Like most of the bloggers for this site, I am active on Twitter. Over the past six years, I have tweeted more than 20,000 times.
Sounds like I have no life, eh?
Well, maybe, but do the math. I average about ten tweets per day. If you're trying to connect with others and occasionally promote a book or six, then that number starts to seem a little less extreme.
I often wonder about whether my tweets ultimately have any type of impact at all. After all, more than 70 percent of all tweets are ignored. Of course, my 140-character messages are relatively bland. I don't go all Justine Sacco.
It turns out that others wonder the same thing. To this end, in August Twitter announced the launch of a new dashboard that lets users understand the data behind their witty observations and social shares.
Here's some of mine:
Your Tweets earned 84.2K impressions over the last 28 days.
That's 14.2% fewer impressions than the previous 28-day period.
Lest I just stare at raw data and summary statistics, here are a few graphs:
Sure, this is all interesting, but it doesn't for a moment help me predict what will make an impact, much less how to go viral.
The Bigger Picture
I can't help but think this serves as a general lesson about dashboards. I have yet to see one that predicts what will happen with any degree of accuracy. For instance, iPad sales have recently stagnated, as has the entire tablet market. Who would have predicted that so early in its cycle? Even smart cookies who spend their days mired in Apple data have a tough time explaining this phenomenon.
In a perverse way, these types of anomalies make me feel better. If full-time analysts studying multi-billion dollar markets frequently get things wrong, how can I possibly understand why some of my tweets do better than others? I am reminded here of a quote from The Big Lebowski: Well Dude, we just don't know.
Simon Says
Dashboards can help us understand what's going on. To be sure, there's tremendous value in that. They fall short, however, when it comes to explaining why and ensuring accurate predictions.
Feedback
What say you?
