

Vera Chien: 19:30

Yeah, I think nearly most of what we do, minus of course, we're talking about analytics. On the analytics side, where we're just analyzing data, we probably do the bulk of that ourselves. But if we're talking about primary research, we outsource 90 plus percent of it.

Henry Piney: 19:49

I'd say Interesting. Okay, and is that because? Because I think there have been, you know, concerns amongst agencies around trends towards insourcing. So I'm jumping kind of like ahead of some of the questions we were going to talk about. But why is that that you'd rely on agencies? Is it because you know that they can recruit and they can deal with the difficult nitty gritty sides of kind of research? I guess in some cases they have sector expertise or external perspective that might be valuable to you guys. What are the good things about agencies? Why do you go to agencies?

Vera Chien: 20:20

Yeah, I mean I think yes, for all of those practical reasons I'd say, and frankly, because more I think again, because of kind of our more slightly different remit, there is nothing really. We don't really have a. We only have one or two kind of pieces of research that we do over and over again. So we don't run any tracking studies on our team. There are plenty of teams and across our company that will do that. So we don't have anything kind of you know that, we just turn the crank on.

Henry Piney: 20:52

It's more ad hoc and kind of customized know that we just turn the crank on.

Vera Chien: 20:56

It's more ad hoc and kind of customized yeah, correct, correct. So everything, almost everything, we do is bespoke. And then not just that, it is you know, I would say 60, 70 percent of what we do is self-initiated. So it's not because somebody asked us to do something or something, somebody's curious about something. It's something that, again, we think just even kind of going back to that e-commerce live stream example something we identified, we think is important, has viability and something that we would do deeper research around, and so that's kind of a great example of how we would approach things. So that's really why I think we end up partnering with agencies to kind of help us with that, because we don't have anything we don't have like, ok, what is going to be the new innovation of the quarter we're going to deep dive into?

Henry Piney: 21:47

We really don't have a cadence, and excuse me if it's like a prying question, but how do you pay for it? Because in my experience of a lot of the companies, the research tends to be allocated to a certain title or a certain platform yeah, almost like a thing. So do you just have a central budget that's allocated that you can use to explore?

Vera Chien: 22:12

Yep, that's right, and so that helps dramatically. And of course, you know, as you can, starting to imagine, we don't have any necessarily stakeholders. We answer to that we need to provide XYZ every quarter or anything like that to, and so it's really we do have a budget, a finite budget. It's not infinite. So we have a finite budget that we just then, you know, just try to be judicious about how we go about spending it and making sure at the end of the day, because obviously you know we must make business impact or else next year there might not be a budget. So we really need to obviously be thoughtful about how can we allocate this finite budget against kind of our purview and remit, which is, you know, optimizing the businesses for today and then balancing that against looking at and doing research that helps inform the future.

Henry Piney: 23:06

Yeah, absolutely. And how do you think AI plays into all this? I mean, where do you see it all going in terms of the insight sector?

Vera Chien: 23:16

Yeah, you know, I definitely. I think lowest hanging fruit is just trying to remove as much of the manual labor, manual time consuming labor. I think that's probably where it's going to be immediately the most useful. I do think it's going to vary a little bit by the experience level of the researcher. So, for example, I think it will be and I know this already especially for more junior researchers, incredible, incredible resource to be able to use it as a jumping off point to craft a screener, to craft a discussion guide, to come up with a starting list of slow-ended responses, things like that. That would be amazing for people where that part of it or that query might be a little more difficult. I think for me right now definitely would love help doing some of the low know, the low-hanging fruit, like I talked about a minute ago. But some of these other examples, like around crafting questions, screener I I think I'm gonna be faster than ai for this yeah, yeah, yeah.

Henry Piney: 24:26

You've done it many, many, many times you know and probably more thoughtful than ai.

Vera Chien: 24:31

For now i'm'm definitely not opposed to seeing where it could help, but in those kind of specific tasks I think I'm okay for now. But what I am really looking forward to is on the analytics side and just evolving it so that you can take a data set and analyze it through using more natural language, rather than having to create and remember what the SQL code is for XYZ or the R. You know, I think for me that and I'm sure there are brilliant geniuses like what I was saying a minute ago about tasks they probably would find it faster to it themselves than to, but I'm certainly not in that R or SQL genius camp. So for me, you know, ai would be incredibly useful and helping me probe through data in in, at least in the way I go about it and you know today, which is looking at different patterns, identifying hypotheses, and then, you know, using more natural language to kind of see what the results of testing through a hypothesis are.

