Would you like less users churning from your app and improved ROI from ad campaigns? Then you need to take advantage of mobile attribution. It is the process of tracking how users interact and engage with your app. This data is then used to improve the user experience, features, and cost-efficiency of mobile campaigns. As a matter of fact, it increases campaign ! performance up to 15-30% Don’t you want results like that? More and more businesses are for exactly these reasons. That’s great and all, too, but there’s a new problem to take care of as a result of this trend: false attributions. taking advantage of mobile attribution Every company that runs mobile attribution campaigns can be costing you serious money and user churn. needs to know what these are they Don’t know what false attributions are or how to avoid them? No problem, because today we’ll be teaching you everything you need to know if you keep reading. What are false attributions in mobile marketing? False attributions are errors in when data conflicts between platforms and users. This causes campaigns to attribute users to the incorrect step or app because of the wrong information being picked up. mobile marketing These incorrect attributions hurt the user experience because the customer isn’t being forwarded to where they wish to be. Furthermore, poor attribution costs advertisers more dollars and can cause damage if false data is taken as truth and used for marketing. Reasons for false attributions There are several reasons why false attributions can occur, to begin with. Understanding them will ensure that your company deters them before they happen, preventing damage to campaigns and the user experience. Here are some of the main causes to be aware of. Lack of IP uniqueness when fingerprinting While fingerprinting offers many benefits for the mobile attribution process, not measuring each individual IP address can cause serious problems. This normally manifests as fingerprinting losing accuracy as it interprets hundreds to thousands of IP’s as the same. Users sharing IP’s can then be falsely attributed like such: Think about public WiFi, for example. Users at airports or coffee shops downloading your app could easily be mistaken as the same individuals and attributed incorrectly like above. Double attribution Do you use multiple different ad networks to ? If so, you are very likely to become a victim of double attribution. run mobile campaigns This is when two different platforms don’t integrate with one another, so they aren’t aware if the other attributes a user. The result is both of them performing the same action, wasting ad budgets. Biased attribution When you work with an analytics company, they are usually either full-stack or strictly focused on attribution. The first type of company deals with everything from media buying to attribution and measuring campaigns. The second simply helps you campaigns and self-serve tools. set up mobile attribution Biased attribution can occur when full-stack companies gear towards a certain type of media or advertising based on their strategies and history. Fraudulent installs The total cost of . While security measurements, processes, and tools are becoming more advanced, there are always a few blackhats who slip through the cracks. ad fraud is expected to reach $87 billion by 2022 Since mobile attribution is normally based on CPI, or cost per install, fraud is possible when criminals use bots to mimic human and fake installations. Similarly, that are done through the equivalent of cookie stuffing. Fraudsters are able to misappropriate attributions through spoofed clicks and redirects with this method. there are fake installs Working with trusted ad networks and marketing platforms is a top-down approach your company can take to avoid these problems altogether. Additionally, it’s wise to have fraud specialists available for both prevention and resolving any issues you experience. Incorrect data from platforms Discrepancies between platforms and tools used for mobile attribution is another culprit for false attributions. This is because they can contain conflicting data which is sometimes as simple as timezone differences. Data in one period can spill over into another, causing campaigns to attribute incorrectly. If you outsource your campaigns, ensure the mobile PPC agency you work with has steps in place to avoid this. Final thoughts on false attributions Mobile attribution helps businesses keep more users on their apps and improve the ROI of campaigns, but false attributions have to watched closely to avoid pitfalls. False attributions are commonly caused by a lack of IP uniqueness, meaning each IP address isn’t fingerprinted individually. Many users are grouped up and attributed similarly as a result. Double attribution is caused when multiple ad networks or platforms are used and not integrated with one another. This causes multiple clicks for the same action to be recorded and taken out of the budget. Additionally, incorrect data such as time spillovers can occur. Lastly, you should only use major trusted networks to avoid fraudulent activities or biased attributions based on their own media. Be aware of these false attribution causes and you can look forward to mobile campaigns performing consistently over the long term!

Different

Keep

False Mobile Attributions: What Are They and How to Avoid Them

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

5 Ways Startups Can Grow Content to Rank Quicker

Using Data Attribution Comparison Table in Google Analytics 4

“When you judge others, you do not define them, you define yourself”. ― Earl Nightingale

What No One Told Me About Being a Product Manager at an Early Stage Startup

What Are Convolution Neural Networks? [ELI5]

Rules of Thumb for Software Engineering

5 Ways Startups Can Grow Content to Rank Quicker

Using Data Attribution Comparison Table in Google Analytics 4

“When you judge others, you do not define them, you define yourself”. ― Earl Nightingale

What No One Told Me About Being a Product Manager at an Early Stage Startup

What Are Convolution Neural Networks? [ELI5]

Rules of Thumb for Software Engineering

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps