[Music] We're going to cover a topic I'm very interested in. Uh, as I think I mentioned yesterday, I um I I gave some support for the Information Commissioner's Office in the UK around I think it's called the Age Appropriate Design Code, which is all

about privacy and how we handle particularly um underage people's data. So I'm very interested in how we do the next topic. The next topic is all about marketing uh, well mastering game marketing in the era of data privacy. We've got Jesse from Geeklab who's

going to come up and talk about that. Jesse, over to you. Back to 2016, the good old times. Makes me feel old to say that, but still, the good old times. Everything that we did in this industry was fundamentally built uh in marketing around device identifiers. What that

allows us to do essentially was that uh we knew the entire user journey from the very first touchpoint into the very very last in-app purchase they made. So essentially, as an example here, from the very first ad, we could know that the same user came to our game, made a small

enough purchase after probably a month or so, you could have churned, but then went to another game of ours and then made a big purchase there, which allowed us to follow this entire journey through the device identifiers and understand the actual ROAS of our campaign even though

like the purchase itself happened on a on a completely different different game. Fast forward around 5 years, um Apple decided to pull a a little trick on us and they removed this this particular identifier that we used, IDFA, through their App Tracking Transparency

framework and what that led us into was this complete darkness essentially, uh, as we know, as we did not know, no longer, uh, the entire years of Journey we weren't able to understand as an example this in this exact same example, like if the user ended up making a purchase on another

game and actually calculate the RWS of our campaigns. Fast forward another five years or so, after a decade from the good old times, uh, I could argue that the situation is even worse in a sense, uh, we're now faced in a situation where a

lot of these networks have solved these issues for themselves, uh, we have multiple different ways of of of trying to identify these users and trying to make sense of all this mess essentially, uh, we still have Google's Advertiser ID and we're trying to model things on

top of the Google data and see if the same things work on iOS. News flash, it it usually doesn't and and in its sense we're we're just in a very very difficult place in terms of being able to make marketing on on iOS effectively.

Um, and that being said, privacy sandbox is also on its way so even like modeling things solely on the Google Advertiser ID and applying things on iOS, uh, will also be something that we can't do in the near future. Um, my name is yes lanan. I did my

time like probably most of the people in this conference at Robo, uh, five years at product marketing primarily launching new games, uh, after which we co-founded the company called Gig Laab, uh, that we've been we've been now running for five years as well and for the past two

years we've been cooking up something quite cool where the entire thing that we've been doing is to fix this like issue that I just mentioned uh and today I'm going to share how we actually did it and and and also just to prove that it's not only words on paper, show some

real data and real case examples with real game companies. Cool. So at the very beginning, what we actually did, we took a step back to truly like analyze and understand like how this entire industry is actually working and where are the decisions made when we do marketing

because we did notice that there's a bit of a mismatch essentially the entire Foundation like I just shared was built on these user identifiers uh sorry, device identifiers which meant that all the decisions were made on user level, however, the decisions that we're making uh are actually made

uh on the creative insight, so in a greater level, so clear mismatch, all the data that we're getting, all the data that we're trying to collect on a user level, however, we're not using that to make the decisions themselves. All right, so that was clear

to us like there's a mismatch, we can actually probably build something around the creative themselves rather than the user level data because this is this is actually where the decisions are made. On top of that, we wanted to take a look like is there any possibility for us to

get back to using these user level uh data points, essentially going to the near future. Uh there's way smarter people at this conference that know a lot more about these things, but uh just to uh actually share sort of the the trajectory that we see is that back from