Henry Piney: 25:41

Yeah, it's a really interesting point. I was just having a conversation actually earlier today with someone like around exactly this, around how, even say, it feels quant data and you want to get a different data cut out of it. And then in the old days maybe currently you go to get a different data cut out of it and then in the old days, maybe currently you go and ask a data processing department or data science sponsor do it for you and that takes however long it takes, and wouldn't it be great just to be able to ask the data questions ago.

Vera Chien: 26:09

Can you show me this cut and it's right yeah, I think the other area where I think ai could really at least selfishly speaking for me, would be in data viz. So being able to again using natural language, you know the, the tool or this this imaginary fictional tool is is based on, would really help create the optimal kind of visualization for a certain point you are trying to make. So, instead of just spitting out your generic bar chart, for example, it would actually create a kind of if you said, hey, I want to emphasize the gender skew of this data point, and it would do that.

Henry Piney: 26:52

Yeah, 100% agreed. Now, vera, I'm conscious of time and you probably have to get on to your next meeting, so I just wanted to ask a final question around some of the differences between the entertainment research sector based on your experience in other businesses.

Vera Chien: 27:07

Yeah, yeah, yeah. So I feel like movies, tv shows and games. So basically the time I've spent here, as well as some of my last role at Xbox or Microsoft, they, I have profound respect in that they are kind of essentially art forms, and I think you touched upon this earlier and so you know, as you know, you know I'm not necessarily going to run a focus group and tell James Gunn or Christopher Nolan like to change the scene or a script or, you know, cast somebody else instead. Most research does not really do that and even if it was done, I don't know how actionable it would end up being. So, you know, I think just that's, I think, the one of the first kind of things I quickly realized, you know, when I started Xbox and of course I don't know why it was, why I had to realize I think I had a hunch already, but it obviously was confirmed as soon as I started working here. But of course, what we do, research is everything outside of that, and I'm now talking more generally, not about my specific role but obviously other teams here. So they will research sort of the marketing, so more marketing research. So what? Optimizing the trailer, you know, other marketing assets, testing those kinds of things, you know, maybe even positioning and you know, whatever, all of those kinds of things.

Vera Chien: 28:28

Regarding the content, games are a little bit different, of course, because there is actually a really large part of it is UX research. It needs to be playable, it needs to be usable. So that is one area where it can impact the actual content itself, the gaming content. Of course, if a part of the game can't be played, that's going to be an issue, but I would say so that is kind of part what I think has been a little bit different about it versus my other roles. Mattel, you know, is a certainly technically, I think, considered a CPG, but it's more of a durable good. So you're not necessarily buying Barbies every week.

Vera Chien: 29:10

Some people are, but you know it's something that is more durable and there's a product development cycle. You know that needs to be followed in order to get something on shelf at the time that we want it to be on shelf, and so I think when we kind of back that up, there's, you know, a lot of the more common well-established phases of research that happened, you know, to get to a product, to the market, and so those are things that don't really exist as much here, just because we aren't launching so many products. And even when we, let's say, release a movie, while we are certainly tracking sort of awareness, familiarity, those kinds of things of a movie, we're not necessarily testing the product itself, those kind of things of a movie. We're not necessarily testing the product itself but we are testing the, the wrapping, the, the packaging, the marketing of it as it gets slowly, you know, over time towards the release date of that movie. So I think those are some of the differences.

Vera Chien: 30:09

And so other research that kind of are more front end and you know, and then typically more front end research involving or evaluative research, involving more, either more advanced techniques or experimental techniques, really just aren't as necessary conjoint for a movie. You know you're either going to do, you know, discrete choice on on. Well, you can, actually we've done discrete choice on streaming services, but I'll take that. But give me an example we don't have the, the volume and the structured development cycle of cpg. So I think that just then varies kind of what we do do, because there's no point in, you know, no need and no point in doing a conjoined for an upcoming movie. It's just, it's not, it doesn't even make sense. So I think it's just, yeah, I think I think that that was certainly something that, if I had to reflect back, it has been really interesting. It's not necessarily it's a negative thing, but it's just because the nature of the businesses, nature of the business models and nature of the content itself doesn't lend itself to more traditional research techniques.

