This is the fourth episode of App Growth Talks, a series of interviews with ASO, Apple Search Ads, mobile analytics and growth experts. Today’s special guest is Andrea Raggi, a prominent expert on mobile performance marketing, user acquisition, in particular Apple Search Ads, and Store Ads Team Lead at Phiture, Mobile Growth Consultancy based in Berlin.
Andrea, could you please shed some light on your experience with user acquisition? How did you start working with Apple Search Ads?
I initially started my career in online marketing and I decided to specialize in mobile-only 3 years ago. I made that decision based on the fact that mobile was increasingly on the rise and was set to establish itself as the main point of contact to reach an ever growing number of users. But of course, chance played an important role as I was able to land a job in a mobile-only e-commerce app, where I started to specialize in user acquisition and mobile marketing.
My user acquisition experience mainly lies in the domain of paid advertising. However, I also have experience on organic user acquisition for mobile, specifically with app store optimization, and lifecycle marketing since I started to work at Phiture. As of now, I have been working, developing and executing strategies to pursue performance-driven marketing with most of the leading advertising channels: Facebook, Google, Apple Search Ads. I have mostly focused on Return on Ad Spend (ROAS) and Customer Acquisition Cost (CAC) with the companies I have worked with. Moreover, I have also been developing LTV models and focused on cannibalization and incrementality.
I started acquiring users with Apple Search Ads in August 2018, when it was released in the European markets. I started with the channel substantially as a test: while I was working in an e-commerce company, we were experiencing a growth phase. That situation induced us to try many different new channels other than the classic duopoly of Google and Facebook.
After a few months of tests, Apple Search Ads turned out to be one of the best channels in terms of ROAS generation.
After that experience I kept working with Apple Search Ads at Phiture, where I have been honing my Apple Search Ads knowledge with many different verticals and clients over time.
What advice would you give to those who are just starting with Apple Search Ads?
Get the basics right. It will save you tons of money and time in the long-term. Make sure you start your Apple Search Ads campaign after having conducted enough research on the market, your competitors and the keywords you want to target. Being prepared and having a strategy in place will help out to overcome the initial fears and uncertainties. What we at Phiture usually do before starting to advertise on Apple Search Ads is having a look at the Apple Search Ads stack to make sure we cover as many variables as possible, while at the same time ensuring we create a consistent strategy and tactics that fit the company’s objectives.
Another suggestion is to keep investigating and not losing the research spirit.
Testing will be the key to better performance and improved results.
Test Creative Sets, new titles and different subtitles for your app, and try out new keywords in your campaigns. Never stop exploring new possibilities as you can’t know in advance what could be successful. Sooner or later you will land in a specific segment of users and/or a specific initiative that performs exceptionally well and is able to generate great results for your app.
You’ve recently introduced the ASA Stack, a strategic framework for Apple Search Ads. How did you come up with this idea?
As many things in life, it happened almost by chance. The initial idea was not aiming at publishing a piece of content, but rather, we wanted to create something to use internally. Our objective was to develop a document or chart that could determine the steps to be taken when inheriting or starting to work on an Apple Search Ads account. Other than that we wanted to map out all possible strategies and optimizations that we could do on an account to make sure we had a kind of guide that could help achieve clients’ objectives. In sum, we wanted to have a document that could help out new team members and also gather ideas & insights on Apple Search Ads account management.
However, the more time was spent on it over the months, the more it turned out the internal document could be a valuable piece of content not only for Phiture, but for the whole community of Apple Search Ads practitioners. Therefore, we started to expand from the three core layers (which mainly cover the Apple Search Ads platform itself and how to scale and/or optimize an account) to two additional layers: “Tools” and “Supporting Insights”. We thought those two extra layers could potentially help strengthen and develop a company’s Apple Search Ads strategy and understanding of the environment. Specifically, we believed the two extra layers could provide additional insights for new Apple Search Ads practitioners and how those could give them an idea on what would be needed to kick-start Apple Search Ads.
