Marketing Your App More Efficiently with Apple Search Ads — Dilip Reddy, Search Ads Optimization

Summary

Podcast Summary: Marketing Your App More Efficiently with Apple Search Ads

Podcast Information:

• Title: Sub Club by RevenueCat
• Host/Authors: David Barnard, Jacob Eiting
• Episode: Marketing Your App More Efficiently with Apple Search Ads — Dilip Reddy, Search Ads Optimization
• Release Date: September 4, 2024

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Introduction to Dilip Reddy and His Journey into Apple Search Ads Timestamp: 00:01 – 02:46

David Barnard welcomes Dilip Reddy, a data engineer turned marketer, to discuss the intricacies of Apple Search Ads. Dilip shares his transition from a computer science background at Bank of America to working with unicorn app companies around 2016. His fascination with data architecture led him to explore Apple Search Ads due to the platform’s granular data insights. Dilip mentions, “Apple Search Ads gives us control over every aspect at a granular level” (05:23).

High Bids and Cost Per Acquisition (CPA) in Apple Search Ads Timestamp: 02:46 – 05:58

Dilip discusses the phenomenon of high bids and CPA in competitive categories like finance and health & fitness. He contrasts Apple Search Ads with platforms like Meta, highlighting that Apple’s intent-based model allows for experimentation despite high CPA. Dilip states, “We cannot stop just because it’s high CPA because they’re high intent” (03:01). He emphasizes the advantage of controlling bids to optimize CPA, noting, “We are in control of everything” (05:23).

Trends in Apple Search Ads for 2024 Timestamp: 06:17 – 10:53

The conversation shifts to 2024 trends, where Dilip observes a move towards expanding campaigns to more countries, leveraging localization strategies. He advises testing new geographies introduced by Apple, such as Brazil and six other Latin countries, to uncover surprising results. Dilip points out, “You can expand to pretty much every country in the world” (07:32). He also notes an overall increase in CPAs, attributing it to competitive bidding and the influx of new apps fueled by AI advancements.

Brand Defense: Necessity or Extortion? Timestamp: 11:50 – 19:46

David brings up the contentious topic of brand defense in App Store Search Ads. Dilip acknowledges its complexity, suggesting that brand defense can be profitable for apps vulnerable to direct competition. He explains, “If your app is easily replaced with a competitor app, you have to run brand” (12:14). Dilip advises experimenting with lower bids on brand keywords to reduce costs while maintaining significant impression share. He emphasizes monitoring impression share through Apple’s provided metrics to ensure optimal budget allocation.

Understanding CPA Variations and Keyword Strategies Timestamp: 19:46 – 30:04

Dilip delves into strategies for managing high and low CPAs across different keyword types. He advocates for classifying keywords based on intent, bidding higher on high-intent keywords like “yoga” and lower on related but lower-intent terms like “pilates.” Dilip explains, “We can expand keywords a lot and think of it as very dynamic” (23:25). He highlights the importance of using both exact and broad match keywords to capture a wide range of relevant searches while maintaining control over CPA.

Managing Seasonality and Its Impact on Campaigns Timestamp: 30:27 – 35:01

The discussion turns to seasonality, with Dilip noting that competitive periods like Thanksgiving can significantly raise CPAs across all categories. He recommends anticipating these trends by aligning campaign strategies with historical data and organic traffic patterns. Dilip advises, “We should not make any assumptions, we can see the data and act accordingly” (34:37). This data-driven approach ensures that campaigns remain responsive to fluctuating market conditions.

Measuring and Optimizing ROI in App Store Search Ads Timestamp: 35:01 – 43:52

David and Dilip explore the complexities of measuring Return on Ad Spend (ROAS) and Return on Investment (ROI) in the app ecosystem. Dilip explains that traditional ROAS metrics may not directly apply to subscription-based apps due to recurring revenue streams. He emphasizes the importance of considering long-term metrics like Lifetime Value (LTV) and time to break even. Dilip states, “ROAS should not be the primary metric. It should be a combination of revenue and ROAS” (43:52). He underscores the significance of cohort analysis and retention rates in evaluating campaign success.

The Hypothetical Impact of Apple Search Ads on App Store Optimization (ASO) Timestamp: 44:27 – 47:48

Addressing the debated topic of ASA’s impact on ASO, Dilip presents a “conspiracy theory” rather than a confirmed hypothesis. He suggests that increased download volumes from ASA campaigns may correlate with improved organic rankings, although this remains speculative. Dilip cautions against allocating significant budget solely for this potential effect, advising listeners to focus on tangible performance improvements instead.

Scalability of Apple Search Ads Timestamp: 48:14 – 55:52

Dilip discusses the scalability challenges of Apple Search Ads, contrasting them with other platforms like Meta. He advises that scaling should focus on adding more relevant keywords and expanding to additional geographies rather than creating numerous campaigns for a single country. Dilip remarks, “The best way to scale is to add more keywords” (50:52). He also highlights the unique advantage of Apple Search Ads in avoiding ad fatigue, as ads are dynamically served based on user intent rather than repetitive creative exposure.

Leveraging Custom Product Pages for Enhanced Performance Timestamp: 55:52 – 58:14

The hosts explore the benefits of using custom product pages tailored to specific keywords. Dilip explains that creating keyword-specific product pages allows for better alignment with user searches, enhancing conversion rates. He provides examples of seasonal campaigns, such as creating a dedicated product page for Thanksgiving deals. Dilip emphasizes the utility of A/B testing through separate product pages to optimize performance and ROAS.

Final Insights and Recommendations Timestamp: 58:14 – End

In closing, Dilip offers actionable advice for new app developers:

• Use ASA for Customer Discovery: “Use Apple Search Ads as kind of customer discovery thing” (58:24).
• Start Small and Scale Gradually: Begin with minimal budgets to test high-intent keywords before scaling.
• Monitor and Adapt: Continuously track campaign performance and adjust strategies based on data insights.
• Focus on Retention: Ensure that in-app experiences are optimized to retain users acquired through ASA campaigns.

Dilip also promotes his platform, Search Ads Optimization, as a tool designed to help scale Apple Search Ads profitably.