Henry Piney: 31:21

Thank you, that is a really interesting perspective. Now I'm conscious in you probably only have about three minutes left, so I might do a quick fire round, if that's all right.

Vera Chien: 31:28

Sure, I can go a little bit over too, no worries.

Henry Piney: 31:30

Okay, well, it's great. It's great, actually, if you can do that. It's fantastic. But I'll ask you some of these questions. Maybe we can just spend longer on them in that case. So who have your mentors been and what did they teach you?

Vera Chien: 31:43

I'd say most of my mentors have been more just, more informal and either whether they were, you know, in my leadership chain or my direct managers so I'll pick a few, you know that kind of maybe stand out to me. You know, and just as I reflect back and think about you know things where I've learned, you know I've been more impactful. So I'll start first of all, early in my career, one of my first managers at Mattel I think one of the things I really, hindsight, really appreciated about this individual was just really the encouragement and receptivity to experimentation, and I'll explain the reason why. You know, I think at the time, because this was a long time ago, market research with kids, believe it or not, was really quite nascent. There really were not many agencies honestly that had expertise. You know there were probably consultants that had some expertise, but really most of the experts were coming from probably academia or some kind of field where they were studying, you know, children, as you can imagine, for Mattel. And so what that then necessitated was that we would need to develop a lot of these kind of methodologies ourselves. We could not take a five-point Liger scale and give that to a five-year-old and expect an attitudinal battery of five-point scale then to answer that, of course, but what we could do is a three-point happy face scale, a very doable, much more developmentally appropriate. And so that's just one example of and that's not even a great example of the things we would have to do to really kind of get some of the same metrics, some metrics, especially quantitatively, around concepts, the typical things you would do in sort of testing products and getting them to to market, so that I really appreciated, you know. You know, you know my one of my like I said, my one of my first manners being extremely open and receptive to experimentation. Sometimes experiments didn't work, you know, you know, but and were meaningful and others really, really weren't, something we continued to kind of to use time and time over. So that's one. I'll speak to another, maybe another time.

Vera Chien: 34:08

At Xbox, I'd say box, I'd say what this manager taught me was that it is so important to be an amazing people manager, and I don't know why that sounds funny, but I think prior to that point, I think I had been really focused on being excellent in my function in research and felt like that was that probably consumed, you know, a large part of my mindset and my obviously my time and so when I initially, you know, was going to be this person was going to be my manager, I sadly was. I was a little disappointed because, you know, this person didn't come from a traditional research experience, had more limited you know experience, and I was like, okay, what is this person going to teach me? What am I going to learn from this person? I learned so much more from this then and especially, you know, as I, you know, get into, you know senior levels where I'm managing people.

Vera Chien: 35:07

You know that how important it is to help. You know your other, even colleagues and or peers, and or you know that how important it is to help you know your other, even colleagues and or peers and or you know direct reports, help you know kind of prioritize, delegate and develop them. And it was just amazing that you know, for somebody who had on paper, you know much more limited research experience, how he truly brought out the best in each you know member of his team and really together made the our collective work so much stronger because of kind of the, the environment that he fostered, you know without.

Henry Piney: 35:44

So I think many, much, much learnings from, from, from that experience in my time working with him, yeah, and that's really fascinating, I mean, and it sounds like he kind of he may well have deferred to your greater technical expertise, but helped add in almost that sounding board and an organizational perspective about should we focus here or here, all that type of thing, rather than kind of drowning in the methodology which you, you know, I mean researchers love methodology and there's a temptation to do that, but I can see how that will be really, really critical. And so, in terms of researchers, what makes a good agency? And I guess the flip side of that, what's not a good agency?

