Digital marketing is an uncertain environment. Apart from the new channels and modes of interaction with consumers, there's also the ability to record, measure, and report on everything. From mouse clicks to Facebook chats, everything that happens online is recordable, measurable, and reportable. If we didn't know it before (and most of us did), a number of intelligence agencies have shown us that recently. Since we've now entered the age of big data and data mining, there are good reasons for recording and processing as much information as you can. However, no human organization can possibly use, or even want, all of the data all of the time. To misquote a great man, "You need some of the data some of the time, but you never need all of the data all of the time."
I discussed this with Bryan Eisenberg, one of the fathers of web analytics, who has expressed similar concerns in his "Smarter Data Manifesto." He said, "Don't measure anything that you can't find a direct line of sight back to your financial statements. You manage by what you measure so focus on those things that affect the bottom line directly and over the long term (brand metrics)."
What you need or don't need is going to depend on your objectives, which will in turn determine what actions you take. So it's axiomatic that you shouldn't measure stuff you can't do anything about. Don't measure form performance if you're not going to change the form, and don't measure Facebook activity if you don't have a Facebook campaign. In addition, there are a few things that people like to measure that are a complete waste of time no matter what your objectives are and no matter what you can action.
Social activity is the most blatant area of difficulty. At the foundation of web analytics is a void we can never fill. We can never really know what sort of person is behind the behavior web analytics records because people don't visit websites, devices do. If you have a look inside the data your web analytics system is recording, you'll see that the "people" it counted were really just IP addresses and system identifiers. You hope that system was being operated by a human, but you can't tell. You hope it was just one person, but if people swapped over in the middle of the session, you'll never know. It's also possible that there was no person behind the device. There are plenty of robots out there driving browsers now.
These robots have always been around, but it's never really been a major problem before now. Before the days of social media, there wasn't much to be gained by writing a program that pretended to surf the web like a person. However, these days, poor web analytics practice has created an entire industry designed just to serve up useless data. The problem stems from counting volume without any reference to quality or segmentation. The vast amount of traffic on the web disguises how varied the mix is within that volume. Raw totals are rarely of any use. The lack of detail disguises so much that they might as well be completely wrong.
I am going to suggest five things you can stop measuring. By all means continue to gather the data, but don't bother reading the reports. These are the popular metrics in social media and search marketing that people spend a great deal of time and money chasing, even though they are a total waste of time.
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Thank you! I constantly ask our clients "did that 'Like' convert or generate into a sale?" If not, then we're simply posting to satisfy our human need for acceptance. ;)Stephen@ashaymediagroup
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