Be fully ready for iOS 14, before it’s here

A few weeks ago we announced AppsFlyer’s SKAdNetwork solution with a blog post and a sneak peek into the dedicated dashboard. On our side, once iOS 14 drops, we’re fully prepared to receive SKAdNetwork postback data, validate its correctness and uniqueness, enrich it with other data points and help networks optimize the advertisers’ campaigns based on these insights. Advertisers will have access to a dedicated SKAdNetwork dashboard that visualizes the data. 

To most advertisers, however, SKAdNetwork is still a new solution. Advertisers have become accustomed to receiving and analyzing data in a certain way and the new SKAdNetwork has turned this whole system on its head. Advertisers are unfamiliar with this new system and the potential value it will provide them. 

It’s a tricky situation; SKAdNetwork will not be fully available until the public release of iOS 14, yet advertisers are eager to prepare in advance and educate themselves (and their teams) about the upcoming changes. What will the data look like? What kind of insights can be gathered? How can measurement and conversion value be optimized? 

There’s a bit of a puzzle here; you can’t be prepared without the SKAdNetwork data, but the data won’t be available ahead of time to allow for preparation.

We aren’t waiting

We are determined to help advertisers prepare for SKAdNetwork insights in the best way possible, so we have designed an exclusive tool to help our customers.

Introducing: SKAdNetwork Simulation by AppsFlyer. This new dashboard helps advertisers get a sense of what their SKAdNetwork data will look like and configure the fields they’d like to measure. Don’t let the “simulation” part of the name confuse you; this dashboard is based on each customer’s real data. 

By experimenting with the SKAdNetwork configurations for this dashboard and witnessing the real impact on the insights, advertisers can optimize and strategize, ahead of the public iOS 14 release. This means that the day iOS 14 becomes available, advertisers will already be equipped with the tools for making the most of their SKAdNetwork data.

How does it work?

As mentioned, this dashboard relies on real customer data, but only the data that will be available for measurement in SKAdNetwork.

• It only includes relevant attribution flows: app-to-app direct click-to-install flows. Flows that will not be included in real SKAdNetwork data, such as view-through and deferred click-through attribution data, are not manifested in this dashboard.
• The dashboard only displays events which would have been mapped according to your current SKAd conversion value configuration.

You can choose which of the 3 post-install modes you’d like to activate, determining the optimal strategy for conversion value mapping. Choose between revenue, conversion and engagement. 

What do I need to do?

Not a thing. If you’re an AppsFlyer customer with an iOS app, you can go check out the simulation dashboard right now. It will already be populated with data for you to explore.

Ahead of the release of iOS 14, however, we strongly recommend you update your AppsFlyer SDK to v6.0.2, and configure the events/revenue you’d like to measure with SKAdNetwork. This SDK is fully iOS 14-ready.
We also recommend that you ensure your advertising partners are integrated with AppsFlyer around SKAdNetwork, so that data can be attributed accordingly.

Join me for a quick tour of the new dashboard:

Log in to your AppsFlyer dashboard

The post Announcing: SKAdNetwork Simulation Dashboard appeared first on AppsFlyer.

Today marks an important milestone for AppsFlyer with the announcement of our next-generation cost aggregation product, Xpend. Over the past few years, we’ve worked with thousands of customers and partners measuring tens of billions of dollars in ad spend through our legacy cost aggregation product. Everything we learned was used to create Xpend.

With Xpend, you can calculate your true ROI with a holistic cost aggregation solution, built on attribution data you can trust.

If you are a performance marketer, you are familiar with the pain of fragmented cost data and are well aware of the market’s need for a cost standardization solution. You’ve done the tedious work of manually generating weekly spend reports for hundreds of channels, pulled together endless spreadsheets, combining data from different sources, filling in missing gaps, and correcting wrong data. And, you’ve likely come to terms with how inefficient and error-prone this all is.

Despite putting in the effort, the data you get is often not at the level of granularity you need to make smart decisions. Simply put, the data can’t be relied upon to allow marketing teams to act fast on their spending goals, or accurately optimize their campaign budget in any way.

Since ROI and ROAS are such important KPIs for performance marketers, it’s hard to imagine not having a solution that can accurately provide cost data at scale or be counted on to attribute that data properly.

That’s why we’ve built on years of experience working with performance marketers to create a product that can truly meet all of their cost aggregation needs, Xpend.

Xpend: an accurate, complete, and actionable solution

Xpend is replacing a previous solution that processed ad spend data manually via an ingestion file or through the attribution link. As marketers struggle to keep up with their scale and data complexity, the Xpend team recognized that a more innovative approach is necessary to achieve real optimization success.

Furthermore, with industry changes looming above, using cost data tied to attribution links alone may pose its own set of challenges. This is why aggregating cost data directly through integrations with network APIs is a critical solution for tomorrow’s marketers

As we have written before, having partial ROI data is almost the same as having no ROI data (as it came to be looked at as a zero-sum game). Data comes from hundreds of channels, ad networks, and custom sources; each with thousands of campaigns and keywords, endless creatives and ads. When you add different currencies, source-specific dimensions, and various placements to the mix and you’ve got yourself what some marketers might call “their worst nightmare.

With the launch of Xpend, we set out to provide solutions to these challenges based on years of dealing with data at scale.

Beyond scale, we understand the need for a reliable platform that is built to support complex schema and data mapping. Rather than having to work with multiple vendors, Xpend lets you access all of your data from one in-house solution. This means you don’t have to rely on ‘hacks’ resorted to by other providers to extract the data in a delayed and untrustworthy process that can conflict with data security and privacy compliance standards.

Measuring ROI at a granular level is no longer a fantasy but rather can be provided for you at the click of a button with the same attribution platform you know and trust. After all, why does attribution need to be separate from your cost data? It doesn’t, and that’s why Xpend is the only right solution.

Cost ETL (Extract, Transform, Load)

Since each channel or source may differ in its campaign and reporting schema, querying and analyzing data directly becomes challenging, which is what Xpend solves for.

CostETL will provide streamlined access to all this normalized cost data directly into an S3 bucket. This makes the process of ingesting data into your own BI system a breeze, with a customized data scheme and regular data updates.

60 + API Integrations, now including Twitter, Tencent Social Ads, and more.

In the past few months alone, AppsFlyer Xpend has reached 60+ API integration supporting all the major networks. We are excited to announce that Twitter and Tencent Social Ads are now fully integrated via reporting APIs into Xpend, as well.

With the industry beginning to shift towards a more aggregate way of measuring marketing efforts, the importance of having an accurate, complete, actionable, and secure cost aggregation solution has become paramount.

In parallel to our innovative solutions for attribution in the aggregate era, we are also ensuring that your entire marketing stack is all-systems-go for the challenges that lie ahead.

It’s time to consolidate vendors, empower yourself with sophisticated solutions, and focus on your bottom-line.

The post Announcing Xpend appeared first on AppsFlyer.

Apple’s App Store has long been regarded as the safest environment for users to install apps. Any developer looking to submit their app to the store must go through a strict vetting process which is designed to protect users from code that puts user privacy at risk, malicious adware, and any other type of harmful content that could harm Apple’s clean image. The term “walled garden” has justified its name.

When it comes to mobile attribution fraud, past assumptions were that various and  familiar fraud methods, which relied on malicious SDKs and code on the user’s device, were considered irrelevant for iOS devices, thanks to this strict vetting process.  

Until recently…

New research by Snyk, the open source security company, revealed a method where app developers can “hide” a piece of their code from Apple’s strict inspections.

“Our research team discovered that a popular iOS Advertising SDK, used by over 1,200 apps in the AppStore, with more than 300 Million downloads combined — injects code into standard iOS functions within the application and is capable of intercepting all HTTP requests made by the app. This gives the SDK access to a significant amount of data including private user information, cookies and authentication tokens, and works to steal potential revenue from other ad networks the application may be using.”  

Danny Grander, CSO and co-founder at Snyk

The case discovered by Snyk was seemingly carried out to perform a sophisticated type of mobile attribution fraud; however, the way at which this scheme came to play was the real cause for concern.

Hidden sophistication

The specific case mentioned above detected a piece of code that was masked when running through Apple’s review. The code was deliberately designed to turn-off once it identified that it was running in a simulated environment, if there was a debugger attached, if the phone was rooted, or if a VPN was enabled. This type of sophisticated masking created a code sequence which is extremely difficult to detect, and likely the reason why Apple missed it during their seemingly meticulous inspections.

The code itself was placed on various iOS apps as a standard ad network SDK, with the intention of harvesting information from ad clicks generated by users.

The potential applications of such a security loophole would mean that similar methods for harvesting sensitive user-data are most likely already in use across other apps for reasons beyond attribution fraud.

While harvesting user-data for other purposes, the case presented is believed to have been mainly focused on generating revenue through mobile attribution fraud, applying an evolved form of install hijacking.

The evolution of install hijacking

Install hijacking is a form of fraud in which a media source steals credit for an app install from another media source. This is often carried out using fake clicks that are artificially injected into the user journey, with the purpose of tricking last-click attribution models into its associated last-click report to the fraudulent source. The closer the click will be to the original ad click, the harder it will be to distinguish between them and detect it as fraud.

These clicks can be generated through malware located on another app on the user’s device, which is triggered once a new app install is identified. 
This new version of install hijacking behaves in a similar way, in that it too relies on a piece of malware. However, this malware is triggered by clicks, rather than an install initiation. The malware can scan through all the clicks coming through the user’s device, and generate a fake click, populated with the fraudster’s details in order to steal credit for any install that may result from those clicks.

Beyond the malicious code’s sophisticated masking, this new fraud version can be extremely elusive and difficult to detect, especially when it is done “correctly”, as it attempts to bypass common CTIT based detection algorithms. 

Let’s examine a few familiar distribution patterns to see how this plays out.

Our first point of reference will be Network A’s CTIT distribution. Network A delivers clean and fraud-free traffic.

Fraud-free CTIT distribution

Example 1: A click is injected 10 seconds after a legitimate click

Now let’s assume that Network B detects each and every click reported by Network A and generates its own click exactly 10 seconds after each click. Network B’s CTIT distribution will now be divided into 2 sections:

Click injected 10 seconds after original click

The installs with CTIT under 10 seconds are attributed to Network A (green), while anything coming in at 10+seconds will be attributed to Network B (orange).

Network B’s CTIT distribution will be slightly skewed to the right, as Network B’s CTIT distribution effectively begins at the CTIT=10 mark. This makes it difficult for standard algorithms to detect. However, CTIT is not AppsFlyer’s only fraud indicator. By analyzing the CTCT distribution (Click-To-Click-Time) we can also identify time difference abnormalities between the two following ad-clicks.

Using CTCT as a continuous variable, allows us to create a visual representation of its distribution in-order to detect anomalies, just like we do with CTIT. When reviewing Network B’s CTCT distribution, activity spikes that could indicate fraud become more visible.

Network B CTCT distribution

In order to remain undetected, Network B won’t actually generate a click for 100% of Network A’s clicks as this will attract too much attention. Alternatively, Network B will generate lower click volumes in order to remain unnoticed.

Example 2: A fake click injected 30+ seconds after a legitimate click

In an attempt to “normalize” it’s activity, Network B will generate its fake clicks ~30 seconds after Network A’s original click.

By doing so, Network B will “sacrifice” some of the potential stolen activity. The upside is that the CTCT graph created for these attributed installs will not look as “bad” as before, which may not be significant enough for standard detection algorithms to detect. However, in this case, the CTIT distribution will be heavily skewed to the right, which will trigger Protect360’s MLE (Maximum Likelihood Estimation) algorithm to detect the pattern as fraudulent, as seen in the graph below (Network B’s CTIT begins at the 30 seconds mark).

Click injected 30 seconds after original click

MLE enables Protect360’s detection algorithms to identify behavior anomalies and curve differences that can’t be seen by the naked eye (no matter how professional it may be). Our detection is carried out by comparing each app’s unique behavior pattern to its own common behavior trends across several variations. Unlike cases where all apps are measured under similar benchmarks, this allows us to compare apples to apples and avoid false detection. 

Key takeaways

Fraud identification cannot rely on just one parameter or set of parameters. Nor can we assume that a specific environment, as safe as it may be, is truly impervious to specific types of fraud or fraud in general.

A solid anti-fraud solution is an adaptive one. One that can creatively use the data points and measurement at its disposal to identify new types of fraud as they materialize.

As iOS now presents a new vulnerability (which many have overlooked), it becomes clear that security and user privacy play hand-in-hand with fraud protection.

The post Flying under the radar appeared first on AppsFlyer.

Ten years ago, when I first started using a smartphone, I installed many apps, and like most people, I was fairly receptive to new apps as well as app install ads. 

Today, though, as the number of apps on our devices increases and our attention span decreases, the threshold for installing a new app is much higher than ever before.

An ad sending users directly to an app store to install an app works well in developing regions, with first time users, and many other cases. However, savvier users seeking information on an item, product, service, TV show, vacation, or promotion featured in an ad may find being rerouted to an app store disorienting or frustrating. In these more advanced app markets, brands should lean on their mobile websites to drive growth, particularly with savvy users.  

Leveraging the web for growth

Great ad creatives and ad personalization are not enough anymore for advanced users. These users need more reasons to install your app and actually remember to use it. How can you create engagement and motivation to install an app, given that engagement with online ads is limited and your app store page is out of your control? One great solution is web campaign-to-app. 

