← The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
Mintegral's Phoena Pang on the new playbook for performance marketing
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- [00:00]
Progressive Insurance Announcer
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Greg Hillstrom
law Parle tu francais hablas espanol par
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Greg Hillstrom
hi, I'm Greg Hillstrom, host of the Agile Brand, and here's a question for you. Is the relentless pursuit of measurable roas fundamentally at odds with building long term customer trust in a privacy first world? Agility requires marketers to move beyond legacy attribution models and embrace a more dynamic approach to measurement and monetization. This is especially true in the rapidly evolving mobile ecosystem, where the rules of
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Podcast Host/Interviewer
engagement are constantly being rewritten.
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Greg Hillstrom
Today we're going to talk about the new playbook for performance marketing in the mobile app ecosystem.
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Podcast Host/Interviewer
We're going to explore how to drive
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Greg Hillstrom
growth and measure return on ad spend
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Podcast Host/Interviewer
in an environment defined by signal loss.
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Greg Hillstrom
Look at the innovative ad formats that are capturing user attention, and discuss the role of AI in balancing automation with creative effectiveness.
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Fina Pang
This
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Greg Hillstrom
welcome to Season eight of the Agile Brand Podcast. This season we're going all in on Expert Mode, MarTech, AI and Customer Experience, talking with the people and platforms behind the brands you know and love. Again, I'm your host Greg Kilstrom and I help Fortune 1000 companies make sense of martech, AI and marketing ops. Hit subscribe or follow to make sure you always get the latest episodes and leave us a rating so others can find us as well. And make sure you check out our sponsor, TechSystems, an industry leader in full stack technology Services Talent Services and real world adoption. For more information, go to techsystems.com now let's dive in. To help me discuss this topic, I'd like to welcome Fina Pang, Vice President of Sales and Global partnerships at mintagril. Fina, welcome to the show.
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Fina Pang
Hi Greg. I'm happy to be on this show with you guys.
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Podcast Host/Interviewer
Yeah, looking forward to talking about this. Before we dive in though, why don't you give a little background on yourself and your role at mintagrol.
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Fina Pang
Sounds good. So hello, I'm Fina. So as you know, graduates introduced me. I'm VP of Global sales and partnership. So I'm managing the global sales team and also the partnership relationship for Minty Girl. And if you don't know Minty Grow, we are like a performance platform, especially in mobile. So we work with more than 100,000 app developers helping them to one, monetize their inventory and second to help them to do very effective user acquisition.
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Greg Hillstrom
Great.
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Podcast Host/Interviewer
Well, yeah, let's dive in here and we're going to talk about a few things. But I want to start with one of the things that I highlighted in the intro and it's really this idea of redefining performance in a privacy centric era. So, you know, with the decline of deterministic attribution, a lot of marketers are leaning on probabilistic models, media mix modeling. You know, from your perspective, what's the
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Greg Hillstrom
most significant mindset shift that leaders need
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Podcast Host/Interviewer
to make when evaluating campaign performance and roas today?
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Fina Pang
Yeah, so I'll say that it would come down to two things. You know, like honestly speaking, I got this question a lot and also the first thing I would tell them is the acceptance of, of the new reality. So I think that a lot of like marketing leaders, they need to get comfortable with the confidence intervals rather than the absolute in like absolute numbers they're getting from their end. So because evaluating the US today you need to require looking at like aggregated trends and also, you know, the like we also like, you know, mentioned. Mmm. To understand, you know, how the different channels influence each other because you cannot trace every individual user. And also the second also I come a lot to this discussion is about the long term incrementality. So instead of reacting to the data fluctuation in very subtle data. So a lot of sophisticated marketing team, so they're looking at the incrementality testing. So sometimes people will do, for example, if I turn this band off, turn this channel off, so would the revenue actually disappear or decrease or for how many percent? I think for those can also go into the analysis. So there are in summary, so there are different things you need to all going to look at when you're looking at the new reality for the performance.
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Greg Hillstrom
Yeah.
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Podcast Host/Interviewer
And beyond modeling, you've noted the importance of creative in boosting performance. Certainly that's an important aspect. How are the most sophisticated apps marketers using creative testing and optimization as a primary lever to drive results when user level data is potentially less available?
