Human Interaction Through Analytics
30 March 2015
With social media, we have more people to talk to than ever and more ways to talk to them. However, our bigger networks do not translate to more meaningful social interactions. Everything we share is carefully curated and censored to show only what we think makes us look our best to the network we’re sharing with, removing spontaneity and authenticity from how we interact.
As our interactions become less genuine, we feel increasingly lost in the crowd and we get lonely. We expand our friend lists and gather followers to make up for feeling lonely, but this doesn’t make up for the human element that we’re losing. No matter how many hashtags we add to our posts, how much we post ourselves all over our profiles and other people’s profiles, we still can’t achieve the genuineness of speaking in person and being heard that we as a species need.
To counter the feeling of not being heard, we seek out statistics that make us able to feel like we’re getting noticed. The first manifestation of the desire to know if the Internet heard us was the Geocities era visitor counters that were worn at the bottom of personal websites as badges of honor. Another indication of the demand for analytics was the spam that appeared in our Facebook news feeds a few times a week promising statistics on who viewed who’s profiles, which got clicked and shared repeatedly.
Analytics are certainly not new — Urchin (eventually Google Analytics) came about in 1997, and they were not the first solution. Businesses have long been using analytics to make their websites better to better serve their visitors and improve their bottom lines. It comes as no surprise that various providers stepped up to provide more powerful tools on the end where money was involved. On the consumer end, there was little money to be had so there was little reason for providers to step up and provide the same services.
These days, those of us who run our own websites or otherwise administer web properties have our pick of a variety of tools and can keep track of huge amounts of information about our content and our visitors; everything from where they are, to what kind of computer they have, to the interests Google thinks they have, far beyond the basic visitor counter. However, a large portion of the online community doesn’t run their own web property, and thus doesn’t have the ability to make use of such tools. Social media is slowly catching up and services such as LinkedIn and Twitter now offer various statistics about personal profiles and others are sure to follow.
Why the demand for analytics? Most people are not monetizing their web content and aren’t looking to improve their bottom line. As we feel less noticed since posting to our growing groups of followers is equatable to throwing papers into the wind, we crave more connection.
Over the majority of sites, other than direct interactions with our posts as “likes” or comments or similar, we have no way of knowing that the words we threw into the cyber wind were noticed, much less that anybody actually cared. Statistics give us another piece of feeling as though we interacted with people — they show us that maybe, just maybe, we were noticed. It allows us to think that at least some of our connections might be listening, similar to how having huge networks makes us think we have a lot of people to interact with.