Vera Chien: 36:29

Okay, well, one thing for sure I've realized over the years is obviously, research industry is very dynamic, just like anything else. I think it for me. I chalk it up to the individuals that are working at these and I know the spirit of your question. But I, I and I say that only because there are many agencies out there where, in past companies, I've had amazing, wonderful experiences with, and then come a new team that I work with, let's say, here or somewhere else. It's a really different experience. So I do really think it's the individuals that you end up working with that make or break it. So that would be the first thing, and I'm surprised all the time. So I'm always really sad when an amazing kind of team or group of individuals that are going to leave because you just never know what's going to happen. So I don't know if you've had that experience, but that's for me what has happened. I will say then, also before I delve into the actual specifics of your question I'm going to assume some basic table stakes, so you know, basic product management, the data is clean, some basic, solid analysis, like I'm going to assume all those things because I mean, I don't know if you can be a viable agency without doing that. So, beyond those things, I think for me that are things that are difference makers, that make individuals like researchers exceptional in an agency, is kind of storytelling. So and again, we will do that together, collaboratively, but really helping think through that so we can, and coming to the table with your ideas, your thoughts around what the story or stories could be as part of a narrative. That's really helpful.

Vera Chien: 38:15

Believe it or not, that doesn't always exist. We talked about data viz. I really do think and it's both for qual and quant. I'm not just talking about quant data being able and that it is related to the storytelling, too able, and that it is related to the storytelling too. You know how you convey information, the insights and the key points. Um, incredibly, incredibly important, I would say it's. It's more than half of the actual time spent on research should be thinking about how you do that, because so much now, at least for is not necessarily directly presenting verbally in real time. Oftentimes it's just email or sent to someone. So it needs to live and stand on its own on paper or at least in a document.

Vera Chien: 39:00

I think other things you know, subject matter, not necessarily expertise. I don't expect that, because that should be me. But having some kind of knowledge and I would say, for example, gaming when I was at Xbox, that's pretty important, you know, to have some experience. Somebody who has never played a game in their life, a console game, is going to be really tricky, I think, for them to be able to be the best researcher they can be. For my project that involves talking to gamers and understanding games and then general creativity in research methodology, research design. Not a huge fan of you know, just copy and paste, because especially the nature of what we've been talking about, what our team does, is more bespoke and more ad hoc, that we really do need partners that can help think about what might be the best ways to tackle this question, this topic. So having a partner in that thinking is always helpful too.

Henry Piney: 39:56

I think they're great, great guidelines. I was just thinking to myself around the data visualization point, but also understanding how to present a client slash friend of mine, who I shall not name as a result, but he pointed out to me. He said listen, you've got to understand. He said most of what you send me. He said I look at on my phone, yeah and so yeah. And I was thinking, yeah and so, yes, there's, of course there's a place for beautiful looking powerpoint presentations, but I can't see those on my phone in a meeting. True, true, I guess I just need the three headlines so that if somebody asks me the question, I can pull them out like really, really quickly.

Vera Chien: 40:38

Yeah. So I think yeah to your point. You know it's maybe it's more about knowing your audience and making sure you tailor the output for whatever screen, whatever you know kind of approach. You know I've certainly presented to more right brain audiences versus left brain audiences, so obviously that inherent in that you're going to present data to creatives much more differently than data to engineering or finance. So being, yeah, knowing your audience and and you know I don't put that on necessarily the agency to know that necessarily, but to the degree they have had experience and can be thoughtful partners with me and understand that is already a leg up in that respect.

Vera Chien: 41:22

Now for the other part of your question, the downsides, or sort of the less good, and again they're individuals, not agencies. I don't think there's any agencies where I don't think I will ever work with again. But some of the personal pet peeves for me are overselling and underdelivering. I don't like that Bait and switching. So that's when everything starts going great. In the beginning You're working with a very senior, perhaps methodologist or something like that. Then all of a sudden, whoa, what happened to that person? They disappeared. And now you get, you know, and at certain phases I get it. I don't expect the chief research methodologist of a you know, one of the top research firms in the world to be you know, to be checking.

Henry Piney: 42:12

Yeah, to doing every piece, yeah.

Vera Chien: 42:13

Yeah, no, no, right, but it's, it's. It's happened more excessively at critical points. I feel like something I watch out for. And then we've talked about this a minute ago like one size fits all solutions. Again, sometimes it can be fantastic and exactly what we need. For me, unless it's a tracking study, I do think we we tend to have more custom, ad hoc things, so people that consistently push a one size fits all solution or or off the shelf a methodology or approach or product which is for me it feels like it's becoming more popular these days at agencies.