In the end, the internal document turned into a piece of content that hopefully will help marketers to understand Apple Search Ads and to take advantage of it to a maximum extent, making it a valuable user acquisition channel for companies.
You’re running Apple Search Ads for a number of Phiture clients. Are mobile game publishers among them? Could you please share some Apple Search Ads tips & scaling best practices for mobile games?
Our client portfolio is really diverse: we have and have had mobile games, financial services, fitness, business, kids and travel apps among others. For all these different verticals, the same recommendations apply as we are all playing according to Apple rules. Of course the strategies will vary and will need to be adapted according to the company objectives, but the levers that Apple Search Ads offer to scale or improve performance are the same for all advertisers.
The first tip that I strongly recommend to follow is to have a robust ASO strategy. Having a well-thought ASO implementation will, firstly, influence your visibility in Apple Search Ads. This can happen thanks to a proper research and selection of appropriate keywords for your metadata. The benefits coming from higher visibility are straightforward: appearing more often in front of App Store users. This higher visibility, in turn, can directly translate into winning a higher number of auctions if your ASO metadata is relevant and consistent to the keywords you are bidding on. If you want to promote a fitness app, it doesn’t make sense to include “cinema” in your title. Clearly, that was an extreme example, but I’d like to convey the message that you should select valuable (and pertinent) keywords aimed at converting users to download your app.
In sum, as Apple rewards relevancy, you have to make sure to strengthen the elements that are able to directly improve your Apple Search Ads efforts, i.e. metadata, screenshots, etc. – all of these components are aiming at increasing your conversion rate. If you take this approach for your app, you will be able to scale more quickly and efficiently by ensuring a solid conversion rate.
In regards to scaling tips which belong to the Apple Search Ads realm only, if you are looking for a quick launch to your Apple Search Ads campaigns, you could implement a Search Match ad group in one of your campaigns (preferably a discovery campaign). The Search Match setting in Apple Search Ads allows you to find new keywords thanks to Apple’s algorithm. These new search terms will be discovered by taking your metadata and similar apps in your category as a benchmark. If you opt for this option, I would recommend to keep a close eye on the search terms discovered as they sometimes tend to be broad.
Another tip to scale could be pushing your bids to a very high amount, enabling you to enter as many auctions as possible. Your user acquisition costs might actually increase as a consequence of this, but if you are aiming at volume at first, this could be a solution that enables you to achieve your scaling goals. This can be a risky approach, but it could also provide some valuable insights on competitions’ bidding strategies and performance.
A final recommendation to increase your scale could be considering targeting LAT on traffic. Limit ad tracking (LAT) is a feature that allows users to opt-out of having an ID for Advertisers. When LAT is enabled (LAT on) conversions from Mobile Measurement Partners (such as Adjust and Appsflyer) can not be tracked. While this feature can be a potential downside as advertisers would not be able to see which in-app actions users are performing, it can provide up to 30% more traffic in certain industries.
Please name a couple of cases when Apple Search Ads helped your clients achieve excellent results.
In our experience at Phiture, Apple Search Ads tends to be a satisfying channel in terms of ROAS achievement or even retention of users. One very successful example that I can share with you is Invoice Simple. As the name suggests, it is an app providing invoicing services via app.
The team at Invoice Simple approached us with the challenges in scaling the Apple Search Ads channel and improving overall performance by increasing the number of users purchasing a subscription (while, of course, lowering the customer acquisition costs).
To tackle the scale problem, we began carrying out extensive keyword research in several languages and organize them in a systematic campaign structure – with different semantic group campaigns and ad groups that are sorted by level of intent. With the help of Phiture’s Engineering Team we also created scripts to help automate keyword distribution and campaign management to ensure a constant flow of new search terms. As an example, newly discovered keywords were automatically tested for lower-funnel events such as subscription.
