New guide: How to run high-performance user acquisition on iOS with SKAdNetwork

  • User acquisition on iOS is broken
  • Overall return on investment is down 38%, and spend is still down by 25%
  • But there is a solution

Privacy isn’t going anywhere, and rightfully so. App Tracking Transparency and SKAdNetwork are here to stay, and while they will likely add new features over time to help marketers optimize user acquisition campaigns, we are never going back to the device ID free-for-all that enabled permissionless tracking and measurement.

At the same time, the reality is that user acquisition on iOS is still largely broken.

Not only has it been challenging for marketers to adapt to the new realities, fundamental metrics and data that advertisers need to run, measure, and optimize campaigns are simply missing. We see the results every day in inefficient campaigns and suboptimal ROI.

Getting expert at SKAdNetwork

So what’s the solution?

Getting expert at using SKAN … and picking the right tool that makes it possible. That’s precisely why we wrote Singular’s brand-new SKAN guide. We call it High-performance UA on iOS using SKAN: How to make it work.

Singular recently released SKAN Advanced Analytics, a new set of features and capabilities that fix the fundamental problems inherent in SKAdNetwork. In a brutally concise way, the SKAN guide walks through each of 7 major problems marketers face when using SKAdNetwork to accomplish attribution.

They are:

  1. missing data
  2. randomized timing of postbacks
  3. limited conversion data,
  4. limited time for conversion value updates
  5. limited campaign attributes
  6. complex conversion value encoding
  7. missing cohorts

The guide explains each problem, details the impact, and then outlines a simple and clear solution for every one.

The solution is using SKAN Advanced Analytics

The solution is using SKAN Advanced Analytics to enrich campaign data, decode conversion values to KPIs, estimate performance even when there’s missing data due to privacy thresholds, and provide usable cohorts for long-term LTV and ROAS calculation.

SKAN Advanced Analytics builds on sophisticated data science, modeling, and machine learning to provide reliable and actionable information. The results are impressive: 87% D7 revenue accuracy on average for clients who beta-tested it.

But don’t take our word for it:

“At Space Sheep Games, we depend on a consolidated view of revenue from in-app ads and IAP to understand ROAS. Partnering with Singular has been super valuable as they are at the forefront of the changes in the market.”

Rene Retz, CEO of Space Sheep Games

Growth marketers from Qiiwi Games, Rovio, Space Sheep Games and many more mobile publishers are finding ways to get the near real-time predictive data they need to optimize campaigns on the fly, and the sophisticated conversion models they need to capture all revenue, regardless of source, and calculate ROAS in ways they previously couldn’t.

“Our strategy has been to embrace the change in paradigm, turn this disruption into an opportunity to grow our business, and build a future-proof UA infrastructure. Singular has undoubtedly been instrumental in helping us pioneer the new ways of running acquisition.”

Kieran O’Leary, COO, Rovio

The result is performance mobile marketing at scale and speed that works for marketers and maintains full and complete compliance with Apple guidelines. In other words, privacy-safe marketing measurement that doesn’t suck.

How to get started

Get the guide here.

You’ll be able to scan it in a few minutes, recognize the challenges, and identify the solutions you need for your growth campaigns. Then you can request a demo and get personalized insight into how SKAN Advanced Analytics can help you deliver the growth you’ve been working so hard to achieve.

“Collecting and analyzing data from SKAdNetwork can quickly become a time-consuming pain. Singular’s SKAdNetwork suite has helped us improve significantly. We’ve been able to optimize data collection and BI models to match our needs and to accurately predict future revenues.”

Marcus Dale, CTO of Qiiwi Games

iOS Performance marketing is back: Singular’s SKAN Advanced Analytics provides accurate D7 revenue

May 18, San Francisco: Singular announces SKAN Advanced Analytics to restore mobile marketers’ ability to run high-performance, predictable, and privacy-safe user acquisition campaigns on iOS.

Since Apple launched iOS 14.5 with SKAdNetwork for ad results measurement, mobile user acquisition spend is down 25% and marketers’ return on advertising investment is down 38%. SKAN increases privacy, but it has multiple challenges, including:

  • Missing data due to privacy thresholds
  • Randomized timing of attribution
  • Limited conversion value reporting
  • Lack of cohort metrics

As a result, it’s hard if not impossible for app publishers to accurately calculate LTV and ROAS. It’s difficult to estimate the value of their new users, making it challenging to optimize ad campaigns and confidently invest in marketing.

Singular is solving those problems with SKAN Advanced Analytics. Using only privacy-safe data that Apple provides via SKAdNetwork and aggregated, non-personal, campaign data from ad partners, Singular is applying data science and machine learning to fill the gaps.

Today we announce the latest update to SKAN Advanced Analytics, SKAN Cohorts, which returns visibility of critical KPIs that marketers currently lack due to SKAdNetwork limitations. The results in real-world tests are nothing short of astounding, reaching 87% D7 revenue accuracy on average for beta clients. 

“Our strategy has been to embrace the change in paradigm, turn this disruption into an opportunity to grow our business, and build a future-proof UA infrastructure,” says Kieran O’Leary, COO, Rovio. “Singular has undoubtedly been instrumental in helping us pioneer the new ways of running acquisition.”

“Collecting and analyzing data from SKAdNetwork can quickly become a time-consuming pain. Singular’s SKAdNetwork suite has helped us improve significantly,” says Marcus Dale, CTO of Qiiwi Games. “We’ve been able to optimize data collection and BI models to match our needs and to accurately predict future revenues.”

SKAN Advanced Analytics helps take the marketing landscape back to the pre iOS 14.5 days with improved reporting accuracy and visibility into cohorted metrics that have been unavailable for over a year. Marketers can now confidently rescale their iOS ad spend knowing accurate measurement is guiding their investment decisions.

Key solutions in Singular’s SKAN Advanced Analytics include:

  • SKAN Modeled Metrics
    Using available data and historical trends, Singular models events and conversion values that Apple censors for privacy protection.
  • SKAN Smart Conversion Management
    Singular provides 7 different conversion models to maximize data marketers get from the 6 bits of conversion data SKAN returns.
  • SKAN Instant Campaign Optimization
    Singular provides near real-time predictive D7 LTV calculations that enable instant campaign optimization for ad partners.
  • SKAN Cohorts
    Singular provides estimated cohorts that give marketers visibility into critical measures like revenue and ROAS for campaigns.

Singular’s SKAN Advanced Analytics is built on the first-ever and still industry-leading iOS user acquisition attribution solution that includes SKAN Advanced Reporting, enriching conversion data with aggregated cost and click data from ad networks. Along with powerful out-of-the-box features and easy set-up, Singular’s SKAN solution enables superior analytics and insight that winning mobile marketers need.

“We’re 100% committed to user privacy, and we’re also 100% committed to giving marketers the data and tools that help them drive massive growth,” says Singular CEO Gadi Eliashiv. “We’ve always believed those twin objectives are not in conflict, and now with our advanced AI and data science, we’ve delivered a solution that proves it.”

“At Space Sheep Games, we depend on a consolidated view of revenue from in-app ads and IAP to understand ROAS,” Rene Retz, CEO of Space Sheep Games. “Partnering with Singular has been super valuable as they are at the forefront of the changes in the market.”

More information: Singular’s SKAN solution

Access the new guide for marketers: High-performance iOS UA: How to make SKAN work

About Singular
Singular’s next-gen attribution and analytics powers marketers to grow faster by uncovering accurate, granular, and timely performance insights. World-class teams from brands like WB Games, Twitter, Lyft, Rovio, Airbnb, Activision, Homa Games, EA, LinkedIn and more use Singular to make smarter user acquisition decisions and analyze the impact of every ad dollar with full-funnel marketing analytics, best-in-class ad fraud prevention, and automatic loading directly into your BI tools.

Scaling ad revenue in 2022: insights from GameHive, By Aliens, Unity, and Singular

It is a great time to monetize apps with ads.

There was almost $300 billion spent in mobile advertising last year alone, and it’s projected to jump to over $400 billion by 2024. Millions of apps have a hybrid revenue model, ads and in-app purchases, while millions more are primarily or completely ad-focused. Business is booming.

It is also a horrible time to monetize apps with ads.

Tracking and attributing ad revenue on apps has always been hard, especially if you want to correlate revenue to user acquisition partners and marketing campaigns. It’s become even more challenging in the past year as SKAdNetwork has made tracking tougher, and Google’s Privacy Sandbox promises to shake up the Android side of the ecosystem in the foreseeable future.

So what is a hardworking mobile monetization professional to do?

Check out our recent webinar, of course, with experts from GameHive, By Aliens, and Unity joining Singular to shine a little light on solutions for the challenges and break through the roadblocks with a few openable doors of opportunity.


