The global pandemic has significantly boosted mobile app usage, with the latest figures showing that global app downloads reached 37.8 billion in the second quarter of 2020 – 9.7 billion higher than the same period in 2019. People are also spending more time on social media. A GlobalWebIndex survey shows a rise of 10.5 percent in social media usage in July this year compared with a year ago.
To ride the wave of growth, marketers engaging in app install advertising will want to prioritize social media and paid search platforms. But to ensure the best return on advertising spend (ROAS), you need to target users who are most likely to engage with your ads. By leveraging AI-powered predictive segmentation and keyword targeting , you can boost your chances of reaching and converting those users.
Once you know your target audience, you need to figure out how much you want to spend on each campaign and ad in order to meet your goal while keeping your cost per install (CPI) down. As technology advances, using data and artificial intelligence (AI) might be your best bet to maximize ad dollars and optimize campaign management.
The Key Challenges of Ad Campaign Management
One of the biggest challenges when it comes to app install advertising campaigns is that they can be incredibly complex to manage. This is because ads are typically run across multiple paid search and social media platforms, including Facebook, Apple Search and Google Ads.
With ads running across multiple platforms, each with their own parameters, it can be tough to monitor campaigns manually 24/7 and figure out which are performing best. This can lead to burst volume or spending and make it hard to optimize budget allocation.
Why the Traditional Ways Don’t Work Anymore
Traditionally, marketers need to manually allocate budgets across different platforms and handle multiple campaigns and ad groups on a daily basis. It also means fine-tuning campaigns based on report analysis and personal experience.
Even when carried out by the most astute marketers, the process can be time-consuming. There is also a lot of trial and error involved in different operational adjustments, such as bidding prices and creatives.
Deciding how much money to allocate for each platform and each ad set after the segments are determined requires constant attention, otherwise it could easily lead to budget waste. For example, you want to put a small ad budget on each ad set, wait to see how many installs they generate, and then decrease or increase the budget accordingly.
Budget automation features on platforms such as Google Ads are designed to help. However, the automated rules used by Google Ads are also based on manual decisions, meaning they have their limitations.
How Smart Budget Management Driven by AI Can Help
To overcome those issues, you can use AI-driven campaign management tools to remove the trial and error involved and predict ROAS to optimize your budget allocation across both individual ads sets and multiple search and social platforms.
1. AI ad set prediction
In order to optimize your ad spend, you first need to set a target KPI and volume for AI to predict how much volume and CPI each ad set can generate for you every day. Based on that prediction, AI can then allocate the right percentage of the daily budget to each ad set.
As your campaign begins to run, performance data from each ad set is sent back to the AI every hour to reinforce the model, and so AI can use the latest data to make new predictions for continuous budget optimization.
2. AI platform prediction
In addition to predicting the volume and CPI of each ad set, AI can also determine your daily budget for each platform.
For example, if your daily budget is US$500, at the beginning of each day, AI will take into account the performance of the previous day, as well as the previous week and month, along with the current burn rate to determine whether to allocate more than US$500 on that day and exactly how much for each platform.
Ultimately, AI can continually determine how much budget you should put on each platform and each ad set in a transparent way to reach the overall CPI and volume target. It is able to do this much more effectively and efficiently than a human ever could.
Ensuring efficient app install ad spend is crucial for driving downloads while keeping your CPI down. AI makes this not just possible but easier by turning trial and error into a data-driven science.
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