It’s 2021 outside, but COVID-19 is still well on its way to transforming people’s content consumption behavior. In this term, mobile is the flagman platform among users, thus, luring advertisers’ budgets and making mobile app tracking attribution important like never before. Attribution helps advertisers find out how to connect with their target audience. But what is mobile attribution? We’ll reveal it right after a brief introduction.

Back to mobile consumer behavior, according to Statista, by the end of this year, the number of smartphone users worldwide will constitute 3.8 billion. Such bloat can be explained by mobile gaming trends and their resistance to lockdown restrictions, as well as by the ability to deliver both entertainment and business apps. At this point, mobile game ads are gaining momentum. Scaling of the mobile audience is an eloquent signal for marketers to perform mobile app monetization.

Since it’s forecasted that the volume of mobile ad spendings in the U.S alone will hit $161.49 billion by 2024, mobile app owners are unlikely to neglect such a bold slice of the revenue. For this reason, mobile advertising attribution is a standard-bearer so understanding mobile attribution tracking is crucial for advertisers.

forecast mobile ad spending us

Mobile app attribution has a sophisticated architecture as it encompasses lots of technical features. So, what is mobile attribution? How does it work? What impact does it have on businesses, and what are the trends? This article is just to answer all these questions.

What is mobile attribution?

Mobile attribution is all about where users come from before installing a mobile app or making a purchase, signup, or app install from an app store. In other words, when a customer clicks on CTA, advertisers want to know the exact channel that triggered the customer. App tracking attribution is the solution for such a challenge. It provides advertisers with real-time data where their campaigns work best, allows them to see how users respond to creatives, and track users’ walkthrough of the entire funnel. Also, once the installation is made, the attribution app allows tracing actions (events) that users are taking therein. Such granular data points are essential for a successful mobile marketing strategy.

For example, an owner of a sports gym can place his ad in a health and care application and run several marketing channels to promote his services, like video creative and banner one. To get data about which one of the creatives generates a higher conversion, mobile attribution comes into the scene. App tracking helps to understand what marketing campaign to use for specific cases. It enables advertisers to pinpoint what channel provides the best results in user acquisition. Plus, this allows advertisers to define the most relevant cohorts and invest ad budgets accordingly.

Besides initial ad campaigns, mobile attribution delivers value for retargeting campaigns. For instance, mobile app owners can reveal users who installed their app but for some reason weren’t actively using it. Or, the mobile app was deleted in a while — it could be caused by reinstallation of the operating system of the user phone so it makes sense to remind the marketer about the app via a retargeting campaign.

Let’s figure out how all these things work!

Mobile app attribution models

The app tracking attribution embraces plenty of options, hence, advertisers are capable of creating quite definite customer journey maps and get valuable analytics and insights that eventually translate into revenue. Each of the mobile attribution models possesses distinctive capabilities that drive concrete analytics to one or another extent. Such diversification appears due to a wide range of goals that each advertiser set to themselves within every single ad campaign. Here they are:

First click attribution

This one is efficient for increasing brand awareness as it allows mobile marketers to see where a prospect came from as it records the very first data point. For instance, a marketer has an ad on Facebook that leads to the page of his online store. When a user clicks on the ad, first touch attribution will provide a marketer with information that such a user landed to the e-store via that ad. And it works the same for any other marketing channel. So this app tracking attribution helps to see what channels drive the most of the marketer’s audience.

  • Pros: it’s easy to implement and allows brands to generate a high-quality pool of demand since it identifies which first touchpoints drive sales.
  • Cons: it provides valuable data concerning only top-of-the-funnel, so marketers can’t evaluate the impact of touchpoints that are beyond the first click.

Last click attribution

With the help of this attribution, advertisers can trace ads that users last clicked on before making an app installation or a purchase. . The main problem is that the customer can make a purchase decision after reading advertisers’ email newsletters but without clicking on links. Still, later, technically they can click on an AdWord ad, and the conversion will be counted and credits will go to AWord, not the email campaign.