We’ve always been big believers in the web. That’s why we’ve invested in web-related products and features like OneLink deep linking and deferred deep linking, Smart Banners, and People-Based Attribution and launched our free-for-life package, Zero, as  part of AppsFlyer’s Zero Budget Marketing initiative to help app developers leverage owned media, especially web, for growth.

Unlimited, untapped opportunities

How can mobile web drive growth and engagement? Landing users on your mobile website opens unlimited possibilities for you to engage with users in different ways. In addition, if the user is a repeat visitor, you may have information about them based on past visits to your website. Since the website is yours, there are so many untapped opportunities. You can, for example:

1. Create personalized experiences, enabling users to explore your service, product, or game on your website and/or landing page. 
2. Create a personalized promotion for a user to complete a transaction in the app, by leveraging OneLink’s deferred deep linking.  
3. Leverage AppsFlyer’s Smart Banners to direct users to an app store, allowing them to install the app, or open it if it’s already installed, at the moment that best suits them. 

Some may claim that this funnel is longer, requiring at least one more click and a “detour” through a website. That’s right – it might look longer, but in fact, for more advanced, goal-oriented users, it is a much more effective funnel for increasing conversion rates and overall ROI. 

High-intent customers need compelling reasons to install your app, and these reasons should come sooner in the funnel. How about delighting them right after they click on an ad with information about the desired product or service and avoiding the possible friction of the app store install page? That’s exactly where web campaign-to-app can help you.

Web campaign-to-app use cases

What would a web campaign-to-app funnel look like? The flow below shows only one of an endless number of examples:

1. A user clicks on a web ad, in-app promotion, or search ad and is directed to the advertiser’s mobile website
2. The advertiser can engage and promote specials in various ways, for example:
   1. Display a customized Smart Banner incentivizing users to install the app and enjoy an additional $10 discount on the shoes featured in the web ad.
   2. Provide promotional content on the page to engage and educate, and include an incentive in hyperlinked text or a CTA button with a deep link behind it.
3. The user clicks on the Smart Banner or hyperlinked text and is brought to an app store to install the app or goes straight to step 4 if the app is already installed.
4. After installing and opening the app, the user reaches the right in-app content, in the context of the promotion, and the media source is attributed.

Another important use case worth mentioning is search engine marketing (SEM) which allows brands to bid on long tail, high-intent keywords, at a lower cost. We see the SEM use case as an especially significant source for app growth going forward.

So what’s new here?

You may be asking yourself: why do we think web campaign-to-app is such a big deal? For the first time, your media partners will be able to launch a campaign with your website — not an app store page — as the destination. More significantly, your partners will get credited for installs and down-funnel conversions based on the configured lookback window, while you can bypass app store platform fees.  

Why now?

Based on our data, web engagement has been underutilized to date. In addition, we believe that iOS 14 will push the market to look for new ways to engage with their users. Now is the time to connect the dots with web campaign-to-app and run paid campaigns to drive traffic to your own website and landing pages; create a new web engagement funnel; and acquire loyal app users. 

From a privacy perspective, because the journey includes ad networks and/or owned digital properties, IDFA does not need to be collected for attribution purposes and first-party data can be leveraged to optimize the experience. 

We’re not the only ones excited by the web campaign-to-app opportunity. We continue to be inspired by some of our customers already leveraging these tools in innovative ways. Some have created promotions focused on in-app conversion while others have deepened engagement with their website visitors.

Implementing web campaign-to-app

Executing on the web-to-app opportunity is not only powerful and compelling, it’s simple. Advertisers need only to carry out the following steps:

• Implement the AppsFlyer web SDK 
• Activate Smart Banners on web pages and/or landing pages
• In the AppsFlyer dashboard, define a redirect parameter in the partner integration area and enable the incoming attribution link parameters as the attribution source
• Update ad links with the ad partner(s)

You can learn more about setting up web campaign-to-app campaigns here. 

To sum up

We continue to believe that the web offers growth opportunities and are very excited about the web campaign-to-app funnel which offers ample advantages:

• Users can engage with your services and products without needing to first install your app (of course, they’ll get to that later, at the right time).
• Advertisers can create personalized, optimized funnel experiences for users on their own websites with first-party data.
• Advertisers can drive in-app transactions by combining web promotions with powerful tools such as OneLink, deferred deep linking, and Smart Banners. 
• Brands can convert higher intent, more engaged users, leading to optimized ROI.
• Advertisers can tap into efficient traffic sources such as a long tail, high-intent search keywords and down-funnel reengagement.  
• Web campaign-to-app is fully aligned with Apple’s iOS 14 privacy guidelines.

Since June, we have urged colleagues, customers, and partners across our landscape to explore ways to optimize privacy and user experience and then introduced two specific pillars that we are building to make this happen: The next generation of privacy-centric attribution and our complete SKAdNetwork solution focused on maximizing its insights potential.  

We are excited to introduce our third pillar which rounds out our approach for iOS 14. We are extremely happy to open a window of innovation opportunities both for our customers and partners. We are also excited about the improved user experience this funnel presents to end users. Thanks to the web campaign-to-app funnel, users will have more reasons to install and ultimately use both your iOS and Android apps. 

The post The web campaign-to-app opportunity appeared first on AppsFlyer.

As connected consumers, we tend to like brands that offer great experiences on mobile, and we are highly engaged and loyal to brands that deliver carefully tailored mobile experiences that we feel bring added value to our life. 

While email is the most preferred channels of communication (eMarketer, 2020), ensuring a smooth path to your app from your users’ mobile inbox is not as simple as it sounds , due primarily to the fragmented nature of the mobile ecosystem: different OSs and a wide variety of devices, channels, and platforms. Mobile fragmentation leads to broken mobile experiences at unprecedented rates, resulting in frustrated customers and lost business.

Fortunately, deep linking technologies lead users to the right app destination ensuring the optimal user journey across every digital touchpoint – increasing installs, revenue, and lifetime value.

Salesforce and AppsFyer’s OneLink to the rescue

Based on OneLink advanced deep linking technologies that are now available directly on AppExchange to Salesforce Marketing Cloud Email studio, AppsFlyer helps marketers build seamless email-to-app experiences that lift conversions and keep consumers happy. 

Let’s review the example below to better understand what makes a mobile experience work or break.

Mobile links prone to breakage

Meet Sophia. Sophia checks her mobile inbox everyday at lunch and does most of her purchases online. Today she is excited to see a new promotion from her favorite shoe store for VIP status members only, offering 40-60% off throughout the store plus extra 10% off applied automatically at checkout for purchases on the mobile app.

Sophia had actually never downloaded the app because the emails she receives from this specific store direct her to the mobile website. With this recent promotion she is highly motivated to download the app. She clicks on the link, excited to soon start her purchase, but unfortunately this regular link immediately breaks, bringing her to the mobile website’s home page, with no apparent way to download the app. Sophia quickly gets distracted and the journey is abandoned. 

Sophia feels disappointed and frustrated and may lose her interest to come back. The shoe store lost a potential deal of a customer that could become a loyal app user. 

In a smart digital world, the shoe store that is interested to significantly grow it’s mobile business and enhance app usage would want to deliver Sophia a completely different user experience: direct her to the relevant app store to download the app and have her app open up where she left off to the specific new promotion that drove her click. 

Let’s continue with the same example of the shoe store and focus on the perspective of the marketing team involved.

Avoiding disruptive user journeys

The new email campaign the shoe store launched a week ago via Salesforce Marketing Cloud – Email Studio had very high open rates and click rates, but there was not a significant impact on mobile purchases since then.

With recent budget cuts, the marketing team understands that owned media needs to be leveraged. Directing users to the mobile app has become a key success factor as mobile sales in apps are rising, and mobile users like Sophia are becoming more common. 

The team is concerned that the current email flow that is based on regular links breaks the mobile experience. They are tired of sending email promotions and just hoping that as many people will open it, click on the CTA and get to their desired destination on the mobile app. 

They are also unable to see attribution data for email campaigns after an app launches and want to gain full visibility on what happened post email, beyond opens and clicks, to start measuring email-to-mobile app conversions.

The team decided to address the following challenges once and for all: 

• Ensure all their email campaigns have mobile use cases in mind by implementing smart links that always work regardless of OS, channel and platform to create frictionless user experiences. 

• Include complete measurement data and analytics to understand the end-to-end mobile user journey.
• Deploy a solution that can be easily and quickly integrated within Salesforce Marketing Cloud.

Creating a seamless mobile journey 

Here’s what the shoe store marketing team can achieve with AppsFlyer’s OneLink deep linking solution within Salesforce Marketing Cloud:

• Deliver personalized experiences specifically tailored to every user’s needs – OneLink detects whether a user has already installed the app. If a user has already installed it, the link opens the right page directly in the app. New users are sent to install the app first and then directed to the correct destination. The beauty is that OneLink always works across every platform and device. 

• Easy setup and seamless integration with Salesforce Marketing Cloud – Email Studio – the installation of the AppsFlyer app from Salesforce AppExchange is very simple, and enables immediate integration of mobile deep links into email CTAs directly from Salesforce Marketing Cloud by dragging and dropping it into the email template. Consolidated deep linking management capabilities that support the execution of email campaigns at scale allow the team to operate in maximum efficiency.

• Move from darkness to light seeing the entire user journey – complete mobile attribution data can be viewed on the AppsFlyer dashboard or exported, allowing to optimize email campaigns results. In addition, mobile app behavioral data can be leveraged to enhance audience segmentation to automate journey builder in Salesforce Marketing Cloud.

• Improve ROI of email campaigns – OneLink shows 25% install-to-click rate through frictionless email-to-app journeys (up to 4X compared to regular links). This means brands can constantly optimize their user acquisition strategy creating rich and meaningful in-app experiences for users.

Revamping email-to-app campaigns 

With OneLink, the shoe store’s marketing team starts to see new data flowing into their organization analytics tools with attribution data that allows them to explore if their email campaigns are effectively driving users into the mobile app and gives them visibility into the key in-app events. 

The team is confident that from now on the email-to-app campaigns they launch will support end-to-end customer journeys across platforms and turn users like Sophia into loyal app users.

To learn more about optimizing your email campaigns within Salesforce Marketing Cloud click here

The post Behind the scenes of a successful email-to-app campaign in Salesforce appeared first on AppsFlyer.

eCommerce mobile marketers live and breathe measurement – CAC, cLTV, ROAS, and so many other two-to-four-letter acronyms. 

However, not all metrics are created equal. 

Given the variety of KPIs to choose from, only careful selection of the right combination leads to the meaningful insights used to drive important marketing decisions. 

For eCommerce businesses, these insights can help you answer some of the most pressing questions in the industry today, such as:

• Which channels bring the most purchasing customers?
• Which campaigns are the most efficient and profitable? 
• Why and when customers churn?
• What is your cLTV and how can you improve it?

The spread of the coronavirus has led many to online channels. According to our State of Shopping App Marketing report, the activity in eCommerce apps surpassed even the rush that was seen in the holiday shopping season. As a result, we expect the upcoming holiday season to be one for the record books. 

Having the right measurement framework to measure the metrics that matter is vital. To point you in the right direction and help you optimize your eCommerce business this Q4 and beyond, we’ve taken a deep dive into 18 important eCommerce metrics.

1) Customer Acquisition Cost (CAC)

Definition: CAC is the cost of acquiring a new customer. 

Acquisition cost can be calculated by different payment methods such as CPM, CPC, CPA, and CPI.

Usually CAC goes hand-in-hand with the LTV metric to measure how much a new customer costs compared to the total revenue they’re expected to generate.

CAC = Total cost of acquiring customers in set time frame / number of customers acquired in same time frame

Why it matters: Marketers use this KPI to optimize the return on their advertising spend (“ROAS”). If the cost of acquiring paying customers can be reduced, the company’s profit margin improves to generate a larger profit.

CAC can be contrasted against other metrics to judge the efficiency of your app’s sales and marketing efforts. For example, an inbound marketing strategy may raise a company’s CAC when it is first implemented, but could reduce the CAC over time.

2) Customer Retention Rate (CRR)

Definition: Customer retention rate is a marker of how loyal your customers are and can be attributed to two both purchases and activity, depending on what you want to measure. 

Essentially, what it does is takes a group of customers who shopped with you in some historical period of time (e.g. 1-12 months ago) and determines the proportion of those customers that you’d still consider active now because they’ve shopped recently (e.g within the last three months).

CRR = [(Number of customers at the end of a period – total number of new customers during that period) / total number of customers at the beginning of that period]

Why it matters: A high retention rate demonstrates that your app provides value to customers, generating repeat usage. It affects the basis of your marketing strategy and is a key in predicting your app’s performance over time.

Retention rates help you build UA strategies and plan budget distribution between the different channels you work with.

In addition, unlike purchase repeat rate (PRR), retention rate incorporates a window of time between two orders in order to look at longer-term loyalty. The window of time that you choose to use is dependent on the types of product you sell.

For example, a grocery store would use a shorter order window than a bed company.

As a rolling metric, it’s a great way to see whether your customers are becoming more, or less, loyal. The truth is, however, that every business will have a different definition of what this should be.

Retention rates in mobile apps can also be driven by pure activity rather then purchases, and it is calculated as follows:

Number of unique users who launched the app at least once during a specific day/week since the install day or week / Total number of users who launched the app for the first time during the selected date range

3) Customer Lifetime Value (cLTV)

Definition: cLTV is the value each customer generates for your business. To improve the cLTV you should improve your customer experience and increase customer loyalty.

