Analytics at work
It has been about a week since my previous post on Linked In about analytics and big data. Let us see the analytics of that article and see what we can learn from it. In the last five days the readership has grown to ~100. Pretty good! Here is demographic information.
Most of them come from semiconductors, have product development in their title and are from Bay Area. These are impressive statistics. But they seem obvious since I am in semiconductor industry and live in Bay area. Another statistic is that 49% came through LinkedIn. This says a lot about the popularity of LinkedIn and probably 80% of this demographics are checking LinkedIn at least once a day. Now the kicker. For this look at the following chart:
This shows the longivity of my article. It peaked the day I published, but steadily declined after (btw, Oct 3rd and 4th were weekends). I can conclude that my readers lose interest after 4 days in my writing. Again, this is just one datapoint. But this itself give me some idea as to how often I should publish. Cool!
Senior Marketing Executive | Fractional CMO | B2B/SaaS Head of Product/Portfolio Marketing | Growth & Revenue Marketing | GTM Strategy | Tech & IT Innovator I ex-GE; ex-Cadence; ex-Synopsys
9 年How cool it will be if it actually told you how you are doing in comparison to other folks in your demographics - your industry , your area.... So that decision is not on you to make but you have competitive studies from various similar and no similar posts to compare and prepare you next article on as well !!! That is the power of analytics ... Just showing usage is one thing helping you make right decisions by - Comparisons and what if analysis is another.. Driving predictivity and optimized behavior through analytics is even cooler !!! That is what we are doing and doing differently at GE with our industrial Internet and with Predix - the cloud based industrial IOT platform !!! Driving outcomes through predictive and optimized analytics for our customers !!!