Check out the full on-demand webinar here: Scaling ad revenue in 2022


However, we also want to share a few highlights here. Think of it as your 5-minute webinar recap, provided by:

  • GameHive’s growth marketing manager, Hafsa Akhlaq
  • Unity’s partner manager of publisher operations, Bryan Streit
  • By Alien’s ads and monetization coordinator Edwin Asberg
  • Singular’s director of product analytics Lisi Gardiner

Let’s dive right in …

UA and monetization misalignment?

What happens when user acquisition teams and monetization teams aren’t aligned? You’re spending money without making money:

“Without having them aligned, it’s kind of like building a bucket with holes with water,” says Unity’s Bryan Streit. “Everything [is] going … to spill out.”

You also miss opportunities:

“We have situations where our ads monetization managers are able to identify new opportunities for UA campaigns that our UA teams can potentially test out,” says GameHive’s Hafsa Akhlaq. “Things like running a UA campaign in a geo where we have high ads watched per DAU, and it’ll probably be cheaper to acquire users over there.”

And you impair future growth possibilities:

“What a lot of people don’t realize is that, with ad inventory, what you’re selling can become more valuable when you actually grow your audience and add valuable players,” says Streit. “If you’re able to purchase high-value players that are coming back after day seven, and they’re going for in-app purchases, the value of your user base is going to be much more, so this kind of creates a loop where you’re able to buy more valuable users, generate more money, then dedicate more money to the UA campaigns.”

Why do you need granular ad monetization data?

Without granular data by campaign and even cohort, it’s really hard to grow ad-supported apps. You simply don’t have the data to optimize.

“We want to attribute ad revenue back to each UA campaign and really get an understanding of the quality of users we’re acquiring from that campaign and then from that network,” says Akhlaq. “It gives us a better understanding of what we’re doing when we’re optimizing … where to really push or where to scale back, especially when we’re optimizing on the publisher level.”

But averages aren’t enough.

Why? Because ad whales exist.

“By only looking at averages, we will miss and we’re gonna be blind on the extremes,” says By Aliens’ Edwin Asberg. “So we will never know which campaign is performing the best, which campaign is performing the worst, and specific to the user, which users are performing the best and the worst … we wouldn’t be able to optimize our games for those specific targets and specific players, specific behaviors.”

What’s the benefit of instant in-app ad monetization data?

Knowing what happened is good. But knowing what is happening quickly enough and in the right place to be able to use that data to positively influence the future is great. And that’s a key differentiator between those who monetize apps and those who MONETIZE apps.

“What’s really been a game-changer for us and for our clients has been making the switch from having the ad revenue data available offline to having it available via the game itself … being able to pass it through the Singular SDK itself, in real-time,” says Singular’s Lisi Gardiner. “We’ve been able to use this data to build ad revenue SKAN models but also mixed models, including session data and ad revenue data. We’ve also started being able to post back this data to the UA sources. Because it is impression level, we can then, you know, combine it and then send it back to the UA source. And so these things have really changed how our gaming clients are basically optimizing and tackling their growth activity.”

In other words, instant optimization of new user acquisition via real-time ad monetization data that marketers can provide to ad partners to tweak and tune campaign parameters.

And it’s not just about future-focused marketing optimization.

It’s also about live ops for existing users: optimizing their game or app experience and therefore also positively impacting retention, revenue, LTV, and ROAS all at the same time.

Because there’s an “ad journey,” just like there’s a customer journey.

“It gives us, essentially, the power to evaluate each player differently, their specific player behavior, and then also spot any irregularities or areas for opportunities,” says GameHive’s Akhlaq. “Are we showing them too many ads? Are we not showing them enough ads … all of this just comes together for us to really tailor the user ad experience … we want players to have the best journey inside of our app. So when they come in, if they’re more likely to watch ads, we give them the opportunity to do so. If they’re not going to watch ads and instead they’re more likely to make a purchase, that we then offer them more enticing bundles in the shop. So it really just allows us to tailor the ad journey, something that we’re continuously taking a look at and working on.”

Bringing the product team into acquisition and monetization conversations

There’s another big team that’s critical to solving for quality user acquisition, health levels of monetization, and optimal customer retention. And that’s the product team, which too often doesn’t have a say in acquisition or monetization mechanics and particulars.

That might be key in, for example, choosing ad formats:

“When it comes to ad format, we make sure that they’re non-intrusive as possible,” says Akhlaq. “For example, inside Tap Titans 2 we have a fairy ad placement that kind of flies across the screen. And you know, to someone else, it might be, like, ‘Okay, well, that’s a bit disruptive,’ but when you take a look at our app, it’s actually very native to the actual gameplay, and it’s something that gets a lot of traction. So it’s something that works well with our players.”

Planning is essential, but so is reviewing performance.

Including how users reacted to ads on multiple measures of that experience, not just revenue.

“We always look at control metrics [and] engagement metrics: retention, session time, etc., because even if our success metric is pretty positive in that specific test but any control metric is pretty low, we discuss with other teams as well the decision to take after that test,” says By Aliens’ Asberg. “So basically, we’re not going blindly with the result of the metric as we’re evaluating, but we see also the impact on other aspects of the game, in this case, the experience of the user.”

Interestingly, By Aliens doesn’t just do that via hard data. The team also uses an ancient tool of marketers: surveys.

While not technologically sophisticated, there’s no better way to get affinity and emotional response insights from users or customer than simply asking them. And, of course, parsing their responses intelligently.

Also: it’s important not to treat every user the same.

“When talking about ARPU and user retention, it’s really all about LTV,” says Unity’s Streit. “And that’s where understanding user base and really understanding the segments and the cohorts within your user base becomes incredibly important. So if you have an IAP whale user, you do not want to give them the exact same experience as someone that’s been in the game for 90 days and that’s never made an IAP purchase. Those are two completely different users, have two completely different play styles, and they deserve two separate experiences to really tailor the game experience to how they play the game.”

When ATT hit, the sky did not fall

While the world changed significantly for mobile marketers on iOS when Apple introduced App Tracking Transparency and SKAdNetwork, the sky did not fall. And mobile growth did not become impossible.

“It changed everything. It also didn’t change everything,” says Streit. “The users are still out there. They didn’t go anywhere. It’s just our ability to communicate with the users has changed a little bit. So developers have had to learn how to best deliver the ATT prompt and manage those data flows, but the basis of providing a good ad product experience in the game remains the same.”

Marketers and developers also had to learn how to deal with different kinds of people in their apps with different levels of data and insights.

And recover from some initial disasters.

“We saw a huge drop in our CPMs. We saw a huge drop in our ads revenue,” says GameHive’s Akhlaq. “Then we were able to figure out some ways to kind of mitigate some of those impacts and get back on track. We found that splitting out our traffic into personalized and then non-personalized setups, and then having different setups, essentially, allowed us better optimize and capture impressions at all price floors.”

And SO MUCH more

There’s a lot more I can’t add in this blog post. Fortunately, the scaling ad revenue in 2022 webinar is available on-demand right now.

Check it out to learn more about:

  • evaluating ad partners
  • pros and cons of mediation platforms
  • programmatic vs waterfall vs hybrid monetization models
  • why some publishers are sticking with waterfall set-ups
  • keys to optimize your ad monetization waterfall
  • ad placements and formats to watch
  • segmentation and monetization

Plus, each webinar panelist adds their own top tips for mobile app monetization, and we answer live questions from the audience. Check it out at the link above.

Google updates Privacy Sandbox: explicitly details MMP role, web-to-app journeys

  • Google updated Privacy Sandbox for Android documentation
  • It’s pretty much as we’ve blogged
  • Google explicitly acknowledges a role for MMPs in attribution
  • Google shares web-to-app conversion paths

Unless you’ve been under a rock or been totally heads-down on your own growth initiatives, you know that Google announced Privacy Sandbox for Android about three months ago, saying at the time that Android’s ATT moment — the deprecation of the GAID — was inevitable.

Now we have more details on exactly what that future of attribution on Android looks like.

MMPs and Privacy Sandbox for Android

Google has broken it down in a simple timeline, and explicitly adds the concept of a mobile measurement partner (MMP) quarterbacking the attribution process.

In the real world, advertisers are running hundreds or thousands of campaigns with dozens of partners, meaning that issues around attribution and incrementality can get complicated. Google’s simplified example shows two adtech partners — one of which could be Google, but not necessarily — both running campaigns for a mobile app publisher.

A smartphone owner taps an ad from both ad networks while also viewing an additional ad later from one of them. 

Interestingly, as we’ve talked about before, adtech providers can set the priority of what Google calls sources: clicks, views, and potentially other pre-install indicators. They are not the only ones, however. MMPs can also set priorities for sources.