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Fina Pang
Yeah. So as a user level data they become like less available. So the algorithm so usually like the machine learning the black box. So they will have less information to find the perfect user for you. So in response to that, so creative has a more important role. So they're not like, you know, as rep of the campaign, but they should be like the primary targeting. So a lot of sophisticated app marketers from what we work with, so they are using a lot of the creative test in the three different specific ways. So I'll say like the first one which also the most common we see is the credit line signal generation. Because when you cannot target by specific interest so your credit will do the filtering. So the marketers usually they're running like broad campaigns. So where the visual hook define audience. But if a creative feature say they're more targeting at the hardcore game strategy. So the algorithm. So we also learn for example what type of user they're engaging with these creatives. So then to drive the users that fit to their game and because of the creative they're generating. And also I would say the second big piece is on the concept testing. So basically rather than testing say oh, what button color I'm using or where I'm going to put this button, that button. So it's about the macro concept. So you're looking about different emotional hook. So for example, you want people to feel, you want people to do the stress relief, you want people to feel competitive. So you have those type of elements like the big rock testing or recall as a hook to test on different like on different concept and to attract the users and to see how they perform. And the third big piece which is also really big on our platform is to diversify the app format as the performance testing is not only on video. So we also put a lot of focus on the playable because the playable actually they actually provide a very high intense signals. So rather than you know, the user like they just watch that. So whether they, you know, finish the mini game or whether they replay the mini game like a couple of times. So this all provide like a really good signal to indicate Whether the user had like a, you know, like a long ltv. So for them.
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Podcast Host/Interviewer
Yeah, well, and I mean to that point, you know, it does seem like there's a renewed focus on things like you just mentioned, you know, in app advertising or playable ads, rewarded video, you know, what's driving kind of this either resurgence or just kind of these diverse methods working. And how do these formats change the value exchange between user, publisher and advertiser?
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Fina Pang
Yeah, well, I would say in general when I see, I wouldn't even call it's a resurgence because I think from what I see the rewarded video has always been like a rising trend similar to playable. So playable right now it's kind of become a norm for people to use. And the reason for that is because there's like a shift toward ROI centric advertising and also the rise of the open Internet because user acquisition on the traditional social platform. So usually you just have one static format versus for the reality video or the playable. You're actually creating the value exchange for the user for the players. So they are more likely to engage with the ad because the reward that you are providing to them. And also similarly for the publisher because the rewarded ad and also the playable you actually giving more things to the users. And the users feel like so they are being considered rather than just oh, I just been, you know, thrown to an ad. And you know, actually a lot of users that will engage with the playable like in the publisher app. So for the publisher they also see higher retention. So it's kind of like a win win for them. And also similar for the advertiser. Right. So rather than just you know, showing like a, you know, ad asking for click. So you actually getting them a lot like high intent lead. So the advertiser they actually pay for the user who have experienced the app before the app, before the user, you know, come into the game.
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Greg Hillstrom
Yeah, yeah.
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Podcast Host/Interviewer
And your role gives you a global view on this as well. You know, are you seeing any regional differences, you know, do different, you know, users in different regions respond to different types of these ad formats. And you know, what can brands learn when planning their strategies, particularly global strategies.
