Ok, done. Thanks. Impact-adjusted numbers are fairer, since that is what you are actually targeting, though there is some subjectivity in the impact adjusting process.
Thanks. It’s not so much that it’s a matter of what we’re targetting—I think some of these plan change are more than 100x more valuable than others. If you take the raw number of customers a company has, when some customers spend 100x more than others, the total number of customers could look good while the business is actually shrinking. Our raw plan change figures are dominated by the smallest, least important plan changes so could be quite misleading in future.
I strongly recommend using the impact-adjusted plan change metric rather than the unadjusted one for 80,000 Hours. Those figures:
Sep 2014 to Aug 2015 − 184.8
Sep 2015 to Aug 2016 − 631.3
Sep 2016 to Aug 2017 − 1202
There’s also our newsletter growth. New subscribers each year:
2014 − 262
2015 − 23,000
2016 − 76,000
2017 so far − 57,000.
Ok, done. Thanks. Impact-adjusted numbers are fairer, since that is what you are actually targeting, though there is some subjectivity in the impact adjusting process.
Couldn’t you put in both types of data so readers can draw their own conclusions?
Thanks. It’s not so much that it’s a matter of what we’re targetting—I think some of these plan change are more than 100x more valuable than others. If you take the raw number of customers a company has, when some customers spend 100x more than others, the total number of customers could look good while the business is actually shrinking. Our raw plan change figures are dominated by the smallest, least important plan changes so could be quite misleading in future.