Join David Booth for an in-depth discussion in this video Understanding where data comes from, part of Up and Running with Adobe Reports and Analytics.
It's going to pull things like the URL that was loaded, the timestamp of when it was loaded, information about the device, the browser, the screen, the IP address. Basically, everything the browser knows about will be collected and sent. And this happens on every single page view and depending on your implementation, more data may be getting sent back to Adobe even within a page view when key things happen that you want to track. Once all that raw data is there, Adobe will process it and store it for you so that it's ready to be accessed.
When you log into Reports and Analytics, the web interface that you're looking at is using all of that processed data to create all the pretty charts and graphs, and reports, and other visualizations you're asking for. Adobe Analytics can also integrate data that comes from different places. And one way your implementation team may have chosen to do this is through what are known as data connectors, which use to be called genesis integrations. Adobe's data connectors help integrate dozens of other third-party solutions and data sources, ranging from ad servers and email providers to video players, surveying tools, and more.
They'll navigate away from a page before the code is finished executing. Implementation teams will make mistakes. And a host of other things can happen. And this is not unique to Adobe Analytics. It applies to any and all web analytics packages that operate this way, which these days, is pretty much the majority, because of all the benefits of this approach. But the good news is that with a proper implementation, only a very small percentage of data should ever be impacted. And the even better news is that when we do analysis, we're much more interested in trends and patterns than we are raw numbers anyway.
To put it in perspective, for e-commerce websites, a good rule of thumb is that you should be within at least 95% accuracy against your system of record. And hopefully better than that. So while you should never do your accounting or pay your taxes against your web analytics data, you can certainly be confident in the decisions that you make based on it.
- Understanding conversion and traffic variables
- Using metric and item-level reports
- Building and sharing dashboards
- Creating and using calculated metrics
- Setting targets and alerts
- Working with ecommerce reports
- Tracking campaigns and leveraging marketing attribution
- Getting data into Excel with Report Builder