Key Takeaways:

• Granular Control and Data Insights: Apple Search Ads provide detailed data, allowing marketers to fine-tune campaigns effectively.
• Strategic Keyword Management: Balancing high and low intent keywords, and leveraging exact and broad matches, is crucial for optimizing CPA and ROAS.
• Adaptability to Trends and Seasonality: Staying responsive to market trends and seasonal fluctuations ensures sustained campaign effectiveness.
• Long-Term ROI Focus: Emphasizing metrics beyond immediate ROAS, such as LTV and retention, aligns marketing efforts with sustainable growth.
• Scalability through Expansion: Adding relevant keywords and exploring new geographies are key strategies for scaling Apple Search Ads campaigns.

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Notable Quotes:

• Dilip Reddy: “Apple Search Ads gives us control over every aspect at a granular level.” (05:23)
• Dilip Reddy: “We cannot stop just because it’s high CPA because they’re high intent.” (03:01)
• Dilip Reddy: “You can expand to pretty much every country in the world.” (07:32)
• Dilip Reddy: “Use Apple Search Ads as kind of customer discovery thing.” (58:24)

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This episode provides a comprehensive exploration of the nuanced strategies involved in leveraging Apple Search Ads for app marketing. Dilip Reddy’s insights offer valuable guidance for marketers aiming to optimize their campaigns, manage costs, and achieve sustainable growth in the competitive App Store landscape.

Transcript

[A]

Welcome to the Sub Club Podcast, a show dedicated to the best practices for building and growing app businesses. We sit down with the entrepreneurs, investors and builders behind the most successful apps in the world to learn from their successes and failures. Sub Club is brought to you by RevenueCat. Thousands of the world's best apps trust RevenueCat to power in app purchases, manage customers, and grow revenue across iOS and Android and the web. You can learn [e-mail] let's get into the show. Hello, I'm your host, David Barnard, and my guest today is Dilip Reddy, a data engineer turned marketer working on an Apple search ads platform called Search Ads Optimization. On the podcast, I talk with Dilip about the impact of Apple search ads on organic search, how to save money on brand defense, and why roas shouldn't be the only thing you optimize for. Hey Dilip, thanks so much for joining me on the podcast today.

[B]

Yeah, I'm excited to be here talking about Apple search ads.

[A]

Yeah, I've been meaning to do an episode on Apple search ads for a long time. And you know, there's so many different frames of reference to talk about it. And so there's a few people I've talked to that I probably will still have on, but a little more like kind of like growth hacky, more kind of marketer focused. But one of the things I'm excited to talk to you about search ads is that you're a data guy and you kind of like stumbled into marketing as a data guy. So let's just kick it off with that story. Like how did you get into Apple search ads as a data scientist?

[B]

The reason is I did computer science and like always data is my go to. Like this what fascinates me. And I started bank of America. There's no like app thing at all. But over time, like I joined like unicorn app companies like in 2016 and that's when the Apple citrus came in. It's because I'm a data architect as well. So I manage all data sources and design architectures. I noticed Apple Switchers is different in a way that it gives like so many data points, so much of data, that extreme granular, including high intent keywords, how the users are reacting and it just was great. And also I created my own hobby apps. They don't solve any real problem. But I started tinkering with applesearch ads and in a weird way that's kind of my on and off. I've been like developing algorithms and all this stuff and that's how I ended up and. Yeah, yeah.

[A]

And then you told me at one point that one of the things that really fascinated you about Apple search ads was that you were digging through the data one time and saw some like really high bids or some high cost per acquisition. Yeah. So tell me about that.

[B]

Yeah, I mean there are some categories right like finance, health and fitness. The bids are like can be like go crazy for some market some keywords but they also bring in high revenue. That's what is interesting because if you look at in a spray and pray networks like meta everything is usually like constant. You expect this and like the same revenue performance because this not intent based, it's just shooting creative across millions and hoping some will fall for it. But Apple Switch has the, even the CPS is high. I find it like, you know there's something we can tinker with and like experiment with because we cannot stop just because it's high CPA because they're the high intent. And in a way it's a limited inventory demand and supply. So it depends on the app, it depends on what keywords we're targeting and what kind of users we're looking for. And especially for very high competitive like finance is one thing. Health and fitness. Yeah we may see bids go really high up and CPA can go high in usa. USA is one of the most expensive storefront.

[A]

And that's the interesting thing about search ads. I mean it's why Google is a, what, trillion, plus dollar company. It's that when people go search for a specific term they're very clearly demonstrating intent. And you know I don't remember all the different categories but there's things like you know, searching for divorce lawyer on Google whereas like the bids are just seem insane but if you're searching divorce lawyer, you know some something's going on in your life and it's a lot of you know the lawyers make a lot of money on divorce settlements and so it's like they can bid really high. And I think there's kind of similar market dynamics at play in the app store where for things like finance and health and fitness where there's high intent, there's high willingness to pay, it makes sense in kind of a competitive bid environment that some of the keywords will get bid up. And it's kind of cool that like what part of what got you into Apple search ads was seeing those high bids and be like wait a minute, this data must be wrong. But no, it's like actually the data was correct. It's just that you can have a return on ad spend with like a 50 CPA if it's the right keyword and the right app and the right monetization. So that's really interesting.

[B]

Yeah. And yeah, the good thing about it is we can control each and every aspect at granular level. I mean you can also like stop some keywords like bid really low. So either forcing Apple to stop giving us impressions or give more installs for the same. Not more installs but similar installs with the lesser cpa. That's the best part. We are in control of everything. It's not like meta. Right. Like we don't know why the CP is going high and I can't do anything about it.

[A]

Yeah, a lot of granular control and a lot of data to. To understand what's going on.

[B]

Yeah, it is a double edged sword. It can get overwhelming especially if a company is running, you know, all 60 countries and 70 countries like thousands of keywords for each country. I mean we have some solutions for that and there's some kind of campus structure you can set up to make it the mental overload much better.

[A]

I wanted to kind of kick things off talking about trends for 2024. I mean things are always changing. You know Apple introduced the brand or not I guess not brand but like the inventory on search and they've kind of been expanding inventory over the last few years. Anything especially interesting in 2024 that they that is changing in app store search ads that folks should be paying attention.

[B]

To A lot of apps now Usually it used to be like we just run into tier one like you know, us, UK like Germany, France and forget the rest of the world. But now I'm noticing the trend of adding as many as countries as possible because if you think about it there's only like five, six localizations that you have to like. For example, if there's a Spanish you can maybe have an entire Latin America. Not entire, but most of the Latin America with the same kind of keywords. Same with Portuguese, German, France. The way is like we identify the keyword builder building for these localizations but you can expand to pretty much every country in the world and for extreme local language that we cannot support or Apple defaults to English anyway so expanding to more countries is what I'm noticing. And.