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Fina Pang
Yeah, totally. So I would say from across other regions I'm working with is very different. So I will start with APAC because in many APAC markets digital first, so particularly in the Southeast Asia and also greater China. So users they are more receptive to those high frequency rewarded format because the reward economy also very deeply integrated into their daily life. So you probably use app in China. You open the app, there are so many button to collect the daily reward. You will never see that in US or Europe. And because of that all the API customers they're also being educated that way. So there is a very high engagement rate with all this reward based app. And also there's also very resilient if you put say 30 ads like for them a day they wouldn't term. It's because of the nature of the user. And these are very different in North America because in North America so the US and Canadian users so they will prioritize more like you know, the brand familiarity and also the convenience rather than you know like showing them a lot of like a lot like showing them a lot of ads. So usually so in US that's why like we would add like more competitive because like you know for from the publisher perspective they don't want to expose the users to too many rewarded ads. So but then for every word ads you show to the user so the US user they will tend to finish it. So we see very high competition rate. But then also because of that there is also like very low patience for there's like you know like long loading playable ad because they're not like less resilient to the you know, to those like rewarded format but like people still going to like finish for that. And also for North American user we see them convert really well for the free trials. So that's also like a little bit different from I would say like other regions and also in Europe. So in Europe it's also like very different because in Europe we see especially for some users like we see they're surpassing us in like I would say like the median LTV in some category. So the users are like more selective. So they have like a very strong preference for quality over the quantity. So usually like you know when we put the ads in front of the European user so we want to make sure so they're like very high production quality otherwise we'll cause like a higher turn rate. And also it's different from us because you know we just say US user they prefer to convert on free trial and actually in Europe so European user they're more willing to pay for premium ad free experience once they're hooked. So what we see like a very interesting trend that in Europe. So if you just I set up like a 0.99 to remove the ad, it's usually converted really well in Europe comparing to other countries.
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Podcast Host/Interviewer
Yeah, yeah, yeah. It's yeah it's fascinating to see the, those differences.
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Greg Hillstrom
Let's talk a little bit.
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Podcast Host/Interviewer
I know you touched a little bit on AI when you know towards the beginning, but I want to talk a little bit more about that in two ways. But I want to start from the user acquisition part of this and I know a lot of people, many are already using different AI tools to help in user acquisition, but sometimes it can feel like a black box. If it works, great, but you don't necessarily always know why. Can you maybe talk through what are some of the most impactful practical applications of AI that you're seeing that are helping, you know, helping brands identify and target those high LTV users that you've mentioned?
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Fina Pang
Yeah, totally. Yes, of course. In our especially in the open Internet, like our machine learning engine, every time that we tell people is like how you Identify have a user is that. Oh yeah, because it's our machine learning algorithm our AI works So how to demystify the AI. So in the UI world. So I would say it's less about guessing but it's more about recognizing right pattern. So when I say I recognize the right pattern is basically we train to identify what's a high value user high LTV user for you. And there are different perspective. So I would say the most important how we utilize AI in our app machine learning engine is about the value based bidding. So now that we actually doing everything is automatically bidding. It's not like the old word of running a CPI campaign. So we are trying to identify the users based on all the postback data event. So when the user when they behave so for example they make a purchase or they interact with the ad all of those signals. So the machine learning engine they will collect and then we will learn. So what are the how the valuable users are going to perform and then we're going to predict the users who kind of similar to those I would say like the whale behavior and try to find those users for you. So that is like the value based bidding and how is how we use AI. And also another thing so which we also talk about is about like the prediction. So the prediction is like how you predict based on. So because you want to predict for the long term value. So every you know, if you learn if you heard about like you know the Data28 model from all this the big ITECH company. So basically you're trying to predict the lifetime value using the first few hours signals. So as I said all this for example the tutorial, how the user finished the tutorial, how the user finish say the game level or how many sessions they play. So all of those data can be used to analyze like how valuable the user is. So those prediction for the user ltv. So those are another I would say like a big thing that we use in the AI machine learning. Basically there's a lot of things the black box but those are I would say the two main things that we look at.
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Podcast Host/Interviewer
Yeah, well of course the other component that we touched a little bit on regarding AI is the creative aspect. So creative automation at scale. Where do you see the ideal balance between human led creative strategy and machine driven iteration?
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Fina Pang
Yeah, I think there's also a common question because a lot of team that when they came to us they're worried about their query team is going to be gone because it's going to all replace my AI which I don't think so, because I think there's still ideal balance, you know, in between like the human and AI flow. So from what I, from what I see or from what I see, like the best practice is that human should define the soul. So which is the emotional hook and also how you're gonna like set your brand strategy, like what's your brand like, you know, what's your story? All of those things, it should be defined by human. But then the AI should be handling the scale so you can generate thousands of the variations. And also all the, like, you know, the iteration, all the A, B testing, all of those you can set up based on AI or you set up like in like automation and all this automation they can enhance based on the result automatically. So all of this testing can be done by AI, but then the human will still come in to defend the core.
