I have a friend who is responsible for gathering & reporting all the stats for his company.Â In speaking with him, I found it interesting when he said â€śalthough stats are vital for reporting, they sometimes donâ€™t tell the full story of what really is going on.â€ť
Numbers donâ€™t report the in-between stages of the sales process, theyâ€™re only black and white, yes or no, conversion or no conversion.Â Numbers do an excellent job of showing trends and forecasting, but numbers are numbers and donâ€™t necessarily give us the whole story. The whole story is about people. He went on to say â€śif I could somehow find a way to track and follow the buying process from start to finish on an individual basis, that would be unbelievably powerful!â€ť
The power of being able to track and analyze individual buying behavior is relevant to your web site as well. There is always more story behind every web siteâ€™s analytics data. Wouldnâ€™t it be great to set a parameter after the fact, to filter out/focus in on, specific visitors by some specific behavior they took on your site so that you could dig into those individual visits one by one? You might want to set a filter to view all visitors who successfully arrived at XYZ page, what their individual visit/click process looked like in order to get some real insights into why the visitor behaved in a specific way.
OnTarget is the tool that allows me (and our other consultants) to easily analyze our clientâ€™s web sites in a way that no analytics program can. OnTarget is so vital in order for me to do my job effectively because it allows me to get individual insights into what my clientâ€™s visitors are doing on their individual visits.
I can look at a search term that sent visitors to my clientâ€™s site and actually see a list of all the individual visits that took place from that term. So instead of only being able to look at aggregate behavior that a search term brought to a web site, I can actually look at each individual visit separately. Sometimes averages lie, so I generally come up with a theory about behavior based on some of the averages, and then I always dig into individual trends to prove or disprove my theories. This helps me determine if changes need to be made based upon personal patterns, not an entire aggregate.
Having access to this information is as good as following a shopper throughout their buying process step by step, except that we don’t have to worry about the shopper’s behavior changing based on the fact that I’m following them. They have no idea that I’ve been spying on their every move!