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<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/09/53293-Mobile-game-marketing-1200x630-1-290x170.png" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Mobile game marketing - OG Image" decoding="async" /></figure>
<p>There are 1.93 billion mobile gamers worldwide. For the first time in gaming history, you and your grandmother might be swiping away at the same game — or, in this one instance, your grandma might befriend a rapper from Florida via Words with Friends. That’s because mobile games are enjoyable and accessible to everyone with [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/blog/tips-strategy/mobile-game-marketing/">Mobile game marketing: Essential strategies made simple</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


There are 1.93 billion mobile gamers worldwide. For the first time in gaming history, you and your grandmother might be swiping away at the same game — or, in this one instance, your grandma might befriend a rapper from Florida via Words with Friends.
That’s because mobile games are enjoyable and accessible to everyone with a smartphone. With player numbers like this, it’s hardly surprising that the industry is projected to reach $173.4 billion by 2026.
And more players means more developers, too. With competition fiercer than ever, this guide breaks down essential marketing strategies so you can stand out above the competition.
What is mobile game marketing?

Mobile game marketing involves promoting a mobile game to attract new, high-quality players at the lowest possible cost. It can also be used to re-engage lapsed users, or to encourage in-app purchases.
Depending on your budget, target audience, and goals, your marketing strategy may involve a combination of paid and organic (unpaid) channels. This could range from optimizing your app store listings to running TikTok ad campaigns.
Although there’s no silver bullet, the foundational strategies outlined in this guide can help you create the best strategy for your mobile game. If you want a bird’s eye view of the mobile gaming industry, read our state of gaming app marketing report. It’s packed with trends, UA spend data, benchmarks, best practices, and more.
Why is mobile game marketing important?
For gaming apps, the goal is to make fun games while generating revenue. In order to do that sustainably, you need to identify marketing channels that help you acquire new players and reel in those who have drifted away.
Let’s dive into the specifics of why mobile game marketing matters.
Lets your target audience find you
You can’t build a good mobile game and expect players to naturally come to you. Hoping that your mobile game will go viral without spending a dime is unrealistic. Even if you don’t spend on Instagram and TikTok ads, you will have to invest resources in finding your target audience and letting them know that your game exists.
So, the first purpose of mobile game marketing is to increase awareness — to show your target audience that you exist in the first place.
Drives installs
Helping users find your app is one thing, but the next step is getting them to actually install it. If you crack the code on what channels work best for your game, then you’ll be able to reliably and profitably grow your game’s user base. You can also tap into new markets that may not have been possible with simply word-of-mouth marketing.

Encourages player retention
Marketing your game can also keep players interested, and even bring back those who stopped playing. By highlighting new content or offering bonus rewards to inactive users, you can increase your player base and generate more revenue at a lower cost than acquiring a completely new user.
Supports diversified revenue streams
There are multiple ways to monetize your gaming app, whether you charge for downloads, offer subscriptions or in-app purchases, or rely on in-app ads. Mobile game marketing can help you maximize these different revenue streams for sustainable growth.
If you’re able to target high-quality users, you can promote special offers and exclusive content to drive more in-app purchases. For example, you can promote a sale on bonus content or battle passes for new players.

What are the different kinds of mobile game marketing campaigns?
To reiterate, there are numerous ways to advertise your game. While some channels, such as Instagram and TikTok ads, are more popular than others, each one has its own advantages and disadvantages. We can break down the various advertising options into three categories: push, pull, and paid.
Push campaigns
Push campaigns “push” information about your game in front of your target audience — for example, through push notifications, email marketing, or CTV advertising. Push campaigns are the most common form of advertising, as you can directly reach your target audience.
Paid campaigns
Paid campaigns are a subset of push campaigns, in which you pay to use the ad space. They include in-app advertising, Meta ads, TikTok ads, pay-per-click ads, and sponsored content. Paid campaigns often yield quick and measurable results, targeting audiences based on demographics, behaviors, and interests.
Pull campaigns
Pull marketing draws new players into your game: a great place to start is by optimizing your app store listing. Other options to pull users in include community management, content marketing, SEO, and incentive or referral programs. While push campaigns typically rely on paid advertising, pull campaigns rely on organic channels over a longer period of time.
The influence of influencers on mobile game marketing

Influencer marketing gets a bad rap, but we live in a world powered by creators. The advertising dollars show it, too. On average, brands will spend 25% more on influencer marketing this year.
Money follows attention, and influencers are an avenue for brands, developers, and advertisers to tap into the cultural zeitgeist. That’s one reason why Brawl Stars spent $3 million to sponsor a Mr. Beast video.
For mobile game marketers more specifically, building relationships with influencers can be a productive strategy. It can be a cost-effective way to widen your organic reach and get your game in front of a highly engaged, receptive audience. Plus, you can put paid ad dollars behind sponsored creator videos to help extend the impact of your influencer marketing campaign.
Best practices for a mobile game marketing campaign
Now it’s time to talk about execution. In order to run a successful marketing campaign, you and your stakeholders all need to be on the same page. Use this section as a guide to create a documented strategy to launch your next campaign.
1. Research your target audience
Your audience is everything. The more you know about them, the happier your wallet will be. Starting at a very high level, it’s important to know the demographics, interests, and location of your target audience. Dig into the analytics from your website, app, and social media for clues. 
Then, take it a step further. Identify what other games they like to play, their hobbies, interests, and lifestyle. Whether you send out surveys, or speak directly to content creators in your space, this added level of specificity can transform your strategy, messaging, and creatives.
2. Research your competitors
With analytics tools like Sensor Tower, App Tweak, and App Radar, it’s easier than ever to see what your competitors are doing. You can also look up the ads they’re running and draw inspiration from their most successful campaigns.
Study competitor reviews, too, to see if there’s an opportunity for you to differentiate yourself. For example, Genshin Impact has long been a market leader for Gacha games. However, players complained about the antiquated movement and combat system. With that insight, Wuthering Waves filled the gap by improving those two aspects in their own game.
3. Build a community
Building a community, or building a game in public, is a great way to get players involved early on in the process. Discord, Reddit, Slack, and Facebook groups are all excellent channels to keep a loyal player base engaged and provide you with the feedback you need to keep improving.

4. Invest in app store optimization
Your app store listing is like your storefront: getting it right will improve your overall install rates and how frequently you show up on the increasingly crowded app stores. By optimizing your app titles, descriptions, keywords, and visuals, you can generate more installs at a low cost. App stores today even reward developers who regularly push updates and run seasonal events.
For a full rundown of ASO, read our guide here.
5. Use a mix of paid, organic, and influencer marketing
An optimized marketing mix involves a combination of paid, organic, and influencer marketing. While some channels can be more effective than others, it’s important to constantly test out new channels, because performance can change overnight. Diversifying your advertising mix means you’re not reliant on a single channel, and opens up opportunities to reach broader audiences.
6. Identify trends that will work for you
The lifespan of games is getting shorter, so it’s important to stay on top of trends to keep your development fresh. For example, live service game models of free games supported by in-game purchases (and battle passes) are popular right now. They offer a good trade-off between generating revenue and incentivizing players to stay engaged.
You can also explore cross-platform gaming, although this may not be right for every game. For instance, Valorant, a popular first-person shooter, has released a console version of the game — but doesn’t support crossplay between PC and console. On the other hand, Fortnite offers crossplay while giving console players an extra edge with aim assist.
7. Create compelling creatives

Returning to the point about understanding your audience, your campaigns are only as effective as your creatives are. Finding the right messaging and design direction is critical to how your ads perform. Once you’ve developed high-quality creatives that convey the essence of your game, use A/B testing to keep optimizing their performance.
8. Analyze your campaign performance
Regularly monitoring and analyzing your campaign performance is critical to your game’s growth, and it all depends on accurate data. Set clear KPIs like CPI, LTV, and ARPU, and work with a mobile measurement partner to ensure your data is clean and accurate across every channel. We’ll cover the meanings of those acronyms next!
Which KPIs to measure

Accurate numbers are the foundation of every successful campaign. However, many marketers fall into the trap of prioritizing vanity metrics, and miss the numbers that really matter. Here are the most important KPIs you should be measuring to determine how your campaigns impact your bottom line.
Average revenue per user (ARPU): The average revenue generated per user over a period of time. This helps forecast revenue and determine if your game is profitable.
ARPU formula: Total revenue / Number of users
App stickiness: How often a user returns to your app. This helps determine if your players are willing to stick around and become loyal players.
App stickiness formula: Daily active users (DAU) / Monthly active users (MAU)
Churn rate: Percentage of users who stop playing your game within a period of time. Similar to stickiness, this indicates how much players are willing to continue playing your game – but you want to keep it as low as possible. If your churn rate spikes after an update, this could be a strong indicator that changes need to be made.
Churn rate formula: [(Users at beginning of time period – users at end) / Users at beginning] x 100
Conversion rate: Percentage of users who complete a desired action. For example, it could measure how many users click install after landing on your app listing page, or how many players click through an ad.
Conversion rate formula: (Number of conversions / Total number of visitors) x 100
CPI: Cost per install, or the cost to acquire a new user to install your game.
CPI formula: Total advertising cost / Number of installs
DAU, WAU, MAU: Daily active users, weekly active users, monthly active users. These measure how many unique users play your game within that time period.
Retention rate:  Percentage of users who use the app continually within a period of time.
Retention rate formula: (Number of retained users / Number of users at start) x 100
LTV: Lifetime value is the total revenue a player generates through their entire time playing your game. This takes into account the average length of time they play and how much money they’re likely to spend. Measuring your advertising spend against LTV helps determine whether your campaigns are profitable.
LTV formula: ARPU x Average customer lifespan
Session length: The amount of time a player spends on the game in one session. This helps determine how sticky and engaging your game is.
Session length formula: Total session time / Number of sessions
The future of mobile game marketing

Once in a while, there are seismic changes in the world of mobile advertising. COVID lockdowns, Apple’s IDFA changes, and the rapid adoption of artificial intelligence are three of the most recent. While we don’t have a magic crystal ball, here’s how we predict mobile game marketing will change in the near future.
AI and creative optimization
From A/B testing tools to full-out AI-generated designs, advertisers have been quick to embrace the power of AI to enhance marketing campaigns. And with new developments flying in by the day, that trend looks set to continue.
Companies like Meta, Google, and Apple already provide AI-powered testing tools that allow you to test various elements such as audio, copy, and design changes in your ads. As these platforms’ AI models advance, we can expect these features to have a more significant impact on the entire ad creation process.
Increased privacy changes and probabilistic modeling
In the post-IDFA world, advertisers are finding new and creative ways to market their games while prioritizing consumer privacy. There will continue to be a balancing act of protecting consumers while providing advertisers with the tools to advertise effectively.
Double opt-in is an example. Mobile game developers must obtain explicit user consent for tracking, which means crafting clear and compelling messages explaining the benefits of opting in.
Another one of the biggest changes in a cookieless world is attribution modeling. A solution like AppsFlyer uses a combination of deep linking, probabilistic modeling, preloaded campaigns, and Device ID matching to help address the challenges of gathering actionable campaign data. Moving forward, advertisers should expect to see innovation in this area.
Increased demand for social gaming
Fortnite and Roblox are two excellent examples of the rise of “social gaming,” where players find a place to meet others and interact in a digital universe. Powered by proprietary in-game engines, where players can create their own game modes and worlds, games are becoming increasingly immersive.
Mobile game developers, specifically, will need to incorporate social gaming elements in meaningful ways moving forward.
Hybrid monetization models
As mentioned previously, there are numerous ways for mobile games to generate revenue, and marketers are increasingly looking to combine these in hybrid models.
While rewarded video ads remain a highly effective revenue source, introducing alternative monetization models like battle passes and exclusive skins can provide new income streams. Mobile games can also partner with other intellectual properties to co-market campaigns, such as featuring Deadpool and Wolverine skins in Fortnite, or offering an Optimus Prime skin in Overwatch to coincide with a movie release.
Key takeaways
Mobile game marketing involves promoting a mobile game to attract new, high-quality players at the lowest possible cost.
Mobile game marketing helps acquire new players and re-engage lapsed players. It can also diversify revenue streams, for example by encouraging in-app purchases.
An effective mobile game marketing strategy involves a diverse mix of channels including paid, organic, and influencer marketing.
Developing a strategy starts with understanding your target audience and competitors. Building a community, optimizing your app store listing, and developing compelling creatives will also boost success.
Keep measuring and optimizing the performance of your app marketing campaigns, focusing on the metrics that impact your bottom line.
Future trends in mobile game marketing will be dictated by AI, social gaming, hybrid monetization models, and the evolving privacy landscape.


FAQs

Do mobile game ads drive revenue?

When done correctly, mobile ads do drive revenue. In the simplest terms, when your cost per acquisition is lower than your lifetime value, you are driving revenue. You can use organic or paid strategies, or a combination, depending on the type of game and the audience you serve.

Is the mobile game market oversaturated?

While the mobile gaming market is becoming increasingly competitive, player numbers are also growing with rising smartphone adoption and consumer demand. This creates a higher barrier to entry and a higher revenue ceiling – meaning smaller developers have to employ more creative UA strategies to stay competitive.

How do you market a game with a limited budget?

To compete with big developers on a limited budget, lean into organic content strategies. Consider filming and producing your own videos, or reaching out to influencers. You could also develop your game in public and build a community, network with other developers, or explore co-marketing opportunities.


The post Mobile game marketing: Essential strategies made simple appeared first on AppsFlyer.

There are 1.93 billion mobile gamers worldwide. For the first time in gaming history, you and your grandmother might be swiping away at the same game — or, in this one instance, your grandma might befriend a rapper from Florida via Words with Friends. That’s because mobile games are enjoyable and accessible to everyone with […]
The post Mobile game marketing: Essential strategies made simple appeared first on AppsFlyer.

Mobile game marketing: Essential strategies made simple

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/09/53274-Performance-creative-1200x630-1-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Performance creative - OG Image" decoding="async" loading="lazy" /></figure>
<p>When it comes to online campaigns, marketers love to focus on data: impressions, clicks, campaign ROI, and more. There are seemingly endless ways to measure how your campaigns perform — but what about the creative side of things? After all, when a user encounters an ad, the creative (text and design) is what they see. [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/blog/measurement-analytics/performance-creative/">Performance creative: Combining data and creativity</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/09/53274-Performance-creative-1200x630-1-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Performance creative - OG Image" decoding="async" loading="lazy" /></figure>
<p>When it comes to online campaigns, marketers love to focus on data: impressions, clicks, campaign ROI, and more. There are seemingly endless ways to measure how your campaigns perform — but what about the creative side of things?<br><br>After all, when a user encounters an ad, the creative (text and design) is what they see. A memorable, and potentially successful, ad usually has exceptional creative (think Super Bowl ads!). But exceptional doesn’t always mean extravagant.</p>



<p>So, how do you know if you’re getting your creative right? Standard performance metrics give you an idea, by indicating how well people respond to your ad. But for a deeper understanding of what, precisely, makes your ad successful or not, you need to explore performance creative.</p>



<p>In this blog, we’ll take a look at what performance creative is, its importance, how it’s measured, KPIs, and everything else you need to know.</p>



<h2 class="wp-block-heading" id="h-what-is-performance-creative">What is performance creative?</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/09/what-is-performance-creative.jpg" alt="What is performance creative" class="wp-image-437536" srcset="https://www.appsflyer.com/wp-content/uploads/2024/09/what-is-performance-creative.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/09/what-is-performance-creative-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<p>Performance creative is where data and creativity meet.</p>



<p>It’s about using the true data behind creative concepts to track their performance and to help plan and optimize creative assets moving forward.&nbsp;</p>



<p>Performance creative covers ad copy, images, and video assets, but a major focus is call to action (CTA) buttons. This is because an ad can be creatively brilliant, but if it doesn’t lead people to click the CTA, it won’t be considered a success.</p>



<p>The development of performance creative means that creative assets are no longer judged on gut feel. Instead, companies can now apply the same rigorous, data-driven approach to creative that they’ve always used for performance KPIs.</p>



<h2 class="wp-block-heading"><a></a>Why is performance creative important to measure?</h2>



<p>Creative is a key element in any marketing campaign, so understanding its performance helps you drive better results — including improved <a href="https://www.appsflyer.com/blog/measurement-analytics/roi-vs-roas/">ROI/ROAS</a> and deeper audience understanding.</p>



<p>Knowing your audience is critical, but it’s not enough by itself. You need data to make sure you’re truly answering their needs. Performance creative can help you identify which creative assets work best for your audience, leading to even better campaigns with better results.</p>



<p>And with hard data to back up your approach, you can justify your creative decisions, budget with confidence, and avoid wasting money on poorly-performing assets.</p>



<p>Let’s take a look at how to dive into the creative data.</p>



<h2 class="wp-block-heading">8 steps to measure performance creative</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/09/8-steps-to-measure.jpg" alt="How to measure performance creative" class="wp-image-437546" srcset="https://www.appsflyer.com/wp-content/uploads/2024/09/8-steps-to-measure.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/09/8-steps-to-measure-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<p>Once you’ve decided to start measuring performance creative, follow these steps to set yourself up for success. There’s no one perfect formula for a successful creative, and that’s why it’s so important to test things out and be open to experimenting. But even as you try new things, these guidelines can help you optimize faster to find more creative winners.</p>



<ol start="1">
<li><strong>Set benchmarks.</strong> Take a look at your historical data to establish baseline performance metrics for your creative assets. This serves as a reference point for future campaigns.</li>



<li><strong>Define your target audience.</strong> Deep-dive into your intended audiences to make sure your creative is resonating with the right people, so you can measure effectiveness accurately.</li>



<li><strong>Understand privacy limitations.</strong> Familiarize yourself with privacy regulations and <a href="https://www.appsflyer.com/glossary/skadnetwork/">SKAdNetwork</a> constraints. This can help you adapt your strategies accordingly and, of course, make sure you’re remaining compliant.</li>



<li><strong>Define your KPIs.</strong> We’ll dive into your KPIs in the next section, but as a first step, select specific, measurable key performance indicators that align with your campaign goals. Popular examples include click-through rates, conversion rates, or return on ad spend.</li>



<li><strong>Implement analytics tools.</strong> Make sure you’re rounding up your various analytics tools so you can track and analyze your creatives.</li>



<li><strong>Set A/B tests.</strong> There’s nothing like a good old A/B test to understand what’s working and what isn’t. These controlled experiments compare different versions of your creative to understand what leads to better performance.</li>



<li><strong>Measure and optimize.</strong> There’s no such thing as a perfect campaign. You’ll have to keep measuring and optimizing your work to keep improving results over time.</li>



<li><strong>Track brand metrics.</strong> In addition to performance metrics, measure brand awareness, recall, and sentiment to gauge how well your brand is doing.</li>
</ol>



<h2 class="wp-block-heading">Which KPIs to measure</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/09/which-kpis-to-measure.jpg" alt="Which KPIs to measure for performance creative" class="wp-image-437556" srcset="https://www.appsflyer.com/wp-content/uploads/2024/09/which-kpis-to-measure.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/09/which-kpis-to-measure-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<p>There are several metrics you can use to measure performance creative. It’s important to select the relevant KPIs for your campaign goals — we’ve listed some common ones below.&nbsp;</p>



<ul>
<li><a href="https://www.appsflyer.com/glossary/ctr/">Click-through rate</a> (CTR): This common metric looks at the percentage of viewers who click on your ad after seeing it. This can be an important indication of how compelling your creative is at first glance.</li>



<li><a href="https://www.appsflyer.com/glossary/conversion-rate/">Conversion rate</a>: This KPI tracks the percentage of users who take a desired action after interacting with your creative. This may be making a purchase or signing up for a newsletter or service. Your conversion rate shows the bottom line result of your campaign and how it’s affecting your business results.</li>



<li><a href="https://www.appsflyer.com/glossary/roas/">Return on ad spend</a> (ROAS): ROAS calculates the revenue generated for every dollar spent on advertising. This helps you understand the overall efficiency and profitability of your creative campaigns. It’s a popular KPI with eCommerce stores.&nbsp;</li>



<li>Creative Quality Score (CQS): This is a composite metric that looks at various aspects of your creative including relevance, engagement, and conversion potential.</li>



<li>Engagement rate: This KPI measures how users interact with your creative beyond clicks, including likes, comments, shares, how long they view a video, and so on. This can give you information about how captivating or shareable your content is.</li>



<li>Bounce rate: This metric typically applies to landing pages or websites, showing how many visitors leave without taking any action. High bounce rates may show that the creative used isn’t working with the linked content.</li>



<li>Time on page: This KPI shows how long users are spending on your landing page or website after interacting with your creative. Longer times typically correlate with engaging and relevant content.</li>



<li><a href="https://www.appsflyer.com/glossary/view-through-rate/">View-through rate</a> (VTR): For video creative assets, VTR measures the percentage of viewers who watch your video until the end, indicating they find your content interesting and engaging.</li>
</ul>



<h2 class="wp-block-heading">Best practices for improving your performance creative</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/09/best-practices.jpg" alt="Best practices for improving performance creative" class="wp-image-437566" srcset="https://www.appsflyer.com/wp-content/uploads/2024/09/best-practices.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/09/best-practices-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<p>So, we’ve established that performance <a href="https://www.appsflyer.com/products/creative-optimization/">creative</a> is where data meets creativity, and that measuring and testing are important. Now, let’s get down to the nitty gritty and talk about some things you can do to make sure you’re optimizing efficiently and moving towards the results you want to see. Experiment with the following ideas to discover what works best for your app.</p>



<ul>
<li><strong>Create a centralized library of assets.</strong> Setting up a digital repository for all of your creative assets makes it easier for teams to access, reuse, and study successful creatives, and can also streamline your production process.</li>



<li><strong>Communicate between teams.</strong> Open dialogue and collaboration between teams facilitate successful creatives. Bring together creative, marketing, and analytics teams to successfully turn performance data into smart creative decisions.</li>



<li><strong>Ensure clear messaging.</strong> Each piece of creative should have a single, well-defined message. That way, your audience can focus on what matters and avoid overwhelm.&nbsp;</li>



<li><strong>Get creative with your testing using AI-powered tools.</strong> Tools that use artificial intelligence and machine learning can help you generate and test multiple creative options quickly, as well as identifying winning combinations of visuals, copy, and CTAs.&nbsp;</li>



<li><strong>Monitor the competition.</strong> Make it a habit to regularly track and understand what your competitors are doing when it comes to creative. This can help you identify trends and potential opportunities and give you new ideas.</li>



<li><strong>Personalize your creative.</strong> Use your data-driven insights to tweak your creative content to specific audiences.</li>



<li><strong>Use storytelling. </strong>In a crowded market, telling a great story that evokes emotions builds a stronger connection with your audience.</li>
</ul>



<h2 class="wp-block-heading">Future trends for measuring performance creative</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/09/future-trends.jpg" alt="Future trends for performance creative" class="wp-image-437576" srcset="https://www.appsflyer.com/wp-content/uploads/2024/09/future-trends.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/09/future-trends-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<p>Rapid advances in technology will shape how we use and measure performance creatives moving forward. Artificial intelligence and machine learning will bring new opportunities to analyze creative elements in a more sophisticated way, delivering deeper insights about how creatives drive performance. And real-time optimization suggestions will enable us to change creatives quickly and effectively to meet KPIs.</p>



<p>There are already some great tools out there to help with this task, including AppsFlyer’s own <a href="https://www.appsflyer.com/products/creative-optimization/">creative optimization solution</a>, which can help with some of the heavy lifting involved in measuring performance.</p>