Remember, in Privacy Sandbox for Android:

Sources = views and clicks

Triggers = installs, sign-ups, purchases


In the example above — and likely in many real-world scenarios, the ad networks prioritize clicks over views, as does the MMP. (Of course this could change in the case of video ads, in-game ads, audio ads, or other formats that are not standard clickable in-app ads.) For each adtech partner, the most recent high-priority source gets credit, so in spite of the fact that Adtech A in the image above registers both a click on Day 1 and an ad view on Day 3, the click gets the credit.

Attribution credit …

As currently set up, Privacy Sandbox for Android assigns attribution credit to each source, even if there’s only one install. In other words, both Adtech A and Adtech B get attribution notifications from Privacy Sandbox. 

Google clearly states that both get credit for the one install:

However, only the MMP — which sees both sides — knows that both ad networks got those postbacks for the same install.

Since Google knows that everyone getting credit for everything is typically bad, ensuring an MMP is in the mix is a good idea to stop a new Privacy Sandbox form of click spam from getting credit for everything. And it’s also important to use deduplication keys:

“When an advertiser uses multiple ad tech platforms to register the same trigger event, a deduplication key should be used,” Google says. “The deduplication key serves to disambiguate these repeated reports of the same event. If no deduplication key is provided, duplicate triggers may be reported back to each ad tech platform as unique.”

While there’s no talk of multi-touch attribution (MTA) here, there’s clearly an emerging capability for an MMP, which sees all the sources and triggers, to provide a very nuanced view of an advertiser’s performance across all paid media partners, giving publishers much better visibility into how their ad campaigns deliver incremental impact. Expect some surprises here, and expect this to change how performance marketing campaigns are built and optimized.

Web-to-app as well as app to web and other combinations

Google also updated multi-channel app install customer journeys, saying that “all combinations of app- and web-based trigger paths are supported.” This of course makes perfect sense: while we’re primarily dealing with Privacy Sandbox on Android here, the entire effort is built on insight and technology that originates from where Privacy Sandbox was first seeded: the web.

That means …

  • App to app
  • App to web
  • Web to app
  • Web to web

… is all part of the plan from the beginning.

And that is precisely what we’ve been hoping for on the iOS side of the table, as we said in May of last year:

With Private Click Measurement, Apple gave us a tool to measure app to web journeys in SKAdNetwork. That’s great, but we also need tools to measure web-to-app journeys.

Getting it on Android makes it more likely that this will arrive on iOS, and since on iOS Apple — like Google on Android — controls the entire mobile operating system, it should be possible. Certainly in mobile Safari, but also in other browsers if a) Apple creates open APIs, and b) Google and other browser makers use them.

In any case, this is good to see from Google: there’s a clear path to high-quality privacy-safe advertising measurement and attribution on Android.

More on Privacy Sandbox for Android from Singular:

Also, here’s a new high-level video from Google for a quick introduction:

Facebook’s not-for-drinking IPA and the United Nations of marketing measurement

You might say it’s kind of the best of times and the worst of times in marketing measurement, with apologies to Charles Dickens.

Because knowing who a person is and which device from where is accessing a service is undergoing wholesale change from a marketing point of view in the age of privacy. IDFA is gonzo, GAID is on the way out, and as any web marketer has known for years now, third-party cookies are an endangered species.

Not shockingly, all of that is changing ad targeting, marketing attribution, and campaign optimization. So times are tough, in a way. But in another very real sense, it is apparently the golden age of measurement technology. Why? Because we are seeing a huge amount of innovation in the space.

  • Apple: SKAN
  • Google: Privacy Sandbox (web and Android)
  • Brave (and others): Blockchain solutions
  • IAB: Project Rearc
  • And more … ID5, Unified ID 2.0 from The Trade Desk … and so on

Plus, of course, there’s a solution from Facebook: IPA.

Interoperable Private Attribution from Facebook … err … Meta

But IPA is not the kind of India Pale Ale you can drink in an English bar. Instead, it’s Interoperable Private Attribution, and it is yet another solution to the eternal marketing dilemma: answering that simplest of questions with far-too-complex answers … what’s working?

And, of course, answering that in a privacy-safe way.

If you’ve checked out Privacy Sandbox for Android, you’ll see a few similarities, Singular CTO Eran Friedman says. The Facebook/Meta IPA proposal is based on three general concepts:

  1. Match keys
  2. Event generation with sources and triggers
  3. Aggregate attribution measurement

Match keys coordinate between publisher data and advertiser data, and crucially have to be built into the computing environment: the browser on the web, or the mobile operating system on smartphones and tables.

“If a user does an action and clicks an ad in one app, and then triggers a conversion in the advertiser app, then there will be a matching key to kind of connect the dots. Then the other piece is the events … two types in the IPA … the source events which happen in the publisher [app]: things like an impression, a click things that the user does in the publisher, and then they have trigger events which happen in the advertiser app.”

Eran Friedman

Those are similar, Friedman says, to conversion events in SKAN, and connect to sources via the match keys.

Double the privacy protection?

However, that’s where Facebook adds yet another layer of privacy protection. Welcome to the concept of trusted servers … or at least semi-trusted.

“They defined a concept of ‘trusted servers’ essentially, which are kind of unbiased, third party services that receive these encrypted postbacks with match keys and trigger events. And these are the ones that are able to decrypt the information and then provide very granular data to both ad networks and advertisers would count how many conversions came from the sources and basically power attribution based on these encrypted postbacks.”

Eran Friedman

Where Privacy Sandbox has a single aggregation service for a trusted third-party, Facebook’s system is designed for two “semi-trusted” services, and both are essential. No single third-party can decrypt the postbacks on its own, making it less likely that any single entity could break privacy in the system.

Advertisers themselves and ad networks could get full data with the help of the semi-trusted services, but the semi-trusted services themselves would have only partial visibility of the granular data.

There is a problem, however.

Because Meta/Facebook is who it is and not Apple or Google, it doesn’t own a mobile operating system or a web browser. While IPA has been built in partnership with Mozilla, which owns the Firefox browser, that only accounts for maybe 3.5% of global browser market share. The obvious question is: why would Apple (iOS, Safari) and Google (Android, Chrome) build support for Facebook’s attribution methodology, Interoperable Private Attribution?

Short answer: they probably won’t.

United Nations of marketing measurement

Which is essentially the reason we need a United Nations of marketing measurement: an entity to bring all the methodologies and technologies from all the platforms and stakeholders together.

Given that the odds of this happening are roughly similar to the UN brokering global peace or solving world hunger tomorrow, the implication is clear.

MMPs like Singular are the trusted third parties of marketing measurement and essentially have to provide an abstraction layer over all the multitudinous methodologies from all the battling players in the market. That abstraction layer then gives marketers a single source of truth without them having to know all the individual intricacies in each platform’s chosen attribution solution.

“We always saw ourselves as the ones who have the role to navigate advertisers and the industry through. Our goal is always to see what we have to work with and build the tools and the reporting capabilities, the management capabilities, so that whenever someone wants to use a tool among the vast toolset that they have, it’s seamless for them to try something out, see if it’s insightful for them, see if it’s relevant for them to use.”

Eran Friedman

But the massive diversity — though it offers challenges —- isn’t all bad.

It’s also driving innovation, Friedman says, since Google could see what Apple did, and Facebook can look at both, and all can come up with better versions in the future.

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MMP in 2030: marketing measurement from the future

What does an MMP look like in the year 2030?

Well to start, no-one knows what “MMP” stands for anymore.

We’re in a time of massive change in mobile, in marketing, and specifically in the niche of marketing that is specific to mobile user acquisition. It’s an odd niche: there was no website user acquisition in the early days of Geocities and Friendster and Homestar Runner. But it’s an important and lucrative niche because mobile was the first truly personal computing platform. Built on the three-foot device (never more than three feet from your body) mobile offers unique access and intimacy to customers (users), making a mobile app install more valuable than a newsletter subscription, a website visit, or any of the other precursor actions to monetizing attention, service, or product in other customer acquisition modes. 

MMPs were built to optimize growth in that niche, but the world is changing. What does the mobile measurement platform of the future look like?

MMPs beyond mobile

This is no shock. 

Any MMP worth its salt is, if not omnichannel, at least multi-channel, with extensive technology to measure and optimize web-based journeys, old-school TV, connected/smart/OTT/streaming TV, email, and multiple other digital and non-digital channels. Sometimes that verges on simplistic — put a Singular link on a billboard, and boom! you’ve got a checkmark in the out-of-door category — and sometimes that’s sophisticated: correlating connected TV ad campaign impacts with app installs and/or marketing conversions via intricate data science.

But it goes beyond the obvious.

With the hundreds of billions of dollars being invested today by Apple, Meta, Google, Microsoft, and thousands of other companies globally to invent the next major computing platform, getting a “user” or (better yet) a customer won’t mean someone installing an app on a slab of glass and metal that slides into their back pocket. 