2012 until like uh the massive privacy scandal that Facebook had with the elections to Apple removing the ATT, sorry, removing the IDFA during the ATT, to also now uh Google starting to roll out the the Privacy Sandbox as well, so we can see that there's a clear path on on

on where things are going, it means that first users themselves us essentially as well have become more understanding of of how our data is being used uh we we we are we voiced it out, we actually if if if someone is misusing our data we we put

them into into responsibility for that, second um this have led to a lot of regulations going forward um some of them good, some of them bad, some of them making things easier, some of them a lot slower uh but essentially a lot of lot of these regulations are are are already

happening and will happen more in the future as well which leads into advertising networks and platforms having to kind of cope into this making this entire space again more fragmented so we we can't really see a future where things would be consolidated even more

so with this we came to the conclusion that again user level Solutions are no longer viable, the only kind of way forward would be to build a a future where everything lies in in in Creative level Solutions because in its core if you actually build something that's that's

working between the game and the ad networks on a creative level we could essentially do attribution and analytics without using any of these user level Frameworks that that now has been given uh to kind of code for the loss of IDFA so as an example

scan with that we would completely eliminate the need to actually use those user-level data points in this process. We'd have something that would work here in between the ad networks and the game. It comes with one downside, which is the fact that the more bottom of the funnel metrics that we're looking at and trying to attribute and optimize, of course the kind of user quality, sorry, the quality of the data points themselves would get a bit worse. Uh, so obviously if if if we have a creative and and you try to optimize towards all the users that

uh, are still playing after day 180, so there would be a lot of false positives, but on the flip side that would still be a a certain data point that we would actually be able to to optimize toward. Word. So yeah, we can see that the

future truly lies in creative-level solutions. Uh, so what we would actually need would be a framework, a a creative-level framework, and this is precisely what we've been now building for about two years, uh, and something that we call the Audience Lab, and like I promised anyone I could

have done this exact exact same speech two years ago when we kind of came up with these theories and everything. Uh, but today, uh, actions speak louder than words. Uh, so we're actually going to share one of our pilot, uh, like partner case studies, a company called Talofa Games,

and and what we did together with them and what the results actually were. So Talofa Games itself, uh, is a company based in in San Francisco. Uh, they're making a game that I feel a lot of people here, uh, could probably resonate with, specifically given that I

I heard that a lot of people were running, uh, yesterday morning, uh, before the conference, so this particular game combines the health and the fitness side of things with something that we also, everyone loves, which is collecting new monsters and and kind of this Pokemon type of a nostalgic feeling, so

with that, they had a massive opportunity. There's two kind of very, very specific audiences that they could build this game for and market this game for, but the problem itself was that they had no idea of understanding which of these audiences worked and what would be the

messages and the the entire marketing strategy that would actually make these these audiences, uh, convert to the game. So what we did, we we jumped in with our framework, the technology that we have, and and here's the results directly pulled out of App Store Connect and Meta

to get the the the costs. But yeah, this is something that I bet like a lot of you, uh, that have done marketing might feel familiar with in the beginning. It's quite difficult. You're you're using these user level frameworks that have these postback

windows and and and attribution, uh, like U windows. It's very hard to understand what the actual sort of what's the outcome of your your decisions actually is, which led to them being very, very, very sort of, uh, this entire daily new users chart being very, very volatile and

and as you can see, really, really hard to actually scale and and make make any understanding of. We jumped in with our our tech and and basically day by day, we've been able to make decisions on a daily basis as well as attribute things on a creative level in real time. What we were

able to do was to take all the data that we had and make these decisions day by day and continuously like uh increase the daily new users to a level in which we were now able to to hit the records uh in two days in a row in relation to cost. This is even

better. We went from extremely high to the lowest that they had leading up to taking the CPI down from 3.8 all the way down to 1.8. All right, now a couple of you might think, okay, looks a bit good, too good to be true. Uh, you probably change the

audience setup or the the GE locations. So no, the networks in both examples, Meta, uh the Goo in both examples, United States. Um, what about the user quality then? Again, because of our creative level framework, we were also able to identify how the users behaved within the game

itself in iOS which led to us being able to also optimize all of our campaigns towards their key metric which in this case, as the game was in soft launch, it was D1 retention. And uh again, this data is directly from the App Store connect.