<p>Tools like these will be even more crucial as privacy restrictions become increasingly complex. Regulations such as GDPR and CCPA are constantly evolving and third-party cookies are phasing out, meaning we’ll have to develop new methods for measuring performance while protecting user privacy.</p>



<p>Looking ahead, performance creative will have to balance new technologies that will improve the way marketers work, with increasing privacy regulations that make it more challenging to gather customer data.</p>



<h2 class="wp-block-heading"><a></a>Key takeaways</h2>



<ul>
<li>Performance creative combines data analysis with creative assets, using the data behind creatives to optimize marketing campaigns. The insights it provides can lead to higher ROI, deeper audience understanding, and better creative decisions.</li>



<li>Key steps in measuring performance creative include setting benchmarks, defining the target audience, understanding privacy limitations, and implementing analytics tools.</li>



<li>Important KPIs for measuring performance creative include click-through rate (CTR), conversion rate, return on ad spend (ROAS), and engagement rate.</li>



<li>To improve performance creative, consider creating a centralized asset library, fostering team communication, and ensuring clear, personalized messaging. Continuous measurement and optimization — for example, using AI-powered testing tools — are key to ongoing success.</li>



<li>Future trends in performance creative measurement will be shaped by advancements in AI and machine learning, offering more sophisticated analysis and real-time optimization while protecting user privacy.</li>
</ul>
<p>The post <a href="https://www.appsflyer.com/blog/measurement-analytics/performance-creative/">Performance creative: Combining data and creativity</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


When it comes to online campaigns, marketers love to focus on data: impressions, clicks, campaign ROI, and more. There are seemingly endless ways to measure how your campaigns perform — but what about the creative side of things?
After all, when a user encounters an ad, the creative (text and design) is what they see. A memorable, and potentially successful, ad usually has exceptional creative (think Super Bowl ads!). But exceptional doesn’t always mean extravagant.
So, how do you know if you’re getting your creative right? Standard performance metrics give you an idea, by indicating how well people respond to your ad. But for a deeper understanding of what, precisely, makes your ad successful or not, you need to explore performance creative.
In this blog, we’ll take a look at what performance creative is, its importance, how it’s measured, KPIs, and everything else you need to know.
What is performance creative?

Performance creative is where data and creativity meet.
It’s about using the true data behind creative concepts to track their performance and to help plan and optimize creative assets moving forward. 
Performance creative covers ad copy, images, and video assets, but a major focus is call to action (CTA) buttons. This is because an ad can be creatively brilliant, but if it doesn’t lead people to click the CTA, it won’t be considered a success.
The development of performance creative means that creative assets are no longer judged on gut feel. Instead, companies can now apply the same rigorous, data-driven approach to creative that they’ve always used for performance KPIs.
Why is performance creative important to measure?
Creative is a key element in any marketing campaign, so understanding its performance helps you drive better results — including improved ROI/ROAS and deeper audience understanding.
Knowing your audience is critical, but it’s not enough by itself. You need data to make sure you’re truly answering their needs. Performance creative can help you identify which creative assets work best for your audience, leading to even better campaigns with better results.
And with hard data to back up your approach, you can justify your creative decisions, budget with confidence, and avoid wasting money on poorly-performing assets.
Let’s take a look at how to dive into the creative data.
8 steps to measure performance creative

Once you’ve decided to start measuring performance creative, follow these steps to set yourself up for success. There’s no one perfect formula for a successful creative, and that’s why it’s so important to test things out and be open to experimenting. But even as you try new things, these guidelines can help you optimize faster to find more creative winners.
Set benchmarks. Take a look at your historical data to establish baseline performance metrics for your creative assets. This serves as a reference point for future campaigns.
Define your target audience. Deep-dive into your intended audiences to make sure your creative is resonating with the right people, so you can measure effectiveness accurately.
Understand privacy limitations. Familiarize yourself with privacy regulations and SKAdNetwork constraints. This can help you adapt your strategies accordingly and, of course, make sure you’re remaining compliant.
Define your KPIs. We’ll dive into your KPIs in the next section, but as a first step, select specific, measurable key performance indicators that align with your campaign goals. Popular examples include click-through rates, conversion rates, or return on ad spend.
Implement analytics tools. Make sure you’re rounding up your various analytics tools so you can track and analyze your creatives.
Set A/B tests. There’s nothing like a good old A/B test to understand what’s working and what isn’t. These controlled experiments compare different versions of your creative to understand what leads to better performance.
Measure and optimize. There’s no such thing as a perfect campaign. You’ll have to keep measuring and optimizing your work to keep improving results over time.
Track brand metrics. In addition to performance metrics, measure brand awareness, recall, and sentiment to gauge how well your brand is doing.
Which KPIs to measure

There are several metrics you can use to measure performance creative. It’s important to select the relevant KPIs for your campaign goals — we’ve listed some common ones below. 
Click-through rate (CTR): This common metric looks at the percentage of viewers who click on your ad after seeing it. This can be an important indication of how compelling your creative is at first glance.
Conversion rate: This KPI tracks the percentage of users who take a desired action after interacting with your creative. This may be making a purchase or signing up for a newsletter or service. Your conversion rate shows the bottom line result of your campaign and how it’s affecting your business results.
Return on ad spend (ROAS): ROAS calculates the revenue generated for every dollar spent on advertising. This helps you understand the overall efficiency and profitability of your creative campaigns. It’s a popular KPI with eCommerce stores. 
Creative Quality Score (CQS): This is a composite metric that looks at various aspects of your creative including relevance, engagement, and conversion potential.
Engagement rate: This KPI measures how users interact with your creative beyond clicks, including likes, comments, shares, how long they view a video, and so on. This can give you information about how captivating or shareable your content is.
Bounce rate: This metric typically applies to landing pages or websites, showing how many visitors leave without taking any action. High bounce rates may show that the creative used isn’t working with the linked content.
Time on page: This KPI shows how long users are spending on your landing page or website after interacting with your creative. Longer times typically correlate with engaging and relevant content.
View-through rate (VTR): For video creative assets, VTR measures the percentage of viewers who watch your video until the end, indicating they find your content interesting and engaging.
Best practices for improving your performance creative

So, we’ve established that performance creative is where data meets creativity, and that measuring and testing are important. Now, let’s get down to the nitty gritty and talk about some things you can do to make sure you’re optimizing efficiently and moving towards the results you want to see. Experiment with the following ideas to discover what works best for your app.
Create a centralized library of assets. Setting up a digital repository for all of your creative assets makes it easier for teams to access, reuse, and study successful creatives, and can also streamline your production process.
Communicate between teams. Open dialogue and collaboration between teams facilitate successful creatives. Bring together creative, marketing, and analytics teams to successfully turn performance data into smart creative decisions.
Ensure clear messaging. Each piece of creative should have a single, well-defined message. That way, your audience can focus on what matters and avoid overwhelm. 
Get creative with your testing using AI-powered tools. Tools that use artificial intelligence and machine learning can help you generate and test multiple creative options quickly, as well as identifying winning combinations of visuals, copy, and CTAs. 
Monitor the competition. Make it a habit to regularly track and understand what your competitors are doing when it comes to creative. This can help you identify trends and potential opportunities and give you new ideas.
Personalize your creative. Use your data-driven insights to tweak your creative content to specific audiences.
Use storytelling. In a crowded market, telling a great story that evokes emotions builds a stronger connection with your audience.
Future trends for measuring performance creative

Rapid advances in technology will shape how we use and measure performance creatives moving forward. Artificial intelligence and machine learning will bring new opportunities to analyze creative elements in a more sophisticated way, delivering deeper insights about how creatives drive performance. And real-time optimization suggestions will enable us to change creatives quickly and effectively to meet KPIs.
There are already some great tools out there to help with this task, including AppsFlyer’s own creative optimization solution, which can help with some of the heavy lifting involved in measuring performance.
Tools like these will be even more crucial as privacy restrictions become increasingly complex. Regulations such as GDPR and CCPA are constantly evolving and third-party cookies are phasing out, meaning we’ll have to develop new methods for measuring performance while protecting user privacy.
Looking ahead, performance creative will have to balance new technologies that will improve the way marketers work, with increasing privacy regulations that make it more challenging to gather customer data.
Key takeaways
Performance creative combines data analysis with creative assets, using the data behind creatives to optimize marketing campaigns. The insights it provides can lead to higher ROI, deeper audience understanding, and better creative decisions.
Key steps in measuring performance creative include setting benchmarks, defining the target audience, understanding privacy limitations, and implementing analytics tools.
Important KPIs for measuring performance creative include click-through rate (CTR), conversion rate, return on ad spend (ROAS), and engagement rate.
To improve performance creative, consider creating a centralized asset library, fostering team communication, and ensuring clear, personalized messaging. Continuous measurement and optimization — for example, using AI-powered testing tools — are key to ongoing success.
Future trends in performance creative measurement will be shaped by advancements in AI and machine learning, offering more sophisticated analysis and real-time optimization while protecting user privacy.
The post Performance creative: Combining data and creativity appeared first on AppsFlyer.

When it comes to online campaigns, marketers love to focus on data: impressions, clicks, campaign ROI, and more. There are seemingly endless ways to measure how your campaigns perform — but what about the creative side of things? After all, when a user encounters an ad, the creative (text and design) is what they see. […]
The post Performance creative: Combining data and creativity appeared first on AppsFlyer.

Performance creative: Combining data and creativity

<p>The post <a href="https://www.appsflyer.com/resources/reports/gated/test1-the-state-of-ecommerce-app-marketing/">[TEST1] The state of eCommerce app marketing</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


The post [TEST1] The state of eCommerce app marketing appeared first on AppsFlyer.

[TEST1] The state of eCommerce app marketing

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/09/53231.SEO-Blog-Post_1200x630-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Dynamic product ads - OG Image" decoding="async" loading="lazy" /></figure>
<p>Have you ever had a concierge shopping experience? An expert listens to your needs, assesses your likes and dislikes, and makes personalized recommendations based on your preferences. Dynamic product ads are the advertising equivalent, presenting the user with highly personalized, relevant content and product suggestions. But, while concierge shopping is resource-intensive, dynamic product ads let [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/blog/mobile-marketing/dynamic-product-ads/">Automate your ad personalization with dynamic product ads</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


Have you ever had a concierge shopping experience? An expert listens to your needs, assesses your likes and dislikes, and makes personalized recommendations based on your preferences. Dynamic product ads are the advertising equivalent, presenting the user with highly personalized, relevant content and product suggestions.
But, while concierge shopping is resource-intensive, dynamic product ads let you personalize online advertising at scale.
And that personalization can give you a competitive edge to move your audience from ambivalence to action. According to McKinsey, 76% of customers are more likely to purchase from brands with personalized interactions.
Read on to learn how you can use dynamic product ads in your app marketing to boost engagement, efficiency, and conversions.
What are dynamic product ads?

Dynamic product ads are a type of online advertising that serves personalized ad content for each viewer, based on user demographics and behavioral data. By automating the creation of personalized ads, dynamic ads display relevant and timely content that is ultimately more effective.
Channels where you can launch dynamic ad campaigns include social media platforms (Facebook, Instagram, Pinterest, LinkedIn) search engines, display ad networks, and in-app advertising. While the specifics of each channel and platform vary, the basic functions are the same.
How do dynamic product ads work?

With dynamic product ads, advertising platforms like Meta use artificial intelligence (AI) and machine learning to do the hard work of personalization for you. Here’s an overview of how it works.
Product catalog: You upload or link your product catalog, containing information about each product, such as its name, description, price, and image. In app marketing, you can include features such as in-app purchases, subscriptions, or deep links to specific content.
Targeting: You set up targeting options to define who should see your ads, based on criteria like demographics, interests, behaviors, and more.
Product matching: When a user matches your targeting criteria, the platform’s algorithm matches them with a product from your catalog that is most likely to be relevant to them.
Dynamic creative optimization: The platform uses the product information from your catalog to create a dynamic ad that showcases the matched product. The ad includes the product image, name, price, and description.
Ad rotation: On certain platforms like Facebook, the ad rotates through multiple products from your catalog to show users a variety of products and increase the chance of conversions.
Conversion tracking: You set up conversion tracking to measure the ad’s effectiveness. This can include tracking sales, add-to-cart actions, or other desired actions.
Dynamic ads on social media platforms
On social media platforms like Meta, you need to set up a product library and add a code snippet that pulls real-time pricing, first-person behavioral data, and other information from your website. Based on user behavior like previously viewed products, the platform builds and serves individualized product ads to users it believes are most likely to respond.