Henry Piney: 42:51

Yeah, I was going to ask that. I was going to ask that as to whether you felt that's actually that's more prevalent, because I think you know, in the from a financing perspective kind of a corporate perspective, there have been all sorts of drivers, you know SaaS, business models like, and so on and so on, that mean that agencies are encouraged to package products, and so you do think you've been seeing more of that in yeah, and I understand, I totally get it Like you know.

Vera Chien: 43:18

I get it Like you know. There are several that other, you know some of the more depth research teams at our company take advantage of, and it absolutely makes sense. You know, if there is one general, for example, I'm just going to use these because they might be more concrete to everybody Movie tracker. Why should 10 different companies pay for their own movie tracker when there could be just one that everybody kind of buys into or, you know, for more economies of scale and if it fits kind of like 70, 80% of your needs, great, you know it totally, I think.

Vera Chien: 43:53

I think again, just for my team specifically, we don't operate, as you know, as much like that and I understand for like efficiencies on the on the agency side, you know, I think. Then what I would ask the you know, the team I'm working with is what are the advantages of using this For me? I know it's economically, you know, more efficient for you because the programming's already done. If it's quant, the ask, the collateral's already there, the guides, the screeners already all built in. I get that, but does this answer all of our key questions and objectives that we need for this new body of work, and if it doesn't, then what is your proposal for? How do we shore up the gaps? If you really feel heart set on this off-the-shelf solution?

Henry Piney: 44:48

Yeah, which seems like a very, very reasonable perspective on your part. I mean, maybe I would say that I don't know, it just starts to be very reasonable. So just a final question actually, I was just going to get a little bit of a guideline, actually on some entertainment material. So what would you recommend? I mean, they could be books, it could be movies, it could be tv streaming series, what, what, what have you enjoyed recently and what would you recommend?

Vera Chien: 45:15

oh my gosh, okay, I watched. I don't watch as many things as you, as surprisingly, but I'm really huge into sci-fi and fantasy, so if that's your, you know if you're interested in that. Obviously, house of the dragon Dragon has been doing amazing for us, so I love Game of Thrones and House of Dragon. I'm almost caught up. And then I'm currently also watching the Expanse. It's a few years old, it's on Amazon Prime. Wow, they're all space related. Maybe that's why I'm getting fed these in my algorithm. Three Botany Problem, also really interesting one based on, based on, you know, many books and apparently really, really quite successful in china. Um, I would say those off the top of my head yeah, no, those are all good.

Henry Piney: 45:58

Those are all good ones I made. I read the first three body problem book ah, okay and then I couldn't make it through the through the second one I haven't watched the series yet you can imagine, it's probably really dense and technical.

Henry Piney: 46:13

Yeah, it's kind of one of these things. It's really intriguing because you think you're kind of getting it and it teaches you all sorts of interesting metaphysical concepts and I go I'm really getting this and you start to feel very smart and then two pages later you feel really dumb. You've totally lost me again.

Vera Chien: 46:31

I think I'm gonna bypass the book. Then, like I am, I guarantee you I will feel the same way. So the the series, the limited series, was a great way of of getting the gist of and I'm sure I missed a ton of things through that, but but yeah, that one was was really intellectually like interesting and you know I enjoyed it avira.

Henry Piney: 46:47

Thank you so much. It's really been a pleasure talking to you and really really fascinating. I loved doing that interview. I think we probably all want Vera's job. It sounds so interesting but also very impactful. I also really like her take on how to work with other departments as well as integration of AI and what's really important in the insights process. Next week, we're looking at the world of marketing data, data and insights from a different perspective, namely, what goes on within your brain, how the different parts of the old grey matter influence what you think, and how brands can use that understanding to create better customer experiences. The wonderful Marco Baldocchi is going to take us through a primer on how you can use neuroscience. Thank you to MXA Labs for sponsoring. Really check them out. It's eye-opening what they can do. Vera for the interview, insight Platforms for their support and to you for listening. See you next time.