We were able to maintain the exact same user user quality while essentially cutting the cost in half uh and and being able to scale up the game quite a bit. So how do we do it? Again, the the tech was in the core which allowed us, gave us the opportunity and all the

tools to make this happen. And it really came down to do two different different main things. First, this is something that uh well, if you do steel marketing on Google, you know that this is this is the hard to to to do in these creative creative tests and creative strategies.

but you really need to be able to make swift decisions if you want to make results like that, uh, a reality. So in this case, we had multiple different creative ideas and we had two different audiences: one for the fitness and outdoor and one for like kind of

games and Pokemon. And with the data that we had in our hands in real time, we're able to adjust like the spend between these ad sets and the different marketing creatives in real time on a day-to-day basis. On top of that, we all know this as

well, so when you have a certain messaging that actually then kind of works for a specific audience, so you want to iterate on that and that's also what we're then able to do because we had the real-time data. So within like 10 days, we were able to make multiple

iterations on the ad, which led to the growth that you saw earlier. On top of that, as we've moved away from the user-level frameworks that we've had, we've now been able to utilize web-based attribution methods as well. So what this leaves us, uh, we were

able to communicate in real time with Meta now in this case and whenever like a user installed a specific, uh, well, came from a specific creative, we were able to give post-backs back to that creative and say like, yeah, spend a bit more money on this particular

one. So yeah, what did Talofa have to do in this case to to make this this a reality? So first we have our SDK that you implement in your game. I I quoted myself that I can install it in five minutes. So if I can

do it. I bet everyone of you can as well. So that's what they did in the in the beginning. They integrated the SDK into their game. After that, we essentially generate different tracking links for each creative. Uh, we have to change the campaign setup a bit to kind of fit into

this this uh schema and the tracking links that we have in our hands and then it's it's the continuous optimization but with that we were able to bring the results that you guys just saw. This is a reality. This is something that we now now have available today. Uh

again not any more theory and and things on paper that I would be able to share here but actually things that we can we can we can deliver to any one of you uh very much today. Uh we have real-time dashboards on iOS uh you can see

anything and everything that's happening on a creative level. Um, we have our booth in in G2 right there. Please drop by. We can show you the dashboard. We can discuss how we can make this a this a possibility for you guys as well. Um

we're very very eager to actually have a chat and share what we've been building for the last two years because yeah we truly think that the future is privacy friendly uh a future where we can make again like great marketing and and make the decisions where on the level in which we

need to make them on a creative level. So we yeah we think the future is privacy friendly and we truly believe that the future itself is Audience Lab that we built. Thank you very much. Oh, I like your bird at the end. Excellent. Uh, so anyone got any

questions any question I'm so for me I think this is really fascinating particularly because uh the thing I think you're nailing is the fact that we have to be content you know we have to be focusing on essentially brand skills which I would argue you know being the

original advantages for Unity as we back in the day we we didn't do we were so focused on on Direct response we're so focused on the the use of data to convert somebody the actual building of a of a of a narrative of a of a a kind

of engaging component in the ad was secondary I would argue is that fair or or do you see this as an opportunity to essentially develop Brands further or do you see it as just another evolution of what we did already yeah 100% I mean like now when we've built the entire

fundamentals alarms use level data and now then like those device identifiers were taken away so if you wanted to build a a a massive brand so well the next speaker knows a bit more about that but uh like uh you were forced to now like either spend massive amounts of money in

scale to to understand the effect and still kind of show it in the dark to understand the actual impact of of your decisions into into how that affects your brand and how you can build up the brand with this now you can actually get that in real time and and and do that

with smaller scale and start to build up the brand even even the very first day that you you you make your first ads completely get it uh last chance for a question if any wants oh we got one there I'll just grab the mic hi thank you for your speech uh just

one question like uh what's the volume of installs required to do that kind of analytics yeah that's the cool thing as well everything is in in real time and we're attributing everything on a creative level so essentially you can do this with with 10 people as much as you

can do it with 10,000 great well thank you very much I can say um amazing stuff and I think the uh the changing of the idfa is she had a profound oh sorry yeah sorry oh we did you have one more question uh no no no I

was I was just trying to catch up with time so okay awesome yeah because I I think I have two minutes left you do you do and I I thought that uh this is a this is a joke that we did in 24 hours and uh okay able to put this in the in

the video as well so one could say now that we're finally out with this thing that we've been building for 2 years so one could say that we're taking the cat out of the bag so uh if if we can so I'd like to share a

video so yes the cat is out of the bag thank you very much [Music] n [Music]

Session: Mastering Game Marketing in the era of Data Privacy - Jesse Lempiäinen, Geeklab.