Dynamic ads on Google Ads
In Google search, instead of waiting for an exact keyword match, the platform creates paid search ads from website content such as page titles and product page data. Dynamic ads use machine learning to optimize and improve the ads’ performance over time.
What are the benefits of dynamic product ads?
So, why should you use dynamic product ads? Admittedly, these ads take more effort to set up on the front end than traditional formats, but they can drive a big impact once enabled. Here are the top six benefits of dynamic advertising.
1. Better conversion rates
Conversion rates for online advertising are low, at 9% for Facebook ads and 4% for Google search. When you draw on behavioral data to remind customers about products they’ve previously viewed or that match their interests, your chance of conversion success shoots up.
Dynamic product ads are also effective because they’re highly visual. For example, Facebook’s dynamic product ads pull product images into a shopper-friendly carousel format that grabs attention.
2. Better for cross-device and cross-channel targeting
As a marketer, you know that it may take many touchpoints over time for customers to finally hit that “buy” or “install” button. Dynamic product ads are built to reach customers across devices and platforms, from Facebook to Instagram to Google, and remind them of their interest in a product.
3. Time savings and greater efficiency

Manual personalization can be time-consuming and expensive, but technology makes customization faster and easier. When you set up automated dynamic ad campaigns, you save your marketing team time they can spend on other tasks.
4. Cost savings
Dynamic product ads not only save time, they save money through better campaign optimization. Static product ads — which aren’t personalized using automation — often waste your budget by displaying ads to a general audience. Using AI and machine learning, dynamic product ads serve ads to users that are most likely to buy.
On average, businesses using Meta’s Advantage+ dynamic ads have seen a 17% reduction in cost per action and a 32% increase in return on ad spend.
5. Higher customer lifetime value
Since dynamic ads can serve tailored content based on product views and past purchases, they’re perfect for growing customer lifetime value through repeat purchases. Dynamic remarketing ads to existing customers tempt them to return and buy again with upselling and cross-selling ad content.
A McKinsey study found that 78% of customers are more likely to repurchase when served personalized content, a win-win for your business and your customers.
6. Higher revenue, faster growth
With all of the benefits above, you can position your company for higher customer acquisition, revenue, and growth.
Let’s dive into how to get started.
How to set up a dynamic product ad campaign in 8 steps
Setting up your first dynamic ad campaign can feel intimidating, but you’ll ultimately have fewer decisions to make than you would with traditional online ads. Once you set up your product catalog and data feed, AI does most of the heavy lifting. The platform can build ads, optimize campaigns, and find new customers without direct input from you.
Here are the steps to get your first dynamic ad campaign up and running.
1. Upload your products to your chosen channel
Log into the platform you want to use for your dynamic product ads, for instance, Meta or Google Ads. You’ll need a business account rather than a personal one.

Google Ads
To promote an entire website or store on Google Ads, simply select the websites or landing pages you want to promote. To create a dynamic remarketing campaign promoting individual products to consumers, you need to first create a product feed on Google Merchant Center. This links your website products in real time so you can serve up-to-date dynamic ads on Google search and Google Shopping.
Social media platforms
On social media platforms, the first step is to create a product catalog. For Facebook and Instagram, most businesses do this by adding products manually or uploading them with a spreadsheet. Brands with large product catalogs may also consider sharing data through a data feed, partner platform, or batch API (more complex options that may require setup from a partner or developer).
Review the products to make sure that your catalog is up to date and includes all the necessary product information (product name, description, image, price, and so on) before you continue.
2. Set up your Meta Pixel (for Facebook and Instagram)
If your campaign is on Meta, you need to set up your Meta Pixel: a small piece of code that tracks user behavior on your website and helps you measure the effectiveness of your ads. Follow Meta’s instructions for enabling and capturing your pixel, then install the Meta Pixel on your website by adding the code to your website’s header or footer.
3. Start a new campaign
Once your product catalog and data stream are set up, it’s time to start building your campaign. Log in to your ad account and navigate to the campaign creation page.
Create a new campaign (dynamic ads are now called Advantage+ ads on Meta) and give it a name and description. Choose the campaign objective that best fits your goals (such as conversions, sales, or website traffic). Choose a conversion location to track, for example your website or app.
4. Choose your audience
Next, define your target audience based on demographics, interests, behaviors, or custom audiences. Each platform will have different options such as location, language, and device that you can select. Set a bid adjustment for your target audience to optimize ad delivery.
5. Set your budget and bidding parameters
Next, set your overall budget and bid limit to keep your costs under control. You can choose to let the platform optimize the bidding strategy for you. For example, Google offers the choice to optimize via target cost-per-action (CPA) or enhanced cost-per-click (CPC).
6. Build your creative template
In social platforms like Meta, you’ll create an ad template to be customized. The template you design should be versatile enough to house any of your product images and text. Design the template according to the platform’s ad template options and best practices.
7. Launch your campaign
Review and confirm your campaign settings before launching. Then click “Launch” and watch the engagement start to roll in.
8. Test and optimize
While AI does most of the work, your campaign still needs a human touch to make sure it’s meeting your targets. Continuously monitor and optimize your dynamic product ads to make sure they’re working as intended and performing at their best.
Monitor your ad budget and adjust it as needed to ensure you’re getting the most out of your ad spend. Regularly review and optimize your product feed and product data to ensure it’s up to date and accurate. Use the platform’s analytics tools to track key metrics such as conversions, click-through rate, and cost per conversion.
Best practices for winning dynamic product ads
Dynamic product ads are a powerful way to showcase your products to potential customers, increasing conversions and sales. Here are some best practices for successful dynamic product ads.
1. Use high-quality product feed and product data
The quality of your product feed and product data is crucial for the success of your dynamic ad campaign. Make sure your product data is accurate, up to date, and well structured, including product names, descriptions, images, and prices. If you use a data feed, make sure it fetches data frequently so you aren’t publishing outdated pricing or unavailable items.
2. Appeal to customers with relevant visuals, messaging, and reviews
Ultimately, your ad creative will determine whether a user clicks on your ad or keeps on scrolling. Your product information should include engaging ad copy and compelling visuals to highlight the unique features and benefits of each app or product.
Since the platform will build the final ads, it’s up to you to make sure that the building blocks you give it — text and images — are high quality and relevant. Check that the images are sized correctly for the platform, optimized for mobile devices, and comply with platform guidelines. Building in customer ratings and reviews will boost your credibility and appeal.
3. Segment your product catalog

Meta recommends segmenting your catalog into product sets, using groups such as product category, pricing, and custom columns to improve campaign targeting. For instance, you can run campaigns by category including lifestyle apps, casual games, or educational apps. You can also promote products by categories such as items on sale, items over a specified price point, or items with excess inventory.
Enhancing dynamic product ads with AppsFlyer
Dynamic product ads open up many exciting possibilities for app marketers. For instance, AppsFlyer used Facebook’s dynamic product ads to show users relevant in-app experiences, before sending them to a general app install page. This deep-linking tactic, facilitated by our OneLink technology, resulted in high engagement and conversion rates and a low cost per install.

You can use dynamic product ads to promote in-app purchases, and offer special deals or discounts to encourage users to buy. These ads can also showcase your app features, such as new levels, characters, or game modes, as well as subscriptions and special offers.
Ultimately, dynamic product ads open the door to a new level of ad personalization and deeper engagement between consumers and brands — without creating a mountain of extra work for you.
Key takeaways
Dynamic product ads offer personalized online advertising at scale, using AI to recommend relevant products to users based on demographics and behavioral data.
Automation in dynamic product ads saves time and money by optimizing ad delivery to the most relevant audience, reducing cost-per-action and increasing return on ad spend. You can leave it to the platform to develop creatives and set appropriate bidding strategies to suit your budget.
Dynamic product ads can encourage purchases through remarketing and repeat purchases and upselling, leading to higher customer lifetime value and faster business growth.
Because dynamic ads are built by your chosen platform, you need to supply it with versatile, high-quality images, copy, and reviews to get the best results from your campaign. Ensure your product feed is up to date, and keep monitoring ad performance and budget. 
The post Automate your ad personalization with dynamic product ads appeared first on AppsFlyer.

Have you ever had a concierge shopping experience? An expert listens to your needs, assesses your likes and dislikes, and makes personalized recommendations based on your preferences. Dynamic product ads are the advertising equivalent, presenting the user with highly personalized, relevant content and product suggestions. But, while concierge shopping is resource-intensive, dynamic product ads let […]
The post Automate your ad personalization with dynamic product ads appeared first on AppsFlyer.

Automate your ad personalization with dynamic product ads

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/SKAN-joint-playbook-AppsFlyer-Google_OG-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Boost your app growth with SKAdNetwork Featured Image" decoding="async" loading="lazy" /></figure>
<p>A blueprint for iOS campaign success It’s no secret that your mobile revenue is heavily dependent on iOS users. That’s why measuring your iOS campaign performance is critical to maintaining a high return on ad spend (ROAS). But, in the absence of user-level data, how do you actually do that? In this playbook, AppsFlyer and [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/resources/guides/app-growth-skan/">Boost your app growth with SKAdNetwork</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/SKAN-joint-playbook-AppsFlyer-Google_OG-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Boost your app growth with SKAdNetwork Featured Image" decoding="async" loading="lazy" /></figure>
<figure class="wp-block-image size-full is-resized"><img loading="lazy" decoding="async" width="271" height="40" src="https://www.appsflyer.com/wp-content/uploads/2024/08/logos.png" alt="Logos AppsFlyer - Google" class="wp-image-436006" style="width:264px;height:auto"/></figure>



<h2 class="wp-block-heading" id="h-a-blueprint-for-ios-campaign-success">A blueprint for iOS campaign success</h2>



<p>It’s no secret that your mobile revenue is heavily dependent on iOS users. That’s why measuring your iOS campaign performance is critical to maintaining a high return on ad spend (ROAS).</p>



<p>But, in the absence of user-level data, how do you actually do that?</p>



<p>In this playbook, AppsFlyer and Google team up to share winning strategies and tools to effectively measure and optimize your iOS campaigns with SKAdNetwork—an essential component for growth. Follow this blueprint, which includes invaluable tips and recommendations to capitalize on the opportunities in the iOS world.</p>



<h3 class="wp-block-heading" id="h-what-s-inside">What&#8217;s inside?</h3>



<ul>
<li>SKAdNetwork basics</li>



<li>Innovative solutions to overcome SKAdNetwork limitations&nbsp;</li>



<li>Industry-specific SKAdNetwork use cases</li>



<li>Best practices for setting up your Google iOS App campaigns for success</li>
</ul>



<style>
.custom-related-posts,.cta-banner {display:none !important;}
</style>
<p>The post <a href="https://www.appsflyer.com/resources/guides/app-growth-skan/">Boost your app growth with SKAdNetwork</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


A blueprint for iOS campaign success
It’s no secret that your mobile revenue is heavily dependent on iOS users. That’s why measuring your iOS campaign performance is critical to maintaining a high return on ad spend (ROAS).
But, in the absence of user-level data, how do you actually do that?
In this playbook, AppsFlyer and Google team up to share winning strategies and tools to effectively measure and optimize your iOS campaigns with SKAdNetwork—an essential component for growth. Follow this blueprint, which includes invaluable tips and recommendations to capitalize on the opportunities in the iOS world.
What’s inside?
SKAdNetwork basics
Innovative solutions to overcome SKAdNetwork limitations 
Industry-specific SKAdNetwork use cases
Best practices for setting up your Google iOS App campaigns for success
The post Boost your app growth with SKAdNetwork appeared first on AppsFlyer.