To calculate the cLTV you should multiply the average revenue per customer with the average customer lifespan.

cLTV= Average revenue per user X average customer lifespan

Why it matters: cLTV helps evaluate the total revenue, or value, of a customer and is the strongest indication of how much can be spent on customer acquisition while remaining profitable (CAC < cLTV) — absolutely vital information for any marketer. In addition, every eCommerce business must know their cLTV as it can affect every aspect related to your business strategy.

4) Share of Non-Organic Installs

Definition: The percentage of marketing-driven installs out of your total installs.

Share of NOI = Number of non-organic installs in a defined time frame / total number of installs in the same period

Why it matters: Understanding your install type split will help you determine your app’s halo effect and the ratio between a paid and an organic user. You can further break down non-organic installs to paid and owned media (e.g. SMS, web-to-app conversions, email) to understand when you can actually save money by using more of your own rather than paid media properties.

5) Churn rate

Definition: The rate that measures the pace at which your customers become inactive:

For example: If a game has an option for a multiplayer experience, and a user invited three friends to join who subsequently installed the app, you just earned three new ‘free’ users.

Monthly Churn rate = [(Total number of customers at the beginning of the month – total number of customers at the end of the month) / total number of customers at the beginning of the month] X 100

Why it matters: Analyzing this KPI allows you to drill down into factors that may have led to app abandonment – for example, campaigns directed to the wrong link, irrelevant retargeting, etc. Improving this KPI will help generate more buying opportunities, thus increasing cLTV.

6) Uninstall Rate

Definition: Measures the rate at which users who installed your app uninstall it.

Uninstall Rate = Number of users who uninstalled an app within a pre-defined window / total number of users who installed the app during a set time frame

Why it matters: The rate of uninstalls can help compare the quality of the users you acquire from different media sources, campaigns, single ads or countries. It is a stronger indication than simply becoming inactive and a high rate may indicate that something is wrong with your app or onboarding process, or that your promotions did not match the user’s expectations.

It also protects user privacy since many advertisers run re-engagement campaigns to retain users who uninstalled. However, doing so may contradict the app store’s terms of use and is not considered good practice. If this is the case use the uninstall data to remove uninstallers from remarketed audiences.

7) Bounce Rate

Definition: This KPI tells you how many customers leave your app after viewing only one page. 

Higher bounce rates can occur after a remarketing conversion, when a user is sent directly to a specific page on the app and leaves without taking any action, or during a UA campaigns if users did not see what they expected (i.e. because there was no deep linking in place, or because there was a gap between the promotion and the app landing page).

Bounce Rate = Total number of one-page visits / total number of app sessions

Why it matters: A high bounce rate can indicate low quality UA sources and landing pages that aren’t optimized for conversion (poor design, low usability, high load times, etc). Eventually a high bounce rate will definitely hurt your bottom line.

8) Average App Session Duration 

Definition: This metric shows the average amount of time customers spend on your app per single visit.

A session begins the moment a visitor arrives at your app and ends when they exit or remain inactive for a predetermined time span. As long as the visitor interacts with your app, the session continues.

Average Session Duration = Total Sessions Duration / Total Number of Sessions

Why it matters: Measuring session lengths and analyzing them based on segments will help marketers to plan their campaigns better, and will help to identify high quality users vs. users who are less engaged.

9) Conversion Rate (CVR)

Definition: The percentage that identifies at what rate people are progressing in your app’s funnel. The conversion rate can be measured between any two events you define, such as install to purchase, add to cart to purchase, etc.

CVR = (Total number of initial event in the app / total number of desired event conversions) x 100

Why it matters: During a campaign a click through conversion rate (CTR) indicates a creative variation’s ability to attract a user and drive engagement with your ad, while a click to install rate can inform marketers about their creative and whether their app store page is properly optimized.

Down-funnel conversion rates (e.g. install to purchase) is an excellent indication of user quality to guide segmentation and marketing decisions.

10) Shopping Cart Conversion Rate (CCR)

Definition: This KPI measures how many customers actually complete the checkout process by purchasing the products in their cart.

CCR = (Total purchase conversions / total number of customers that added products to cart) x 100

Why it matters: For marketers, this KPI enables various segmentation options when remarketing to engaged users (e.g. discounts to users who abandoned their cart encouraging them to complete their purchase). 

11) Repeat Purchase Rate (RPR)

Definition: The RPR can tell you the number of customers that return to your app in order to make an additional purchase. It can help you with measuring customer loyalty as well as plan your sales strategies.

 RPR = Purchases from existing customers / total purchases

Why it matters: Repeat purchases drive higher LTV for each acquired or organic customer. The higher the repeat purchase rate, the higher the ROI.

The fact that people buy from you repeatedly also means they like your product, that you have found the right audience, and that your targeting is synced and relevant for your clients.

In addition, repeat purchases indicate people are loyal to your brand and are probably recommending it to their friends. The more devoted they are, the stronger your community. Marketers should nurture these users, target them wisely, and give them special offers that will later translate into more purchases and a better k-factor (virality).

12) Purchase Frequency (PF)

Definition: The purchase frequency value measures the average number of orders your customers made during a specific period of time. This is an ideal KPI to measure customer loyalty and to highlight underperforming products or categories.

PF = Total number of purchases over a time period / total number of unique customers during the same time period

Why it matters: An extremely strong metric to indicate customer loyalty, the ability to identify these users for smarter lookalike targeting and remarketing can make a big difference (for example by rewarding them, or even in some cases to exclude them from paid remarketing as they are highly engaged — there’s no need to spend money marketing to them).

13) Time Between Purchases (TBP)

Definition: This KPI shows how long a customer goes before making an additional purchase. You can use this KPI to customize your campaigns per customer behaviors.

TBP = 365 / purchase frequency

Why it matters:  Time between purchases is a metric that shows you how often an average customer goes before making a repeat purchase. This is a good KPI to measure because it allows you to tailor retargeting and owned campaigns to their behaviors.

14) Average Order Value (AOV)

Definition: AOV tells you how much your customers usually spend in a single order.

AOV = Total revenue / number of orders

Why it matters: Average order value (AOV) is a useful KPI for measuring customer behavior, to identify different segments according to spend, or to see which channels are most effective in terms of revenue.

15) Return on Ad Spend (ROAS)

Definition: Return on advertising spend, (ROAS), is a marketing metric that measures the efficacy of an advertising campaign. It helps online businesses evaluate which methods are working and how they can improve future advertising efforts.

 ROAS = Revenue generated from an ad campaign / cost of the ad campaign

Why it matters: This metric is the holy grail for performance app marketers. It tells you how much money you make on every dollar you spend on advertising — in other words if you are profitable! This allows you to adjust your ad campaigns or exclude products that are not worth their high ad costs.

16) Cost per Acquisition (CPA)

Definition: Cost Per Acquisition is a marketing metric that measures the aggregate cost to acquire one paying customer on a campaign or channel level. CPA is a vital measurement of marketing success, generally distinguished from Cost of Acquiring Customer (CAC) by its granular application.

 CPA = Total campaign cost / number of conversions

Why it matters: Knowing your cost per conversion is key. How much money are you paying, on average, to get someone to actually buy your products? You can then compare this to the price of the product to see which items are doing well and which ones are underperforming. And, naturally, you will be able to see if your CPA on one site is higher or lower than it is on another site.

18) Number/Share of First-Time Purchasers Driven by Remarketing

Definition: The number or share of users who complete a purchase after engaging with a remarketing ad within a pre-defined window.

The number or share of users who complete a purchase after engaging with a remarketing ad / The number or share of users who complete a purchase

Why it matters: App remarketing is all but mainstream among shopping app marketers, and in many cases makes up the lion’s share of marketing conversions (vs. non-organic installs). With UA costs increasingly rising, remarketing’s huge success on the web is also replicated in apps.

18) Web-to-app conversion

Definition: The share of users who start their buying journey on the web and convert in the app.

The number of conversions in app / Total number of users who start on web and install the app

Why it matters: In a world where users constantly switch between devices, and considering that Google searches end up in mobile web sites, it is highly recommended to convert them to the app. The native app offers a far better user experience and has shown much higher conversion rates than the web. A smart web to app banner can encourage them to install the app and this is great use of your owned media.

The Final Word

Don’t overcomplicate it and don’t use too many metrics. Experiment to find the best ones for your app and optimize them to their full potential. 

With every action they take in your app (or inaction), your customers are signaling to you what to measure. This should be your best indication of what’s important now and what will matter tomorrow.

The post 18 metrics eCommerce marketers should measure this holiday season appeared first on AppsFlyer.

The 11th AppsFlyer Performance Index — ranking the best media sources in mobile advertising since 2015 — is out with a special WFH Edition! Its data covers the first half of 2020, a period in time marked by millions of people, across the globe, working from home due to COVID-19 and social distancing policies. 

What effect did the pandemic have on the rankings?

We’ve seen mobile metrics across the board spike during lockdown as people at home were looking to be entertained (streaming video & music, playing games), to communicate, work out, order food, make online payments, and more. To meet this heightened demand, we saw marketers aggressively pursue new users.

That said, there was only a marginal impact on media source rankings in H1 2020. Marketers were extremely busy, but they used the same media sources they’ve used over the past few years — a consolidated list of leading, fraud-free partners with powerful tech and scale of data to optimize campaigns.

What’s new in the WFH Edition? Enter the IAP and IAA indices!

The evolution of our index is mostly tied to our rapidly growing scale and the strict thresholds we’ve used to ensure statistically valid results. Edition I of the Performance Index included only global gaming and non-gaming rankings, while in Edition X the rankings were broken down by geo, platform, and sub-category.

Granularity is the name of the game. 

But the index has always been based on retention data as the key factor to success. That’s because each and every app we have in our system has this data. 

Despite the fact that AppsFlyer has a 65% global market share, Edition XI marks the first time we’ve had sufficient scale to release revenue and monetization-driven rankings (unlike retention data, monetization data requires unique configuration and implementation, and therefore fewer apps have this data).

1. The IAP Index: Media sources are ranked on their ability to deliver users with the highest likelihood to complete an in-app purchase (IAP) using the share of paying users metric (install-to-purchase conversion rate). The importance of IAPs in a freemium-driven app economy is massive, and takes precedence over retention in performance app marketing.  
2. The IAA Index: Media sources are ranked on their ability to deliver users who monetize best with ads — vital information for apps who rely on in-app advertising (IAA) as a key revenue stream.

While IAP has been around from the early days of mobile gaming, IAA arrived later, opening a whole new revenue stream, and gradually becoming an integral part of most games across multiple genres.  

As always, Edition XI also includes the Retention Index, the Remarketing Index, and the Growth Index. All in all, these 5 indices provide a complete report card on the mobile media landscape across multiple angles.

To give you a taste of the results, here are the top 3 findings:

1) Facebook quality powers social network to the #1 cross-index position

The standard Performance Index, or the Retention Index, has Google atop the universal power ranking by a small margin. Its position is driven by superior scale across the globe, and particularly in APAC. 

But, when we look at the IAP Index, Facebook leads Google by a wide margin in the universal power ranking thanks to superior quality. 

In a performance index, the share of paying users is a stronger indication of performance than retention. Add to that the fact that it also dominates the IAA Index as well as the Remarketing Index, and its overall #1 cross-index position is clear.

A platform breakdown shows Google is a clear winner in Android thanks to its leap in developing countries where the OS dominates, while Facebook controls much of iOS (note that Google stopped claiming iOS Search conversions to App Attribution Partners in early 2020, so this subset of Google conversions on iOS was not considered for this report). 

2) Unity Ads emerges as the leader of the gaming triopoly 

The leap in scale achieved by Unity Ads distanced it from its two main competitors ironSource and AppLovin (although its quality is actually the lowest among the group). The network’s growth was driven by both onboarding a large number of new clients and increasing budgets with existing ones across the globe. 

In the IAA Index, Unity Ads was second only to Facebook, thanks to its scale being significantly larger than ironSource (quality-wise there was only a minor gap). It is the main platform for game developers to create mobile games on, and as a result they have a massive long-tail of indie games that monetize with ads, many of which continue working with the Unity network post-launch. 

3) Apple Search Ads boasts best share of paying users in IAP Index

Apple Search Ads (ASA) is providing great results for Non-Gaming apps. These apps are particularly well-suited to match strong intent that can be drawn from what users search for in the App Store. As a result, ASA had the highest share of paying users in the IAP Index leading it to the #2 spot in the index’s universal power ranking. 

Part of its success can be attributed to the pandemic. Organic growth in the App Store led marketers to start and/or increase their app store optimization efforts, bringing Apple Search Ads to the front, driving impressive growth and strong performance.

For all the insights from the 595 rankings across 11 regions and 32 categories, open The AppsFlyer Performance Index WFH Edition today!

The post New monetization rankings highlight AppsFlyer Performance Index WFH Edition appeared first on AppsFlyer.

Mobile marketing is going through a paradigm shift. With the industry moving towards a more aggregate way of measuring marketing efforts, marketers’ ability to measure and understand the impact of their marketing investments is further curtailed.

Without any intentions of sitting on the sidelines, we’ve set ourselves a goal to help our customers and the entire mobile ecosystem to successfully navigate this new era of mobile marketing.

Today marks another milestone in accomplishing this goal. We’re thrilled to announce the launch of AppsFlyer’s Incrementality solution, a product that truly empowers marketers to gain a better understanding of the real value that their marketing efforts hold.

What is incrementality measurement and how does it work?