At least, that’s not all it’ll mean.

Because “MMPs” aren’t first and foremost mobile measurement platforms, they’re first and foremost measurement platforms. The “mobile” part of the name is a modifier, and it could easily be replaced by smartglasses or wearables or even some futuristic cloud-based edge-capable personal AI that inhabits all of our devices and, like Tony Stark’s super-awesome but completely unrealistic Jarvis, has all the required data, access, answers, and insights we need at any given moment.

A world beyond mobile

Not shockingly, the world is not standing still.

For my Forbes columns and TechFirst podcast, I’m tracking at least 11 megatrends from smart matter to infowars to greentech and automation. Several are most relevant for apps, publishers, brands, and marketers, including:

  • Artificial intelligence
  • Virtuality
  • Decentralization
  • E-dentity

I’ll go into more detail on these in a subsequent post, but suffice it to say that technological, social, and political changes are impacting the landscape in huge ways. Privacy will continue to grow. We’ll move farther towards a Ready Player One-style metaverse, continuing on the path we’ve walked since ARPANET more than 50 years ago and the first dim stirrings of HTTP in 1990. The yin and yang of centralization-decentralization will continue its pendulum swing, now trending (at minimum in terms of hype) in the direction of decentralization. And AI will infuse literally everything, becoming a core foundational piece of apps, software, and services.

With that as context, here’s a few things that you can expect in an MMP of the future.

One note:

Don’t take the 2030 date too seriously. Many of these exist today in some form. Many more are coming much sooner, but will be much more fully developed. And if I miss something you think should be on the list … let me know!

M is for multiple, many, and multitudinous

It’s obvious today but it will be increasingly necessary: marketing measurement platforms increasingly need to ingest data from a huge number of data sources. That doesn’t just mean many platforms and thousands of ad networks like Google, Facebook, ironSource, and Applovin. It means dozens if not hundreds of fundamentally different kinds of sources, often using vastly different methodologies, and combining it all to create data-driven insight.

Today, that looks like this:

  1. IDFA (in very limited supply)
    Some apps still generate a significant percentage of opt-ins, which can still be useful depending on the other party in the adtech ecosystem getting opt-in as well. But I’d be shocked if IDFAs were still available in eight years.
  2. GAID
    At least until 2024. After that … see #4 …
  3. SKAdNetwork, or SKAN
    Apple will probably be on SKAN v5 or v6, but the broad strokes will likely be the same: no granular data, privacy-first, minimal marketing data.
  4. Privacy Sandbox on Android (and web!)
    Privacy Sandbox will be mature and full-featured and very usable, while still keeping granular device-level data behind a privacy shield.
  5. Cost & campaign data from ad partners
    Wherever brands are investing in properties and buying ads, cost and campaign data will be available, providing both network-reported inputs (views/impressions) and network-reported results (clicks/actions).
  6. In-app data
    Think of “app” broadly here … while it might be in some kind of mobile device like a smartphone, it could be an app on a pair of smartglasses or it could be embedded in another kind of device. The data will still be first-party data via logging, a CRM/DevOps/LiveOps type of tool, and marketing measurement or attribution SDKs or APIs, but each platform will have slightly different rules on what data brands can access or export, even if it’s on a first-party basis.
  7. Store data
    App Store, Google Play, alternative app stores, and app stores on emerging platforms like VR and AR: all will generate somewhat analogous datasets around installs, ads, CTR, and A/B tests.
  8. Alternative economy data
    Of course most MMPs ingest data about in-app purchases and ad monetization inside apps, but increasingly we’re seeing the rise of complex economies using platform or brand stores of value or cryptocurrencies. Increasingly we’ll also see these start to bridge apps and platforms, and they’ll be a more and more important measure of the health and growth of an ecosystem that publishers want to measure. Think blockchain-query-requiring insights like activity, value, recency, frequency, engagement, and so on.

Tomorrow, who knows what that will all include. Some parts are obvious, but some we won’t even really be thinking about today. Some options:

  1. World data
    Weather? Sure. Climate trends? Macro-economic trends? Micro or geo-specific trends? Sure. Hype and buzz from all different areas of communities and verticals that drive people’s time and purchase behavior, both specific to a brand, specific to a vertical, and general but applicable to your business? Absolutely. Some of this happens today, particularly in massive and slow old-school incrementality measurement methodology, but it’s all going to get much more sophisticated.
  2. Cloud gaming
    Well, it’s happening today, and is likely to continue to grow …
  3. Emerging platforms
    Car operating systems, home operating systems, edge device data …
  4. Additional sources
    We don’t know about them yet … but guaranteed there will be more than matter.
    1. Apps on Starlink? 
    2. Mesh protocol services? 
    3. Darknet products to cross splinternets?

Over the next six years, these sources will have to be broadened to multiple app stores (even on iOS) and multiple platforms both handheld, wearable, desk-bound, audible, home-focused, car-focused, and more … plus all the ad networks and marketing tools that grow up around each of them. 

And, as I’ll chat more below, they’ll all add up to increasingly useful incrementality measurement in an age of aggregation not granularity, data but not trackability. Call it science, call it art, call it magic, incrementality is getting better and better and will be a source of not-quite-real-time insight for both strategic and tactical use.

Connected … built in to all your tools

MMPs like Singular already tie into major publishers’ data architecture via API or ETL, but BI is ridiculously bespoke today. Every publisher has something just a little different (or a lot different) which takes time, energy, and focus to build and maintain, and privileges the large and wealthy.

Expect this to get easier and quicker in the future, where the data you need for custom purposes is instantly connected/integrated/used in any tools you wish. Including, if you wish, your ad partners’ platforms.

Always-on continual incrementality testing

As mentioned above, this will become standard. Sure, this is in some sense already doable today, but it’s still fairly clunky and of debatable value: more strategic than tactical. It will become much more integrated into default, automatic marketing platforms.

Aligning the marketing campaigns you want to run against the measurement outputs you want to have — including always-on continual incrementality testing — should be automated right from campaign inception to close, with near-real-time reporting on how incremental each channel and effort actually is. And, of course, marketers should be getting suggestions (and perhaps also automated changes, see below) on adjusting spend and channel mix to minimize duplication or overlap, and maximize results at a given level of ad spend.

Modeled single source of truth

We’re operating in an increasingly uncertain world of performance marketing. 

With the death of granularity, privacy thresholds, censored data, and missing campaign information already on iOS and coming soon to a theater near you on Android, few things are certain. (Although, let’s be honest, in the IDFA/GAID last-click era, certainty came with the cost of some amount of correctness: the world and a customer journey is much more complex than one click and one conversion.)

Multi-touch attribution as a function of near-total tracking is dead. Modeled attribution that intelligently mixes deterministic but aggregated platform data with first-party usage data with marketing inputs data will give marketers a model of reality that they can trust.

Within certain parameters. Plus or minus a certain percentage.

Some things are certain: when you act, there are impacts. Modeling those in an increasingly complex world of marketing data will provide a single source of — if not truth — or at least reasonably trustworthy truthiness.

And that will serve as a firm-enough foundation for future action.

Intelligent

There’s a significant amount of artificial intelligence built into a modern MMP, and it’s continuing to grow fast. Particularly in areas where you need modeled measurement due to censored data, or predictive analytics.

But the MMP of the future requires much less effort and knowledge to set up, and much less challenge to get what it knows out. Natural language queries? Sure, we’re seeing them already and they will be commonplace. Conversations with your measurement partner? Absolutely. Anticipating your needs and providing you the data you want when you want it, in the format you like it? Sure. Ad fraud warning signals? You bet.

Automated alerts are here already, mostly for known knowns and known unknowns. What about the most dangerous class of events, unknown unknowns? Brand danger due to a completely unrelated news incident in which someone wearing a t-shirt with your logo did something unspeakable in what is now a viral VR video? 

You get the picture.

But that’s just the beginning. Today we’re already using machine learning to drive modeled insights. Tomorrow the inputs will be much more complex and the models much more refined.

Automated

Marketers can automate a lot today, including spend. There’s a lot more to come, including goals, recommended campaigns, suggested spend, plus automated shifts as the platform detects opportunities or weakness. Also, think AI-built creative changing automatically with AI-driven intelligence as your measurement platform senses failure. Tailored, of course, not just by platform or channel but across the board as winners and losers become clear.

Much of this is doable today in part. 

It’ll all get significantly easier.

Almost extinct

OK, sure, this is a bit tongue-in-cheek. But let’s be honest: ad networks like to own their own measurement (why could that be?) and suites continue to grow. The independent measurement platform that is solely focused on best-in-class marketing insights is in some sense an endangered species.