A blueprint for iOS campaign success It’s no secret that your mobile revenue is heavily dependent on iOS users. That’s why measuring your iOS campaign performance is critical to maintaining a high return on ad spend (ROAS). But, in the absence of user-level data, how do you actually do that? In this playbook, AppsFlyer and […]
The post Boost your app growth with SKAdNetwork appeared first on AppsFlyer.

Boost your app growth with SKAdNetwork

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/State-of-Gaming-2024_OG-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="" decoding="async" loading="lazy" /></figure>
<p>The past year appeared to be a period of modest, stable growth for mobile gaming. However, this calm exterior is misleading. Beneath the surface, significant shifts were taking place.  The main trends include the strengthening of hybrid monetization, the positive results for Casual games compared with Mid-Core and Hypercasual categories, and the contrasting revenue outcomes [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/resources/reports/gaming-app-marketing/">The State of Gaming App Marketing &#8211; 2024 Edition</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/State-of-Gaming-2024_OG-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="" decoding="async" loading="lazy" /></figure>
<p>The past year appeared to be a period of modest, stable growth for mobile gaming. However, this calm exterior is misleading. Beneath the surface, significant shifts were taking place. </p>



<p>The main trends include the strengthening of hybrid monetization, the positive results for Casual games compared with Mid-Core and Hypercasual categories, and the contrasting revenue outcomes between in-app advertising and in-app purchases.</p>



<p>To dive deep into these trends, and many others, AppsFlyer analyzed over 21 billion installs of nearly 15,000 gaming apps. </p>



<h3 class="wp-block-heading" id="h-what-s-inside">What’s inside</h3>



<ul>
<li>The new monetization mix between ads and purchases</li>



<li>Insights about revenues trends, including an industry first analysis of VIP users (&#8220;whales&#8221;)</li>



<li>Ad spend by genre and by countries</li>



<li>Key growth metrics across markets, genres, and sub-genres</li>



<li>Best performing creative variations by genre</li>
</ul>
<p>The post <a href="https://www.appsflyer.com/resources/reports/gaming-app-marketing/">The State of Gaming App Marketing &#8211; 2024 Edition</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


The past year appeared to be a period of modest, stable growth for mobile gaming. However, this calm exterior is misleading. Beneath the surface, significant shifts were taking place. 
The main trends include the strengthening of hybrid monetization, the positive results for Casual games compared with Mid-Core and Hypercasual categories, and the contrasting revenue outcomes between in-app advertising and in-app purchases.
To dive deep into these trends, and many others, AppsFlyer analyzed over 21 billion installs of nearly 15,000 gaming apps. 
What’s inside
The new monetization mix between ads and purchases
Insights about revenues trends, including an industry first analysis of VIP users (“whales”)
Ad spend by genre and by countries
Key growth metrics across markets, genres, and sub-genres
Best performing creative variations by genre
The post The State of Gaming App Marketing – 2024 Edition appeared first on AppsFlyer.

The past year appeared to be a period of modest, stable growth for mobile gaming. However, this calm exterior is misleading. Beneath the surface, significant shifts were taking place.  The main trends include the strengthening of hybrid monetization, the positive results for Casual games compared with Mid-Core and Hypercasual categories, and the contrasting revenue outcomes […]
The post The State of Gaming App Marketing – 2024 Edition appeared first on AppsFlyer.

The State of Gaming App Marketing – 2024 Edition

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/53207-SKAN-vs.-Sandbox-feature-image-1-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="SKAN vs. Sandbox - изображение на главной странице" decoding="async" loading="lazy" /></figure>
<p>The app marketing world is still adjusting to the evolving privacy changes on iOS, and we are now on the verge of another round of disruptions with Privacy Sandbox on Android and the new opportunities that it introduces. It&#8217;s only natural to stack iOS and Android against each other, so we decided to examine the [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/blog/measurement-analytics/skan-vs-sandbox/">SKAN vs. Sandbox: what advertisers need to know</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/53207-SKAN-vs.-Sandbox-feature-image-1-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="SKAN vs. Sandbox - изображение на главной странице" decoding="async" loading="lazy" /></figure>
<p>The app marketing world is still adjusting to the evolving privacy changes on iOS, and we are now on the verge of another round of disruptions with <a href="https://www.appsflyer.com/hubs/sandbox/">Privacy Sandbox</a> on Android and the new opportunities that it introduces.</p>



<p>It&#8217;s only natural to stack iOS and Android against each other, so we decided to examine the similarities and differences between <a href="https://www.appsflyer.com/glossary/skadnetwork/">SKAN </a>(soon to be revamped as AdAttributionKit) and<a href="https://www.appsflyer.com/glossary/android-privacy-sandbox/"> Privacy Sandbox</a>. Don’t worry though, we’ll (try to) keep things simple.</p>



<h2 class="wp-block-heading" id="h-before-we-begin">Before we begin</h2>



<p>Google’s Privacy Sandbox is a broad initiative. It’s a suite of marketing infrastructure tools, covering targeting, retargeting, SDKs, and of course attribution.</p>



<p>Since SKAN focuses mostly on attribution, and for the sake of comparing apples to apples (See what I just did there?), we will focus on comparing SKAN to Sandbox&#8217;s Attribution Reporting API.</p>



<h2 class="wp-block-heading" id="h-scope-and-approach">Scope and approach</h2>



<p>Doing it the “Apple way”, SKAN is often perceived as a “black box”, naturally specific to iOS only.</p>



<p>With Privacy Sandbox, Google has taken a more collaborative approach and is gradually introducing the different modules for both web (starting with Chrome) and Android, allowing industry leaders such as AppsFlyer to iterate, build innovative solutions using the Sandbox building blocks, provide ongoing feedback, and actively influence the core principles. This approach comes with a cost, as Google often has to reverse decisions &#8211; as it did with the recent web cookies deprecation <a href="https://privacysandbox.com/news/privacy-sandbox-update/" target="_blank" rel="noreferrer noopener">announcement</a>.</p>



<h2 class="wp-block-heading" id="h-elimination-of-device-ids">Elimination of device IDs</h2>



<p>The primary principle for maintaining user privacy is to obscure persistent user identifiers such as <a href="https://www.appsflyer.com/glossary/idfa/">IDFAs</a> or <a href="https://www.appsflyer.com/glossary/gaid/">GAIDs</a>, and both SKAN and Privacy Sandbox are designed to minimize the use of identifiers.</p>



<p>Notably, Apple’s <a href="https://www.appsflyer.com/glossary/app-tracking-transparency/">ATT</a> framework requires user consent to access IDFA, while Google hasn’t announced any plans to use an ATT-style opt-in mechanism.</p>



<p>We’re being asked a lot about the future of GAID (Google Advertising ID) and whether it’s planned to be placed behind an opt-in wall like web cookies are. There’s no formal answer on this one yet. However, bear in mind that none of the Privacy Sandbox APIs use GAID, which can provide a good indication of future direction.</p>



<h2 class="wp-block-heading" id="h-data-aggregation">Data aggregation</h2>



<p>Both SKAN and Privacy Sandbox use data aggregation, grouping user data into anonymized cohorts to prevent individual profiling. This is a big deal for advertisers, but it&#8217;s an even bigger deal for ad networks and publishers that will no longer be able to track users and will have to find new creative ways to optimize their ad performance.</p>



<p>You can expect lots of&nbsp; innovation in this area in the coming months and years.</p>



<h2 class="wp-block-heading" id="h-reporting">Reporting</h2>



<p>SKAN 4 and AdAttributionKit provide three postbacks and dictate aligning to pre-defined time windows of 2, 7 and 35 days. Kind of like a full-service restaurant that serves meals on specific hours only.</p>



<p>In contrast, the Sandbox Attribution API is like a 30-day buffet. You cannot get wild and eat all that you want due to some “budget” limitations (more on that later), but you’re not tied to strict time windows. When the month ends, it’s time to put the forks down!</p>



<p>While Sandbox’s flexible reporting windows are great news for advertisers, the 30-day limitation might disappoint some marketing managers looking for longer revenue metrics.</p>



<h2 class="wp-block-heading" id="h-random-delays">Random delays</h2>



<p>With privacy-first attribution, data is never received in real-time in order to prevent the option to correlate report data with specific individuals. This forces advertisers to make longer experiments and leads to slower decision-making and reduced agility.</p>



<p>SKAN postbacks arrive with significant delays: 24-48 hours delay for the first <a href="https://www.appsflyer.com/glossary/postback/">postback </a>and 24-144 hours for the 2nd and 3rd postbacks.</p>



<p>Privacy Sandbox incorporates two delay mechanisms to enhance privacy:</p>



<p>Event-level reports (designed for campaign optimization) are delayed by at least 1 day following an ad click and 1-30 days after an ad view—Talk about being late for the party!</p>



<p>Conversely, aggregatable reports (designed for analyzing campaign performance), are available within hours — certainly&nbsp; a relief for advertisers.</p>



<h2 class="wp-block-heading" id="h-privacy-thresholds">Privacy thresholds</h2>



<p>There&#8217;s a joke about a fan telling a little-known artist, &#8220;I bought your album!&#8221; and the artist responds, &#8220;Oh, it was you!&#8221;</p>



<p>This kind of sums up the challenge with privacy-focused ad measurement. When the numbers are small, pinpointing individuals becomes too easy, which isn’t great for privacy.</p>



<p>Both SKAN and Privacy Sandbox address that issue using privacy thresholds, but the implementation is different.</p>



<p>In low volumes, SKAN simply doesn&#8217;t give you information on post-install activity (as well as campaign information). That’s the main reason why we at AppsFlyer developed a null modeling solution for SKAN to compensate for that signal loss. Privacy Sandbox uses the notion of “noise”. It adds fake data to mask the real numbers. The noise can be significantly deceiving when data volumes are low, but as volume grows the relative noise size reduces and becomes negligible.</p>



<p>Tip: For both SKAN and Sandbox, low data volumes can pose challenges for advertisers. It&#8217;s best to allocate adequate budgets to each media source and avoid splitting campaigns excessively. This strategy ensures data volumes are sufficient to bypass privacy thresholds, providing more reliable reports. The more focused your budget, the more reliable your data.</p>



<h2 class="wp-block-heading" id="h-bit-based-attribution">Bit-based attribution</h2>



<p>Both SKAN and Sandbox use “bits” to represent conversion or campaign data. Values represented by bits are more challenging to use but they ensure data is controlled, standardized, and more importantly: no direct identifiable information (like names, IDs, or even specific actions) is transmitted.</p>



<p>SKAN uses postbacks to share conversion data with advertisers and <a href="https://www.appsflyer.com/glossary/ad-network/">ad networks</a>. Privacy Sandbox provides APIs available for ad tech companies to access the attribution reports.</p>



<p>To help you get the most out of those bits, MMPs like AppsFlyer offer standardized methods for converting and interpreting bits into human-friendly metrics and actionable insights.</p>



<h2 class="wp-block-heading" id="h-data-granularity">Data granularity</h2>



<p>SKAN allocates 2-4 digits for source identifiers (depending on the number of installs) and permits only six bits for post-install conversion data (equivalent to 64 possible conversion values). This significantly limits the granularity with which marketers can analyze campaign performance and post-install activities.</p>



<p>In contrast, Privacy Sandbox offers 128 bits for the campaign sources and post-install events. I’ll save you the calculations and the weird numbers but trust me, you’ll get over a billion times more data with Sandbox than you do with SKAN.</p>



<p>Keep in mind, though, that in the Privacy Sandbox each source event, like an ad <a href="https://www.appsflyer.com/glossary/ctr/">click</a>, has a maximum number of &#8216;values&#8217; it can use, known as the contribution budget. Sandbox limits you to certain contribution budgets and adds random noise. This means that even though the data can be pretty granular, you’ll need to plan your budgets carefully and prioritize upfront.</p>