  • Pros: this mobile app tracking model shines at its best when a conversion is the main goal of a marketing campaign and advertisers need to see the exact action that drove the sale or installation. It’s also easy to use and it doesn’t require any sophisticated calculations.
  • Cons: contrary to the first touch, marketers here are missing data about nurturing of a customer. So all efforts on email campaigns, content strategy, retargeting approach, etc. are staying veiled.

Multi-touch attribution

Here, marketers get the whole picture of a customer journey by setting equal credit values to each step. So if a user saw an ad on Twitter, from there landed on the mobile web site of an advertiser, and after that redirected to the official Facebook group of the company, and then went to the app store to make a purchase — all these steps will be traced.

  • Pros: the multi-touch attribution is a powerful data-driven and app tracking tool since it ensures the visibility of all marketing channels that are used to make a conversion.
  • Cons: it’s not that easy to release it since it requires a solid knowledge background from a marketer. It also involves knotty calculations that can be a real chore.

Time-decay attribution

It encompasses the same touchpoints as the linear attribution, but the share of credits is different. In this case, the higher the credit rate the closer (in time) touchpoint from the conversion. The model fits perfectly for long-term marketing campaigns, so advertisers can get the entire picture of a customer journey and focus their efforts on the most conversion-driving touchpoints.

  • Pros: it covers all touchpoints with a bias on the latest touchpoints that often have a crucial decision-making influence. Hence, advertisers get real-time data about the whole purchase lifecycle with emphasis on the last stages.
  • Cons: depending on the goal of a campaign, the top and middle of a funnel might be more important rather than its bottom. For this reason, this option fits very specific campaigns.

U-Shaped attribution

Another web attribution implies diversification of credits among different touchpoints. Normally, credit for the first touch here is set at the rate of 40% that is equal to the last touch credit rate which also constitutes 40%. The rest 20% are evenly split between other middle points. It provides an understanding of what channel drives the most relevant audience, and which one is most efficient to make sales.

  • Pros: in many campaigns, the first and the last touchpoints are the most decisive so the U-shaped model is capable of coining crucial data about a customer journey for many marketers since credit values here have the appropriate accents. Still, it brings some understanding of the intermediary stages.
  • Cons: if a campaign has a goal of nurturing a customer, this option will underestimate the middle part of a journey that normally contains core data for that purpose.

W-Shaped attribution

It is very similar to the U-Shaped mobile app attribution but it assigns a 30% credit rate between the first touch, lead conversion stage (when a prospect becomes a lead), and last touch. The remaining 10% are distributed to all other touchpoints that took place in a customer journey. With this mobile app tracking, advertisers get a deeper understanding of the impact of intermediary events rather than with a U-Shaped model.

  • Pros: a very useful tool for B2B marketing that already has a plain funnel picture so the business owner knows what stages his buyers are passing through. It shifts attention from auxiliary channels to the main one(s), thus helping to define where the audience comes from, at what middle stages it turns into leads, and see what last actions affect them best to make a purchase.
  • Cons: It’s not very suitable for B2C mobile marketing that has a short cycle of a user journey as it is designed for long-term campaigns. Also, if a marketer needs to learn more about a user’s behavior outside of the first, middle, and final steps, this is not the way to go about it. Plus, this model is a bit tricky, so not everyone will be able to handle it.

View-through attribution

This attribution solution allows you to detect users who watched an ad but didn’t click on it. However, after a while this user searches, let’s say, for a mobile app that was advertised and eventually installs it. If so, view-through will be counted, let’s say by Google. In this way, this attribution helps to measure conversions that have a time gap between seeing an ad by a user, and ultimate installation.

  • Pros: this mobile ad approach provides extra data points regarding the efficiency of impressions which is usually based on clicks. Here, advertisers can include into their reports some impressions that weren’t clicked, still, delivered a sale.
  • Cons: count of conversions has a time limit. For instance, Google has a 30 days time frame when view-through conversions are effective. So if an ad was seen on January 1, and the targeted action (app install, sign up, etc.) was made in the middle of February, it won’t be counted.

Choosing web attribution model

Now, when advertisers are aware of such a cluster of mobile app attribution models, the next logical move is to find out which one to pick. In nutshell, there are three general questions that a marketer should answer to make the right decision. This stage is pivotal as adjusting the underfitting mobile attribution concept most likely to turn all marketers’ efforts in vain. Let’s have a look at what’s on the agenda here:

What are the marketing goals? Despite the ultimate purpose of any business is to drive revenue, to achieve that, marketing campaigns often pursue different outputs. This can include:

  • creation of strong brand awareness
  • leads generation
  • driving conversions

A clear understanding of the goal(s) will indicate what data points and subsequently what part of the funnel (top, middle, bottom) marketers should stick to and what channels to use.

What kind of business are you? Usually, mobile marketers are divided into B2B and B2C. While B2B commonly performs omnichannel marketing, B2C is less diverse here. So in the first case, the linear attribution model can be the clue, and as to the second type of business, the last touch concept should make sense.

What is the lifecycle of conversion? Long-term sales lifecycle have a good odds to bring value to advertisers by running Time Decay attribution. As to the short-term, such a business can benefit from single-source attribution mobile options.

choosing mobile attribution model

Challenges in mobile app attribution

Mobile attribution is a sophisticated area comprising complicated algorithms, technologies, and infrastructure. Bad actors follow the money, so mobile ads are subject to fraud problems. Fake mobile app installs are one of the most popular types of scams when mimicking a real user, bad actors are making iterative installs and get credits for that. To minimize such a risk, advertisers should partner with reliable tech providers that use in-house anti-fraud tools, or that use services of external anti-fraud agencies.

Another challenge for ensuring safe mobile attribution on devices is that iOS and Android operating systems are two completely different environments which is why marketers have to deal with specifics of each of them. Add to that a multiplicity of device types that support different creative characteristics and mobile ad sizes. Also, there are sundry of identifiers which all in all creates a fragmentation challenge.

As we can see, there are a lot of concerns within the attribution model, but mobile app owners and tech providers are constantly working on the development of fraud resistant measures, improvement, and optimization of the operational environment making a worthy backfire on fraudsters.

Since Google has announced its intention to phase out third-party cookies by 2022 in terms of its Privacy Sandbox initiative, the world of digital advertising felt somewhat strained. The decision to develop new app tracking solutions has been explained by a desire to bring next-generation privacy on the web.

Indeed, according to a Pew Research Center study, 72% of Americans suspect that the vast majority of their actions online are under the monitoring of advertisers, technological companies, or other agencies. At the same time, 81% of respondents believe that potential risks from the collection of their data by companies are higher than benefits.

At this point, the digital advertising industry is on its way to shift to new realities and creating new solutions to identify users. As to Google, in its recent announcement, it has stated that the company will cease user-based identification once third-party cookies that are representing mobile ad attribution roles, will fade out. As an alternative, they will perform cohort targeting with their new FLoC technology.

Since Apple’s IOS 14 and IDFA canceling are around the corner, the tech behemoth has been developing its proprietary solution —SKAdNetwork. Its API allows marketers to run campaigns and simultaneously ensure user privacy. The solution requires three participants:

  • Ad networks
  • Source apps
  • Advertised apps

Details of this model Apple has outlined in Registering an Ad Network and Configuring the Participating Apps official documentation. The mechanism of work looks like this:

mobile attribution skadnetwork

The Bottom Line

Within the global digitalization boosted by the pandemic crisis, more and more people go mobile. Today, with the help of mobile devices, people can find almost everything they need for their day-to-day life. Mobile phones are serving as one of the key communication gadgets and sources of entertainment. Advertisers understand that they should follow the audience as it's an infinite market for any business vertical. Answering the question of what is mobile attribution for marketers, it’s fair to say that it’s a powerful revenue-driven area that ensures an efficient operational environment within a multi-billion market.

Today a state-of-the-art mobile advertising mobile DSP can provide comprehensive options to target the most relevant audience precisely. When attribution models are calibrated well, success is a matter of time as practice shows. SmartyAds DSP has been successfully connecting businesses of diverse industries with their audiences by virtue of programmatic targeting. Our DSP solution helps companies to achieve their strategic marketing goals due to efficient ad campaigns and their precise attribution.

Measure and adjust your mobile ad campaigns effectively on SmartyAds DSP.

Written by
Irina Kovalenko, CMO of SmartyAds
March 2021