However, there are still some independent players with a hard focus on marketing intelligence for their customers. To continue to grow — and exist — they increasingly need to play well with others, so privacy-safe data can continue to flow.

Marketing measurement’s role: make it all make sense

Nothing changes.

For an MMP of the future, nothing changes in the ultimate mission. Which is, of course, to make it all make sense. What is the correlation between everything I’m doing to everything I’m getting … and which parts of what I’m doing are driving the best parts of what I’m getting.

When marketers know that, they have power. Power, quite literally, to change the future in ways that boost their brands’ growth.

That’s the MMP — if the acronym still exists — for 2030.

In-game ads exploding: why non-intrusive ads embedded in games are growing

Games don’t just have ads anymore. We also have entire games as ads. Even worlds as ads, as Lego builds out a kid-safe space with Epic in the metaverse. And increasingly lately we’re getting non-intrusive ads inside games. As in: inside the gameplay. On the walls. In the halls. Embedded right inside the actual architecture and artwork of a game, not grafted in via a rewarded ad loop or pasted in via an interstitial.

In-game ads, clearly, are the new OOH (out of home) advertising. 

In a very metaversy way.

In a sense, this is no shock. Everything is an ad network today, right? I mean, if Doordash, Zoom, CVS, Walgreens, and Instacart are ad networks, if Amazon owns a truly massive ad network, almost everything where people gather can be an ad network. 

Even ads can have ads, right?

And it makes perfect sense: movies and TV still occupy more of people’s time, around 2,000 hours a year, but gaming is closing in. While the average American spends only a few hundred hours a year playing games, binge gamers spend close to 500. And young people are increasingly tuning into games and out of TV.

Which means ad dollars have to go somewhere.

And games is one big and still rapidly-growing space with billions of gamers globally, many of whom don’t really watch TV much anymore, if they watch it at all.

“The way people are consuming media these days, you don’t reach 100% of your audience on TV anymore,” Steve Hartmann, a VP at Experian, recently told WSJ.

So where do in-game ads go?

If you’re not interrupting attention and highlighting your ad full-screen and requiring player interaction to continue, where do your ads go?

On the walls.

In the stadiums.

On the buildings.

On a jersey.

Wherever ads go IRL.

In short, wherever it makes sense given the construction of your game. So it could be a skin in Fortnite for players to choose. It could be the name of a stadium in your sports game. It could be real-looking (but virtual, of course) ads on the side of a race track.

And they can be designed right into the look and feel of your environment, like this in-game ad for a fake product, Nuka Cola, in Fallout:

in-game ad for a fake product, Nuka Cola, in Fallout

That could, just as easily, be a real product from a real company that is hoping to inspire real sales. And guess what: that real company could be you — the game publisher — cross-promoting another of your titles.

Ads in games: who’s leading the industry?

Microsoft is reportedly working on ads for Xbox games. That’s smart, because not only is Microsoft massive in gaming, having just acquired Activision Blizzard, it also has a significant ad network. That’s not just Microsoft Ads, which reaches almost a billion people, it’s also Activision Blizzard Media which — coincidently, perhaps — already offers an in-game ad product.

According to another report, Sony is working on something similar for Playstation. That could be used to support free-to-play games on the console, or reduce the cost of pay-to-play games.

(Grain of salt: both of these are unconfirmed by either Microsoft or Sony so far.)

The giants might be testing the waters, but there are multiple startups creating non-intrusive monetization solutions for games:

These are a few that come to mind. (Ping me with additional players if you see that I’m missing one.)

The value of in-game ads

Hey, money is good. It pays for developers (and marketers) and it keeps servers humming. But so do other forms of advertising. What’s good and interesting about in-game ads?

First off, they don’t interfere with gameplay.

Most ads are intrusive. Even if like rewarded ads they happen at the discretion of the gamer, they take gamers out of the world they’re in, out of the game they’re playing, and into a different reality. That may be a necessary evil, but even unnecessary evils are still … sort of evil. So letting players play seems like a good idea.

It’s also kind of free money.

I mean, you might have rewarded videos or interstitials. If so, there’s a natural limit on how many you can show and how often you can expect a player to engage with one of them. But a brand on a storefront is just there … it’s part of your playscape anyways. While it may not work for a game set in a primeval forest on a far-distant planet, it probably works for your game set in a fictional New York City.

And in some sense it’s kinda cool: real ads in synthetic spaces inside games. There’s a realism to that that can work really well.

Oh and guess what … you’re probably not feeding your competitors. Existing ads in games on mobile or console might tend to be for the kinds of things players in your game might like, such as games. In-game ads can be for brands in clothing or cars or laptops, making them non-competitive with your own games.

Challenges of in-game ads

Just because in-game ads offer some unique opportunities doesn’t mean they’re problem-free. While most can be very easily integrated via no-code SDKs, you’re going to have to make them fit somehow in your game.

So you’ll need some pre-thought and product work, at minimum.

In addition, because it’s in-game and intended to be non-intrusive, there’s no click or tap or linking out to an App Store or Google Play or console maker or publisher site. That means deterministic user-level performance data isn’t going to happen, and you’re going to have to rely on data science and mixed models and big data for next-generation marketing measurement.

It’s possible.

It’s doable.

But yes, it’s different.

That said, everything is different now as iOS uses SKAN and Android moves to privacy sandbox. And marketers are just having to adapt to new realities.

Talk to Singular

Looking for help to measure the unmeasurable? Book some time with a Singular expert and we’ll walk you through the Singular solution for marketing measurement in post-IDFA, post-GAID times.

Protected Audience API (formerly FLEDGE) in Privacy Sandbox on Android: reinventing the mobile ad network?

How will Google’s new Protected Audience API work in Privacy Sandbox on Android? And how will an ad go from an advertiser through a publisher to a person? If Google’s privacy plans come to fruition, that flow is going to change significantly on the world’s most popular computing platform in less than two years. 

When Apple introduced SKAdNetwork to iOS in 2021, it changed the privacy narrative on the planet’s most profitable mobile platform. Privacy Sandbox on Android is largely seen as Google’s answer, but the technology that Google is building into PSA goes far beyond privacy. There are significant changes to how mobile SDKs operate, major upheaval to how advertisers target audiences, and huge transformation in how attribution will work after the GAID is retired from service.

But there’s also a massive transition in store for mobile ad networks, and how an ad leaves an advertiser’s digital fingers on a long winding path to a human’s eyeballs.

Today we’re going to dig into exactly that part.


This post is part of an ongoing series on Privacy Sandbox:

  • SDK Runtime (how Google is sandboxing SDKs)
  • Topics API (how Google sees ad targeting working)
  • Protected Audiences API on Android (this post on how Privacy Sandbox will do audiences and remarketing)
  • Attribution Reporting API (how Google is proposing ad measurement will work)

The big change: the ad network now lives in your app

We’ve had mediation and app bidding and monetization capabilities in apps for some time now. So building ad network functionality into our mobile devices is nothing new. But Privacy Sandbox on Android signals a major shift in how that works. And in what is actually happening.

  • What data goes where
  • Who gets access to information
  • Where the ad auction actually takes place
  • And much more …

In traditional (as in: current) ad targeting, auctioning, and serving environments within most apps, ads come to our mobile devices, generally speaking, in one of two ways:

  • App bidding (header bidding)
  • Ad waterfall

In a waterfall world, an app looking to fill an ad request goes to a sequential list of preferred ad networks looking to fill the slot. The first one that says yes — with a presumably competitive bid but not one that is guaranteed to be the highest — wins and fills the slot with an ad. In an app bidding world, there’s a real-time auction between multiple ad networks and demand-side platforms simultaneously: everyone gets a crack at the slot, and the highest bidder wins. 

While the ad fill request is initiated from within a publisher’s app, the actual auction generally takes place on an ad server (in some cases the publisher’s own), and the data informing each player bidding on each ad is generally sent to additional servers owned or used by those companies. There it can be enriched with additional data that helps ad networks value the impression appropriately and guides both the types of ads they feel would be appropriate for that slot and their bidding strategy: specifically the price they’re willing to pay for that impression.

So today, a lot of the mobile advertising ecosystem that both compensates developers/publishers and drives growth and user/customer acquisition happens off-device and involves a lot of data that is sent, managed, processed, and stored in multiple companies’ cloud systems.

A lot of this changes in Protected Audiences API

First off, at least some ads will be stored on device and periodically fetched in the background. There is an endpoint defined in the code for rendering creative, so presumably at least some parts of the ads and/or creative can also be streamed live. In addition, there’s a daily update URL that marketers can use to keep ads fresh.

Interestingly, ad networks will often want to send multiple ads for the same slot.

“Ad tech platforms may want to send multiple contextual ads back to the device and invoke the ad selection workflow to enable app install-based filtering in order to maximize chances to show a relevant ad,” Google says.