<h2 class="wp-block-heading" id="h-technical-complexity"><br>Technical complexity</h2>



<p>SKAN is like a black box managed by Apple, delivering just the essentials like winning campaigns and conversion counts.</p>



<p>In contrast, Privacy Sandbox is designed as a set of building blocks—enabling industry players like AppsFlyer to build their own solutions on top of it. These solutions must comply with strict cloud infrastructure guidelines to maintain privacy.</p>



<p>In addition, Sandbox offers a cross-network last-click attribution through the presence of a neutral player such as an <a href="https://www.appsflyer.com/glossary/mmp/">MMP</a>. That means AppsFlyer and other MMPs will have a significant role in the Sandbox attribution data flow providing insights on cross-network last-click attribution.</p>



<p>This key difference makes the Sandbox a more complex technology but also opens up opportunities for innovation and disruption in the industry.</p>



<h2 class="wp-block-heading" id="h-presenting-the-full-picture">Presenting the full picture</h2>



<p>Both SKAN and Privacy Sandbox are tailored to their respective operating systems (iOS and Android), making it hard for advertisers to see the full picture.</p>



<p>Add the fact that some ad networks haven&#8217;t fully adopted SKAN yet (which also doesn&#8217;t support Apple Search Ads), along with the fact that Privacy Sandbox is just getting started, and you&#8217;re left with a reality split across several &#8216;buckets of truth&#8217;—far from ideal for analyzing global campaign performance and make informed decisions.</p>



<p>In such a fragmented landscape, having a single source of truth is crucial. AppsFlyer continues to bridge this gap with its pioneering <a href="https://www.appsflyer.com/blog/measurement-analytics/ssot-bridging-data-gaps/">Single Source of Truth (SSOT)</a>, which consolidates all campaign data across media sources and platforms into one centralized view.</p>



<h2 class="wp-block-heading" id="h-summary">Summary</h2>



<p>In a privacy-first era, advertisers need to adapt to a new reality in which personal information is never revealed, measurement is aggregated and anonymous, the reporting intervals are long, and data is delayed and obscured.</p>



<p>While SKAN keeps attribution simple but very limited, Privacy Sandbox offers a much wider range of capabilities and data granularity, but requires a much heavier technological effort and the creation of complementary solutions.</p>



<p>AppsFlyer is already developing its next-generation products that will support Privacy Sandbox, enabling advertisers to seamlessly adopt these new technologies, protect user privacy, and enhance their marketing strategies.</p>
<p>The post <a href="https://www.appsflyer.com/blog/measurement-analytics/skan-vs-sandbox/">SKAN vs. Sandbox: what advertisers need to know</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


The app marketing world is still adjusting to the evolving privacy changes on iOS, and we are now on the verge of another round of disruptions with Privacy Sandbox on Android and the new opportunities that it introduces.
It’s only natural to stack iOS and Android against each other, so we decided to examine the similarities and differences between SKAN (soon to be revamped as AdAttributionKit) and Privacy Sandbox. Don’t worry though, we’ll (try to) keep things simple.
Before we begin
Google’s Privacy Sandbox is a broad initiative. It’s a suite of marketing infrastructure tools, covering targeting, retargeting, SDKs, and of course attribution.
Since SKAN focuses mostly on attribution, and for the sake of comparing apples to apples (See what I just did there?), we will focus on comparing SKAN to Sandbox’s Attribution Reporting API.
Scope and approach
Doing it the “Apple way”, SKAN is often perceived as a “black box”, naturally specific to iOS only.
With Privacy Sandbox, Google has taken a more collaborative approach and is gradually introducing the different modules for both web (starting with Chrome) and Android, allowing industry leaders such as AppsFlyer to iterate, build innovative solutions using the Sandbox building blocks, provide ongoing feedback, and actively influence the core principles. This approach comes with a cost, as Google often has to reverse decisions – as it did with the recent web cookies deprecation announcement.
Elimination of device IDs
The primary principle for maintaining user privacy is to obscure persistent user identifiers such as IDFAs or GAIDs, and both SKAN and Privacy Sandbox are designed to minimize the use of identifiers.
Notably, Apple’s ATT framework requires user consent to access IDFA, while Google hasn’t announced any plans to use an ATT-style opt-in mechanism.
We’re being asked a lot about the future of GAID (Google Advertising ID) and whether it’s planned to be placed behind an opt-in wall like web cookies are. There’s no formal answer on this one yet. However, bear in mind that none of the Privacy Sandbox APIs use GAID, which can provide a good indication of future direction.
Data aggregation
Both SKAN and Privacy Sandbox use data aggregation, grouping user data into anonymized cohorts to prevent individual profiling. This is a big deal for advertisers, but it’s an even bigger deal for ad networks and publishers that will no longer be able to track users and will have to find new creative ways to optimize their ad performance.
You can expect lots of  innovation in this area in the coming months and years.
Reporting
SKAN 4 and AdAttributionKit provide three postbacks and dictate aligning to pre-defined time windows of 2, 7 and 35 days. Kind of like a full-service restaurant that serves meals on specific hours only.
In contrast, the Sandbox Attribution API is like a 30-day buffet. You cannot get wild and eat all that you want due to some “budget” limitations (more on that later), but you’re not tied to strict time windows. When the month ends, it’s time to put the forks down!
While Sandbox’s flexible reporting windows are great news for advertisers, the 30-day limitation might disappoint some marketing managers looking for longer revenue metrics.
Random delays
With privacy-first attribution, data is never received in real-time in order to prevent the option to correlate report data with specific individuals. This forces advertisers to make longer experiments and leads to slower decision-making and reduced agility.
SKAN postbacks arrive with significant delays: 24-48 hours delay for the first postback and 24-144 hours for the 2nd and 3rd postbacks.
Privacy Sandbox incorporates two delay mechanisms to enhance privacy:
Event-level reports (designed for campaign optimization) are delayed by at least 1 day following an ad click and 1-30 days after an ad view—Talk about being late for the party!
Conversely, aggregatable reports (designed for analyzing campaign performance), are available within hours — certainly  a relief for advertisers.
Privacy thresholds
There’s a joke about a fan telling a little-known artist, “I bought your album!” and the artist responds, “Oh, it was you!”
This kind of sums up the challenge with privacy-focused ad measurement. When the numbers are small, pinpointing individuals becomes too easy, which isn’t great for privacy.
Both SKAN and Privacy Sandbox address that issue using privacy thresholds, but the implementation is different.
In low volumes, SKAN simply doesn’t give you information on post-install activity (as well as campaign information). That’s the main reason why we at AppsFlyer developed a null modeling solution for SKAN to compensate for that signal loss. Privacy Sandbox uses the notion of “noise”. It adds fake data to mask the real numbers. The noise can be significantly deceiving when data volumes are low, but as volume grows the relative noise size reduces and becomes negligible.
Tip: For both SKAN and Sandbox, low data volumes can pose challenges for advertisers. It’s best to allocate adequate budgets to each media source and avoid splitting campaigns excessively. This strategy ensures data volumes are sufficient to bypass privacy thresholds, providing more reliable reports. The more focused your budget, the more reliable your data.
Bit-based attribution
Both SKAN and Sandbox use “bits” to represent conversion or campaign data. Values represented by bits are more challenging to use but they ensure data is controlled, standardized, and more importantly: no direct identifiable information (like names, IDs, or even specific actions) is transmitted.
SKAN uses postbacks to share conversion data with advertisers and ad networks. Privacy Sandbox provides APIs available for ad tech companies to access the attribution reports.
To help you get the most out of those bits, MMPs like AppsFlyer offer standardized methods for converting and interpreting bits into human-friendly metrics and actionable insights.
Data granularity
SKAN allocates 2-4 digits for source identifiers (depending on the number of installs) and permits only six bits for post-install conversion data (equivalent to 64 possible conversion values). This significantly limits the granularity with which marketers can analyze campaign performance and post-install activities.
In contrast, Privacy Sandbox offers 128 bits for the campaign sources and post-install events. I’ll save you the calculations and the weird numbers but trust me, you’ll get over a billion times more data with Sandbox than you do with SKAN.
Keep in mind, though, that in the Privacy Sandbox each source event, like an ad click, has a maximum number of ‘values’ it can use, known as the contribution budget. Sandbox limits you to certain contribution budgets and adds random noise. This means that even though the data can be pretty granular, you’ll need to plan your budgets carefully and prioritize upfront.
Technical complexity
SKAN is like a black box managed by Apple, delivering just the essentials like winning campaigns and conversion counts.
In contrast, Privacy Sandbox is designed as a set of building blocks—enabling industry players like AppsFlyer to build their own solutions on top of it. These solutions must comply with strict cloud infrastructure guidelines to maintain privacy.
In addition, Sandbox offers a cross-network last-click attribution through the presence of a neutral player such as an MMP. That means AppsFlyer and other MMPs will have a significant role in the Sandbox attribution data flow providing insights on cross-network last-click attribution.
This key difference makes the Sandbox a more complex technology but also opens up opportunities for innovation and disruption in the industry.
Presenting the full picture
Both SKAN and Privacy Sandbox are tailored to their respective operating systems (iOS and Android), making it hard for advertisers to see the full picture.
Add the fact that some ad networks haven’t fully adopted SKAN yet (which also doesn’t support Apple Search Ads), along with the fact that Privacy Sandbox is just getting started, and you’re left with a reality split across several ‘buckets of truth’—far from ideal for analyzing global campaign performance and make informed decisions.
In such a fragmented landscape, having a single source of truth is crucial. AppsFlyer continues to bridge this gap with its pioneering Single Source of Truth (SSOT), which consolidates all campaign data across media sources and platforms into one centralized view.
Summary
In a privacy-first era, advertisers need to adapt to a new reality in which personal information is never revealed, measurement is aggregated and anonymous, the reporting intervals are long, and data is delayed and obscured.
While SKAN keeps attribution simple but very limited, Privacy Sandbox offers a much wider range of capabilities and data granularity, but requires a much heavier technological effort and the creation of complementary solutions.
AppsFlyer is already developing its next-generation products that will support Privacy Sandbox, enabling advertisers to seamlessly adopt these new technologies, protect user privacy, and enhance their marketing strategies.
The post SKAN vs. Sandbox: what advertisers need to know appeared first on AppsFlyer.

The app marketing world is still adjusting to the evolving privacy changes on iOS, and we are now on the verge of another round of disruptions with Privacy Sandbox on Android and the new opportunities that it introduces. It’s only natural to stack iOS and Android against each other, so we decided to examine the […]
The post SKAN vs. Sandbox: what advertisers need to know appeared first on AppsFlyer.

SKAN vs. Sandbox: what advertisers need to know

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2022/07/7629-Data-Clean-Rooms_1200x1200-2-290x170.png" class="attachment-thumbnail size-thumbnail wp-post-image" alt="" decoding="async" loading="lazy" /></figure>
<p>The post <a href="https://www.appsflyer.com/resources/guides/data-clean-rooms-v1/">It&#8217;s time to come clean &#8211; the complete data clean rooms guide</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


The post It’s time to come clean – the complete data clean rooms guide appeared first on AppsFlyer.