In regards to performance, we focused on optimizing CAC and ROAS by optimizing bids and acquisition goals. The engineering team also developed scripts that could pause keywords on non-performing days of the week. Moreover, thanks to a model developed with our data science team, we managed to estimate the best converting keywords for subscription, which helped management adjust their strategic decisions on user acquisition.
The results were extremely satisfying: we increased the budget from a 5 figure to a 6 figure monthly budget, with the overall spend increasing by 50%.
As a consequence of the higher scale, the number of subscriptions increased by 51%. Moreover, the Customer Acquisition Cost decreased by 6% over the first 60 days which helped increase the Return on Ad Spend for the client.
Finally, we discovered thanks to creative A/B testing that a new screenshots set was generating a 13.4% increase in conversion rate from impressions to the first invoice completed. After applying these new creatives in the organic search results, the search conversion rate to download increased by 15%.
Does an optimal bid exist? If so, how to discover it?
I don’t believe in a perfect bid, but I certainly believe that we can get to an optimal bid. The reason why I don’t believe perfect bids exist is that the environment (user behavior, competitors, etc.) is always changing and therefore perfection is volatile and unstable. However, there are some tricks we can use to make sure we are always as close as possible to an optimal bid.
Always optimize your campaigns, don’t mistreat them. Constant analysis and optimization are the only way to make sure we maximize the results. This might sound obvious, but do not create a campaign, let it run and hope for results to come. I have seen it many times, as marketers are busy and do not always have much time to spend on Apple Search Ads. If that’s the case, spare your efforts from the beginning. Results will usually only come with time, effort and constant optimization.
In the end, after a countless number of optimizations, you may find an excellent bid – able to deliver excellent Return on Investment.
If that’s the case, don’t rest on your laurels and remember that status quo may change. This once again means constant analysis and optimization even after hitting or overachieving targets.
A special way with which you could, in my opinion, get excellent results is with the use of AI or some sort of rule-based bidding. These are the best ways to cope with changes in the environment (competitions’ bids being altered, change in demand, etc.) as bids will be changed as soon as certain conditions would be hit.
SearchAdsHQ provides you with rule-based bidding which I have used in many instances and that has helped us keep spend and KPIs under control.
These tools would be specifically helpful if some sort of ‘seasonality’ happened over the weekend. Let’s say that your gaming app always experiences a surge in downloads over the weekend, but you are not working on Saturdays and Sundays and therefore, you can’t track – and control – what’s happening.
If you rely on these rules or machine-based tools, you would make sure to quickly adapt bids to a near-optimal state and ensure that your performance and KPIs are able to cope with the constant changes in the environment.
How do you use Creative Sets in Apple Search Ads? Any best practices?
I like Creative Sets testing because they are a potential way to increase not only your Apple Search Ads conversion rate but also your organic conversion down the line.
I believe it could be a helpful resource to help you discover whether a different combination of screenshots or different assets might be converting users to download better than your current ones.
If you decide to run Creative Sets tests in Apple Search Ads I would recommend to run A versus B variants. I would not recommend running an A/B/C test as that would slow down the testing process since you will need lots of additional downloads. The approach we follow at Phiture is always starting with a hypothesis: that gives us an idea on what and where to start testing. Another tip on where to start is choosing very different value propositions or selecting assets that are very different in nature (portrait vs. landscape assets or app preview vs. no app preview).
Once you have chosen what to test, to evaluate the winners I would suggest to pay attention to the tap-through rate (TTR) since that signals users interest as well as ad relevance. However, I recommend you to identify the winning version based on the conversion rate from Impressions to Downloads because that’s how you are actually acquiring users.
Finally, when measuring the results of the test, it is important to:
- make sure that you have an industry standard 95% confidence interval or higher;
- have at least 1,000 downloads per variant to validate your experiment and ensure your test has enough data in its sample, hence giving it enough reliability.
Many publishers are concerned about the cannibalization issue. What would you say about Apple Search Ads brand ad incrementality?
Cannibalization is certainly a hot topic everybody is talking about lately. I have carried out many tests with clients on it and the results were very different. Cannibalization can happen, but there are very different extents to which your app may experience that. I have seen almost no cannibalization to medium-high cannibalization.
I have also seen many benefits generated from Apple Search Ads, such as brand defense, higher visibility and, in some cases, a boost in organic traffic too thanks to higher category rankings.
If you are concerned about cannibalization and the resources invested in Apple Search Ads, I would certainly recommend testing its overall impact by, for instance, pausing your campaigns (or top ranking keywords) for a week and measuring the impact on organic traffic change.
If you decide to stop your Apple Search Ads efforts though, you should consider the possible trade-offs such as the complete loss of brand defense and the potential impact on visibility in the App Store.
Are you ready to give up your first line of defence and allow your competitors to appear in the App Store before you do? Are you ready to lose at least a good 20-30% of users to those competitors?
On top of that, Apple Search Ads can be extremely beneficial for small apps that do not rank high organically or for companies that rely on acquiring users with keywords that have a low organic rank. Losing that visibility could trigger a lower amount of downloads and a drop in category rankings.
While it can be difficult to answer questions on cannibalization on the spot and without evidence, I would certainly recommend evaluating the potential impact of it first and then base your decisions on the obtained data (and potential trade-offs) and decide on whether to opt out of your Apple Search Ads efforts.
Another hot topic I cannot ignore: Apple removes IDFA. This is certainly a game changer. In your opinion, what should we expect?
Apple’s iOS 14 and the willingness of Apple to only allow collecting IDFAs with explicit consent will represent major changes to the mobile industry.
One major implication could be a shift from deterministic user-level ROAS optimization to a probabilistic campaign optimization based on an expected outcome.
Is mobile marketing and its measurement of performance going to become more similar to TV advertising, where we are not able to precisely determine the amount of revenue we are generating?
Another major shift could possibly involve moving away from being media buyer optimizers to becoming marketing strategists, or even placing even more attention on the topic of incrementality. In regards to the former, as we won’t be able to directly track events (and revenue) for many users, we will possibly need to shift our focus even more on strategy and execution. In terms of the latter, we could increasingly focus on a probabilistic guidance on where money should be spent (how do I allocate it to network A, B or C?) and how that could potentially help companies get incremental results.
While many things are still uncertain, we know for sure that the deprecation of IDFA will result in the reinforcement of user privacy. People will have control to decide whether to allow their behaviour to be tracked or not within the apps.
I believe that this is certainly a good step to be taken and it gives power to users to decide what to do with their privacy.
Moreover, since the IDFA has been around for some time, it has established itself as the main source for advertisers to track data and identify users’ behavior within one app. As a matter of fact, thanks to its convenience and insights it can provide, the whole mobile advertising industry has been building on IDFAs since it is the most effective and precise way to track mobile advertising performance on iOS. For instance, Mobile Measurement Partners (MMPs) utilize IDFAs as one of their main building blocks to attribute installs.
Many companies will have to rethink themselves (and possibly their business model too!). For instance, will Google follow cope with the pressure that they are facing on increasing users’ privacy?
We’re about to witness a revolution in the industry and this is very exciting, in my opinion.
What’s next in Apple Search Ads? And will it expand and develop into something bigger?
Yes, definitely. Apple is increasingly seeing an increase in revenue coming from this side of their business. As such, we have to expect Apple Search Ads expanding and developing into something that goes beyond the App Store listings. For instance, recent updates to the APIs possibly suggest that the next forefronts of the new ad placements will be “News” and “Maps”.
Here users will be able to find, on the one hand, editorial content which can be promoted among ‘normal’ news articles. On the other hand, I expect certain shops, restaurants, etc. to be able to promote themselves on a map.
In sum, I see the potential for Apple to grow in the ads business. This revenue stream will probably increase and become more important for Apple’s future and diversification of its portfolio of products and services. As such, I believe that they are just preparing the groundwork to expand to something bigger.