This is the subhead for the blog post
When attempting to understand performance across all of your marketing initiatives, it is important to have the flexibility to view data that answers existing questions and develops new inquiries. In order to accomplish this, the underlying data must be both all-encompassing and granular. Once this robust dataset is gathered and cleaned, there are many ways in which to present the information.
While it is good to have choices, too many options can become confusing, making it unclear which visualization to choose. Therefore, the development of data visualization starts with one question: What is the end user trying to accomplish?
There are two tasks that rarely fit well into one view, and it is important to choose between high-level aggregation and deep-dive analysis. Clearly, if the goal is to dig into the data, a limited view is not going to allow for robust analysis. Conversely, if the goal is to get a quick snapshot, granular data with multiple filters can create unnecessary noise that will increase the time it takes to find an otherwise quick answer.
When to Use High-Level Aggregation:
- When attempting to quickly view data across channels, a snapshot of marketing programs allows for a general look at total performance.
When to Use a Granular Analysis Tool:
- When attempting to dig down into the data and understand the exact cause of high-level changes, an analysis tool will identify exactly where optimizations should take place.
The best option is to use these two approaches in tandem, starting with an aggregate view that identifies items in need of investigation. A good visualization will then lead you to the granular analysis tools, and allow you to pinpoint the cause of high-level anomalies. Multi-channel reporting is powerful only to the extent that data can be tailored to the end user. It must balance between not doing too much while allowing for deep-dive analysis if necessary.