It’s time to come clean – the complete data clean rooms guide

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/08/53206-State-of-Gaming-2024_OG-290x170.jpg" class="attachment-thumbnail size-thumbnail wp-post-image" alt="" decoding="async" loading="lazy" /></figure>
<p>The post <a href="https://www.appsflyer.com/resources/reports/gated/gaming-state/">[Report] The State of Gaming App Marketing &#8211; 2024 Edition</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


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[Report] The State of Gaming App Marketing – 2024 Edition

<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_OG-290x170.png" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Overcoming signal loss OG image" decoding="async" loading="lazy" /></figure>
<p>The privacy era has led to a loss of data signals that has significantly hampered marketers’ ability to target, measure, and optimize their campaigns. According to Mckinsey, up to $10 billion is at risk because of signal loss — in the US alone! But thanks to innovation and adaptation, overcoming the challenge is more than [&#8230;]</p>
<p>The post <a href="https://www.appsflyer.com/blog/measurement-analytics/overcome-signal-loss/">How to overcome signal loss by building a new data reality</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


<figure style="margin-left: 0; margin-right: 0"><img width="290" height="170" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_OG-290x170.png" class="attachment-thumbnail size-thumbnail wp-post-image" alt="Overcoming signal loss OG image" decoding="async" loading="lazy" /></figure>
<p>The privacy era has led to a loss of data signals that has significantly hampered marketers’ ability to target, measure, and optimize their campaigns. According to Mckinsey, up to <a href="https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-demise-of-third-party-cookies-and-identifiers" target="_blank" rel="noreferrer noopener">$10 billion</a> is at risk because of signal loss — in the US alone!</p>



<p>But thanks to innovation and adaptation, overcoming the challenge is more than possible by building a new data reality based on filling gaps in existing data, as well as creating new data signals.</p>



<p>In this blog, we’ll explain what led to this reality, the impact of signal loss on marketing, and how to overcome it. Let’s dive in!&nbsp;&nbsp;</p>



<h2 class="wp-block-heading" id="h-what-is-signal-loss">What is signal loss</h2>



<p>The loss in data signals as the result of diminishing levels of user level data identifiers. These identifiers have been, and in some cases still are, the backbone on which performance-driven marketing measurement is based on. Signal loss is therefore a massive change and challenge in the digital marketing landscape.&nbsp;&nbsp;&nbsp;</p>



<h2 class="wp-block-heading" id="h-background-what-led-to-this-reality">Background: What led to this reality</h2>



<p>In recent years, there’s been increased scrutiny from legislators and consumers to protect user privacy through various regulations (GDPR, CCPA, DMA, to name a few major recent ones).</p>



<p>At its core, it&#8217;s about controlling how user level data is being shared across different companies and how consent to share this data is requested and presented.</p>



<p>In parallel (whether reactive or proactive), Google and Apple have developed mechanisms to limit/deprecate user level data via:&nbsp;</p>



<ul>
<li><strong>iOS &#8211; App Tracking Transparency (ATT):</strong> Led to the rate of installs with an <a href="https://www.appsflyer.com/glossary/idfa/">IDFA</a> dropping from 80% (due to Limit Ad Tracking) to only 27% (still very important for modelling).</li>
</ul>



<ul>
<li><strong>Android &#8211; Google Advertising ID (</strong><a href="https://www.appsflyer.com/glossary/gaid/"><strong>GAID</strong></a><strong>) deprecation:</strong> It is assumed that Google will eventually fully deprecate Android’s user level identifier, but not before 2025.</li>
</ul>



<ul>
<li><strong>Web &#8211; 3rd party cookies:</strong> After years of planned deprecation of cookies on its Chrome browser, Google decided in July 2024 to keep them after all, and adopt what appears to be a similar approach to ATT. “Instead of deprecating third-party cookies, we would introduce a new experience in Chrome that lets people make an informed choice&#8230; We&#8217;re discussing this new path with regulators, and will engage with the industry as we roll this out,” the company said in a <a href="https://privacysandbox.com/intl/en_us/news/privacy-sandbox-update/">statement</a>.&nbsp;<br><br>Although Google did not provide any details about this &#8220;new experience in Chrome that lets people make an informed choice&#8221;, it appears that signal loss will be mitigated, going from full to partial deprecation from non-consenting users only. But just how much is impossible to tell as there are still many unknowns: will Google use an opt-out or opt-in mechanism? Single or dual consent (advertiser and publisher side)? Strict/fixed or flexible use of language/UX functionality? Time will tell.</li>
</ul>



<p>But while the loss of user-level data is currently an iOS reality because of ATT, it will soon expand to Android and later to the Web, affecting all digital marketers. And while each scenario is different, the underlying story remains the same.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="160" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_4.jpg" alt="Overcoming signal loss - fading out user level data" class="wp-image-432920" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_4.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_4-300x72.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<h2 class="wp-block-heading" id="h-the-impact-of-signal-loss-on-advertisers">The impact of signal loss on advertisers</h2>



<p>While this ecosystem shift is a much-needed step to combat prevalent abuse in user data, it has been a painful adaptation for marketers who rely on user level data for targeting, measurement, and optimization.&nbsp;</p>



<h3 class="wp-block-heading" id="h-nbsp-1-measurement">&nbsp;1) Measurement</h3>



<p>Signal loss has a significant impact on measurement, creating two main challenges for marketers:</p>



<p><strong>a) Fragmented data</strong> has been a challenge for years but has increased significantly since iOS14.5 was released. To name just the important data sources:</p>



<ul>
<li><a href="https://www.appsflyer.com/glossary/mmp/">MMP</a> attribution (deterministic and probabilistic) and consequent in-app data</li>



<li>OS and stores (<a href="https://www.appsflyer.com/glossary/skadnetwork/">SKAN</a> and later Sandbox) data and consequent in-app data</li>



<li>SRN attribution data</li>



<li>iOS consenting user data</li>



<li>Apple Search Ads data</li>



<li>Top down measurement data (incrementality and <a href="https://www.appsflyer.com/glossary/media-mix-modeling/">MMM</a>)</li>



<li>Beyond mobile data: <a href="https://www.appsflyer.com/resources/guides/ctv-advertising/">CTV</a>, Web, PC&amp;C, offline</li>
</ul>



<p>And that’s just in iOS.</p>



<p>How does one reconcile data from so many sources and frameworks to understand performance?</p>



<p><strong>b) Limited and delayed data:</strong></p>



<p>SKAN and <a href="https://www.appsflyer.com/blog/mobile-marketing/ad-attribution-kit-wwdc24/">AdAttributionKit </a>(SKAN’s successor) offer intentionally delayed signals and only up to 64 values (and only 3 in later postbacks). And despite improvements in AdAttributionKit and <a href="https://www.appsflyer.com/glossary/android-privacy-sandbox/">Sandbox </a>data, which is said to reach a 30-day LTV, OS data will still come in delayed and limited. As marketers rely on real time, post-install signals for optimization, the fact that OS data is delayed and limited is a significant hurdle.&nbsp;</p>



<h3 class="wp-block-heading" id="h-nbsp-2-targeting">&nbsp;2) Targeting</h3>



<p>When user level data is not available:</p>



<ul>
<li>Advertisers cannot create remarketing segments, and as a result they cannot engage effectively with their existing engaged customers, which leads to increased cost per action</li>



<li>Advertisers cannot create suppression lists so they end up targeting the same users, which leads to increased <a href="https://www.appsflyer.com/glossary/cpa/">cost per new acquisition</a></li>



<li><a href="https://www.appsflyer.com/glossary/ad-network/">Ad networks</a>’ ability to optimize delivery is significantly hurt, which leads to higher costs across the board</li>
</ul>



<p>In short, signal loss resulting from privacy measures has compromised the completeness of data, posing a risk of misinterpretation and, consequently, misleading insights and the wrong decisions. As a result, a marketer’s job in the signal loss era is 10x harder and so is measurement!</p>



<h2 class="wp-block-heading" id="h-how-to-overcome-signal-loss-to-maintain-confidence-in-measurement">How to overcome signal loss to maintain confidence in measurement</h2>



<p>Before ATT, marketers had a rich view with full user level data granularity, like an ultra HD 8k resolution image:</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="671" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1A.jpg" alt="Overcoming signal loss - the picture pre ATT" class="wp-image-432931" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1A.jpg 671w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1A-300x165.jpg 300w" sizes="(max-width: 671px) 100vw, 671px" /></figure></div>


<p>However, the new data reality where user level data is diminishing is a fact and there’s no going back. In this reality, there are a lot of holes, making it difficult to see the full picture.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1B.jpg" alt="Overcoming signal loss - the current data picture" class="wp-image-432941" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1B.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1B-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<p>Therefore, marketers must leverage every available data signal and consolidate the different data sources into a single source of truth to measure their campaigns with confidence.</p>



<p>To create a new “data picture”, gaps must be filled wherever possible and new data signals must be added to further compensate. Let’s explore this.</p>



<h3 class="wp-block-heading" id="h-nbsp-1-filling-in-the-gaps-in-the-existing-data-set-with-modeling">&nbsp;1) Filling in the gaps in the existing data set with modeling</h3>



<p>Modeling has been around for years but it wasn’t truly needed in the past since most data was deterministic. However, in a reality of signal loss, it becomes a must, and it can be done with models that do NOT infringe on user privacy. And with AI at our side, the accuracy of models is dramatically improving model accuracy.</p>



<p>Modeling is used to fill in the gaps in:</p>



<ol style="list-style-type:lower-alpha">
<li><strong>OS attribution: </strong>Because SKAN data comes in late and limited (and so will data from Sandbox), gaps in the data are created. With modelling, real time signals, geo-level data (not available in SKAN), and <a href="https://www.appsflyer.com/glossary/ltv/">LTV</a> data for day 7, day 30, and beyond can be provided.</li>
</ol>



<ul>
<li><strong>Modelling on the media side: </strong>SKAN limitations make measurement difficult for Self-Reporting Networks, and since they&#8217;ve always relied solely on deterministic attribution, they miss out. By leveraging <a href="https://www.appsflyer.com/glossary/probabilistic-modeling/">probabilistic modelling</a> on top of deterministic, they gain lost credit. According to our analysis, Snap increased its share in the iOS install pie by 138%, and its eCPI dropped 46%.&nbsp;</li>
</ul>



<p>Moreover, large media companies like Google and Meta have also been placing more weight on modeling to navigate and overcome data signal loss challenges in their advertising and marketing strategies.</p>



<p>For instance, Google Ads utilizes machine learning models to refine bidding strategies, while Meta&#8217;s Ads Manager platform employs predictive modeling to tailor ad delivery and targeting. Additionally, both companies leverage data modeling to create personalized experiences, reach relevant audiences, and optimize campaign performance.</p>



<ul>
<li><strong>Bottom-up (last touch) measurement:</strong> Incrementality and Media Mix Modelling (<a href="https://www.appsflyer.com/glossary/media-mix-modeling/">MMM</a>) provide a <a href="https://www.appsflyer.com/blog/measurement-analytics/piece-measurement-puzzle-together/">complementary perspective on campaign performance</a> without having to rely solely on last touch bottom-up signals.</li>
</ul>



<p>To continue with the high res image analogy, modelling helped fill up some holes, but it’s still not enough.&nbsp;</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1C.jpg" alt="Overcoming signal loss - the new data picture" class="wp-image-432951" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1C.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1C-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<h3 class="wp-block-heading" id="h-nbsp-2-utilizing-and-creating-new-signals">&nbsp;2) Utilizing and creating new signals</h3>



<ol>
<li><strong>Top of funnel creative and campaign signals: </strong>With fewer bottom funnel signals, more focus is now placed on the top of the funnel where there is an abundance of data tied to creatives and campaigns. This covers two areas:</li>
</ol>



<ul>
<li><strong>Data from creatives:</strong> Rich and highly granular signals can be obtained, for example, by identifying, within a single ad, scene types (e.g. user generated content, animation/real-life footage, opening/closing) and specific elements (anything from color, scenery, objects, texts etc).</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="671" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_3.jpg" alt="Overcoming signal loss - creative optimization" class="wp-image-433530" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_3.jpg 671w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_3-300x165.jpg 300w" sizes="(max-width: 671px) 100vw, 671px" /></figure></div>


<ul>
<li><strong>Enriched-engagement types (EET):</strong> The <a href="https://www.appsflyer.com/blog/measurement-analytics/enriched-engagement-types/">current attribution standard that only looks at clicks or views is flawed</a>. There are many signals in between that can provide valuable performance data and redefine attribution logic.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="671" height="371" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_2.jpg" alt="Overcoming signal loss - enriched engagement types" class="wp-image-432961" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_2.jpg 671w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_2-300x166.jpg 300w" sizes="(max-width: 671px) 100vw, 671px" /></figure></div>


