NPS
Some handy snippets for calculating NPS and accuracy.
[nps]
((promoters/total )  (detractors/total))
[nps_var]
((1  [NPS]) ^ 2 * promoters/total + (0  [NPS]) ^ 2 * neutral/total + (1  [NPS]) ^ 2 * detractors/total)
Suggested Usage:
select npsdate , total as sample_size , [NPS] as nps , (sqrt([NPS_VAR]) / sqrt(total)) as moe2 , (sqrt([NPS_VAR]) / sqrt(total)) as moe , [NPS]  (sqrt([NPS_VAR]) / sqrt(total)) as moe_lower from ( select [created:aggregation] as npsdate , count(1)::float as total , count( case when recommend <= 5 then 1 end )::float as detractors , count( case when recommend > 5 and recommend < 9 then 1 end )::float as neutral , count( case when recommend >= 9 then 1 end )::float as promoters from your_nps_survey_table group by 1 ) as respondents
You can use moe_lower, moe and moe2 to show error bars on results. Make moe_lower the same color as the background.
Like
Follow
3
7replies

Two things I've found valuable in using NPS are:
 reporting it as a 30 day rolling calculation (i.e. for each possible date, calculate NPS based on all survey results in the previous 30 days)
 the above, but with segmentation (e.g. for our product based on customer size)
You see some seriously interesting things looking at it this way, especially with the segmentation.Reply