With incrementality, you can determine the real value of your marketing efforts by measuring which conversions were made as a result of your marketing campaigns and which would have still occurred organically, without them.

To determine the incremental lift of a specific marketing channel or campaign, an experiment is used in which the target audience is randomly split into test and control groups, ensuring a minimal bias between them.

The test group, usually consisting of 80-85% of the total audience, is exposed to the normal campaign and sees ads while the control group is excluded from the campaign.

Splitting audiences into ‘control’ and ‘test’ groups

This way, you are able to uncover the incremental impact of your marketing campaign or channel and measure the engagements that would have occurred in the absence of this specific investment.

Incrementality for remarketing

AppsFlyer’s Incrementality solution is built around remarketing and is fully integrated with Audiences, to enable a streamlined process of creating and managing incremental lift tests for remarketing campaigns. This integration also enables automatic segmentation to test and control groups and ensures there are no overlaps between them.

Incrementality measurement made easy

Incrementality testing is a long and complicated process that may be prone to poor execution and interpretation. There are many challenges in measuring incrementality as it requires knowledge, expertise, and a robust testing environment to ensure that the right insights are derived and the right decisions are driven.

This is why up until now, very few companies have been able to successfully integrate incremental testing into their campaign optimization workflows and utilize its powerful insights.

With the launch of Incrementality, that’s all about to change.

AppsFlyer’s Incrementality solution simplifies the process of designing, executing, and analyzing incremental lift tests at scale. Marketers can focus on the end-goal of their test without having to worry about the heavy lifting that comes with it.

Test, learn, grow, repeat.

The AppsFlyer Incrementality Dashboard provides a detailed view of your test results and allows you to perform both granular and macro-level analysis of every channel, audience, and creative.

The intuitive and simple to use interface encourages you to dive deeper into the different stages of the test and makes it easy to involve stakeholders that are less acquainted with advanced analytics on the journey.

For even more advanced analysis and deeper insights, we offer fully detailed raw data reports that can be sent directly to your Amazon S3 bucket in real-time.

Where Incrementality meets attribution

Attribution and incrementality are completely independent concepts that complement each other to achieve a more effective mobile marketing strategy. They each serve a separate function in understanding the full picture of how campaigns are performing and the actual value they’re driving.

When used alongside each other, they form an integrated marketing measurement strategy where Incrementality can be used to validate hypotheses derived from attribution.

With this first-to-market solution, AppsFlyer is the only attribution provider to offer both solutions under one platform.

We’re just getting started

With the industry shifting towards a more aggregate future, solutions that provide advanced insights into campaign management and optimization will inevitably play a bigger role in marketers’ decision making processes.

AppsFlyer’s Incrementality solution facilitates innovation by providing a framework for testing and analyzing remarketing campaigns and tactics at scale.

And we’re just getting started. New capabilities surrounding incrementality measurement for UA strategies will be added in the future, ensuring that your entire marketing stack is all-systems-go for the challenges that lie ahead.

The post Announcing Incrementality: The complete solution for measuring remarketing effectiveness appeared first on AppsFlyer.

In 1997 we were introduced to ‘Snake’: a simple, intuitive, and addictive mobile game. It didn’t have ads or in-app purchases, and there were no game loops or incentives.

So much has happened since — the smartphone was born and the rest is history. In the early 2010s the free-to-play (F2P) or Freemium model was introduced, attracting new users and developers in massive numbers.

What quickly followed was that a huge variety of apps had surfaced to match user preferences. Mobile games were differentiated by things like game design, complexity, difficulty, monetization strategy, game plot, and so on.

It wasn’t long before the app stores divided mobile games into genres and sub-genres, and so we ended up with Casual games (including Board, Card, Puzzle, etc.), Hardcore & Midcore games (including Simulation, Action, Strategy, Role Playing etc.), and Social Casino games. Each genre and sub-genre was characterized differently and suitable for a different target audience.

Gaming categories in Google Play and the App Store

During the last decade, the mobile gaming industry has enjoyed exponential growth in the number of actual players installing, exploring, playing, and most importantly knowing what the industry has to offer and shaping their own preferences accordingly. In fact, Newzoo estimated that there are currently 2.5 billion mobile gaming players worldwide, a number which is projected to near 3 billion by 2023.

To keep up with the massive player appetite, mobile game developers were quick to react, rapidly creating new games, and innovating to create new types of games. In 2020, there are a staggering 1.2 million mobile games in the App Store and Google Play alone.

The current reality and why an update is needed 

For most games, the only common factor these days is their app store category. For example, if you browse through the Puzzle category in Google Play, this is what you’ll see:

Clearly, if you drill down further you’ll notice games that are very different from one another — in game mechanics, complexity, monetization models, features, etc.

There are significant drawbacks to this reality, namely:

1. App store discovery is far less effective for users.
2. Targeting similar players by app store classification is inaccurate and prevents marketers from reaching the potential of their user acquisition campaigns.
3. Competitive analysis becomes far less effective as it isn’t based on an apples to apples comparison.

With such growth and variety of games, and in light of the above challenges, it is no wonder that the boundaries between the different gaming genres are constantly changing, and that developers are combining properties of different genres in their game.

Current store categorization classifies games such as Candy Crush Saga, My Talking Tom, Coin Master, and Homescapes under the same category (Casual). But these games have completely different game mechanics, different monetization, and a different target audience (my 3 year-old loves My Talking Tom, but won’t build a village in Coin Master or even play Candy Crush).

Another example can be found within Strategy games, where you’ll find Clash of Clans (in Google Play) — a game that requires players to invest time and money in building their village and clan, and includes multiple layers of complexity and strategic decision-making; but it also includes Cooking Frenzy — a game that allows you to cook and serve different dishes and earn rewards for your virtual cooking abilities.

There’s no doubt that these are great and highly successful games, but they have nothing in common. Grouping them under the same category in the app store is misleading for end-users and marketers who target Strategy games.

Last but not least, there are Hyper Casual games, the fastest-growing gaming genre in the last couple of years, by far. It is very much different from its current Casual games categorization (sometimes you can even find these games under genres like Action, Puzzle, Racing, etc.). Hyper Casual games have completely different mechanics, features and complexity and deserve their own category in the stores.

Even in our own AppsFlyer reports, we had to change the app store classification to align with what game developers were looking for. We decided to define Hyper Casual as gaming apps with the vast majority of their revenue coming from ads.

The road to relevance and accurate taxonomy

Realizing the shortcomings of the current classification, more and more gaming apps decided to manage their own taxonomy or use 3rd party providers that have created their own categorization logic to meet demand from gaming developers.

Different companies use different methodologies, definitions, and criteria when classifying games into genres and sub-genres, and also provide their own analytics dashboards to use their data to make better decisions. By doing so, they push the gaming ecosystem to the next level, where the in-game characteristic defines the game and the segment it belongs to.

For example, let’s explore the popular Match3 game (currently divided in the app stores between Casual and Puzzle) and what GameRefinery included in its taxonomy. A standard game has its own sub-genre under Casual games, but if a Match3 game also has character development features, it will be labeled as Puzzle RPG, giving it another dimension and far better relevance in discovery.

Another example from GameRefinery is Arcade games, a popular category in the app store, with a blurred definition. In the app stores, we’ll see games such as Subway Surfers, Temple Run, Jetpack Joyride, and Sonic Dash. These games might define their games in the app store as Arcade, but in fact attract a different type of users.

GameRefinery categorization

As mentioned earlier, different companies will do this differently but with a similar goal in mind. For example, AppAnnie recently introduced its own take on gaming categorization. The company leveraged AI tools to create and maintain an automatic taxonomy tool, examining in-game characteristics to provide a granular definition of gaming categories.

This taxonomy focuses on three main categories; casual, core, and casino, broken into dozens of sub and sub-sub categories, divided by very specific game mechanics. And so we’ll see sub-sub categories such as breed-battle, card-battle, and summon battle (under core > strategy), and stunt racing, kart racing, or combat racing (under casual > racing).

This emphasizes that categorization is ultimately subjective and can be done differently with various levels of granularity.

Granularity is the name of the game

As the examples above illustrate, new game classification is not only about reshuffling the existing deck, but rather adding more cards for deeper granularity. Mobile gaming is so big, it demands it. 

Why is granularity important?

1. For developers: Whether you’re planning to penetrate a specific genre, or you already have a live game running, knowing your current and future competitors is key to success. By exploring games with similar functionality (feature-set, design, benchmarks, etc.) you can have a better understanding of what you’re up against, and act accordingly by changing strategies, adding/removing features, exploring launches in new markets, etc.
2. For marketers: You invest many resources into digesting data and using it to make decisions that will eventually help you hit your performance targets. Using granular categorization will give you an additional layer when targeting relevant users that play games that are [truly] similar to yours and there is a better chance that they will install your game after seeing your ad (improving IPM). This is a key tool for marketers to allow them to invest their budgets where it counts.
3. For users: There are over 2.6 billion players globally, many of whom obviously like different games, with a different design, features, complexity, storyline, and so on. Players who explore new games can do it by engaging with ads they see for the games they already play, or use the app stores to find their next favorite game. 

Granular categorization will certainly make life easier on end-users who want to play a game that fits their preferences instead of wasting their time installing and uninstalling games that are not a good fit (furthermore if this happens often, there is a risk that they will just ignore ads or refrain from app store discovery).

A recent Facebook report found that 49% of players are influenced by the game genre when trying a new game (image below) – the highest of all factors. This emphasizes just how important granular and relevant genre classification is, and the impact it has on user experience and player decisions.

A final word on the need for standardization

The importance and necessity of relevant and granular game categorization is clear. It would only make sense to expect this to come directly from the app stores, providing gaming developers and marketers with a single source of truth.

Let’s admit it, organic discovery in gaming is becoming harder and harder for users, making organic growth a huge challenge for gaming app marketers. With the current store categorization, finding a game that truly matches your preferences and would keep you playing longer is not an easy task.

The App Store and Google Play should adapt to the new reality and give users, developers, and marketers what they need to succeed.

The post Why a new game classification in the app stores is in order appeared first on AppsFlyer.

ROI in mobile marketing is an elusive metric. It is seemingly easy once you know your total expenses and total revenue. But the reality is that your ROI stats may be wrong.

The accuracy of your ROI data is dependent, first and foremost, on accurate attribution data, which in turn leads to accurate revenue and cost data. 

The accuracy of cost data is particularly tricky because there are numerous cost sources but no real standardization. 

To make matters worse, working with separate cost and attribution providers creates all sorts of problems which we’ll cover in this blog. It is part of our new complete guide about ROI: Finding Your True North: Measuring Your App Marketing’s True ROI >>

Why separating attribution and cost providers is risky

There are several reasons why the practice of working with two providers – one for cost aggregation and one for attribution – is bad practice. The bottom line: it can easily lead to wrong or incomplete data, and from there the path to draining your marketing budget and even putting your business at risk is quick.

Let’s explore why this happens:

1) Sub-par attribution solution: There are no shortcuts to the years of heavy-lifting required to build a robust attribution platform. Anything short of that and attribution data cannot be fully trusted. 

Data Accuracy. Garbage in, garbage out. If your decision input parameters are wrong, your decisions’ outcome will be wrong. In modern marketing, attribution data is the source of the most important marketing decisions. The end result: marketers are often making bad decisions without even knowing it.

There are two main reasons for this: fraud and mis-attribution.

In both cases, measurement appears to be correct, which tells you that you have made the right decisions. But in reality, what often happens is that you end up buying your organic users and fraudulent traffic. When you make that mistake over and over again, you risk entering a bleeding cash cycle.

In this cycle, strong performance leads marketers to ask for more budget from their CEO, and the CEO approves because it’s working. However, the numbers are wrong, and the company ends up pouring more money into the wrong sources.  

2) Data mismatches: When the cost provider is not the owner of the attribution data, its ability to connect this data to its own cost data is a significant challenge. 

A proper attribution-cost integration must be uniquely built per ad network, not by building a generic cost integration. 

Let’s take the following scenario: an integration built with the API of network A includes field X which the advertiser uses for creatives, but the network that works with the attribution provider passes the creative on field Y. In such a case, your Excel or BI platform will see two separate rows:

Overall, a massive number of cost/attribution data point pairs that should have been matched are not, leaving many empty lines. The end result: decision-making is based on inaccurate data.

On the other hand, when the attribution vendor has holistic cost data it can easily aggregate, normalize, and standardize both data sets into one ‘coherent’ data set. 

3) Privacy & security risk: Some marketers provide their attribution platform’s dashboard credentials to their cost vendor, which then runs a process known as data scraping to obtain the attribution data. It is important to understand that this method is both error prone and a severe security risk when sharing credentials providing access to your 1st party data. 

4) Lack of granularity —> sub-par optimization: In theory, a marketer can fill many of these empty lines by settling for the lowest common denominator — often the media source level or even media source and campaign level — losing any meaningful granularity. That means the creative-level data in the example above won’t be leveraged to fully optimize the campaign.

What level of granularity is needed to push the needle? Your data should go all the way down to the creative, geo, site id, and keyword level. 

The bottom line: [Robust] attribution & cost aggregation are inseparable.

To learn more about ROI and what you need to get it right, check out the complete guide Finding Your True North: Measuring Your App Marketing’s True ROI >>

The post Why attribution & cost data are better together to achieve true ROI appeared first on AppsFlyer.

On September 16th of this year, the highly-anticipated iOS 14 was widely released to the public. While the industry knew this version was due to come out sometime in September, Apple gave developers less than 24 hours’ notice about the public release date.