<p><strong>2) [More] 1st party data:</strong> With data sharing between different companies limited, the value of 3rd party data sinks. Instead, marketers must step up their use of 1st party data and prioritize its collection and utilization. This includes:</p>



<ul>
<li>How to properly collect it, ask users for their info (UX and legal included)</li>



<li>How to make sure the data is clean and actionable</li>



<li>How to use it in <a href="https://www.appsflyer.com/glossary/owned-media/">owned media</a></li>



<li>How to use it paid media (remarketing, commerce media)</li>
</ul>



<p>This data need not remain only within a company’s own environment. A <strong>data collaboration platform</strong> can then serve as a trusted environment for 1st-party data monetization, audience activation, and measurement. By allowing brands to share this data with different companies in a privacy-compliant way, marketers can truly maximize the potential of their own highly valuable data.</p>



<p><strong>3) Omni-channel signals: </strong>Apps, Web, CTV, PC &amp; Console, as well as commerce media networks and out-of-home all present unique opportunities to digitally acquire and engage with a user base. By connecting attribution across channels, marketers can tie new data points and user behavior across their various platforms together to provide a holistic understanding of how cross platform marketing drives business outcomes.</p>



<p><strong>4) Single source of truth (SSOT):</strong> As mentioned above, data fragmentation has led to an extremely convoluted reality that’s become largely non-actionable for marketers.</p>



<p>Enter SSOT which creates a single reality by combining data from multiple sources and applies robust tech solutions to identify and remove duplicate installs, fill missing data/gaps in geos, web-to-app, longer LTV, null CV modeling, organic, remarketing etc.</p>



<p>According to our analysis, by consolidating the data into a single view, the average app sees a 29% lift in attributed installs, a 40% drop in eCPI, and a 62% surge in revenue attributed to marketing.</p>



<p>At present, SSOT is centered on iOS but the solution for Web and Android will be similar.</p>



<p>When we add new data signals, we gain information that wasn’t there before for a wider picture of our marketing.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="670" height="370" src="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1D.jpg" alt="Overcoming signal loss - the new data reality" class="wp-image-432971" srcset="https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1D.jpg 670w, https://www.appsflyer.com/wp-content/uploads/2024/07/53149.-Blog_-How-to-overcome-signal-loss_inline_1D-300x166.jpg 300w" sizes="(max-width: 670px) 100vw, 670px" /></figure></div>


<h2 class="wp-block-heading" id="h-the-bottom-line">The bottom line</h2>



<p>Signal loss has created a challenging environment for performance marketers. With diminishing user level data, driving growth is much harder. Innovative solutions are needed to fill in the gaps in the existing data and create new data signals to allow performance marketers regain control and measure their campaigns with confidence.&nbsp;</p>
<p>The post <a href="https://www.appsflyer.com/blog/measurement-analytics/overcome-signal-loss/">How to overcome signal loss by building a new data reality</a> appeared first on <a href="https://www.appsflyer.com">AppsFlyer</a>.</p>


The privacy era has led to a loss of data signals that has significantly hampered marketers’ ability to target, measure, and optimize their campaigns. According to Mckinsey, up to $10 billion is at risk because of signal loss — in the US alone!
But thanks to innovation and adaptation, overcoming the challenge is more than possible by building a new data reality based on filling gaps in existing data, as well as creating new data signals.
In this blog, we’ll explain what led to this reality, the impact of signal loss on marketing, and how to overcome it. Let’s dive in!  
What is signal loss
The loss in data signals as the result of diminishing levels of user level data identifiers. These identifiers have been, and in some cases still are, the backbone on which performance-driven marketing measurement is based on. Signal loss is therefore a massive change and challenge in the digital marketing landscape.   
Background: What led to this reality
In recent years, there’s been increased scrutiny from legislators and consumers to protect user privacy through various regulations (GDPR, CCPA, DMA, to name a few major recent ones).
At its core, it’s about controlling how user level data is being shared across different companies and how consent to share this data is requested and presented.
In parallel (whether reactive or proactive), Google and Apple have developed mechanisms to limit/deprecate user level data via: 
iOS – App Tracking Transparency (ATT): Led to the rate of installs with an IDFA dropping from 80% (due to Limit Ad Tracking) to only 27% (still very important for modelling).
Android – Google Advertising ID (GAID) deprecation: It is assumed that Google will eventually fully deprecate Android’s user level identifier, but not before 2025.
Web – 3rd party cookies: After years of planned deprecation of cookies on its Chrome browser, Google decided in July 2024 to keep them after all, and adopt what appears to be a similar approach to ATT. “Instead of deprecating third-party cookies, we would introduce a new experience in Chrome that lets people make an informed choice… We’re discussing this new path with regulators, and will engage with the industry as we roll this out,” the company said in a statement. 
Although Google did not provide any details about this “new experience in Chrome that lets people make an informed choice”, it appears that signal loss will be mitigated, going from full to partial deprecation from non-consenting users only. But just how much is impossible to tell as there are still many unknowns: will Google use an opt-out or opt-in mechanism? Single or dual consent (advertiser and publisher side)? Strict/fixed or flexible use of language/UX functionality? Time will tell.
But while the loss of user-level data is currently an iOS reality because of ATT, it will soon expand to Android and later to the Web, affecting all digital marketers. And while each scenario is different, the underlying story remains the same.

The impact of signal loss on advertisers
While this ecosystem shift is a much-needed step to combat prevalent abuse in user data, it has been a painful adaptation for marketers who rely on user level data for targeting, measurement, and optimization. 
 1) Measurement
Signal loss has a significant impact on measurement, creating two main challenges for marketers:
a) Fragmented data has been a challenge for years but has increased significantly since iOS14.5 was released. To name just the important data sources:
MMP attribution (deterministic and probabilistic) and consequent in-app data
OS and stores (SKAN and later Sandbox) data and consequent in-app data
SRN attribution data
iOS consenting user data
Apple Search Ads data
Top down measurement data (incrementality and MMM)
Beyond mobile data: CTV, Web, PC&C, offline
And that’s just in iOS.
How does one reconcile data from so many sources and frameworks to understand performance?
b) Limited and delayed data:
SKAN and AdAttributionKit (SKAN’s successor) offer intentionally delayed signals and only up to 64 values (and only 3 in later postbacks). And despite improvements in AdAttributionKit and Sandbox data, which is said to reach a 30-day LTV, OS data will still come in delayed and limited. As marketers rely on real time, post-install signals for optimization, the fact that OS data is delayed and limited is a significant hurdle. 
 2) Targeting
When user level data is not available:
Advertisers cannot create remarketing segments, and as a result they cannot engage effectively with their existing engaged customers, which leads to increased cost per action
Advertisers cannot create suppression lists so they end up targeting the same users, which leads to increased cost per new acquisition
Ad networks’ ability to optimize delivery is significantly hurt, which leads to higher costs across the board
In short, signal loss resulting from privacy measures has compromised the completeness of data, posing a risk of misinterpretation and, consequently, misleading insights and the wrong decisions. As a result, a marketer’s job in the signal loss era is 10x harder and so is measurement!
How to overcome signal loss to maintain confidence in measurement
Before ATT, marketers had a rich view with full user level data granularity, like an ultra HD 8k resolution image:

However, the new data reality where user level data is diminishing is a fact and there’s no going back. In this reality, there are a lot of holes, making it difficult to see the full picture.

Therefore, marketers must leverage every available data signal and consolidate the different data sources into a single source of truth to measure their campaigns with confidence.
To create a new “data picture”, gaps must be filled wherever possible and new data signals must be added to further compensate. Let’s explore this.
 1) Filling in the gaps in the existing data set with modeling
Modeling has been around for years but it wasn’t truly needed in the past since most data was deterministic. However, in a reality of signal loss, it becomes a must, and it can be done with models that do NOT infringe on user privacy. And with AI at our side, the accuracy of models is dramatically improving model accuracy.
Modeling is used to fill in the gaps in:
OS attribution: Because SKAN data comes in late and limited (and so will data from Sandbox), gaps in the data are created. With modelling, real time signals, geo-level data (not available in SKAN), and LTV data for day 7, day 30, and beyond can be provided.
Modelling on the media side: SKAN limitations make measurement difficult for Self-Reporting Networks, and since they’ve always relied solely on deterministic attribution, they miss out. By leveraging probabilistic modelling on top of deterministic, they gain lost credit. According to our analysis, Snap increased its share in the iOS install pie by 138%, and its eCPI dropped 46%. 
Moreover, large media companies like Google and Meta have also been placing more weight on modeling to navigate and overcome data signal loss challenges in their advertising and marketing strategies.
For instance, Google Ads utilizes machine learning models to refine bidding strategies, while Meta’s Ads Manager platform employs predictive modeling to tailor ad delivery and targeting. Additionally, both companies leverage data modeling to create personalized experiences, reach relevant audiences, and optimize campaign performance.
Bottom-up (last touch) measurement: Incrementality and Media Mix Modelling (MMM) provide a complementary perspective on campaign performance without having to rely solely on last touch bottom-up signals.
To continue with the high res image analogy, modelling helped fill up some holes, but it’s still not enough. 

 2) Utilizing and creating new signals
Top of funnel creative and campaign signals: With fewer bottom funnel signals, more focus is now placed on the top of the funnel where there is an abundance of data tied to creatives and campaigns. This covers two areas:
Data from creatives: Rich and highly granular signals can be obtained, for example, by identifying, within a single ad, scene types (e.g. user generated content, animation/real-life footage, opening/closing) and specific elements (anything from color, scenery, objects, texts etc).

Enriched-engagement types (EET): The current attribution standard that only looks at clicks or views is flawed. There are many signals in between that can provide valuable performance data and redefine attribution logic.

2) [More] 1st party data: With data sharing between different companies limited, the value of 3rd party data sinks. Instead, marketers must step up their use of 1st party data and prioritize its collection and utilization. This includes:
How to properly collect it, ask users for their info (UX and legal included)
How to make sure the data is clean and actionable
How to use it in owned media
How to use it paid media (remarketing, commerce media)
This data need not remain only within a company’s own environment. A data collaboration platform can then serve as a trusted environment for 1st-party data monetization, audience activation, and measurement. By allowing brands to share this data with different companies in a privacy-compliant way, marketers can truly maximize the potential of their own highly valuable data.
3) Omni-channel signals: Apps, Web, CTV, PC & Console, as well as commerce media networks and out-of-home all present unique opportunities to digitally acquire and engage with a user base. By connecting attribution across channels, marketers can tie new data points and user behavior across their various platforms together to provide a holistic understanding of how cross platform marketing drives business outcomes.
4) Single source of truth (SSOT): As mentioned above, data fragmentation has led to an extremely convoluted reality that’s become largely non-actionable for marketers.
Enter SSOT which creates a single reality by combining data from multiple sources and applies robust tech solutions to identify and remove duplicate installs, fill missing data/gaps in geos, web-to-app, longer LTV, null CV modeling, organic, remarketing etc.
According to our analysis, by consolidating the data into a single view, the average app sees a 29% lift in attributed installs, a 40% drop in eCPI, and a 62% surge in revenue attributed to marketing.
At present, SSOT is centered on iOS but the solution for Web and Android will be similar.
When we add new data signals, we gain information that wasn’t there before for a wider picture of our marketing.

The bottom line
Signal loss has created a challenging environment for performance marketers. With diminishing user level data, driving growth is much harder. Innovative solutions are needed to fill in the gaps in the existing data and create new data signals to allow performance marketers regain control and measure their campaigns with confidence. 
The post How to overcome signal loss by building a new data reality appeared first on AppsFlyer.

The privacy era has led to a loss of data signals that has significantly hampered marketers’ ability to target, measure, and optimize their campaigns. According to Mckinsey, up to $10 billion is at risk because of signal loss — in the US alone! But thanks to innovation and adaptation, overcoming the challenge is more than […]
The post How to overcome signal loss by building a new data reality appeared first on AppsFlyer.