VK Activator Stats – Part 3
Because it seems I have nothing better to do, and people are interested, I decided to dig a bit deeper into the retention/churn dimension discussed in the last post and continue the analysis started here. At some point I’ll actually get around to updating my blog with tales of my own activations, rather than data on everyone elses 😀
First, let’s define a new activator as someone who has their first activation in a particular year. Let’s then define an old activator as someone who has had their last activation in a particular year. By definition, this is taken at the end of the year, so for 2017, there are no old activators yet.
Unsurprisingly, there’s a big increase in new activators early in the SOTA program’s history in VK, and once we hit 2015, this rate slows down dramatically, and is overtaken by people who have, by our definition, ‘left SOTA’.
I acknowledge that a person who last activated in 2016 and hasn’t activated in 2017 yet will be counted as an old activator, but 7 months of inactivity isn’t an unrealistic definition, and so I am comfortable with the statistics as they currently stand.
From this, we can calculate net retention rates. I’ve chosen the new year as an arbitrary cutover date of our ‘subscription’, but while this analysis could be done for any particular date, I’m pretty happy the results will not dramatically change the analysis.
To calculate retention, we take the total number of activators last year, then calculate the total number of activators at the end of the next year. This is last year’s figure, plus the new activators this year, minus the old activators. We compare the ratio of this year to last year to get our retention rate.
As can be seen, a steady decline, with a little bit of noise in the data. This one is probably the more concerning one for me given the long term trend. No analysis has been performed on why, but the original post speculates.
I was then asked by Grant VK4JAZ about splitting by association. This isn’t easy as people can change association, but based on their stated “Home Association” in the database, the stats are as follows:
From these, and using the same methodology above, we can track, by VK association, the total number of active activators:
This suggests that, apart from VK7, all associations have seen decreases in activators and activity since each association kicked off. It remains to be seen if this could be called a plateau, or if it’s a genuine decrease. The retention rate figures suggest its a decrease.