[A]

And Apple introduced new geographies this year, right?

[B]

Yeah, yeah, Brazil and I think six other Latin countries. So yeah, this is the best way and people are seeing some surprising results. So my advice is test these countries because we can't just assume oh because this country is this, we should not run it there especially. The effort is pretty much same. It takes maybe a few minutes to just copy and paste the campaigns.

[A]

Right, but you don't want to just copy and paste the campaigns. Right. You want to copy and paste and then spend a little time kind of honing it in for that market. And then, you know, check your CPAs and your return on ad spend and stuff like that.

[B]

Yeah. Whenever there's a new storefront, my go to is start with bids, like too stupidly low. That will never get impressions. But that's fine. We can always increase it. If you start bids high for a new country, we don't know what is the base. I can start with $10. Apple happily give me $10 bids, but maybe I can get the same number of installs or 90% of installs if I bid half. Right. So. And also the trend is, I'm noticing, is the CP is going a bit higher. And I'm assuming it's also across all ad channels, because I don't deal with other ad channels. But the data suggests CPs are going a bit high year by year. So we are dealing with that.

[A]

Yeah, it kind of makes sense because as apps get more sophisticated about monetization and really get their monetization dialed in, then they can spend more. And so the market dynamics is like, as consumers get more comfortable spending, as inflation causes higher prices to make more sense. You know, as apps work on their funnels and paywalls and all the things like we talk about on the podcast, it's like we're kind of creating the problem. Like as more apps get more sophisticated, then they can bid higher because they're going to still get a return on ad spend even with that higher CPAs. It kind of makes sense that there's just like kind of rising CPAs, especially with the most high intent search ads.

[B]

Yeah. I think there is also a trend of, I call these apps Hyperscalers. It's like Temu, right? Like they bid on 100,000 keywords for some reason. But the reason is maybe, I don't know why, but they must have like billions of marketing. Right. So unfortunately, it will raise up. It's like a wave lifting up all the boards kind of thing. Right. So because TEMU is waiting for each and every possible English character, I mean, this letter and word Hindi dictionary, it may mean that, you know, the CPA may be going high. I'm not saying this is the reason exactly, but this is a trend I'm noticing as well.

[A]

Yeah, it probably contributes to it for sure.

[B]

Yeah. And there's a new search inventory came in that didn't exist before. ChatGPT is the AI everything AI, yoga AI. Right. Like pretty much there's like entire new generation of search terms come in. So the inventory went up as well. So it's not like all like high CPA for the same inventory, but also the apps like skyrocketed number of apps released. Ironically, AI is making easier to create many apps at scale as well. So yeah, this is the trends so far.

[A]

Yeah, yeah, that's really interesting. And the explosion of apps thing is interesting. I mean it does seem like AI has kind of accelerated. That is that, you know, like you said, for every, for every major category you might want to bid on, there's probably somebody who is either built like a more really sophisticated app or rebranded an existing app to say it's the AI version of it. And then people are looking for more apps because they're thinking, well, hey, I've been using this productivity to do list. Is there a better AI version of a to do list that's going to make me more productive? And then they go back in search, whereas maybe they weren't searching some of those terms before because they kind of had their, their, the app that they used.

[B]

It would be interesting to see the iOS new version with the built in AI, how it's going to impact a lot of apps. Yeah, let's see how it goes with the AI.

[A]

So one of the hotter topics I want to get your take on is brand defense. So you know, you have some people say never do brand defense. You're just like, it's extortion from Apple and Google to force you to do brand defense on SEO and aso. But what are your thoughts? Like can it work? Can it be profitable? How should you structure it if you do do it? Like how do you think about brand defense on App Store search ads?

[B]

Yeah, obviously it's a touchy subject. I have some opinions, but what I would do is like I asked the inquire company, what is your like, like what is your plan like? What do you think of this? Because it depends on each and every company. On a surface level, this is what I would suggest. If your app is easily replaced with a competitor app, you have to run brand. The unfortunate situation here is that if we lose impression share that, we cannot measure that because it's a lost opportunity. We can only measure something, I mean incrementality, but it's a loss of revenue. Right. If you think about it, let's say A company is running Facebook TikTok brand awareness, all that touch points made that user come to the app store right before downloading. If a competitor solved the exact same problem, it's a really huge risk, right? Like we made all the hard work and now the competitors are benefiting from it. There are some apps like with apps with network effects and like we know these apps cannot be replaced with on other apps they do not need to run you know, brand. For example, maybe bank of America. No one creates an online application but there's an opportunity for like fintech apps, right? Because that's their opportunity. Bank of America doesn't need that but fintech can capitalize on that opportunity. My suggestion is test with bidding lower for the brand keywords. You'll be surprised. You may be paying. Let's take one example. An app is getting 100% impression share. To be honest it's not 100 because there's never 100% impression share. Let's say 90% impression share.

[A]

Is there a way to measure that incrementality testing or does Apple actually show you this impression share?

[B]

This is the best part. Apple does give us impression share per search term per country. So that is one thing we can keep track of. This reason why it allows us to conduct this test is bit lower for brand and test it out and if you retain same impression share you essentially half the cost still getting the same impression share. It is a test because we don't know how impression share can take a hit. And maybe some companies are okay with 70% impression share if it reduces cost by 70%. So it's a nice trade off. He's still retaining. We're still like letting go of our impressions for other competitors. But we can use that budget for generic high intent. And these are actual new users, right. And regarding Apple, extraordinary. I mean it's not unique to Apple, right? Like I mean it's every ad channel, there's no trademark on search terms. So yeah, it's unfortunate reality of everyone has to deal with but it's also an opportunity, right?

[A]

The impression share is an interesting way to approach it though because you're, you're right. It's like if, if you can spend half as much money and get 90% impression share versus twice as much money to get to a hundred percent. That extra 10% is probably not incrementally better than just spending less and getting the 90%. And then something you and I were talking about was how the, the search ads algorithm does tend to prefer the actual branded app where you could potentially even bid a lot lower than your competitors and still win the bid. Because Apple's not just going with the highest bid. There is some amount of like them trying to fit the best app. Right?

