Since Apple’s release of Custom Product Pages (CPPs) in late 2021, industry professionals have been racing to adopt the revolutionary capability. However, there’s still no pragmatic framework detailing how to take full advantage of the gift we’ve been given.
This playbook is that missing piece of the puzzle. The Storemaven research team has developed an easy-to-follow guide on how to maximize the potential of CPPs which will, in turn, translate to optimal conversion rates and ROAS for your paid traffic.
Throughout this playbook, we will use the “Royal Match” by Dream match-3 game in our examples, one of the most successful genres today in the App Store.
For those of you who aren’t familiar with Royal Match, it’s a game that involves several other mechanics besides match-3:
- Competition against other players in various challenges to win rewards
- A guild mechanic where you join a team and enjoy shared rewards
- Build mechanics where you build parts of a beautiful castle the more you play
- Mini-games with short, unique levels
There are several messaging lines that Royal Match can lead with, which are apparent throughout their ad creatives.
A refresher on CPPs, and what they’re good for.
Now that we’ve spent some time with Custom Product Pages, we’ve identified two main values to be aware of…
Value 1: Increase paid traffic conversion rates (CVR) and ROAS
The optimization value is pretty straight forward. Up until now, all of your paid traffic installed your app or game depending on a single product page which acted as the “ending” of a user journey.
The average team runs paid UA campaigns on multiple ad networks, employing campaigns with many different unique selling points as the creative strategies. Based on Storemaven tests that we’ve run over the past few years (more than 500M users tested), there’s a few clear factors that influence CVR:
- How close the messaging on the ad creative level is to the messaging on the App Store product page
- The preferences of a specific segment of your audience and the messaging on the App Store
Although the first point might be more straightforward, we saw in our tests that conversion rates dramatically decrease when there’s a mismatch between messaging on the App Store and audience preferences.
For example, players that tapped on an ad in a match-3 game would have a different motivation to download Royal Match than players who tapped on an ad in a PvP shooter game.
Value 2: Regain privacy-first, aggregated, and deterministic attribution data from Apple
This is a less known value of using Custom Product Pages. In App Store connect, Apple shares data regarding the performance of each CPP in terms of downloads, redownloads, retention, and sales.
This can be leveraged to get deterministic and aggregated attribution data that can help you make better UA decisions. If used properly, each CPP can surface the performance data and the quality of users coming in from specific networks and campaigns.
In the days since iOS 14.5 and the death of the IDFA, using CPPs for measurement (basically using Apple as a form of a privacy-first, aggregated, and accurate MMP) can’t be discounted.
Each UA campaign you run that utilizes a CPP allows you to regain the ability to calculate accurate ROAS.
Five things you must know about Custom Product Pages
The holistic CPP playbook to maximize your mobile audience growth
In order to capture these two massive values and boost your paid growth, we developed this five-step framework.
Step 1: Mapping
First step involves mapping your paid audiences (referral audiences in App Store connect lingo.)
The main points you need to understand here are:
- Where am I getting most of my downloads from?
- Which ad networks
- Which countries
- Which types of networks are we using? SANs (FB, Twitter, Snapchat, Tiktok, etc.) vs. Ad Networks (Ironsource, Vungle, Applovin, Unity, etc.)
Looking at Mobile Action data (thanks team!) we can see that Royal Match is utilizing many different ad networks:
* The percentages are based on Mobile Action data. Real data might be different.
The main action to take at this step is to cluster these sources as follows:
The reason for grouping like this? It’s driven mostly by the fact that in order to truly measure the value of different UA campaigns and channels with CPPs, you need a way to separate traffic at the CPP level (in App Store Connect) which is by looking at the sub-publisher (named app-referrers) level and filtering for results.
So with a CPP that gets traffic from Tiktok & and Unity, you can filter the app referrers that drive traffic to the page and see results separately for each of the networks. With ad networks that use many different sub-publishers as app referrers, you won’t be able to separate which app referrer is coming from which network.
In Royal Match’s case, we would cluster these ad networks to:
- Multi Domain SANs (self attributing networks) – networks that are self-attributing but have inventory on many different apps: we would put Google and Facebook here.
- Unique Domain SANs – networks that are SANs but have a single app where traffic is coming from, hence a single app referrer. We would place Twitter here.
- Ad networks – we would place Vungle, Unity, Google (Admob), Liftoff, Adcolony, Applovin and Ironsource.
Two more important clusters would be paid search on the App Store through Apple Search Ads and brand efforts (influencers, and email in Royal Match’s case most probably).
Now we have something like this:
Two clusters of UA sources. Those that can be blended together and use the same CPP, and those that require their distinct CPP for measurement purposes.
Step 2: Planning
Now, planning is the fun part. By analyzing the audience segments that currently comprise the entire paid UA audience, we can pinpoint the biggest opportunities for CPPs, as well as the main themes that run through some of the paid UA funnels.
To do this, you must analyze the sub-publishers that are driving the most value for your game and app, and understand the context in which users in these sub-publishers are coming from.
Storemaven’s Funnel Analytics solution helps you automatically analyze your Referral traffic which boils this entire process into a click of a button -> see it live
For example, let’s say that Royal Match zoomed in on the most valuable traffic segments and found three main contextual funnels.