Unlike previous years, this year the new iOS was released ahead of the new iPhone models and not simultaneously. As one might expect, this slowed the adoption rate of the new iOS (as the new devices are sold with the new iOS installed). According to our data, iOS 14 surpassed 46% adoption just last week, and this rate is expected to rise dramatically when the new iPhone 12 becomes widely available in November.

Apple announced an abundance of new privacy features when iOS 14 was introduced in June, most notably the new App Tracking Transparency (ATT) framework that was expected to all but diminish IDFA collection. While the release of this feature was postponed to early 2021, giving developers more time to prepare, a curious phenomenon has occurred: since the public release of iOS 14, the industry has noted a massive surge in iOS devices with zeroed IDFA.

Zeroed IDFAs were introduced with iOS 10 back in 2016, and are the result of the user opting out of ad tracking. Prior to the release of iOS 14, the average worldwide rate of devices with Limited Ad Tracking enabled was around 24%; the US and Europe had the highest prevalence of LAT devices (30% and 18.3%, respectively). Since the release, the numbers of zeroed-IDFA devices have skyrocketed, and now stand at an astonishing 45% of all iOS 14 devices worldwide.

The aforementioned ATT was designed to replace LAT. Rather than offering iOS users the opportunity to opt-out of sharing their IDFA with advertisers in their device settings, the new AppTrackingTransparency framework (ATT) requires users to actively opt-in to IDFA collection when using the app. Users that had turned on LAT previously would automatically be converted to ATT-negative users, maintaining their status of sending a zeroed IDFA to advertisers. For this reason, we expected the prevalence of zeroed IDFA devices to stay constant.
Clearly, this is not the case.

So what is happening? And why?

The four horsemen of the IDFA apocalypse

The surge in zeroed-IDFA devices post-iOS 14 release became immediately apparent, causing much confusion and frustration in the industry. After some research and investigation, we have uncovered the cause.

The shift from LAT to ATT didn’t turn out to be a binary “opt-in/opt-out” scenario, as we anticipated it to be. In reality, the new iOS 14 user has four possible states of existence:

1. Not Determined – No ATT dialog was presented to the user, therefore the user made no active choice about sharing their IDFA. This status also includes user devices where LAT was turned on in earlier iOS versions. (IDFA shared/not shared accordingly)
2. Denied – The user chose via ATT to not be tracked by the app (IDFA not shared)
3. Allowed – The user chose via ATT to allow tracking (IDFA shared)
4. Restricted – Access to IDFA sharing is blocked without any end-user input (IDFA not shared).

Due to the delay in deployment of the ATT framework, we expected that most users would fall under the Not Determined status. We expected roughly 75% of devices to be Not Determined after the public release of iOS 14. In reality, only 62% of devices are now in Not Determined status.

Surprisingly, the sum of Denied and Allowed is around 20%. While Apple postponed the implementation requirement for ATT to early 2021, some developers went ahead and integrated it in their iOS 14 apps anyway. The ATT framework prompts the user to opt-in to allow tracking when they use the updated app. Unsurprisingly, when prompted, the majority of users (99%) choose not to allow tracking. 

The big surprise in these results, however, is the 18% of devices that fall under the Restricted category. These devices send zeroed IDFAs, without the users having made any proactive choice about sharing it whatsoever.

Restricted status: Explained

Let’s address the elephant in the room: why are we seeing an 87.5% increase in zeroed IDFA devices in iOS 14?
The answer lies in the Restricted devices category. This vaguely-defined category creates complexities for the industry, bringing on scenarios that weren’t foreseen. 

First, let’s define what Restricted means here. A Restricted device will report similarly to a LAT-enabled device: the IDFA will be zeroed across all apps. Users with Restricted devices have reported that the LAT privacy setting (“Allow Apps to Request to Track”) on their devices is grayed out, meaning they cannot change this setting on their own.

Source: reddit

What’s more, this setting appears to be open to some manipulation and prone to bugs. Savvy iOS users have reported that they’ve been able to “ungray” the setting, by logging out and back into their iCloud account.

Source: reddit

Why would a user be Restricted in the first place?

This is a good question, with no official answer to be found. There are some assumptions and partial answers from Apple. We have collected what we know so far:

1. User age
   1. The user is under the age of 13, or between the ages of 13-18
   2. The user’s age is unknown
2. Education
   1. The device is in Education mode
   2. The App Store account was created by an educational institution (known as Managed Apple ID)
3. Restricted profile
   The device has a profile installed with a preset restriction. An example of this would be “MCFeatureLimitAdTrackingForced”. This may be set by an organization for employee devices, for example.

Facing the future, head on

iOS 14 has disrupted the mobile marketing landscape and we expect the pace of disruption to increase as the adoption of iOS 14 grows. That’s why we built a culture of agility and innovation into the heart of our company that allows us to not simply adapt to, but anticipate and plan for, whatever changes lie ahead.

We admit it – this sudden uptick in IDFA-zeroed devices was surprising to us; surprising, but not alarming. It is simply another aspect of the evolving landscape that we are well-equipped to support. With mobile attribution and measurement becoming ever more complex, we’ve invested in building the largest and most experienced team of developers in the industry to support brands with the measurement tools they need to succeed and make sure they stay competitive in today’s ever-changing market.

 Learn more about AppsFlyer’s iOS 14 readiness

The post The untold story about zeroed IDFAs on iOS 14 devices appeared first on AppsFlyer.

It’s a cool autumn morning and you’re getting ready for work. You decide to drop-in at your local coffee shop and get your favorite morning java. Just as you walk in you see a long line and you’re already late for work, but you really want that coffee. Next to the cash register, you notice a sign inviting you to skip the line by scanning a single-use QR code to place your order. Usually, you would weigh heavily on downloading any app, wondering if you even want to give it precious real estate on your phone and considering what the privacy implications may be. 

Well… not anymore. Using App Clips you now have the option to scan a seemingly one-time QR code for purchases without having to download the full app. Go ahead and jump to the head of the line.

This is awesome for you since you’re part of a limited group of new iOS 14 users, but what about the Android and existing iOS users?

Now with AppsFlyer’s first-to-market attribution solution for Apple’s App Clips, brands can provide a seamless user experience with measurement and deep linking capabilities for all iOS and Android devices, not only those with iOS 14. 

What are App Clips?

As we followed the changes in the mobile ecosystem and listened to Apple’s announcements at WWDC 2020 we understood quickly that Apple’s focus was to gain overall value from iOS devices with less attention to the standard app install. 

This is why the App Clips are so revolutionary, changing the way we use apps and bridging a gap between two worlds. Quick loading with the native experience, App Clips have the benefits of the full app, such as, Apple Pay, and Apple sign-in, without the possible burden of installing the full app. 

Let’s start with the basics. For consumers, using an App Clip is not your typical app download experience. App Clips offer your consumers a truncated, lighter version of your app. Users need not input any personal information, allowing greater privacy and transparency. 

If we look back at the coffee shop example, a customer could make repeated purchases without ever having to share any data, as App Clips cannot access data from apps like: photos, location, contacts, messages, and more. 

How it works

The process begins with an invocation (with our coffee shop example let’s use the QR code), which will lead the customer directly to the coffee shop menu. 

user scans QR code

Once scanned, the QR code will invoke an App Clip allowing you end-to-end functionality all the way to closing out your purchase via Apple Pay.

Apple’s App Clips were designed for iOS 14 users only, which as mentioned above leaves you wondering about the user experience for Android users. What will happen when the QR code for example is scanned by an Android device or an existing Apple user with iOS 13 or below? 

With AppsFlyer’s App Clips attribution solution, attribution data is captured and user experience is frictionless and measurable—regardless of device or version—through the existing deep linking capabilities of OneLink.

AppsFlyer’s solution unifies the experience across iOS and Android

How are App Clip conversions attributed?

Measuring metrics such as app engagement is something that marketers have come to expect. The AppsFlyer solution treats App Clips just like an app with all the capabilities for measurement that you have grown accustomed to. 

With OneLink you have the option to tailor your brand, adding and changing parameters to the invocation URL directly from the AppsFlyer dashboard.

user scans coffee shop QR code and downloads the full app 

This is important because for all iOS and Android users:

1. 1. 1. You can see how many people are installing and using your App Clip
      2. You can see the behaviour of users inside the App Clip
      3. You can see how many people went from the App Clip to the full app
      4. You can see the behaviour of the users inside the full app

Building a better experience together

Now that you have skipped the line and have your favourite coffee to sip as you drive to work we are happy to have met the needs of the “here and now”. Your experience was seamless, delightful, and stress-free.  

For the coffee shop marketer, our solution brings you one step closer to a wider audience of users providing you with all the measurement capabilities needed to increase your business value. 

We want to hear about your experiences and how you envision using App Clips. To learn more about the technical aspects of AppsFlyer’s attribution solution for App Clips click here or request your demo today.

The post First-to-market attribution solution for Apple App Clips by AppsFlyer appeared first on AppsFlyer.

In 2020, savvy app marketers are emphasizing not only the acquisition of new users to their apps, but also the re-engagement of their existing and lapsed ones through owned and paid channels.

Poor user retention, deeper measurement, improved data-driven skills, and better segmentation tools are all leading causes behind this phenomenon.

To understand the impact of re-engagement, particularly paid remarketing (also known as retargeting), we’ve analyzed 7 billion remarketing conversions of over 2,000 apps.

We’ve found that while the share of remarketing from all marketing-driven conversions (which include non-organic installs and remarketing conversions) per app has stabilized, adoption rates have grown. In fact, remarketing is now an integral part of an app’s marketing strategy, boosting its user lifetime value and profitability.

For the most comprehensive global and regional benchmarks to date on remarketing, check out our report, The State of App Retargeting – 2020 Edition.

1 in every 5 apps run remarketing campaigns

Remarketing is used by 20% of apps worldwide, an 18% increase compared to 2019 and a 65% jump since 2018. As we can see from the chart below, APAC leads the way in both adoption and share of conversions. 

Judging from the share of remarketing conversions and the share of apps running remarketing campaigns, we can say that this activity has proven itself for most apps.

A category breakdown yields the following:

• Across all verticals, the average growth in the share of remarketing conversions from 2018 to 2020 was 14%. Notably, however, is Europe’s growth, with the share of conversions rising by 22% in 2020 compared to 2018.
• The Finance vertical saw significant growth in conversions year over year, jumping by over 50% — this is especially interesting as the number of apps running remarketing campaigns has barely changed (+4% 2018 vs. 2020), meaning that the apps that use remarketing are doing it more YoY.
• Shopping apps are the real stars of remarketing, experiencing the highest growth rates across the board, growing by more than 30% in the share of remarketing conversions.
• Gaming apps had a 250% lower share of remarketing conversions than Shopping. The reality is that only a small percentage of Gaming apps run remarketing. Given the substantial revenue uplift of Gaming apps that do remarket (see ahead), they are clearly missing a significant opportunity.

Does investment into remarketing actually result in lifetime value uplift across the board? Find the answer to this question and others in the data below.

Why invest in remarketing?

Let’s take a minute to understand the benefits of running remarketing campaigns in today’s hyper-competitive landscape:

• Retention is still a huge challenge. According to AppsFlyer retention data, while non-organic retention increased by around 20% into 2018, day 30 retention of organic users only increased by about 5% in all verticals. Overall, rates remain low, reaching only 5.5% and 6.8% on day 30, for non-organic and organic respectively.
• User acquisition costs rising. The reality today is that it costs marketers more money to acquire new users for their apps. Although not a pure apples-to-apples comparison when we compare CPI and CPC, the cost to acquire a user is 5-10x more expensive than the cost to re-engage a user.
• Accessibility of advanced measurement infrastructure. Before turning to the increasingly sophisticated marketing analytics tools, it’s also important to recognize the evolution of marketers, and the mobile ecosystem at the core of it all. While technology has allowed for richer analysis and better measurement, improved data-driven skills among marketers can also be credited with sharper segmentation and more effective remarketing efforts.
• Availability of more robust segmentation tools. With increasingly more advanced segmentation tools at their disposal, marketers can drill down into their app’s unique audience segments to see which users deliver the greatest revenue and which are most likely to churn, among others. That way, they can avoid overwhelming the wrong users with remarketing ads and focus only on those with the greatest potential.
• Increased adoption of deep linking for personalization. The steady adoption of more sophisticated deep linking technology for personalized user experiences by marketers has led to an increase in the opportunity of remarketing as well. Working with targeted audience segments, deep linking smoothly delivers users to appropriate and customized landing pages within the app, increasing remarketing campaigns’ relevancy, decreasing churn, and ultimately improving overall profitability.
• Performance. As evident in the data below, it is clear that remarketing positively influences not only the revenue from your users but also the overall performance of your app in most cases.

Remarketing leads revenue KPIs upward

The consistent rise in performance metrics tells the story about the value of app remarketing:

Share of paying users gets a boost from remarketing. In this simple comparison, we looked at the share of paying users in two groups – those who run remarketing campaigns and those who don’t. We found that in most markets and categories, remarketing campaigns increase the share of paying users. 

• Overall, apps running remarketing campaigns in Q1 2020 averaged a 6.5% share of paying users, more than 50% higher than those not running remarketing.
• Significant differences are seen among Entertainment, Lifestyle, and Midcore Games, where those who run remarketing campaigns see more than 100% higher share of paying users.

Average revenue per paying user (ARPPU) uplift. To go even deeper, we examined two groups of paying users among apps that run remarketing: those who were exposed to a campaign and those who were not. We then compared the revenue uplift (an overall ARPU comparison would not be as accurate because of significant variance in the audiences, since apps tend to remarket high quality users).

• In contrast to the low share of both remarketing conversions and the number of apps actually running those campaigns, the payout for Gaming apps that do remarket users is massive, showing a significant uplift in ARPPU, especially in EMEA where remarketing leads to 2x higher ARPPU.
• Despite Shopping’s domination in the share of remarketing conversions, the revenue from such efforts in this vertical is not as high as other categories with a global average uplift of nearly 20%, which is still significant. Furthermore, with a relatively high scale of paying users and purchases, this uplift is significant when it comes to actual revenues.
• In the US, Entertainment apps had the most impressive uplift, generating close to 150% higher ARPPU vs. users who were exposed to remarketing campaigns.

Key Takeaways

1. Remarketing not a luxury, but a necessity. Given that apps running remarketing campaigns see a 50% higher share of paying users, it is evident that these campaigns directly and consistently support performance and profitability. Moving forward, investment in remarketing is no longer reserved for savvier marketing teams; instead, it should be considered a vital component of your app marketing efforts overall.
2. Launch dynamic remarketing. The best results are often achieved through a dynamic remarketing campaign rather than a static one. Increased relevancy and personalization can make all the difference. Here’s a good read that will help you get started.
3. Big payouts for Shopping. In general, we can see the massive opportunity of shopping apps: according to Criteo, mobile retail generated 3x higher conversions in-app than on mobile web. This adoption, along with the consistently positive correlation between remarketing campaign spend, a high number of conversions, and revenue, makes it clear that the Shopping vertical will continue to enjoy increased profitability through remarketing efforts.
4. Gaming vertical as an anomaly. From our data, we can see that 16% of apps in Gaming run remarketing campaigns versus 59% of apps in Shopping. Despite, or perhaps because of, the savviness of marketers in this vertical, remarketing is not prevalent, at least partially because of the complexity involved in measuring these campaigns. We will not explore these questions in-depth in this report; however, we can only conclude that there is clearly a missed opportunity here. Remarketing is on the rise, with high payouts (in terms of performance uplift) for apps that invest, and yet, only a very small share of Gaming apps actually do.
5. UX is everything. That’s why understanding when to start remarketing, for which audience and how often, is critical, as increased frequency can generate serious problems and potentially damage a brand beyond repair.
6. Incremental measurement for true remarketing analyses. Measuring remarketing is best done by looking at the incremental effect. There are so many things that might affect your users’ experience besides the remarketing ad – where they were acquired (maybe even organic), their stage within the app, their overall app experience – so make sure you isolate the remarketing effect. 

Good luck re-engaging!

The post App remarketing drives 50% more paying users appeared first on AppsFlyer.

Your app is up and running, congrats! You’ve tested it repeatedly, fixed bugs, monitored performance, confirmed with beta trials that it actually works for users, and submitted it to the app stores.

Now you need to dive in and do what it takes to get your first 1,000 users. That might seem daunting at first with millions of apps in the stores to compete with, particularly if you don’t have a background in marketing. 

But once you know the basics and you’re open to experimentation, you can increase your mobile installs efficiently and start to see a return on your investment as your users engage with your app.

Focus on owned media

Generally speaking, the most cost-effective way to get started is by channeling your efforts into what you already control, which is known as “owned media”—those are the channels that you “own,” through which you are likely already communicating with your first users and potential users. Owned media typically includes your social presence (Twitter, Facebook, Instagram, Snapchat, Pinterest), your email lists, users you already have who can invite others, and even your website.

Your job then, is to pair each of those channels with the user acquisition tools (platforms and mechanisms that help you get installs of your app) that will drive installs of users who are most likely to engage with your app and generate revenue.

Create seamless user experience

Everything you do to get users to install your app should be framed by one crucial factor: user experience. You should never lose sight of it, because if users can’t install and use your app easily—without any irritating or confusing bumps along the way—they’re not going to stick around. 

In mobile app marketing, you want to get app installs in a way that is “frictionless” or “seamless” for the user, meaning that they get from one place (e.g., an email you’ve sent) to another (e.g., a specific page within your app) without any snags. 

No matter the channel or device you use to reach a user, the mechanism that takes the user from a link in one of your owned media channels to the app store where they can install and use your app (or, if they’re an existing user, to launch the app) is called redirection; the user taps on a link you generate and is redirected to the app store. If that path is compromised by a bad user experience, like a broken link or being dumped somewhere that isn’t relevant, that’s “friction,” and you’ve likely lost that user right out of the gate.

Redirection supports a host of user acquisition strategies, it frees you from having to worry about building and maintaining infrastructure, and over the long term, it helps measure, iterate, and improve whatever user acquisition strategy you choose. If you’re pursuing new users (as startups generally are), then you want to become particularly familiar with deep linking, which happens after redirection and makes a new user’s journey smooth from first impression of your app to engagement and even purchase within the app—a journey which can include personalized content that resonates with the user. Basically, deep linking makes sure that when a user launches your app, they go directly to a specific page rather than to the app home screen.

For example, let’s say you reach out to prospective new users (on any channel) and offer them a discount if they download your app. They tap on the link, are directed to the app store, download the app, and boom, as soon as they open the app, there’s the discount they were expecting to see; on your side you can then tell exactly where that install came from—if it came from browsing on the mobile web or from an SMS, for example.

But the beauty of deep linking isn’t just rooted in the personalized content and the seamlessness of the user experience—it’s also in attribution: done right, deep linking makes the user experience engaging and friction-free and provides you, the app developer, with the data (attribution) that tells you where that user came and what they do once they download. 

All of this is great, right? It is…but the truth is the mechanisms that streamline the user’s journey and provide you with attribution data can be more complicated than you would expect when you look under the hood—there are all sorts of factors and variations that can make redirection and deep linking complicated, like what OS and device existing or new users have or where they are when they click on the link (e.g., social app, email app, etc.). That means, in theory, that you have to generate multiple links that will work for all of the different possible device, platform, and app scenarios, which is a headache.

The good news is there are powerful tools that, with a bit of time investment, can easily create those multiple links that you need to reach users and get them to install your app and engage with it, no matter where and from which device, platform, or app they’re coming from. The magic of it all is that each of those links leads to the right content—whether in-app or not—and is created by the same tool. That’s where the road to meaningful engagement opens up. 

So get started with getting those first 1,000 installs by arming yourself with basic knowledge about how deep linking and each owned media channel work best together, and the tools that can keep them working together efficiently.

For this specific purpose we created the video series: How to land your first 1,000 mobile installs. Every video is focused on a different channel you can use. This time around – Social!

Your first campaigns: Pitfalls, tips, and tricks

Social campaigns

Social is an incredibly strong growth channel because the audience, whether they’re your friends, family, or other followers, are self-selecting: if you’ve got them, it’s because they’re already interested in you and perhaps even your app. 

In an ideal world, you would be able to post a single link on social that leads to the app store to install (or even to a particular page within your app); new users ( those that don’t have the app installed) and existing users (those that do have it installed) would tap on it, and presto, they land exactly where you want them to be (and where they expect to be—no surprises!))

But as we noted above, it’s more complicated than that because there are so many variables (new users, existing users, iOS, Android, etc.)—and social apps in particular —often break Universal/App Links.

Those broken links get back to the issue of creating extremely annoying stumbling blocks that can alienate users: they tap on a link for your app in a social app and nothing happens, or they reach your app’s home page instead of a landing page, or they wind up routed through the app store even though they already have the app installed. All of these, unfortunately, are common scenarios. 

But again, if you familiarize yourself with deep linking options, you’ll find those that have workarounds. AppsFlyer’s OneLink technology for example, offers you reliable deep links as well as the option to create landing pages that obviate broken experiences from social to an app.

Email campaigns

Email marketing has long been one of the most reliable channels for acquiring and retaining users, and it’s inexpensive, relatively simple, and extremely effective. Moreover, given that these days many users open email on mobile, the leap from email to an app can be relatively friction-free when you embed a call-to-action in the email, like “download the app” or, to give a more specific example from the travel category, “Check out these cheap flights.”

But that doesn’t mean using email marketing to app installs is without challenges—those rear their heads when it comes to measurement. While email service providers wrap links (shorten them automatically) and track opens (always a crucial metric to track), wrapping in particular can break links on iOS as well as on Android (to a certain extent). 

That means you need a deep linking solution (like AppsFlyer’s OneLink) that ensures that the user has a seamless experience moving from your email to your app, and that you can easily compare data from your email service provider with that from your attribution provider to measure their effectiveness side-by-side. Armed with that information, you can make smart decisions about where to channel your marketing budget. 

Referral invites, word-of-mouth and SMS

When it comes to increasing your mobile installs, there’s nothing quite like the magic of referrals—they’re where the possibility of your app going viral and growing at scale originates. But just like every other approach to getting new installs, you need to be smart about it: you need to incentivize referrals and you need to measure how they’re performing. 

Yet again, this is where deep linking is invaluable: with a single link, you can measure and attribute which user originated every new install and each action inside each new install AND make sure that the link maintains personalized content to attract, engage, and retain new users. 

SMS offers one of the best channels for referrals and user acquisition overall because it’s so tidy: an existing app user can invite other users through their mobile phone contacts, again using a deep link, without the messiness of needing to know if the user has an Android or iOS device. 

But there is a limiting factor with SMS referrals: you have very little room on the screen to make your pitch. Again, that’s where a good deep linking solution from a good attribution provider can make a huge difference. OneLink, for example, enables you to send extremely short links that you can customize, so you’re sending a link that is relevant and doesn’t eat up space on the screen. 

Also, when it comes to re-engagement of existing users, a deep link delivered via SMS offers ideal friction-free re-engagement; all the user needs to do is tap on the deep link in the SMS, and they’re instantly in the app, looking at whatever customized content you’ve created for them.

To sum up, getting your first 1,000 users is a huge milestone for any app creator just starting out —once you’ve reached that benchmark, smart tools and a keen awareness of user experience can help you build still more momentum. 

Remember, in today’s hyper competitive app space where users have extremely high expectations, anything that falls short of a world-class first time experience with your app and you risk an uninstall within a click of a button. 

It’s that simple. If you take the time to learn how to combine your owned media with redirection and deep linking, you will be well on your way toward capturing and keeping valuable users.

Here at AppsFlyer, we’ve launched our free-for-life package, Zero, as a part of AppsFlyer’s Zero Budget Marketing initiative – aiding app developers leverage owned media, especially web for growth. You can create your free account within seconds. 

The post How to get your first 1,000 app users appeared first on AppsFlyer.

To change a person’s mind, let alone an entire community can be difficult. In the summer of 2019 AppsFlyer set out to challenge one of our industry’s long standing philosophies regarding mobile ad fraud identification.

Mobile ad fraud has always been a pain point to almost every app marketer. Anti-fraud vendors sought out to battle or at least minimize this ache- each with their own solution or approach – some were more successful than others. 

However, one commonality can  be found within all solutions – they all worked under the same basic assumption that all fraud can and should be identified and blocked in real time.  

Last year we planned for Protect360’s relaunch where we were given an opportunity to rethink many core assumptions regarding mobile attribution in general and fraud detection specifically. 

We knew that fraudsters are just too sophisticated to settle for simplicity, so we challenged the belief that all of their activities can indeed be identified in real-time.

We started the post-attribution fraud detection journey under this exact assumption and with a nagging feeling that something big was being overlooked.

This meant admitting a potential weak spot – one that could damage the way our solution is perceived.

So was post-attribution fraud detection the right thing? 

Market feedback

As the mobile attribution market leader, any new feature that we introduce is naturally followed by market reactions, especially when pointing out a weakness that you’re looking to solve.

Our competitors were first to respond by claiming that AppsFlyer can now only identify fraud post-attribution – missing the point completely. 

Post-attribution fraud detection was yet another layer of protection for our customers. This was meant to identify and block new fraud patterns as they emerge, associate them with fraudulent clusters, and effectively teach our algorithm new fraud patterns on-the-go.

A new fraud pattern would consist of several initial installs – sometimes amounting to hundreds or even thousands. These installs are not yet recognized as fraud, as they still don’t match any existing fraud detection rule and their suspicious cluster has yet to reach sufficient statistical significance to be considered as fraud. 

Once passing our strict thresholds and labeled as fraud, the initial installs contributing to the identification process will also be associated with the fraudulent cluster, and labeled as fraud retrospectively.

This means that installs who would otherwise be disregarded in the detection process are now properly treated and rejected.

So, despite what some competitors had to say, this additional protection layer was in fact strengthening our real-time detection, adding more query points to our ongoing fraud learning algorithms, and protecting our ecosystem in a way that other vendors simply couldn’t.

Results don’t lie

Early beta testing and models showed a greater impact than anticipated with roughly 16% additional fraud detected.

As we officially launched this feature at full scale in July of 2019, large scale results started rolling  in. The first month of full scale post attribution activity showed an astounding 27% of fraud detected post attribution.

Post attribution monthly trend

This served as a double benefit:

1. A pattern that was identified as post-attribution fraud in a given period will be recognized as real-time fraud from that point on. 
2. Fraudsters were now left with very little room to operate, which translated into lower overall fraud rates in the following months.

As the biggest player in the attribution landscape, this actually meant a shift in the needle in terms of industry fraud rates, as fraudsters were now focusing their attention on other less vigilant vendors and their customers.

Key takeaways

The average post-attribution fraud rate in 2019 was ~20%. 