[B]

Yeah, it's because of one mechanism is that cost per tap model. Apple only charges an app company if someone taps on it. If you get a million impressions with zero taps, you basically got all this free 1 million impressions. So if that's the case, right, like, you know, if Apple just takes highest bid, like Temu will be showing up for every search term. But it's not. The reason is imagine like if I'm a yoga app, a famous yoga app, and someone is searching for the yoga app of my brand, a competitor may not get same level of engagement. A lot of users may see the ad and oh, you know what? I, I don't care about it. I heard about this app. So I'm going to download that. Apple is losing too. And it's also not great user experience, right? Like some, if a user is typing for yoga brand of xyz, they're expecting to say xyz, not so eventually Apple may like shift the terms to brand, even if you're bidding like let's say half of the competitor because there's some calculations. It is also a test because it's not guaranteed outcome. Imagine I'm just generic yoga app and the competitor has way better screenshots, way better messaging, way better ratings. I may lose that and Apple may think, you know what, this competitor app is actually working better more than this brand. So Apple may like give the impression share. So it is a bit of test. But yeah, that's where it's ideal to monitor the impression share and make sure we're not tanking.

[A]

Yeah, that makes a lot of sense because yeah, you're right. And your example earlier I think is maybe even better. It's like if somebody's searching bank of America, they're probably not going to tap on an ad for Chase Bank. And so Apple doesn't make money when somebody searches bank of America and they show Chase. Because people are looking for the bank of America app because they bank at bank of America. They're not searching bank of America because they're looking for a bank, they're looking for the app. And so, I mean, it's probably the exact opposite on like SEO, it's like, you know, if somebody's searching bank of America online or like, you know, other kind of keywords, it might make more sense. But on the App Store specifically, when somebody's looking for a very specific app. Apple's not making money if people are having to scroll past the ad. So yeah, it makes a lot of sense. So on brand defense, you just, you really experiment and try and bid as low as possible to maintain as much impression share as you're comfortable with to make sure you're not kind of losing out on the opportunities. Man, I bet, I mean, that advice alone, you know, I don't know how it does seem like a lot of companies, you know, they just kind of throw money at app store search ads and don't operate in a very sophisticated way. And of course, tons of them, you know, hire consultants or have internal people who are really good or have agencies working on it who know these kind of things. There's probably folks listening to this podcast who, who don't know that and, and aren't, you know, paying close enough attention. And you may have just saved them like tens of thousands of dollars. Just go in there and lower your bid and watch impression share.

[B]

I mean, there's one more thing about the roas and case studies and like, one thing I noticed is a lot of case studies don't mention if it's generic or brand. This brand usually has highest ros of any kind of if you think about it, right. Like that's what we made the user come to App store and their highest intent possible. So when we seeing the revenue ros, I would consider brand as its own entity. We treat it as, we do not compare brand with any other high intent generic keywords or competitor keywords or like broad match keywords. I would treat it as two different things. I do not even mix up the data as an entire like Apple cider strategy.

[A]

Yeah, yeah, that makes a lot of sense. Yeah. Because if your overall ROI looks amazing, yes, because you're cannibalizing. But if you can pay half, your ROI is going to look even better. So that's great. We already kind of talked a little bit about the trend in CPAs going up, up, up, but I wanted to dig into that a little bit. So we kind of talked about some of high cpa, like finance and health and fitness and some of these categories that are going high. What about like low cpa? Are there some categories that like, are opportunities, some arbitrage available in the App Store? In certain categories, yeah.

[B]

Even with the high competition categories, like we can have some cpa, we can improve CPA better by just expanding high intent and low intent keywords and bid accordingly. For example, yoga. I know yoga. If someone's typing Yoga Yoga is high intent for my app. I'm talking about yoga because it's such a generic app but I also know if someone is doing pilates or some kind of maybe there's a low intent. They may not be interested in my app but it's still like some if someone is looking for health and fitness and Pilates maybe they're low intent but I won't bid same as I would bid for yoga. So I classify that as low intent. That way you can expand keywords a lot and also keywords we can think of it as it's very that's where the night and day difference of performance can occur. In Apple search ads if I'm choosing bad keywords like have 10 keywords that are not relevant to app I'm bidding $10 each. We're going to have some troubles. This is a human thing, right? Like we know much better. You can use AI ChatGPT to have some ideas but the final say should be yours of okay we are using this keyword because it's low intent and we'll bid lower and in hopes that we get more suggestions. And the best part about Apple searchers is there are two types of keywords. Exact is not 100% exact but it's more like yoga for women for example is that if I'm bidding as exact keyword that's fine but there's another keyword type called broad match. What it means is any variations can also we can all right automatically show serve for me if yoga for women is same intent as yoga for women in 30s I know it's a long tail but yoga for women I don't care what the following search terms are because I already know yoga for women and these keywords usually are dynamic because if you look at the app store app if you type yoga you'll see Apple suggest some search terms and these change very often. So the competition would may not exist for some of the search terms and that's a low hanging fruit run the broad but obviously bid lower. I'm a big fan of classifying keywords and bidding different for each based on their group brand. And regarding low it's also very dynamic. Even with the high competition some keywords may not have any competition at all. And there's like think of stock market there's like so many, so many people trying to buy stocks and we cannot predict what's going to happen. So this is where you know we try to have as many as relevant keywords and we expect some may go down in impression Share some may go up. Overall, we just see an improvement in performance.

[A]

So is that how Broad Match works? I'm a little naive here. I have not, unfortunately. I mean, you and I were talking about like I actually want to start running app store search ads campaigns for my weather app. I've been holding off because I'm like, I don't know if they're going to be profitable and like it is tough in a category like weather and. But so I'm a little naive to exactly how all of this works. But maybe that's good because I think a lot of the folks who listen to a podcast like this don't necessarily like day in, day out run campaigns. So it's helpful to kind of define some of these terms and describe in a little more detail how some of this works. So broad match. If you do a broad match for like yoga for women, will it broad match anything related to yoga for women? Or does it still have to have like yoga and women in the search terms? Like how dangerous is it to set a broad match? Will it just like pull any random stuff in there?

[B]

Yes. Just because we said your yoga for women, it doesn't mean that Apple may. Apple may show for truly unrelated if it thinks that. If Apple algorithm thinks, for example, Peloton. If Apple thinks Peloton is related to Yoga for Men, our ad we may be paying for peloton keyword. But the good thing is we can even track this. There's a report called search terms Report. It's better to occasionally check, you know, this report and make sure, okay, all our spending is going to the right kind of keywords. Usually the search terms is not perfect. Apple only shows search terms if they're. If we spend enough and if you get enough impressions. But that's fine. That's what we want anyway, right? We don't need like thousands of search terms.

