Appsflyer is mostly used to get events data and real-time events data and tracking and reporting.
Real-time attribution is one of the reasons Appsflyer stands out. It supports click-through, view-through, and other attributions. We also track installed events and conversions across multiple channels. You also have live dashboards. All of these are good features.
Appsflyer has this cross-platform feature, which I liked.
Since it's known, we have onboarded pretty big clients and they really prefer Appsflyer over other alternatives.
Two points I've deducted from Appsflyer: one for reporting, which could give more insights and more access to raw data and events. The other point would be that many times we run into problems, and Appsflyer tech support is a bit hard to reach. If it's easier, I think that would be better.
The main factors I consider when evaluating attribution solutions like Appsflyer are features and reliability. Data accuracy and integration are basically the most important factors, and capability to measure performance across multiple channels is crucial. I also look at how well the platform integrates with different networks and tools, especially when we run across multiple channels. Real-time reporting and post-install events are important. Having features like fraud protection, privacy compliance, and others is good. Pricing is also considered, but for our performance-driven campaigns, accuracy and scalability are a higher priority.
Appsflyer has a positive impact on teamwork because it has a single source of truth that teams can rely on. Any of the teams can access the same data which reduces discrepancies. The dashboards and reports can be shared, which also makes collaboration easier.
From a programmatic perspective, Appsflyer is one of the more reliable platforms when it comes to cross-channel management. It's strong for enterprise-level use cases and integrates well with other traffic sources, which is very important for our setup. Compared to other tools, it offers more robust post-install tracking and better scalability. However, it's less flexible in terms of custom reporting and onboarding new users requires more time due to the depth of features. Privacy limitations, especially with SKAdNetwork, also affect the level of detail available for optimization.