While this significant increase in identified fraud is impressive, the biggest takeaway from this feature should be the approach of challenging industry misconceptions. 

Basic work assumptions, habits, and beliefs can often be exploited by ad fraudsters, as they live and breath the industry’s culture just like legitimate marketers. They take advantage of these beliefs, as they see them for what they truly are – weak points and loopholes – an opportunity for them to strike.

Since releasing post-attribution AppsFlyer went on to challenge more of these potential loopholes such as the false positive test and CPA campaigns – still believed by many to protect from fraud – when in fact they are intentionally targeted by fraudsters.

The introduction of post-attribution fraud detection was the right move.

It helped AppsFlyer’s customers save millions of dollars since its introduction. But most importantly, it was yet another step to reduce fraudsters margins and profit.

The more steps we take to lower fraud’s ROI, the closer we will get to lowering fraudster motivation to operate. It is our job to make their operation less profitable and difficult to operate – one step at a time.   

The post Post attribution fraud detection – was it the right move? appeared first on AppsFlyer.

Tik-Tok, Tik-Tok… ranging from 15 to 60 seconds where every second counts. With potentially millions of people waiting to hear what you have to say, be careful not to make a boring and cliché ad that will be scrolled past.

Last year, I shared some tips on how to hack your performance creative strategy. At the time, I wasn’t considering a platform like TikTok Ads as I wasn’t fully aware of how powerful this platform was. In this post, after a year’s long journey through the world of ads with TikTok, I’ve narrowed it down to the 6 most important lessons.

But before we dive into the creative, let’s put things in context: TikTok is the world’s fastest growing social media platform, ranking as the most downloaded app in 2020 with 817M downloads in the last twelve months. According to Forbes magazine, the user base in the U.S. alone is growing at a staggering pace of five-folds in just under 18 months. TikTok, is continuously gaining followers and driving engagement, peaking as the hottest platform out there. 

Source: App Annie, October 2020

Brands and marketers have come to understand the power of TikTok and are shifting their focus and creative efforts at producing engaging content that drives user-generated videos and scale views around campaign initiatives and Hashtag Challenges.
This trend continues to spearhead globally driving engagement, and as such, companies, apps, and game developers are filtering in.

Don’t make ads. Make TikToks.

TikTok Ads have changed the way we think about ads. If you are a marketer, a CMO, a UA Manager, or a founder of a company, you know how to communicate your brand message and target your ads to reach the best potential users out there. You may be ahead of others with your own company brand book, outlining tone, do’s and don’ts, look and feel, and more. But TikTok has a completely different logic.

Advertising and communicating on TikTok challenges us to go beyond our traditional approach and really focus on the audience, adjusting the way we tell a story. Which is why you shouldn’t create standard, traditional  ads; instead, you need to start thinking about what’s right for TikTok.

Over the past year we have been running ad campaigns  on TikTok for several clients, achieving  some great results. After continuous A/B testing within the platform here are some of the best practices we’ve come to learn.

1. Create ads with vertical video in mind

TikTok is a vertical platform by nature and to maximize user and brand experience, all your video assets should look as native as possible, aligned with the ad specs. Despite the fact that square videos can be uploaded and advertised, a 9:16 ratio has greater potential for higher performance. 

2. Start with a high impact visual or an engaging hook

Unless you catch their attention you will be scrolled. Discover what motivates your viewers and  keep them engaged. Maybe it’s something eye-catching, or even shocking. In any case, the key here is to hook them in and improve the overall performance of the ad.

3. Think musical.ly

TikTok at its foundation is a musical platform (previously named as Musical.ly) where all TikTok videos play with the sound automatically ‘on’. Matching your videos with the right music and sound will spark greater engagement and attention. 

Tip!  Try to be geo specific and tap into the popular sounds/song to capture your audience.

Subscribe to AppsFlyer content

The latest mobile marketing tips & trends delivered to your inbox.

4. Be concise and keep videos SHORT

Your viewers are bombarded with ads, with their home feeds splurging with content, which means their patience is cut short.

Think of TikTok ads as your best elevator pitch. You have less than 60 seconds, and less is more, to get your message across. We noticed that the more powerful videos ranged between 10-25 seconds have greater engagement. 

Tip! Stay focused and be quick about it. 

5. Lean on trends

Adapt your message to the latest trends: music, effects, dance, or challenges; this way there is a greater chance that your ad will get noticed or even outperform your competitor. 

What brands entice your viewers? What is the latest viral challenge? Deep-dive into the platform and find out more  (or ask your TikTok Marketing Partner), and use these selling points to your favor to achieve your goals and create the best user experience possible!

6. User-generated content dominates

As I mentioned, TikTok challenges all companies and marketers on the creative production front. How we communicate our products, apps, games, add values, features, and more requires us to think outside of the box. 

You can still present your brand, you just have to think like a TikToker. Measure your performance and user behavior and constantly evolve your marketing strategy accordingly.

The bottom line: If you want your ads to succeed on TikTok – don’t make ads. Make TikToks.

The post 6 tips to running high impact ads on TikTok appeared first on AppsFlyer.

2020 has shaken up the landscape of mobile apps – and mobile gaming in particular. Lockdown conditions and social distancing have meant more sofa time, and with that comes more and more people turning to their screens for a much-needed distraction. 

Games are in greater demand than ever, leading to a 45% rise in the number of gaming app installs compared to 2019. There was also a 25% increase in in-app purchase (IAP) revenue during and after Covid-19 lockdowns – in short, this represents a real game changer for mobile. 

But is this accelerated growth set to be a long-term shift, or is it likely just a short-term phenomenon that will see a correction in KPIs to something closer to what we were seeing before February 2020?

The new State of Gaming App Marketing report analyzed 9.2 billion installs for answers. We’ll cover a few highlights in this blog including install and revenue trends, as well as growth opportunities across the globe.

Growth by genre: a new normal for some, but perhaps not all

With app installs up 45%, it’d be easy to assume that business is booming across the whole gaming market during a period of spectacular growth. However, if we look closer, much of this is owed to immense growth in a handful of categories, with much more modest shifts in others.

Above all, the “softer” gaming categories of Hyper Casual (HC) and casual were the clear winners, with a 90% growth in HC alone.

Even better news for Hyper Casual devs comes from the growth in non-organic installs, which increased by a staggering 250% in 2020 compared to the previous year. Clearly, HC marketers were quick to seize the opportunity.

The rapidly growing audience brought on by lockdown restrictions across the globe has led to a large rise in the number of new players for these softer categories, with a particular appetite for the snackable, instant entertainment provided by HC and, to some degree, casual games. This also suggests that beginner players – those who might be trying mobile gaming for the first time – are starting with the most accessible genres.

However, this growth has come at a cost – and it’s a cost that introduces some uncertainty as to whether this boom in softer categories is a new normal that’s here to stay.

‘In marketing we [continue to] trust’

WIth demand for mobile games on the rise, many developers and marketers continued their significant investment in paid user acquisition, leading to a 70% year-over-year jump. This proved to be a sound strategy, particularly when huge numbers of people were suddenly confined to their homes, many with free time to fill.

Despite heightened organic demand this year, which grew 57% more than the previous year compared to only a slight increase in non-organic installs (NOI), the latter’s growth was more than twice as high.

Beyond the opportunity brought about by the pandemic, there are two main reasons behind the robust growth in NOI:

1. Organic discovery for the average app continues to be extremely challenging and only getting harder each year.
2. Gaming apps have the confidence in their ability to leverage data to drive profitable marketing investments.

At the same time, cost per install (CPIs) – particularly in casual and HC – were low during this period. Our data sample suggests that developers spotted this and brought their user acquisition budgets forward to late Q1 / early Q2 as a result. The outcome was that all categories spiked during March and April (+35% in April vs February) before dropping later in the year.

However, heightened demand drove prices up after lockdown. The US showed a 35% rise, while across APAC the jump was 45% among iOS CPI since March. Some of this was down to big brands who initially pulled back their spending amid increased uncertainty – but their return drove bid prices up across genres and GEOs.

Gaming apps maintain heightened IAP revenue post-lockdown

Although installs of gaming apps spiked when lockdown started in March, in-app spending followed in April and peaked in May (+25% vs February), and later again in July. It appears that these apps were able to leverage the large number of users who installed during lockdown and remained engaged throughout.

This is yet another indication of how different 2020 was compared to 2019. Last year, most revenue was generated during Q1, then dropped sharply in Q2. This year, the opposite is true in terms of revenue distribution. The casual app genre has been a driving force behind this shift, with its figures jumping 55% from March to May and remaining high through the rest of 2020.

As countries around the world came to grips with the pandemic, users clearly turned to IAPs in greater numbers as part of their light entertainment diet. The need for a distraction saw a significant shift in spending patterns.

This contrasts sharply with in-app advertising (IAA) performance: while IAP revenue climbed 67% from February to August, IAA revenue gradually decreased throughout the year. It appears that players had a lower tolerance for ads in 2020, but were more willing to make purchases in a world that suddenly had restrictions on where people may traditionally spend their disposable income, such as travel, restaurants, sporting events and cultural activities.

High growth markets – where can we diversify?

In 2020 so far, large developing markets like Brazil, Vietnam and Russia have seen some of the highest increases in growth of paid user acquisition. These are markets that not only have huge populations, but also ones that have been hit hard by Covid-19.

In the main, this is not a surprise – the major growth markets in 2020 are largely what we’d expect to see. Not exactly a new normal, but perhaps an acceleration of old norms instead.

So where can user acquisition look to diversify? Some of the fastest-growing markets (outside of the top 10) across all categories include Colombia, Peru, Morocco, Egypt and parts of the Middle East and Africa. For the booming categories of casual and HC, Australia, Malaysia and South Africa are also in play. 

With CPIs rising due to the increase in competition, this is absolutely the time for developers to innovate when it comes to user acquisition. Whether that’s investing in new fast-growing territories, or turning to new channels such as TikTok or Snap, adaptation will be key as we head towards 2021.

We’ve looked at drivers of growth and retention – let’s wrap up by examining how (or if) monetization has changed in 2020.

So, is there a new normal in mobile gaming?

Wrapping up, it’s clear to anyone with a passing interest in mobile gaming that 2020 has been a year of huge growth in the market, with unprecedented circumstances leading to more people than ever before looking for entertainment and distraction.

But will these new global conditions lead to long-term accelerated growth? Certainly, there have been some positive short term gains in the market, and there are some indicators that this growth may persist into the future.

However, with much uncertainty on the horizon – not only in terms of the far-reaching effects of the pandemic, but also other factors like iOS14’s changes to the App Tracking Transparency framework and rising CPIs – it’s difficult to say for sure what’s around the corner.

It’s therefore important that you continue to closely monitor your numbers, and so will we as we continue to report on the state of the industry into 2021.

For more detail and insight, including the latest regional performance benchmarks from 16 top markets around the world, check out the 2020 Edition of our State of Gaming report.

The post Was 2020 a game changer for mobile gaming? appeared first on AppsFlyer.

How exciting, we’ve just released the first ever universal links and app links validator. The idea is very straightforward, we want to empower app developers and marketers to build a phenomenal user experience across devices.  

Until now, there was no easy way to test all of your links in one spot. A place where you can validate your website links, ensuring that all of them are working properly, and that they all lead users to the right spot within your app, is a must.

How seamless is your web to app experience? Test it out using AppsFlyer’s free App Links Validator.

If you’re reading this, I’ll bet that you’re probably a big believer in the power of website campaigns in helping you attract users to your mobile app, and I’m sure that you’ve invested precious time and resources in it.  I’m talking about ads, banners, content, and everything in between, to convey the value of your app throughout your website experience. That’s fantastic. Keep it up.

While your web to app marketing promotion might be top-notch, if I asked for your level of confidence regarding your app links’ not breaking, how sure would you be? 

The more extensive your website is, the more complex it becomes at keeping all of your links validated at all times. The challenge is, that If you have both Android and Apple apps ensuring all links are validated can be cumbersome.

Then came App Links Validator. How does it work?

The first step is to plug your website URL. You have an added option to add the app prefix and bundle identifier for deeper configuration mapping (relevant only for Apple). 

When  you hit “validate my files”, our tool will get to work. Within a few seconds you’ll be able to see the required configuration tweaks you’ll need in creating  a seamless user experience. 

Our App links validator will be scanning through your general link configuration, as well as your specific Apple and Android links. 

We’ll be looking at:

•  HTTPS protocols
• DNS
• JSON Scheme
• 200 status code
• App clips (only for Apple)
• What else?

If there’s an issue with any of those, you’ll see a X sign followed by a detailed description of what needs to be fixed under the relevant app configuration.

If your JSON file is valid, you’ll notice that we included the actual code for you to grab directly from the tool. 

NOTICE we’ve also included troubleshooting tips that’ll ensure you make the relevant adjustments at ease. 

I tested and fixed my links. What’s next?

First of all – great job! 

When you’re ready to step it up, we highly recommend using web products that can boost your conversion rate to new heights. 

Here at AppsFlyer, we’ve invested in web-related products and features like: OneLink deep linking and deferred deep linking, Smart Banners,  People-Based Attribution, and launched our free-for-life package, Zero, as a part of AppsFlyer’s Zero Budget Marketing initiative – aiding app developers leverage owned media, especially web for growth. Feel free to start using  these tools today!

The post Does your website support AASA and App Links in 2020? appeared first on AppsFlyer.

Over the past several years we’ve noticed a shift with advertisers and their campaign strategy moving from strictly CPI based campaigns to a mix of CPI and CPA, with some advertisers going as far as relying solely on CPA.

This transition makes perfect sense, as campaign performance is no longer measured solely through user click-to-install conversion rates. User LTV (Life Time Value) has long been the measuring stick for a successful user-acquisition operation, and you can’t determine LTV without deep in-app data.

Alongside the clear benefits of measuring various points within the user journey and rewarding publishers accordingly, comes the inevitable risk of fraud.  In-app and CPA fraud has long been discussed by AppsFlyer, and has been labeled by many as the next frontier in the ongoing battle against fraud.

AppsFlyer’s recent State of mobile ad fraud – 2020 edition paints a grim picture of in-app fraud rates hitting unprecedented numbers. Some app verticals show greater risk of in-app and CPA fraud, and unsurprisingly these verticals are the ones who have adopted in-app data and measurements the most.

These stats highlight a contradiction with common industry beliefs that CPA campaigns aid in preventing fraud. While they have introduced a new layer of data that helps mitigate fraud to a level, they are now themselves the target of modern fraud methods.

The equation is simple – fraudsters follow the money, and right now, the money lies beyond the install attribution.

In-app activity measurement can be used for two main objectives:

1. Measure user activity across key points across the app experience to determine everything from app functionality to user LTV.
2. Reward media sources for delivering users who reach specific checkpoints within the app – CPA.

While only the latter directly relates to monetary value, both objectives can be manipulated to affect an advertiser’s view of a certain media channels’ value.

Spoofing in-app event logs can create a false image of value in an attempt to whitewash fraud at an install level, as event engagement can be presented in an attempt to determine user legitimacy.

When reviewing CPA events the stakes are higher. CPA rates can often reach over 10X the amount of their associated CPI rates, as they represent higher value and user quality. A savvy fraudster can do the simple math of one successful CPA fraudulent activity potentially generating a return greater than ten or more installs. This requires greater sophistication and technological abilities; however, in return, fewer successful actions are required to generate an equal payday. 

The fraudster can settle for fewer actions, meaning lower chances of attracting unwanted attention from anti-fraud solutions. A smart fraudster could even be falsely considered as a quality media source by some advertisers who only measure media quality by general CPA activity. 

Does this mean that these verticals should drop their in-app measurement efforts?

Of course not.

In-app measurement advantages easily outweigh the disadvantages presented by new forms of fraud. 

However, a new method of measuring, reviewing, and acting based on in-app data is required. Advertisers can no longer settle for a skim of their data to draw deep conclusions.

Deep-dive into your app data

The only way to efficiently fight fraud is through data. The more data you have, the better equipped you will be in understanding where the perpetrator is, its volumes, methodologies, and most importantly, how to handle it.

In-app and CPA fraud data has been available through Protect360’s raw data reports for a while, we are proud to introduce the latest addition to Protect360’s anti-fraud suite: the In-app activity dashboard.

In-app fraud dashboard

The new in-app fraud activity dashboard separates in-app fraud activity from install fraud. These are foundation discussion points that should be analyzed and treated differently.

Our, first of its kind, dedicated dashboard makes your in-app fraud investigation work significantly easier. Presenting you with all of the in-app and CPA activity that is blocked in real-time or in post-attribution. 

Saving time and money

Fraud breakdown overview

The dedicated fraud overview widgets highlights the general status of your current in-app fraud activity. The overview will present both the overall volume of identified fraudulent events and an estimation of savings associated with the identified activity.

The estimated savings are of course dependent on the information you provide AppsFlyer. The more accurate the CPA valuation per event will be, the more accurate the savings estimation is. 

The fraud trend chart will break down your in-app fraudulent activity by real-time blocks and post-attribution detection per the defined time frame. Post-attribution detection is relevant not only for install attribution, but also for in-app activity. 

As mentioned above, some fraudsters will deliberately set their sights on your in-app activity, disregarding the install CPI. This breakdown is crucial for better understanding where sophisticated fraud lies and what sources deliver it. 

Your very own in-app fraud index

Top in-app fraud media sources

The Top IAE fraud by media source widget acts as an indicator for specific media partners who are responsible for highest in-app fraud volumes.  Each partner’s activity will be broken down by real-time fraud, post-attribution fraud, and their non-fraudulent activity in percentages (%).

Keep in mind that while it may seem like an easy hit-list, this is merely the first step of your necessary investigation. The next step will be to explore each partner’s data, identifying specific site IDs, and treating these issues together with your partners to construct a mutually beneficial media portfolio.

The exploration is necessary and can be carried out via the breakdown table (at the bottom of the screen) and through your raw data reports.

Hands on the wheel

In-app fraud sunburst chart

The In-app fraud breakdown chart is a dynamic and responsive visualization for your in-app fraud data. Hovering over any of the chart’s layers will provide insight of the indicated section like: fraud type, channel, volume, and more.  It further provides specific details of each section within its  layer. Clicking on a specific section within the layers will restructure the chart and provide a deeper view into the chosen layer’s details and the layers constructing it.

It is best to start your drill-down process from the inner layers of the chart and work your way through the dynamic pie charts as they unfold. For example, begin with a general overview of fake installs vs. hijacked installs, drilling down into fake in-app events, then see how many were created following fake installs, at which you can then identify which media partners delivered this activity, and at what volume.

Uncover the truth

In-app event fraud breakdown

Similarly to install fraud, a general overview of your activity isn’t enough. The in-app event fraud breakdown table provides the information required for any thorough investigation of in-app fraudulent activity.

Digging deeper into each media partner’s activity breakdown will help identify specific fraudulent site IDs within their activity. Using the chart wisely with  all the tools reviewed here, alongside raw data reports, will aid in constructing a quality media portfolio and in-turn minimize the presence of in-app and CPA fraud to your campaigns.

What’s next?  

The in-app fraud activity dashboard is one more  step towards AppsFlyer’s long standing ambition of providing its customers and partners a fraud-free ecosystem. We understand that in-app fraud is  the next challenge for mobile ad-fraud, with fraudsters adapting to new market realities and opportunities presented by the growth of CPA campaigns and in-app activity measurements. 

Future developments are still to come, as integrations with additional AppsFlyer capabilities are planned to ensure a more comprehensive protection layer. Offering custom capabilities  at defining, event-level, rules to eliminate risks of sophisticated fraud by utilizing each developer’s own activity logic, and more. Looking ahead, empowering our customers with tools that allow deeper control over sophisticated fraud methods that affect more than install attribution is paramount for us.

Stay tuned.

The post Introducing AppsFlyer’s First-to-Market CPA Fraud Dashboard appeared first on AppsFlyer.

2020 has been a year unlike any other, but the familiar rhythms of the calendar have persisted for the world of eCommerce despite the unprecedented conditions driven by the coronavirus pandemic. The holiday season is upon us, and it all kicks off with a significant date in the retail diary: Black Friday 2020.

Black Friday itself is now an event that stretches far beyond a single day. “Cyber Monday” follows on its heels, but many retailers offer Black Friday deals far in advance of that final Friday in November.

In fact, in recent years we’ve seen that the end of November period was actually the real peak of the holiday season for mobile shopping apps, surpassing pre-Christmas December sales.

Black Friday 2020 is set to shatter records. This blog will explain why by citing data from Black Friday 2019, and from the 2020 surge AppsFlyer reported in our recently-published State of Shopping App Marketing.

The COVID impact to date

The COVID-19 pandemic has had far-reaching impacts on the entire world. One of those impacts is economic, so naturally we were keen to explore how this has affected eCommerce in our latest report.

Here are the key findings for EMEA:

Increased demand. The pandemic led to a 35% increase in eCommerce app installs from March to April 2020 alone, surpassing the peak of the Q4 2019 holiday rush.

Heightened spend. iOS users spent 50% more on average in April 2020 vs. the November 2019 peak.

Aggressive marketing. Non-organic installs grew 56% between February and May 2020 as marketers invested in user acquisition, capitalizing on the increased “sofa time” brought on by lockdown restrictions, and later social distancing and safety concerns.

Clearly, with brick and mortar stores closed for months on end as part of the COVID-19 restrictions across the globe, digital retail has come to fill the void.

A look back at Black Friday 2019

We know that the Q4 holiday period is when retail typically booms – but what about Black Friday specifically? We looked at the data from Black Friday 2019 and compared it to the average of the previous four Fridays to see what kind of impact this retail event showed last year.

You won’t be surprised to learn that there was a big uplift in virtually all KPIs, but let’s drill a little deeper into four key takeaways from our data sample.

Black Friday leads to huge increase in revenue. The UK, France, Germany and Russia all showed huge upticks in revenue as shoppers flocked to retail apps during the event.

That said, some territories performed vastly better than others. A 98% revenue increase in the UK is a solid return, but Black Friday proved even more successful at driving purchases in France and Germany. Russia stands far ahead of the crowd, with a revenue uplift that doesn’t lag far behind the country that started it all: the US.

Black Friday drives organic installs demonstrating pure consumer intent. This is certainly an impressive impact on revenue driven by Black Friday – and some of that revenue spike can be attributed to a rise in the number of shoppers, reflected by an increase in organic installs across Europe.

Once again Russia leads the way, almost doubling the amount of organic installs vs previous weeks. The appeal of a sale or a bargain, and the awareness of Black Friday as an event, has clearly taken hold across Europe.

Non-organic installs drop in EMEA on Black Friday as marketers focus UA in the build-up. While Russia saw a dramatic increase in non-organic installs (NOI) on Black Friday, this was very much an outlier in EMEA. France, Germany and the UK all saw drops in NOI on Black Friday itself, with the UK falling by over a third.

As we’ve seen in previous years, it appears that marketers’ user acquisition strategies were focused on acquiring users in the weeks leading up to Black Friday, to have as large an audience of app users as possible ahead of the event.

The fact that Black Friday often begins weeks earlier may also have played a part here, with UA aimed at getting the maximum return on investment over a longer period of time.

UK outperforms the US in remarketing conversions. We can see the effects of those drops in NOI on remarketing conversions. With UA budgets spent in advance to acquire new users, more marketing effort was focused on reengaging existing users on Black Friday itself. This is particularly true in the UK which stood apart from the crowd in 2019, more than doubling the average from the previous Fridays.

Of the other territories in our sample, most showed a slight reduction in remarketing conversions with only Russia recording an uplift – albeit one way behind the UK figure. What makes this even more notable for the UK is that it far outstripped remarketing conversions in the US, which did not show any real uplift.

Black Friday 2020: a 1+1=3 scenario

There is plenty of encouragement here to expect a strong digital retail performance heading into this year’s holiday season. Based on the previous Black Friday, and the COVID effect, we can foresee installs and revenue taking significant leaps during this year’s Black Friday.

In other words, 1+1 = 3.

This is in line with the broader trends among retail, which has been pivoting to digital for several years at the expense of physical stores. According to eMarketer, retail eCommerce accounted for 28% of all holiday spending in the UK in 2019, a new record high.

Last month, a survey of shoppers in Germany found that the majority intended to shop online this Black Friday as opposed to in stores, with 40% of those surveyed saying that they intended to switch from in-store shopping to online as a direct result of the pandemic.

In a year in which shoppers have embraced eCommerce more actively than ever – often due to the necessity of shopping online brought on by lockdowns and social distancing – it’s clear that this trend will only be accelerated on Black Friday.

Potential headwinds for marketers in 2020

However… there’s a few notes of caution that are also worth exploring before we wrap up. While it is highly likely Black Friday 2020 will be a huge boon for retail apps – consistent with performance through the year so far – there are several possible headwinds to consider.

Economic downturn. We shouldn’t overlook the negative impact that COVID has had on many people’s livelihoods. This has only been exacerbated in recent months as COVID cases rise again in Europe, and many countries re-enter a second lockdown.

While total revenue should see a further jump on 2019, the average spend per consumer might not see much (if any) change year-to-year. Economic hardship resulting from the pandemic means a reduction in disposable income, but at the same time consumers haven’t had the opportunity to spend on things like travel, culture, sport etc that they would have in a “normal” year. Instead, there may be a greater desire for retail therapy: a willingness to treat oneself during a difficult period

Higher CPIs than at the start of the pandemic. When marketers brought forward their user acquisition budgets at the start of the pandemic in Q2, they did so during a period where CPIs were low. Lots of big brands held off during this period of uncertainty, and reduced competition drove down CPIs across several European countries.

Naturally, once those big retailers re-entered the playing field, CPIs rose again, in some cases to higher levels than they were pre-pandemic. This was particularly noticeable in the UK, which saw a 110% growth in CPIs between March and May. Businesses that weren’t prepared for lockdown in Q2 are now much more likely to be geared up for the next few months.

The holiday period is already a highly competitive space for marketers, and the increased media cost means that marketers have a greater-than-ever need to leverage data to ensure high-quality returns through smart targeting. Marketers should also explore remarketing and re-engagement on Black Friday itself, which is likely to be lower-cost and therefore deliver a greater ROAS than user acquisition.

To sum up

Black Friday is traditionally a successful period for retail, and particularly digital, and most indicators more than suggest that 2020 will continue that trend and even greatly accelerate it.

Indeed, the eCommerce performance from earlier this year shows that shoppers are downloading and using retail apps more than ever – and spending more within them.

That should only spell good news for digital retail in the coming days and weeks. Look out for AppsFlyer’s analysis of Black Friday 2020 performance in early December.

The post The data has spoken: Why Black Friday 2020 will be one for the record books appeared first on AppsFlyer.