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Greg Hillstrom
Yeah, yeah.
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Podcast Host/Interviewer
So to make best use of all of the, you know, kind of everything that we've talked about, I guess, you know, for marketing leaders out there that want to maximize really across the board, what's a capability that they really need to be investing in to make sure that their mobile strategy is not only effective today, but really positioned for growth in the coming years.
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Fina Pang
Yeah, totally. So I would say like the most critical investment is probably going to be like open Internet diversification. So I'm saying this, you know, also coming back, you know, coming from like a Google background. So I used to work in the walled garden, but then I work in the open Internet and I see the importance of, you know, basically like enriching users in different perspective. So you want to be able to diversify your budget to bridge the gap between the walled garden and the open Internet and especially like in 2026. So we also see a lot of report the user attention, they have been like highly fragmented across a lot of high engagement open Internet sectors. For example, people use more show drama, people use a lot of AI driven apps or other utility apps. So those are already the play games. Right. So those are not like wall garden. So and also to capture those and the leaders, they also need to invest in more smart bidding in like a smart bidding, like a strategy. So how are you going to be looking at the data? How are you going to be set up your database bidding strategy? So outside the wall garden, because people are more used to like, oh, you know, doing user acquisition in Google matter, but then outside the Google matter, like outside the wall garden in the open Internet, you need to like set up like a new strategy of, you know, like how to, you like how you measure like the user value and also you know, in general like how you're going to be measured the total like the channel efficiency.
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Podcast Host/Interviewer
Yeah, yeah, yeah. Well Fina, thanks so much for joining today. I've got two, two last questions as we wrap up here. The first one, if we were having this interview one year from today, what is one thing that we would definitely be talking about?
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Fina Pang
Yeah, I think there's also, there's like something, you know, our company we're working on a lot I think we'll be talking about like maybe in one is about the agent flow. So we want to be shifting the company rather than just having AI as a tool but also having a, as a operator. So for them in the context of our company. So I want to be able to transform say from our AM to do all the campaign management but then having the AI agent to really manage the campaign. But they manage a campaign from end to end, not like in the single task but do more like in the like as I said like agentic flow. I think that going to be like the future of ITech and hopefully you know, we can talk about more in one year that will be having more mature product.
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Podcast Host/Interviewer
Yeah, love it. Yeah, we'd love to have you back on. We can chat about it.
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Greg Hillstrom
That's great.
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Fina Pang
Yeah.
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Podcast Host/Interviewer
And last question for you. What do you do to stay agile in your role and how do you find a way to do it? Because consistently.
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Fina Pang
Yeah, I think for me it just also like I know two things. I was like one is I to stay open but then the second thing is also like very relative to the first thing is to get as many feedback as possible because especially in my role like I work with all functions. He's like, I work with product, I work with marketing, like sales account manager, you know, from different regions and everyone that will have their own voice, you know, based on, you know, their like interaction with the clients and also meeting with the clients and hearing their feedback about our product. So usually when I get those feedback how can I leveraging all the data signals I get into my feedback loop to make my thinking better. And also again I don't have just one sad thing. I need to follow this rule 100%. Things changing so fast these days. So keep hearing you know, what's coming in, you know, have like a very like open like curiosity mindset is very helpful for me to stay agile. Yeah, love it, love it.
- [24:58]
Podcast Host/Interviewer
Well again I'd like to thank Fina Pang, vice president of sales and global partnerships at Mintagril for joining the show. You can learn more about FINA and
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Greg Hillstrom
mintagirl by following the links in the show notes. This episode is brought to you by Tech Systems. They're leaders in full stack, tech services, talent solutions and helping companies put it all in action. You can learn more@techsystems.com that's teksystems.com and thanks again for listening to the Agile Brand podcast. If you like the episode hit subscribe and drop a rating so others can find the show too. And if you're interested in consulting, advisory work, or if you need a speaker for your next event, feel free to reach out. Just visit Greg kilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.
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Fina Pang
The Agile Brand.
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Progressive Insurance Announcer
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Fina Pang
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Progressive Insurance Announcer
business credit.