If you want to move your audience, then a whole lot actually…
The gold standard for analytics is “actionable insight;” how much smarter, faster, or efficient do we become when the right people get the right information in the right format at the right time?
General purpose analytics solutions are typically built to ingest anything and everything. “Adapters” translate data sources into a common (proprietary) analytics framework – and then the slicing and dicing begins! While obviously flexible, this approach only works if users have a safe and reliable means to collect (and deliver) raw data into their systems; with application analytics, this is rarely the case.
Recording applications “in the wild” is not an easy or simple task. In addition to the functional requirements to capture the right kinds of runtime telemetry, application instrumentation must meet a host of performance, privacy, quality, and security requirements as well – requirements that vary wildly by industry, use case, and target audience. …and, the demand for high fidelity application analytics has never been greater; you can thank the adoption of feedback driven-development practices coupled with the operational complexity of mobile and cloud computing plus the ever-evolving concerns around privacy and security for that.
So what’s a development team to do? Well, it turns out that there’s nothing new about having to record complex real-world events and then package them up to inspire and move audiences – media moguls and hit makers have been doing all along!
Developers, if you know you should be including analytics inside your application development process, I recommend that you take a page from the recording industry – it turns out they know a little something about the complexities of capturing user behavior across heterogeneous devices and in diverse settings (the only big difference is that they call their users “musicians”).
I've taken the liberty of condensing a post from a site dedicated to teaching the art and business of audio production and mapping it to the patterns and practices of effective application analytics implementation. You can see the original post at the recording process if you want to check my work.
The infograph below maps each step in "the recording process" to its app analytics analog. I've underlined key points in the original post and added my own take-away.