Why?

Because targeting lives largely on-device, using privacy-safe data that Topics API assembles from our app use history. Plus, the sandbox has access to additional targeting data such as language and a rough geographic location. 

While I’m sure ad networks and other players will try to enrich data about devices or people, it’s not clear how they’d be able to do so under PSA. This could have a major impact on how ad networks, including the emerging titans of adtech, are able to differentiate their services. Device graphs based on identifiers like GAID are going to wither on Android, just as they’ve become largely useless on iOS with the de facto deprecation of the IDFA.

(Major platforms like Facebook or Twitter or Snap or Tiktok or even Google itself, of course, have plenty of their own data and will retain their own targeting and auction systems for their owned apps. Similarly, first-party data on first-party platforms will provide incentives for the continued consolidation of content, capability, and ad monetization.)

It’s not 100% clear which data will be available for the buy-side to make bidding decisions. 

Clearly Topics will play a role, and Google says time and coarse location will be available, but Google also refers somewhat obliquely to “contextual information” and “seller signals” that are “supply-side platform specific signals,” and potentially more. Google says “the auction code, such as the bidding logic may need access to private user data such as app install sources.” For that reason, “the runtime will not provide network or storage access.” This suggests that Google is making additional data available which cannot be revealed for privacy purposes but is useful for pricing ad impressions and settling ad auctions. I’m guessing here, but this seems to be more than just topics from the Topics API, because Google is already censoring some of the data around topics (such as when a user deletes one) so that adtech SDKs don’t learn too much about users.

“Ad tech platforms will need to prepare to have some parts of their current auction and ad selection logic deployed and executed on the device,” Google says.

The actual auction or sale of an ad impression also happens on-device. The buy side and sell side meet in the app, and the buy side players run their bidding logic within the sandbox in self-contained Javascript that does not have either network or local storage access.

Functionality in that bid logic will generate a calculated bid amount, and bids will work sequentially for all ads with no guaranteed sequence. 

However, there will be filtering on both sides. Publishers can block ads from campaigns they don’t want buying impressions on their apps — presumably, you’d block your direct competitors from advertising to your users in your app — and buy-side platforms can filter ads based on on-device signals. One example Google gives of those on-device signals is ad usage for frequency capping, but presumably there will be more filters.

One of them is filtering for the right ad from multiple that a winning bidder might have prepared and pre-uploaded for a given slot.

The winning ad “has the highest score,” Google says, which presumably includes the right price, and the right degree of relevance. Once a winner is determined, the privacy sandbox sends optimization signals basically immediately to both sell-side and buy-side: “to enable capabilities such as real time budgeting, bidding model updates, and accurate billing workflows.”

Another big change; audiences. And remarketing (but not retargeting)

While there are plenty of changes in Protected Audiences API for ad targeting, ad auctions, and ad serving, there’s also significant changes to how marketers will be able to create and use audiences.

Goodbye GAID, goodbye audiences? Goodbye remarketing?

Not quite.

But yes, a lot of change is coming to audiences, targeting, remarketing, and retargeting on Android. On Android today marketers can create custom audiences — including audiences built with people who once used their apps — and target or retarget them at will. (Just as in the recently-deceased golden era of mobile marketing on iOS, of course.) 

But because Google is deprecating the GAID, the mobile advertiser on which these capabilities are built, that functionality is changing, and some of it looks like it will be lost forever. Fortunately, as Google is doing so, it is replacing the disappearing functionality with something that will keep at least some of these marketer superpowers alive. And, maybe, even add a few.

First: remarketing vs retargeting.

These are similar and confusing terms with conflicting definitions, but here’s how I define them in the context of mobile apps and mobile marketing. (And yes, I threw re-engagement in there because … why not.)

TermRelationshipMobile examplesIdentifiersChannels
RemarketingExisting user/customerAbandoned shopping cart notificationNone 100% required
GAID (now)
Protected Audiences API (future)
Email address
Phone #
Ad
In-app notification
Email
SMS
RetargetingFormer user/customerGive us another try; re-download the appGAID (now)
Email address
Phone #
Ad
Email
SMS
ReengagementLapsed user/customerOpen the app you already haveNone 100% required
GAID (now)
Protected Audiences API (future)
Email address
Phone #
Ad
Push notification
Email
SMS

The key insight in the context of Privacy Sandbox for Android? The main way retargeting is done today to recapture former app users is via GAID, and PSA doesn’t include a mechanism for that.

Privacy Sandbox for Android does include a mechanism for remarketing, but it’s explicitly labeled from Google as a solution for people who still have and are still using your app. Reengagement use cases would follow the same logic, because both would use custom audiences that are defined in-app. As it currently stands, however, there is no mechanism in Protected Audiences API for targeting former users of your app: traditional retargeting.

“Audience information is stored on-device and can be associated with relevant candidate ads for the audience and arbitrary metadata, such as bidding signals,” says Google. “The information can be used to inform advertiser bids, ad filtering, and rendering.”

Audiences, which you once created with whatever parameters you wished and targeted via IDFA, GAID, or email address, will be time-limited with a default expiry which can be overridden (probably a timer which needs to be called from time to time to ensure that it is still relevant.) They will have near-instant functionality, which is important for abandoned cart scenarios, for example.

“When an owner adds a user to a custom audience, it may fetch candidate ads from a buy-side platform,” Google says. “Returned ads and metadata can be stored in the custom audience’s “ads” field. Ad tech platforms may want to use this feature if they would like to start serving ads to this user right away.”

Very interestingly, just as with Topics API users can see what topics they’ve been assigned and delete ones they don’t want, people will also be able to see when apps have put them in custom audiences. And, like Topics, they can delete themselves from those audiences. In a very important point that marketers will need to pay attention to, doing so will prevent apps from adding them to audiences in the future. 

“The proposal intends to give users visibility to the list of installed apps that have at least one associated custom audience,” Google says. “Users can remove apps from this list. The removal will clear all the custom audiences associated with the apps and prevent the apps from joining new custom audiences.”

That’s kind of a big deal, and Google says details on that are to be determined and released in the future.

App publishers also have some control here: apps can manage how audiences are created from them, and can grant that control to ad networks they trust.

Much more to know about Privacy Sandbox on Android

With targeting, serving, and measuring ads on Android all changing, it’s clear that even though PSA provides much more than SKAN in terms of data, it also changes much more than SKAN in terms of how the mobile ad ecosystem functions. As the industry provides feedback and Google updates its documentation, we’ll continue to update you here.

There is, of course, much more to know about PSA. For more insight, check out these additional articles by Singular experts, including CEO Gadi Eliashiv.

That’s a small selection.

While PSA is definitely still in the future, it’s also definitely coming. And as we saw with SKAN on iOS, when it comes, there will be multiple industry players and partners who are unprepared and unready.

Our suggestion: don’t be one of them.

Talk to Singular about how to future-proof your marketing measurement and mobile attribution: book a demo today.

Making Privacy Sandbox on Android work: conflicting credit, shared aggregation keys

What if multiple ad networks claim credit for every single mobile app user you acquire under Privacy Sandbox on Android?

Sounds unlikely? Actually, it’s precisely how Privacy Sandbox on Android is architected. As currently architected, attribution decisions are only based on touch points: clicks or impressions. And attribution is done individually for each ad network. In fact, each ad network gets a postback with that attribution decision.

When every ad network claims credit

There could be a few issues with this …

In a real world scenario where you potentially have multiple ad networks all serving clicks and impressions to the same user … you could have multiple ad networks all trying to claim credit for that eventual conversion.

Jonathan Chen

There’s a huge problem in that for an industry that’s built around last-click attribution. There’s also a huge opportunity in that for an industry that’s built around last-click attribution. MMPs like Singular will have to review “triggers,” as Google calls conversion events, match them with installs, take into account the priority that each trigger has been given, and de-dupe install credit claims. This is important in a pay-per-install world so that marketers don’t get double billed, but it’s also an opportunity to explore partial-credit models and (dare we say it) a limited version of multi-touch attribution.

There are a lot of complexities here, and a lot of concerns around potential fraud. We’ll explore that more in coming posts and reports.

Aggregation keys: learning to share

Google is building a framework and an architecture so that ad networks, advertisers, and measurement partners can tag data like clicks, impressions, campaign variables, and cost. Those can’t be connected in as granular a way as GAID allows, of course: this is inside the privacy sandbox. But in an aggregation service running in a trusted execution environment in the cloud, measurement partners can connect pre-install and post-install data in a privacy-safe way.

The requirement: common aggregation keys.

In order to get the resulting attribution report, your aggregation keys need to match … so you need to figure out how to communicate with your ad network: ‘Like, hey, what key did you use when you started the click … I need to use that same key.”