- 40% of their paid referral traffic comes from Match-3 story type of games
Tapping ads like this one:
- 30% of their paid referral traffic comes from Social Casino games
Tapping ads like this one:
- 20% of their paid referral traffic comes from Build & Develop
Tapping ads like this one:
This analysis showed us there are, to begin with, three types of audience segments we can optimize towards. Of course, each one can be broken down further, but for simplicity purposes let’s keep it at three.
Looking at current Royal Match App Store Pages, a good three value themes to start with would be:
Step 3: Implementation
With the right themes in mind, it’s now time for implementation. You may not have 35 different creatives for CPPs just yet, but there’s still a ton of value to unlock by using CPPs with duplicate creatives and deploying them for different UA campaigns and channels to enjoy the measurement value.
One important thing to remember here is that App Store Connect doesn’t allow you to use more than two filters, so you can’t see results both at the sub-publisber level and a GEO level at the same time.
So it’s crucial you deliberately send traffic from one GEO per CPP using your UA campaign setup (it can be a group of similar countries as well). Once operating in this way, you know which GEO and which network/campaign the results in each CPP represent.
As for the contextual funnels we uncovered in the previous step, Royal Match can now easily analyze the sub-publishers they want to target through each network, set up a campaign with a white list of these sub-publishers, and deploy the CPP with the right theme.
You can deploy more CPPs by creating duplicate ones with the same creatives (so Royal Match could have i.e. 12 CPPs with the same Build & Develop theme creatives). As you create new ones and keep track of which product page ID gets traffic from where, you can enjoy that regained measurement capability.
So, back to our Royal Match example:
- Four CPPs will be dedicated to constant A/B testing (see here how to A/B test Custom Product Pages.)
- For each of the SANs, based on campaign targeting and GEO, a different CPP will be used with the right theme.
- For each Apple Search Ads campaign, a different CPP will be used that matches that campaign’s audience context (searching for brand keywords, competitor keywords, and more general genre keywords such as “match-3”).
- For each of the ad networks, after Royal Match identified which sub-publishers belong to each contextual group, (Build & Develop, vs. Casino vs. Match-3 stories) the UA team will set up a campaign with a dedicated white list and deploy the matching CPP.
This will ensure both the conversion rate and ROAS of each campaign is maximized by matching the most relevant product page to the campaign’s audience and ad creatives, as well as getting the measurement for each of the campaigns at a CPP level.
Step 4: Measuring
So what does this CPP measurement look like?
This is a game changer, as you can now see aggregated and privacy-first data on campaign performance powered by Apple.
If you implement CPPs according to the implementation plan, you have a new avenue to see the revenues coming in from each campaign, compare it to its cost, and calculate accurate ROAS again. This includes Facebook campaigns as well, which immediately gives you back the visibility you need to make better UA decisions.
Step 5: Monitoring & Optimization
As we started out with just three themes, over time there will be more and more opportunities to unlock. In our Royal Match example, they might find opportunities with audience segments and funnels that are driven by competition, cooperation or even progression in an endless world.
For each new opportunity, the four CPPs dedicated for testing can be used to test different messages on these new audiences, choose the one that performs the best, and then deploy it by setting up a new UA campaign with the relevant white list.
When identifying that a certain CPP is underperforming, it signals that a creative strategy’s effectiveness might be decaying.
By monitoring CPP performance over time, you can quickly identify performance drops and go back to testing using your four test CPPs.
In our Royal Match example, after a couple of months the creative strategy used to build the Build & Develop theme is less effective, and a refresh is needed to increase conversion rates back up.
Two work processes you need to implement with ASO & UA
When setting up a new UA campaign
Make sure you always choose a CPP for the campaign that matches the audience you’re targeting in terms of creatives and messaging. When choosing the CPP, make sure to look at your UA clustering so you don’t mix and blend sources that will make it impossible to measure the effectiveness of that campaign through CPP data from Apple.
When looking to optimize conversion rates and ROAS
A robust testing process should be deployed. At any given time, there is no reason why you can’t run a test to improve CPPs performance. These a/b tests are native, easy to run and set up. And by always identifying your top opportunities as well as your lowest performers, you have the comfort of always seeing conversion rates maximized as every case is handled. This means:
- No big opportunity exists in terms of a contextual audience segment that can’t be leveraged with a CPP to maximize conversion rates and ROAS.
- No important UA campaign is being left behind in terms of measurement when you’re pointing it to a CPP and getting the data back from Apple
- No performance drops without them being handled by getting back to testing.
In a nutshell – you’ll be maximizing your impact on your org and team. You’ll be implementing a world-class system for paid conversion rate optimization and measurement in the App Store. You’ll be safeguarding your future from relying on temporary fingerprinting technologies for measurement and have a robust UA decision-making engine once again.
You’ll master CPPs.
Need some help with your CPP strategy to boost your conversion rates and ROAS? Storemaven has built the CPP stack you deserve.
- Storemaven’s contextual advertising CPP planning solution, Funnel Analytics, allows you to achieve the mapping and planning stages with ease.
- Your CPP management, measurement, and monitoring hub provides you with everything you need to measure and monitor your CPP performance.
- Your CPP testing and optimization tool gives you everything you need to setup CPP a/b tests natively on the App Store and keep testing, always.
If you’re looking for help or guidance on how to deploy your CPP strategy, or you’re looking to get a team to manage the process for you, let’s chat.