PocketGamerbiz

데이터 프라이버시 시대의 게임 마케팅 소개

발표자는 데이터 프라이버시, 특히 미성년자 데이터에 대한 관심을 표명합니다.

데이터 프라이버시를 고려한 게임 마케팅을 마스터하는 방법에 대해 Geeklab의 Jesse를 소개합니다.

게임 마케팅에서 포괄적인 사용자 여정 추적을 위해 디바이스 식별자에 의존했던 과거에 대한 논의가 시작됩니다.

디바이스 식별자를 통해 여러 게임에서 사용자 여정을 추적하고 광고 투자 수익률(ROAS)을 계산하는 방법을 보여주는 예시입니다.

Apple의 앱 추적 투명성(ATT) 프레임워크의 영향

Apple이 ATT 프레임워크를 통해 IDFA를 제거하면서 사용자 여정 추적 및 ROAS 계산에 상당한 문제가 발생했습니다.

5년 후 상황은 더욱 악화되어 여러 광고 네트워크의 솔루션으로 인해 파편화가 발생하고 있습니다.

iOS용 Google 광고주 ID 및 모델링 사용 시 발생하는 문제점이 강조되어 있습니다.

연사는 데이터 프라이버시 시대에 게임 마케팅의 과제를 해결하는 것을 목표로 하는 자신의 회사인 Geeklab을 소개합니다.

사용자 수준에서 크리에이티브 수준 솔루션으로 초점 전환

분석 결과, 게임 마케팅에서 사용자 수준의 데이터 수집과 크리에이티브 수준의 의사 결정 사이에 불일치가 있는 것으로 나타났습니다.

가까운 시일 내에 사용자 수준 데이터 포인트로 돌아갈 가능성에 대해 논의합니다.

데이터 개인정보 보호 규정과 사용자 인식의 궤적을 분석한 결과, 사용자 수준의 솔루션은 더 이상 실행 가능하지 않다는 결론에 도달했습니다.

제안된 솔루션은 사용자 수준의 데이터에 의존하지 않고 어트리뷰션 및 분석을 위한 크리에이티브 수준의 프레임워크입니다.

크리에이티브 레벨 프레임워크의 적용 사례를 보여주는 탈로파 게임즈의 사례 연구를 소개합니다.

건강 및 피트니스 애호가와 아이템 수집을 즐기는 사람들을 대상으로 하는 탈로파 게임즈와 게임에 대한 설명입니다.

탈로파 게임즈는 어떤 타겟이 가장 효과적인지 파악하고 마케팅 전략을 맞춤화하는 데 어려움을 겪었습니다.

일일 신규 사용자가 개선되고 설치당 비용(CPI)이 감소한 결과가 표시됩니다.

사용자 품질 분석 결과, 비용을 절감하면서도 동일한 품질을 유지한 것으로 나타났습니다.

실시간 데이터에 기반한 신속한 의사 결정으로 광고 지출 및 크리에이티브 전략을 조정할 수 있었습니다.

성공적인 메시징에 대한 반복과 웹 기반 어트리뷰션 방법의 사용이 강조됩니다.

SDK 통합 및 캠페인 설정 변경을 포함하여 Talofa Games가 솔루션을 구현하기 위해 취한 단계에 대한 설명입니다.

실시간 대시보드에 대해 언급하고 부스 방문을 초대합니다.

데이터 개인정보 보호 변화의 맥락에서 브랜드 구축에 집중하는 것이 얼마나 중요한지에 대한 질문에 대한 답변입니다.

분석에 필요한 설치 수에 대한 질문에 대한 답변으로 크리에이티브 수준에서의 실시간 어트리뷰션에 대해 강조합니다.

마무리 발언과 솔루션을 소개하는 동영상이 언급됩니다.