[A]

So then in this case, like if you have a yoga app and you see in the report that it's bidding for peloton and it's a high bid and you're not getting good roi, do you go in there and then specifically say don't bid on peloton.

[B]

So the good thing about that is we can track which keyword is causing peloton to causing our app to show up for Peloton. Usually I just go in there and tone it down to really stupidly low that either we get really, really cheap like installs or we force Apple to not show or ad. I'm not a big fan of removing keywords too Much often these are dynamic trends, right? Let's say I have a yoga for women and Apple is showing peloton search term for my app this week. It doesn't mean that it's going to keep doing that forever, right? Like maybe next month that might be my most profitable keyword. If I just remove that keyword, I just lost my opportunity forever. But if I bid low and I can retry it later, two, three months and see how is it performing. I think yoga for women is not a great example for abroad, but you can think of as a let's take weather since your app. Hopefully I'm not giving away weather app secrets. Imagine we are bidding, we just don't know anything about apples or chats. But we know our app is about weather. So you can run on whether as exact. It means that any variation whether like we show the ad and we pay high for that. Let's assume we did not do any keyword research. We don't have any keyword list if you also bid on broad of the same. So we are running two keywords. Basically Apple measure weather map, weather information, weather alerts. As far as we concerned, those are also relevant for us, right? So and you can go to the multiple levels like now weather alerts, we can bid on weather alerts because Apple showed oh, there's a weather alerts keyword. Now we do the same thing. We add weather alerts as exact and also broad. And our hope is that if someone is searching for weather alerts Philadelphia, it's still relevant because map still relevant. And if someone is searching weather alerts Los Angeles, same thing. So that way like you can. That's why I'm a big fan of maintaining a relevant keyword list because this is one time action, right? Like once we add weather alerts we're not gonna. Unless the app changes entire business model and the name and the functionality, it's really rare that the keyword is gonna be applicable forever.

[A]

No, that's a good point though because like for my app it would actually be the opposite. So we would start with weather as a broad match and we would prob see that weather alerts is a very low intent keyword because we actually don't have alerts in the app. It's something we actually want to add to the app. So then what you're saying is what we would do then is put weather as broad match when we see weather alerts come in and it's not creating a great roi. Even if maybe it is driving downloads because people don't Realize the app doesn't do it. But then they get into the app, it doesn't do it, they leave a bad review, they don't buy or they cancel the free trial or whatever. So then we make weather alerts an exact match and then we've been really low because maybe we still get impressions and maybe we still make some money but we want that specific keyword to be super low price. But then when I add the feature then we already have some relevancy for it and then I can bump the bids back up. Right.

[B]

In this case, like when we are sure this a particular keyword is really badly performing and it's consistent over and over again, you can actually add it as a negative keyword. Basically what we're saying to Apple is anything that says weather alerts, yeah, take me out, I'm not in the game. So that's actually much better. But we need to be absolutely sure that this keyword is never going to be a good fit. I noticed some advice that, yeah, just remove negative any keywords that don't generate revenue in first week. That is really not great strategy in my opinion because everything is dynamic. Right. Like some competitors may be bidding high this week, they may not drop off tomorrow. It's all dynamic. That's why I'm a big fan of Apple suggests it gives us a lot of data to validate and test our hypothesis. Yeah. In this case, if we know this keyword is a bad news. Yeah we just add it as negative keyword one time thing and we never have to worry about it again.

[A]

So is that, is that how exact and broad match work? So I mean a lot of people who like work in the industry are constantly managing things will know that. But I'm sure there's a lot of folks listening who don't. And then honestly even the people who work in this day in, day out could probably learn some of the intricacies about how it does and doesn't work from you as much as you've managed this and like work with so many different folks over the years. So. So yeah, how does broad match work?

[B]

Yeah, the goal for us when you, when we are using broad match is to capture like exponential number of search terms that are still relevant to our app and added benefit is usually for these keywords because these are so dynamic they change every week. They may be low in popularity, so they will. Our competitors may not be bidding really.

[A]

So, so we've talked a bit about fluctuation but one of the biggest fluctuations is seasonality. It's like, you know, I'm sure January 1st, all the search terms related to health and fitness are bid to crazy and that's to be expected. But any other things you think people should be watching out for seasonality wise or how does that impact CPAs? And how should you be preparing and structuring your campaigns for seasonality so you don't end up like, you know, paying too much, but also so you don't miss out on the opportunities when there maybe are higher, higher ROI searches, when maybe you are bidding lower even when there are higher intent people coming in.

[B]

Yeah, I mean for us, storefront, like the Thanksgiving is usually the highest competitive space. It's the same similar phenomenon, like a wave lifting up all the boats kind of thing. So even if it's nothing, even if our app, it has nothing to do with shopping, we may see our cpa, you know, going up a bit high. Even summertime is like, usually for like it depends on kind of apps. Like for some categories the summary is actually the cheapest CPA for some reason. You can think of this as cool if I'm education app. And usually the best time period to test any new app is, I mean if you're, if someone is thinking of trying out Apple searchers is during February till summer. This is kind of a kind of weirdly low energy in the competitive space because the January high is gone and now things are coming back. But it depends on the app too, right? Like if my app is dealing with something with for example, flights like flight tracker, obviously like I can benefit much because there's not peak travel season. Yeah, those are the seasonality trends and.

[A]

Some of them are counterintuitive too. Like I was actually talking to Ryan Jones from Flighty recently and he was saying how surprised he was that holiday travel is such a, like I thought, I think the conversation was related to me saying, oh, you must do like really good business in the summer. He's like, no, actually like the summer's fine, but the holidays is where people are like way higher intent, like traveling more, care more about delays and stuff like that. And so some of these like seasonal trends are probably counterintuitive. And like even you're running your app thinking, oh, you know, let's take all trails for example. It's like, oh, well the summer is going to be peak season maybe, but are there, are there ways that you kind of, I mean, pretty much you just need to be watching week in, week out. Are there, but are there specific ways that you track these campaigns to make sure that you're not missing out on either potentially bidding lower kind of when CPAs maybe drift lower or bidding higher when there's actually higher intent people coming in. How do you manage that on a day in, day out basis?

[B]

It depends on how our app category, how the competition is. For some apps it depends on what our competitors are doing. Because when I'm saying competitors, I'm not talking about exact close competitors, I'm talking about any app that are bidding heavily and for a long time. For our primary keywords, high intent keywords, it depends on that. For day in, day out, usually we should not. We just keep in mind that hey, this is expected and we can look over. The good thing is it should correlate with organic traffic as well. So we can just come back to app store connect and check last two years what's our trend and we can expect similar in appreciate shares. I'm not a big fan of changing bits by the seasonality because like I said, it's like stock market, right? Everything is dynamic. We cannot predict that we'll get impression share of this keyword but we can see the results and act on it. I mean that's the best thing about data, right? Like we don't have to make any assumptions, we can see the data and act accordingly.

[A]

So what you're saying is the better tactic is just to watch the keywords and so if you're getting a higher ROI on a specific keyword matter, the seasonality, that's when you would experiment with increasing the bid and then if you see ROI drop then that's when you experiment with lowering the bid and you kind of like you should just be doing this as like standard practice anyway, not necessarily focused on the seasonality.

[B]

When I say watch keywords means it's like constant process, right? Like imagine I'm running an Apple search campaigns for my company and I just go in every day, every week, once in a while and I'll just be according to what I'm seeing, it doesn't matter. Maybe Germany is the least performing campaign. It doesn't matter what season, right? I just, yeah, you know what, I'm not going to spend too much budget so let me bid lower for the entire ad group. Maybe US is least performing but Germany is best performing in December for some reason, I don't know because these are all external factors we cannot analyze like why it happened. We can just react what we're seeing based on past 15 days or past seven days.

[A]

So. And speaking of ROI, how do you think about ROI? Because you know, you're not always going to be able to get. I mean the magic is like, oh, I plug in a keyword and like 150% ROI in seven days and then you spend a million dollars a month and you're just making money hand and foot. But that's not how it actually works in the real world. But so how do you first measure RO ROI and then how do you think about roi?

[B]

Yeah, imagine. I'll take, we'll take an example of a regular generic app with seven day free trial and some.

[A]

Let's talk about my app. So if I start running because I am going to start running weather app store search ads on different weather terms and so I'll, and I'll probably be talking about this over time on the podcast and like you know what's worked and what hasn't for me. So yeah, a weather app. So I start running ads for my weather app. So we'll use that as a hypothetical.

[B]

What is the free trial? Is there free trial?

[A]

Seven days.

[B]

Seven days. Perfect. Here's the thing about revenue in Apple search ads. Apple search ads by default doesn't give revenue, doesn't show revenue. Like unlike Meta, you know, Google Ads. But there's some ways that you can use mmps like other platforms and get the information and link it up and revenue cat. Yes. Yeah, revenuecat does a great job like linking up keywords and ad groups and you can use that information to analyze. My recommendation is like do not go in there expecting a hard number as revenue go and if it doesn't hit, take the entire channel down. Because these are really dynamic and there are so many things that we can improve on. For example, it's totally different of revenue. If I Google right now what is a good ros. The usual wisdom is 400%. What they mean is like okay, if you spend $100, you expect $400 coming back. But that is not for app. That wisdom is not for app marketing because for simple reason we have subscriptions, right? And Also all this 400% auris golden metric is for like for example, if I'm selling T shirts, yeah, there's a metric I can follow on but because if I'm a person who buys my T shirt will never buy same T shirt next month. But app, there's a important metric called time to break even. What it means is it's fine even if you don't get 100% RS in the first week. I mean obviously if we get that, that's good. But even if you get like 40% or 50% always. It's actually not bad result because we can still improve on add more keywords, we can fine tune and also there is a, we can check our ltv. Right. And because we are bidding for high intent, we know that these users are perfect users of our app. So we can expect we can improve the in app like experience to make sure they don't churn. And if you have a monthly subscription, hopefully, because if you think about it, cohorted ros mean we only spend that, let's say we spend $3 for that install for that user who started this free trial and they did convert. In that case we only spent $3 one time for that user and that's it. But the revenue is like hopefully our app is better and not like there's not huge turn we can keep on, the revenues keep coming in. So there's a time delay. We just have to keep track of it.

[A]

And so then every app developer has to kind of decide from a cash flow perspective, from a long term business perspective. I mean I was talking to one person who, you know, because you hear so much in the industry of like oh, you know, what's your seven day ROAS? What's your 30 day ROAS? You know, are you getting ROAS positive in 90 days? Like what's a metric? And I was talking to somebody who has like really great organic traffic. So their business is just spinning off cash. And so their metric was 365 day ROAS. So their, their metric was can I spend today and at least get to 100% by the first annual renewal. And for a lot of businesses that can make sense, like if the cash flow makes sense, if you're wanting to, like really. And then the cool thing like you're saying is like those people who renewed that first year, you get to roas positive in 365 days, which again is crazy. It's hard to float that if you know, for a lot of companies. But then like a bunch of those people are going to new the next year and the next year after that. And so it's an arbitrage opportunity to grow faster. Now if you have the cash and you have some level of confidence in those renewals that you're going to start stacking those cohorts sooner and sooner. That's actually why I want to start advertising for my weather app as soon as possible and I'm kind of kicking myself for not starting is I should at least be picking up the low hanging fruit. And maybe this is kind of the message for Those of you who aren't currently doing it, even for those of you who are and maybe could even spend more than you currently are, is that, I mean this is magic of the subscription app model is that that LTV is not capped. Even if you have a average LTV for most apps who are reasonably retentive, whatever average you calculate today is likely to just keep going up year after year after year after year. I mean, I was looking at my own app and seven years in, I still have 20% of people who subscribed within the first month. So seven years still have 20% of people. And so if I can stack more of those cohorts now versus stack am later, even if I'm not getting 100% ROAS on day seven, if I can afford the cash to do that and expand the business, it's going to pay dividends in the long run. But you just got to make sure you, you have some level of retention and confidence in that and then you have the cash and the risk tolerance to go ahead and invest more heavily.

[B]

Yeah, obviously the, the caveat is that we have all the basics sorted out. What I mean is the install to free trial ratio, the free trial to conversion ratio. But this is nothing to do with Apple C Chats, right? The goal of Apple C Chats is bring in new users. We have to improve those in app conversion rates anyway ourselves, regardless if you run ASA or not. And one more thing about ROS is ROS should not be the primary metric. It should be a combination of revenue and rs. For example, we can think of two apps. Let's take Meditation, let's take Headspace and Com. These are imaginary numbers, so don't sue me. Imagine Headspace and Calm. Both are running appleset chats and Headspace is spending, let's say a million dollars and their ROs is 75% ROs. But Calm is spending $2 million. With 65% always on the paper, it looks like Headspace is doing much better, right? Like because it's getting 70% RS within like first 30 days or whatever. But in long term the. Com is actually better positioned to lead because at the end of the one year they both are going to have 100% RS anyway according to their LDV metrics. But com generated double the amount of revenue that Headspace, even though there is a ROS is not great for the. Com app. So it is a combination of revenue and ros and if we don't consider revenue, our competitor will and they will eventually like bid higher or whatever. The RS we're getting currently is going to suffer because now they're going to bid higher for our positive RS keywords. So yeah, revenue is one of the major number as well because that's what we want. Right.

[A]

Well and the other thing that revenue takes into account that you, that's hard to factor in is that there is some organic lift when you're running aso. I know this is another kind of controversial topic and I know you have some hypothesis around the impact, but the reality is there's some impact whether your hypothesis is correct or you know, tons of people in industry are like, oh, it's going to be magic, like run ASA and then your ASO is going to be amazing. But so what's your hypothesis on the. The impact of ASA on aso?

[B]

I would call it conspiracy theory. I would not even call hypothesis because that's such a. Take it with grain of bucket, with bucket of salt.

[A]

This is why I love having you on versus like a growth hacker because a growth hacker would have just been like, oh yeah, 100%. This is how it works. You're like, you see the data day in and day out and you're like, this is even a hypothesis because you want to have a level of confidence in the answer. But yeah, what do you think? Because honestly, you probably your conspiracy theory is probably better than a lot of folks who speak confidently about this.

[B]

My theory is that download volume correlates with organic ranking. It's one of those trend that it doesn't matter what app, it always correlates with such a strong efficiency. The second factor I think is this is where the conspiracy theory part comes in. Even at the keyword level. Imagine we are having same amount of downloads. There's not much huge change in the download volume. But you start running for weather apps Apple search ads. Let's say Weather Radar maybe is one of the feature of your app.

[A]

Yep, that's a great keyword for my app. Yeah.

[B]

So Weather Radar, you imagine your current organic ranking is maybe 70 or something. As soon as you start running Apple switchers for that particular Weather Radar system and our app generates some installs, you may see the organic ranking go really high, maybe even reaching top 10 or top 20. Just the skyrocketing within, but the download volume is same. That's my conspiracy theory that maybe App Store considers Apple search as keyword as part of App Store and now even the App Store algorithm can see that. Oh, you know what, this weather app is totally relevant to Weather Radar because users are clicking on it and using it and don't avoid it.

[A]

But then why wouldn't it change the download volume? If you go from like if I start advertising for weather radar and I get go from I'm probably like 200 in that search currently, so I go from 200 to 20. Why would download volume not change?

[B]

I'm only talking about that particular keyword. It's an imaginary hypothesis that we are running Applesearch ads for only that keyword. Let's assume our daily download is like 100 units in US and we started running that keyword for two installs a day. I'm giving an example maybe at the end of the week the download volume is not that high like 100 versus 102 installs. But the organic ranking for every other keyword may remain same. But for this particular keyword, what we're running in haphazard charts we may see a kind of organic ranking uplift. But like I said, take it with buckle of salt. It may not happen. I don't recommend spending a lot of budget just for that purpose because it may happen. It may not happen.

[A]

And yeah, it does seem like Apple's search algorithm. Although it's still frustrating, it doesn't feel like they're still especially great at it, but it does seem like it's gotten more and more sophisticated over the years. So the people who who think there's going to be a one to one response in taking a certain action might be surprised. And like you said, yeah, it's it's a lot of money to put on the line. When any kind of algorithm like this, there's not a level of certainty on it.

[B]

While we are on the topic the dollar volume organ rank, the theory is that it is kind of like a chicken and egg issue for especially for new apps or apps that are actually best in the class, better than all the competitors, but the competitors will be always number one. In that case, do not treat Apple citizens as a like there's a channel we should never run on because this may be the better option because as long as your app is better than competitors and they're ranking number one even then you can actually get high intent. As long as we talked about the basic or in app conversion ratios are basic. These are all great. If that's the case, you don't even need to run million install campaigns, you can just target those high intent. We're not going to get quantity, but we'll get the quality users and as long as we're scaling up our revenue, why does it matter how much if you're ranking number one or not? I'm talking about opposite charts. Obviously it matters that we rank number one, but sometimes it's next to impossible for some keywords. We can never rank number one.

[A]

Right, yeah. No, that makes sense. And speaking of scaling, that's actually something I wanted to talk to you about and that, that's kind of the, the challenge with App Store search ads is that even though it can be an incredible source of really high intent downloads, the kind of what everybody in the industry talks about, it's like, well, that's great, but it's not scalable. So how do you think about scalability in App Store search ads?

[B]

Scalability? I mean, obviously we cannot compare Apple search ads with meta campaigns or TikTok campaigns because it's apples versus oranges. We are looking quality versus quantity. In my opinion, the best way to scale is to adding more keywords. High intent, low intent, like segmented by it. And adding broad match keywords that will literally be exponentially increasing our awareness and more countries by default. That's a easy way to scale and just monitor campaigns and employ some kind of a workflow like campaign structure should be in such a way that it's easy to maintain them. I'm not a big fan of like creating hundreds of campaigns for one country because you only have one competitor set of keywords. Right? Like you cannot have multiple competitors. We don't need to run different, different ad groups. Yeah. The bottom line is adding more keywords, relevant keywords. The more relevant, the better they are. And adding more. There's always competitor share that we can improve. And brand is something, as we talked about it is its own thing. We do not consider brand as our. Because brand is kind of steady flow. Right. Like, I mean it's a good thing. The brand impressions go up. But that's how I scale.

[A]

Yeah, but then what, what are the. I mean, do you see? I guess it's just going to be so contextual, right? It's like for a health and fitness app, it's like if they're willing to spend the money, it can be a massive channel because there's a ton of high intent people coming and searching relevant keywords. But then if you're in a niche, a really small niche where like you're really only relevant to very small number of searches, then you're going to hit the wall sooner. Right. So it's just very contextual of when you're going to hit the wall. But then you don't know that you've really hit the Wall until you've done the experiments with Broad Match and experimented with the bidding and tried stuff. Right?

