Why Digital Analytics Have Become so Complex

There are many truly fascinating things happening in the world of analytics. Today we can pretty much measure everything, in theory, and the number of data points has exploded in recent years.

But while we have more and more data to work with, we have also started to realize that we have a big problem. More data doesn't lead to more insights. In fact, today's analytics are both confusing and misleading because we attribute value to specific metrics without realizing the mismatch and the lack of context.

Many people blame this on how ridiculously the digital world works, and the huge amount of intentionally misleading metrics that we see every day. Like the view metrics on social networks, which have almost nothing to do with a real view.

And while there are a lot of problems with how we do things digitally, the main reason our analytics is so confusing is simply because it has grown up. Digital analytics isn't as innocent as it once was when everything online was simple. Today, the digital world almost entirely mimics how everything else works in the real world. And think about how impossible it is to do good analytics there.

Let me give you an example.

Think about how you would measure a retail shop located at a premium location with a ton of outside foot traffic. And ask yourself this:

• How many people are walking by your store every month?
• How many people glance in the direction of your store windows?
• How many people actually realize what they are looking at?
• How many people connect that with an interest?
• How many people are actually influenced by it?
• How many people stop to take a look at what you have to offer?
• How many people translate that into a real intent?
• How many people walk into your store?
• How many people decide to buy something?

 

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