Many restaurant owners can tell you, with decent accuracy, the revenue they expect in a given night based on how many customers are waiting for a table at any moment. The number of people in line is a leading indicator of revenue. And the restaurant owner who is that in touch with key metrics has more instinct than many large companies when it comes to their analytics.
When it comes to web data, organizations should think like the restaurant owner and look at the leading indicators. If it’s repeat traffic you want, what are the factors that drive repeat traffic? What kind of content, merchandising and promotions are likely to drive people back to the site over and over? And if you don’t know the answer to that question, you should re-think the way you set up data in your analytics system.
When it comes to analytics, be careful what you measure…and what you don’t. For example, if you are looking at repeat traffic make sure to factor out web site bounces because people who stumble upon your site accidentally and leave in 20 seconds are generally not the customers waiting in line at the restaurant. They are people who come to your driveway only to make a U turn. And you don’t care about the leading indicators for an unqualified audience. Sure, you’ll want to dig deeper and find out who they are and why they left so quickly. But when you factor out non-core traffic, the leading indicators that drive key metrics for the core traffic are more evident. (Because there is less noise in the data).
Leading indicators help you probe more deeply than high level metrics. They help isolate the things that can really drive your business and truly shed light on your web operations. Just be careful when interpreting data to distinguish between loose connections and things that, with statistical significance, drive those connections. That’s when art meets science. And in the world of analytics, that’s where to find the gold.