[B]

Yeah. And Apple Search is one of those things where the competitors can dictate what we can do next. For example, imagine there's a weather app and imagine there's, for some weird reason there's no weather app in Apple Searchers ever running Appleset chats. Your app is the only one that has Appleset shares. In that case, your CPA will be like probably in cents in US. Your RS can skyrocket. But that's like a dream scenario. But imagine you have like 25 weather competitors, weather app competitors in the United States. Unfortunately it means that for the same number of installs your CPA probably like is 10 times now. But the good thing is competitors also dynamic. Just because they're bidding for a keyword doesn't mean that Apple considers them relevant. Same phenomena brand as well. If you're your competitor running same weather radar keyword and for some reason your app is performing better and Apple can see that even if you're bidding half of your competitor, Apple will still prefer your ad. Because Apple has to make money too, right? Like they can't just show the other app if it's not getting too much of traction.

[A]

Yeah, yeah, that's interesting. And then, and so then part, part of what you're saying is like even, even if you are super niche and you're like, oh, it's gonna, it's gonna tap me out really quick, go get those keywords because they're gonna be so cheap. So if you're, if you're in a niche and you're not running Apple Search ads, you're probably leaving money on the table because there probably are some high intent, low traffic keywords that still you're just printing money if you can pick those up.

[B]

Yeah, we just need to adjust our expectations. Like we can have like a million dollar day one, you know, meta, meta kind of, you know, blitz. But if we have our expectations set.

[A]

And yeah, and the interesting thing too is like even though meta, you can theoretically scale even for a niche app, like you'll saturate that kind of ideal customer profile. And so yeah, you can scale near infinite on meta, but you might not scale profitably near infinite because it's similar. Like as you start bidding higher and as you start saturating your market and those high intent users that you're going to be able to get to, then your costs are going to go up too because now you're, now you're ending up with medium intent people and then low intent people. So like nothing's truly infinitely scalable unless you're. I mean like I guess these like Temu and stuff like that. Like when anybody is truly a potential customer there are like you can't scale to a level that a lot of apps can't. But most apps aren't that so and.

[B]

One of the interesting thing is that how ad channels can behave differently for the same app. Obviously any mature app company will be using multiple ad channels at the same time. Meta and Apple search ads and Google whatnot. The difference is that Apple searches is relatively easier channel to maintain. The reason is we don't have to create this influencer videos make it quirky like and there's a thing called fatigue. Imagine you probably noticed that if you're using Instagram and using same ad every day like it something will set in and will never it's actually create may create a version to the app. But Apple searchers we don't have that problem. Right. Because we are targeting new user looking exactly for that keyword. So the ad fitting is not a really huge thing. There is some display formats like search tabs or today tabs but it's not like that extent of Instagram where we see like 10 ads of the same app in a row. And it's not that great experience. And it's easier to scale because we're not dealing with creatives. Apple such as creatives is our whatever the screenshots we have metadata. Right. And the keywords we don't change keywords. Right. Like it's always the same keywords. We may add it. I mean we may pause them or we may be lower. But with the Radar, until your app exists in the App Store the weather radar is always be relevant. We don't need to think creatively. And it's great for people like us who are developers because we don't have to worry about creative videos that catch people's attention.

[A]

Yeah. Speaking of creative and App Store screenshots and stuff though, how has product pages and being able to send specific keywords to specific product pages started to change the game? Because there is a certain level now where you can experiment a little more with creative on the App Store because you can create a separate product page for these different kind of use cases. Have you seen that help accounts scale and get to better robots.

[B]

Those are good problems to have because if you're considering a keyword specific customer product pages it means that we already maximized whatever the impression share and we are reaching. Let's assume like there's a shopping app and they maximized 80% of impression share for all generic terms where custom product pages can move the needle is let's assume there is a TEMU is running a ad for Thanksgiving and it's like a month long feature, right? But Temu won't say Thanksgiving in the title and subtitle and screenshots, but they can create its entire custom product page just for Thanksgiving and have Thanksgiving all across only for United States. And they can use that to scale up those Thanksgiving people who are creating I'm saying Thanksgiving it should be Black Friday, right? Black Friday deals. And yeah that way like you know, Temu can scale up those keywords and in a indirect way I have also like custom product pages for a B testing this is one easy way to like simply implement a B testing and see and you can even use similar search terms like for example bid for half the United States states for our default product page and use utilize the new custom product page. We want to test and see which one performs better and just compare each. There shouldn't be much difference between east coast and west coast anyway. Or you can also try ad scheduling, which means during the first half of the day you can use it. But I'm not a big fan because the time of the day may dictate for example, like if I'm, if I'm a yoga app, I may be looking in the morning. Right. So the geographical separation might be a good place to test.

[A]

Yeah. Interesting. All right, well it's been so fun chatting today, but we do need to wrap up as we do. Is there anything else you want to share or anything you want to tell the audience?

[B]

Yeah. For new apps, use Apple search ads as kind of customer discovery thing. And you can, I mean you don't have to spend daily budgets like hundreds of dollars. You can even get 5, 6 installs a day spending 10 $20. But use that as high intent and use them as because you want to target high intent users and improve your app. And check us out. Our platform is designed to scale Apple search ads profitably. Scroll search adsoptimization.com and find me on LinkedIn and ask me any questions. And I'm always happy to talk about Apple Switch ads.

[A]

Awesome. And as I've kind of been wrapping up these podcasts too, if you have specific questions instead of hitting them up on LinkedIn where only the two of you could talk, feel free to do it on on the sub club community. So we'll, we'll po post this podcast on the Sub Club community. You can respond to that or just just tag dilip so that your questions can be beneficial to the rest of the community as well. But yeah, I was checking out your company, and again, it's really cool that you started this from a data perspective, and it's clear that you've built the algorithms to make it so much easier for folks to do a lot of things that we talked about today to manage those bids to automate some of that as well. So, yeah, it looks like a really cool platform and something I'm going to be checking out myself.

[B]

Yeah, sounds great.

[A]

Awesome. Thanks for joining me. And thanks for sharing all these great nuggets with folks. Thanks so much for listening. If you have a minute, please leave a review in your favorite podcast player. You can also stop by chat.subclub.com to join our private community.