Jonathan Chen

It’s very likely that MMPs will play important roles there just as the manage conversion models under SKAdNetwork on iOS.

Privacy thresholds vs differential privacy: a key difference

Though they’re both designed to serve similar purposes, there’s a key difference between the privacy thresholds in Apple’s SKAN framework and the differential privacy in Google’s privacy sandbox.

Privacy thresholds actually withhold data from marketers and measurement platforms until the thresholds have been surpassed. This is sometimes referred to as censorship of the data. The idea is that if there’s too little data, marketing platforms could infer too-granular data with a fairly high level of certainty about their new users within a particular time frame.

Differential privacy is … different. (Sorry.)

It is introducing noise to postbacks, but not just random noise

“The way the sandbox introduces the noise is through differential privacy. And one of the things about differential privacy is, when you look at a large enough dataset, it should still be accurate. When you look at specific chunks of data, like for an individual user, you can’t know with 100% certainty that it is true, but in aggregate, everything is accurate.”

Jonathan Chen

All the data is there: it’s just mixed up so that Google ensures that individual privacy is maintained. Which means that campaign-level reporting should be excellent.

Less stress (more data, more postbacks)

I’ve heard multiple marketers tell me SKAN is stressful because you basically have one shot at getting it right. You get one postback, and it contains all the data that you’re ever going to be able to definitively tied to a specific conversion (not a device, not a user, just a conversion). Which means that, if you’re going to use that data for predictive LTV, for ROAS calculation, and for campaign optimization, it’s extremely high leverage.

At lot weighs on that one postback.

In that sense at least, Privacy Sandbox on Android is going to be a lot less stressful. While each of the PSA postbacks has less data (3 bits for conversion events attributed to a click, and 1 bit for conversion events attributed to an impression) there are 3 postbacks for click-attributed conversions and 1-2 postbacks for impression-attributed conversions.

That means in the most common case, clicks that lead to installs, you get three shots at getting revenue, events, funnels, or engagement data. In other words, users who don’t engage, buy, or act immediately are not instantly lost in terms of pLTV or ROAS.

Stay tune for more Privacy Sandbox and SKAN insights

We’ve already shared a lot about Topics API and SDK Runtime as well as a deep dive on mobile attribution in Privacy Sandbox and an introduction to Sandbox integration. There’s more to come (and yes, still on SKAN, which is still extremely challenging for most mobile marketers).

Scroll down just a bit on our blog home page to sign up to the Singular digital marketing newsletter.

15 secrets to maximizing revenue with subscription-based apps

There’s been a fundamental change in what people want over the past decade, and it’s one that has given rise to the subscription economy, subscription services, and subscription-based apps.

Subscription services are not about ownership. They’re about access. And brands that offer access are becoming some of the most popular on the planet.

Music via Spotify. Cars via Lyft. Entertainment via Netflix. Gym via ClassPass. Education via Masterclass. Food via Hello Fresh. Goodies via Candy Club. Beauty via Birchbox. Grooming via Dollar Shave Club. Pet care via BarkBox. Games via Apple Arcade or Play Pass. Or Stadia or PlayStation Plus.

This is happening via physical devices too. Apple already has subscriptions for music and fitness and news and storage, all bundled up in Apple One, and you can buy an iPhone via subscription too. In fact, that’s rumored to be a big new shift in how Apple comes to market … much like Adobe did with Photoshop years ago.

Young people are used to this. It’s how they’ve grown up with music and entertainment.

Older people … perhaps not so much. 

But if you think about it, we already often buy cars by subscription. (We call it leasing.) And while it might be a shock to think of them this way, the very jobs that billions of us work at are actually kind of the ultimate subscription service. After all, we sell two weeks of our time in exchange for a certain sum of money .. month after month after month. That’s a B2B subscription service, essentially.

As everyone in mobile marketing knows, subscriptions are becoming huge in apps. They’re  part of a shift in app monetization, in fact, that offers versions of products that are ad-free.

“We are moving away from [an] ad-funded tech economy towards a subscription one,” startup founder, former Google product manager, and current Twitter executive Nick Hobbs told me.

How can you build and grow subscription-based mobile apps?

There are plenty of apps that try to bolt on a subscription service to an existing product. And plenty of apps that just offer it as one method of payment. There are far fewer who build it into the core of their product offering, the essence of their product experience, and the foundation of how they market their app.

Those, ultimately, turn out to be the most successful.

Here are 15 tips for app publishers and marketers who want to be successful in offering subscription services and monetizing via subscription revenue.

1. Develop and launch subscription apps differently

When you’re building for ad-based monetization or in-app purchases, you can often build, if not a minimum viable product, a smallish version of your full vision. With subscription apps, while you don’t have to boil the ocean, you can’t release something obviously partial and expect to be able to monetize it immediately via paid subscriptions.

Your app has to be good enough, clean enough, and useful enough that you can convince someone to pull out a credit card and agree to a monthly or annual payment.

2. Have much higher product development standards for subscription apps

An ad-supported model can kinda suck, if it still does what you want. 

I mean, many of us still endure obnoxious ads on live TV that take up 20% or more of our viewing time if we want to watch live sports. Most of us are OK with free apps that monetize via ads, even interstitials, as long as we get access. And rewarded ads are the ultimate value exchange that many mobile users happily agree to.

Subscription products are different:

“When you’re trying to build a subscription business, your first, second, and third priority has to be building a radically superior product.”

– Nick Hobbs

Make it so much better the value is obvious and the choice to subscribe is easy for your target audience. Your user experience has to be way better. It can’t just be like a little bit better. It has to be fundamentally a different experience that is vastly superior to what came before it.

4. Advertise your subscription-based apps differently

Many apps offer a free tier (sometimes ad-supported) and a subscription tier, which is a valid option. But that has implications for how you advertise.

First: benchmark. Not everyone is going to become a paid subscriber. And in fact, the numbers are going to seem very, very low if you’re new to subscriptions.

“3% of users become paid subscribers.”

– Vitaly Davydov, CEO and co-founder of Adaptly, a service to boost in-app subscriptions

Second, optimize on events, not value. Traditional ways of marketing to users or customers who have wildly different value — think $0 LTV to multiple thousands — don’t necessarily work for subscription customers, who might all be in one tier of value, or else in just a few tiers.

That may make it tougher to use advertising products like Facebook’s VO (value optimization):

“If you’re selling the same subscription to everyone … the LTV of those different users is actually fairly similar, which renders the whole model of value optimization a bit useless,” says mobile marketing consultant Thomas Petit.

5. Pick the right pricing

This is one of those that is super-simple to say and super-hard to actually do.

In a conversation with subscription expert Vitaly Davydov, however, I picked up a few tips about how to know that your pricing is right, and have data to back it up. First off, you have to be able to answer this question, perhaps via exit interviews when people cancel:

“Answer the question: why do people cancel their subscription?”

 – Vitaly Davydov

Secondly, you need to explore price elasticity and the dependency between your pricing and your subscription retention rate. You can do this by running a test: pick a representative sample of your paying users and increase the price 10%. Try a 20% price hike with another group. If you’re losing paying customers, you might consider a dangerous option: a price reduction, or a coupon, or a free extension.

Then you crunch the data:

  • Usage
  • Retention
  • Billing issues
  • Cancellations

Davydov says that in most cases a 20% increase will change very little. I you try for more, you’ll likely see some degradation … but often not as much as the increase in revenue you get from the price hike. Understanding the curve between pricing and retention is the key.

The best marketers I know … know this curve pretty perfectly among different segmentations, among different countries, different devices, different platforms.”

 – Vitaly Davydov

This gets complex quickly: it matters what country you’re working with, what devices people are using, and what kind of users you have. But knowing this will help put you on the path to profitability.

6. Choose the right time to sell

Long-form sales letters might be great for get-rich-quick scheme selling. Mobile app subscriptions? Not so much.

One expert says you need to jump in right away:

“Onboarding is the first couple of screens before you dive into the main app. And our statistics show, if you sell during this couple of screens, you will have the most monetization out of your app. And I think that the big idea is: you make your sales funnel shorter.”

 – Vitaly Davydov, CEO and co-founder of Adaptly

The customer journey there is very defined and very simple: have a need, search for it on Google or the App Store or the Play Store (or see an ad in another app), install the app, and start solving that problem immediately.

Your app or audience may require a free trial. If so, you’re going to have to find events leading up to or during that trial that are predictive, both on Android and iOS, as Thomas Petit learned the hard way. In one trial he fed a very early event back to Google as an optimization signal: completing a form. It turns out that the ones who were savvy enough to do that easily and quickly on a phone were mostly people under 20 who didn’t convert to paying subscriptions.

Oops.

In 20-20 hindsight, the results were entirely predictable: off the charts, but not in a good way.

“What happened is the conversion between free trial and paying subscription was completely off the chart, but off the bottom … it was less than half of what we usually had,” Petit told me.

So if you’re using event optimization for ad networks to optimize on — and on iOS if you’re not getting the paid sign-up immediately you’ll need to — you’re going to have to get really smart about which event to pick. And, of course, be flexible enough to adjust it if and when needed.

“The lesson here is really look at your cohorts: don’t assume that they’re going to behave the way your previous cohorts do because as soon as you’ve got a little bit of variance we’re actually talking about big money differences.”

 – Thomas Petit

7. Sell for the right period of time

Everything matters in subscription monetization: 

  • how you present
  • what you offer
  • your brand image
  • the look
  • the feel
  • the social proof
  • the timing
  • the price 
  • and … yes … also the term

It turns out that in a lot of cases yearly subscriptions might be a better option, even if a shorter term seems like a lower level of commitment that would be easier to get.

“Selling yearly subscriptions now works better than selling monthly or weekly subscriptions, because people can’t measure it. You know, you get a lot of money up front and it’s less risky than asking a user to pay each week. And so we see now a rise of yearly subscriptions.”

 – Vitaly Davydov

One decision, one big chunk of access, one moment for a year’s worth of value?

The benefit as a consumer is that your customer can make one decision for the entire year. You don’t have to make a decision every week or every month — that’s just annoying — and you can feel like you’re paying a lump sum and getting a significant term of service. Car insurance works that way, as do many other kinds of insurance, and software as a service (SaaS) increasingly has longer-term commitments for better pricing.

Personally, I like to get that payment out of the way and get down to doing whatever it is I want with the software, utility, game, or service.

8. Understand your customers’ needs better than they do themselves

Can you know your customers’ needs better than they do themselves? You might have to, if you want to build a successful subscription product.

Nick Hobbs managed Google’s iOS app, and then built Brief, a subscription news product that Twitter acquired. 

“You have to understand at a fundamentally deeper level than your customers what their needs are … and then meet them. And they will feel that. They may not be able to articulate every part of it. They may not know that that one animation at the end that says ‘You’re all done,’ that’s what they love. But we know, and we guide them through that, and make sure they have a great experience every day.”

 – Nick Hobbs (sold his news subscription company to Twitter)

That takes time. It takes research. It takes feel … the kind of feel that founders and product builders only get from deep personal engagement with a problem or scenario or persona.

9. Take advantage of your new ad-free user experience

Since your product is now a subscription product, you don’t have to monetize with ads. The benefit here is that you can focus every pixel of every screen on achieving exactly what a user and customer wants.

The reward?

Better retention as a subscription product

“We learned that if you remove ads or lessen them in that new user experience, you will see better retention because people will get, of course for us they will get to that editing magic moment faster and not be distracted,” says Jeff Roberto, VP of growth marketing for PicsArt.

Bonus!

10. Add friction when you design the decision point

It is completely counterintuitive to design additional friction points into a user experience or a customer journey. In fact, it sounds suicidal.

But it makes sense.

You have to build a significant wall between what a free user gets and a customer gets. There has to be clear and obvious differentiation between free and paid, and free users needs to be continually getting enough to stimulate their appetite but not quite enough to satisfy.

Plus, they need to be able to see over the wall into the promised land of all good things: your amazing subscription service.

All of this takes artistry as well as math.

“You just can’t … you can’t look at logs, you can’t look at data and find those things. You have to get in there and deeply understand the actual user pain points.”

 – Nick Hobbs

Intentionally creating friction and designing a clear differentiation between OUT and IN is important work for those who want to win in subscription services.

11. Continually delight your customers because you must must must keep them

Getting the customer decision and winning the subscription is step one.

(And note, I’m saying “customer” not “user.”)

But if you can’t continually delight the people in your app by consistently delivering a high level of value and occasionally surprising them with a new hit of “wow” or “nice” or “they added that?!?” you risk losing them.

“At the heart of recurring revenue, the most important thing is not getting more people — it’s  keeping the people that you have. If you have a really leaky funnel where you’re losing people after a few months, you can acquire as many as you want and your business model doesn’t work.”

 – Nick Hobbs

Translation: retention becomes your key metric, not acquisition. Acquisition matters — of course — and no-one comes into your bucket without it. But focusing on acquisition when you don’t have retention nailed will just simply kill your economics.

And beware:

“80% of subscribers unsubscribe pretty quickly in just three months or four months.”

 – Vitaly Davydov, CEO, co-founder of Adapty

You’re facing an uphill battle. Victory goes to the prepared.

12. Become an expert in lifecycle marketing

Lifecycle marketing is about the entire customer journey, not just the part where you get them. And since succeeding in subscription marketing is about keeping customers even more than initially winning them, it’s critical.

“Lifecycle marketing basically has three pillars … there’s conversion, engagement, and retention,” Thomas Hopkins, former head of performance and lifecycle marketing for Masterclass and current CEO of Perfect Storm Studios told me. “And each one of them plays a different role depending on the time of the product’s life cycle.”

Getting really good at lifecycle marketing means that users you acquire turn into customers you keep, via engagement and retention strategies. And that requires knowing both your product and your customer very well, and also knowing a lot about how your customers engage with your app.

It also means you look at your metrics differently than a pure acquisition marketer.

“The last piece is retaining them and making sure that you can keep them,” says Hopkins. “In terms of metrics … we’re specifically looking at the number of emails we send to the ratio … of people that actually convert.”

 – Thomas Hopkins, CEO of Perfect Storm Studios

Of course, that might be email, or it’s more often going to be in-app ads or web ads, or other marketing campaigns. But the key insight is you’re not tracking CPI as much as CAC. Cost per install matters, but cost of customer acquisition is much more important. As is, of course, LTV in order to determine the CAC you can profitably sustain.

13. Earn the double thank you

Don’t forget that every day, people can cancel. They can forget. They can get busy. They can get out of their subscription.

“You can use a product for three months, then forget about it. Then again after three months, you can write to Apple Support and say, ‘Hey, you know, I really don’t like this product anymore.”

 – Vitaly Davydov

That means you need to embrace the concept of the double thank you … every day, every week, or even every time someone uses your app and engages with your product.

What is the double thank you? It’s what you do pretty much every day in the real world.

“The idea of the double thank you is it’s that moment when you go to buy a sandwich and you hand them the $5 and they hand you the sandwich, and you say ‘thank you’ and you’re so happy you got that sandwich for $5, and they say ‘thank you’ because they’re so happy they got your business.”

 – Nick Hobbs

Every single time they use your app, earn the double thank you.

14. Surprise your customer … in a good way

I’ve talked about product and quality and subscriptions, and how subscription-supported apps need to be better, easier, more worthwhile than ad-supported apps.

Don’t forget to surprise people (in a good way) ever so often.

“How do you keep and retain and keep people’s perception of the brand very high? And so the way that we think about it is that our goal is to treat it as a membership. And what does a membership mean? It means early access. It means additional opportunities that being a nonmember you wouldn’t have.”

 – Thomas Hopkins

Make it special. Make it white glove. Make it early access. Make it red carpet. But only for your paying subscribers.

(Of course, just like at the nightclub, it doesn’t hurt to let everyone else see the high rollers get in quick and easy.)

15. Be scrupulously honest and aboveboard

It may seem silly, but if you want long-term success with subscription apps, you have to be extremely honest and aboveboard with everything, including how to cancel and not pay. Yes, it’s counterintuitive, but it’s about trust and brand, and earning long-term committed customers who boost your retention rates to the stratosphere.

“If you sign up to a 7-day free trial for our courses package, we will send you four emails I think during that period of time saying, ‘Listen, you’ve got a 7-day free trial here and it’s going to automatically bill you on this date,” Christopher Plowman, the founder of CEO of Insight Timer, a 20-million-plus-member mediation app, told me recently. “’So if you don’t want to be billed, unsubscribe, click here. Here’s the link.’ We send them a link, we send them the button.”

That’s radical honesty and openness.

And customers who are treated that way learn that you respect them, respect their finances, and respect their commitment to your app. In turn, it earns you customer loyalty.

Bonus tip #16: Become multi-platform and multi-channel and multi-media

There’s a lot to do when building a successful subscription app or subscription business. For apps, do your best to become multi-channel in your messaging and value delivery.

That means you offer, when and where possible, value via:

  • App
  • Web
  • Email
  • Push
  • In-app
  • Video
  • Audio
  • And more …

The multiple platforms is business insurance against problems on your platform, whether that’s iOS or Android. The multiple channels and multiple media is to deliver value however your customer wishes to consume it.

Singular can help

Growing subscription apps is hard. You need great data from all sides: spend, attribution, in-app, and more. And you need insight on how to grow.

Book some time with a Singular expert to learn how we can help …