Within the context of a global economic crisis and the post-Covid digital cooldown, app developers need to engage with innovative mobile UA strategies to stand out from the crowd and make it through the crisis.
In mobile user acquisition, advertisers must know where to concentrate their investments, and where to allocate more budget depending on the most effective campaigns, channels, ad platforms, and other sources. One of the essential steps, therefore, consists in tracking the performance results and campaign trends. In other words, it has to do with monetization metrics.
Considering the new challenges that the digital market is going to be faced with in 2023, it will be even more important for advertisers to keep relying on metrics and measurement despite «the privacy tidal wave» that has been striking the market since the summer 2021.
After going through monetization metrics, we are going to discuss a bit why measurement of monetization metrics is even more important today than it was in the past and how it has changed within a privacy-shaped digital ecosystem.
Monetization Metrics to enhance your mobile UA strategies
First thing first, monetization metrics allow you to understand if you’re earning some profit from your advertising spend, and whether your paid efforts have been worth the spent. Before diving deeper into them,we need to bear in mind that differences can be very subtle, but not least important. In this paragraph, we are going to discuss them in relation to LTV vs. ARPU, and ROAS vs. ROI, to avoid confusion and clear things out.
- LTV and ARPU
LTV (Life-Time Value) is a core monetizationn metric that calculates on average the revenue generated by a single app user during their lifetime within the app. It helps advertisers know what to expect in terms of profit and users’ behaviors for any single app install campaign. For this reason, LTV is proven to be a key optimization tool for your campaign providing marketers with a clear outlook of the available budget to allocate to their mobile UA strategies with no risk of money squandering.
On the other hand, ARPU (Average Revenue Per User) estimates the average revenue generated per user or unit within a limited time frame. ARPU does not consider the whole time a single user engages with the app, as LTV does, but just a limited period. It can be helpful to determine whether your paid mobile UA strategies are profitable or not.
By comparing the average revenue per user generated within different UA strategies and ad networks, you can determine whether you brought in high-quality users. In other words, those who are more likely to generate revenues by carrying out in-app or post-install events.
- ROAS and ROI
How do you get to know if your paid efforts on your mobile ua strategies are worth it? ROAS (Return on Ad Spend) measures how much revenue an ad campaign generated by allowing you to calculate the performance of digital advertising spend.
Once you have set your CAC (Cost Acquisition Cost) and your KPIs, you can achieve your ROAS by using A.I. and machine learning algorithms. It can be established also by comparing the total spending for a given app install campaign with LTV.
How does ROAS differ from ROI? The former calculates the net profit by measuring the return on a particular investment against the cost of that investment. In this sense, ROI (Return on Investment) serves to estimate the long-term profitability of your mobile UA strategies. Conversely, ROAS is more apt to optimize your mobile UA strategies from a short-term perspective telling whether your app install campaigns are contributing or not to the overall profit.
Why do you need to count on metrics for your mobile U.A. strategies?
According to a study by Appsflyer, to deal with «the perfect storm» in which advertisers may find themselves in 2023, digital marketers must achieve two new priorities: «stability and profitability».
As we said in the introduction, the global economic downturn – resulting in a different focus from growth to profitability- may affect advertising spend. For this reason, they require greater accountability on ROI and heightened scrutiny of marketing business.
ROI, LTV, and ARPU still matter and will matter in 2023. Indeed, mobile U.A. strategies will still depend on the volume of users they acquire. Moreover, the desire to improve revenues generated from users comes from the necessity to increase ROI. All the more so because of the global economic outlook.
How to combine measurement with privacy rules and boost your mobile U.A. strategies
Since the summer of 2021, we have also witnessed the impact of Apple’s privacy-driven policy regulations on mobile UA strategies. Indeed, new privacy rules may have limited the efficiency of measuring monetizatio metrics and mobile UA strategies depending on the collection of data about users’ behaviors.
Considering the central role of metrics in setting up a successful campaign, it is worth wondering: can advertisers keep measuring effectively under this «privacy tidal wave»? Yes, they can but there are some specifics we need to consider first:
· Measuring ROI in 2023
Measuring ROI and demonstrating its incremental value will be of core importance in 2023 to optimize your budget. However, it will not be as immediate as it was before. For this reason, advertisers need to recur to testing operations, geo holdouts, and using MMM (Marketing Mix Model).
· What to do in the post-ATT age?
With the App Tracking Transparency, (Apple's policy requiring all iOS apps to ask users for their consent to share their data), it will be necessary to conceive a new measurement framework to let marketers adapt to this new privacy-driven landscape and welcome the change as an essential part of the ecosystem.
It still will be possible to drive efficient advertising campaigns, but testing and iterating will be essential, as well as the use of MMP’s attribution data, SKAN data, MMM, to assess their campaign’s results by funneling all their data sources into a single platform.
· Contextual Targeting
Embrace the move from behavioural targeting to contextual targeting for apps where ads are displayed to users only based on the actual context of the apps. The context may not depend on the content, in the case of web pages, but on the device itself, the time and language, the app category, and the session inside the app, the internet service provider as well as the operating system.
Such an amount of data may strike us as not being enough for efficient mobile UA strategies. In this context, where data availability decreases more and more, machine learning algorithms play a fundamental role in optimizing campaigns through contextual targeting. AdTech companies have been able to develop technology algorithms that can target the exact users even with fewer data without increasing the costs but optimizing your app campaign as efficiently as possible.
To conclude, it seems that creativity, flexibility, and resiliency may be key attitudes for marketers and advertisers to successfully face 2023 challenges.