Hello, since I saw this post, I switched a couple of things to using ACSI. I always thought NPS seemed pretty bad, and mostly only included it for comparison with groups like CEA who were using it.
Do you have any data you’re able to share publicly yet?
Additionally:
The American Customer Satisfaction Index is an alternative which has stronger empirical grounding, as well as a huge number of publicly available benchmarks. It uses 3 questions, on a 10 point scale, whose scores are averaged and normalized to a 0-100 scale:[1]
How exactly are you calculating it? The Wikipedia formula seems wrong to me, unless I’m misunderstanding it.
(I have 9 answers for each of the three questions. The average responses are 9.4, 9.6, and 9.3. So I think what I’m supposed to do is =((9.4*1+9.6*1+9.3*1)-1)/9*100 . This gives me “303.7037037” which clearly seems wrong.)
My interpretation of what it should be:
=(((9.4+9.6+9.3)-3)/27)*100
Which equals 93.8. The simpler but slightly less accurate =((9.4+9.6+9.3)/3)*10 comes out similarly, at 94.4.
(Caveat that I didn’t realise that you were supposed to include labels on 1 and 10 for each of the questions until I checked the Wikipedia entry just now to calculate it, and I’m not sure how this would affect the results. The labels seem pretty weird to me, so I suspect it does affect it somehow.)
Hello, since I saw this post, I switched a couple of things to using ACSI. I always thought NPS seemed pretty bad, and mostly only included it for comparison with groups like CEA who were using it.
Do you have any data you’re able to share publicly yet?
Additionally:
How exactly are you calculating it? The Wikipedia formula seems wrong to me, unless I’m misunderstanding it.
(I have 9 answers for each of the three questions. The average responses are 9.4, 9.6, and 9.3. So I think what I’m supposed to do is =((9.4*1+9.6*1+9.3*1)-1)/9*100 . This gives me “303.7037037” which clearly seems wrong.)
My interpretation of what it should be:
=(((9.4+9.6+9.3)-3)/27)*100
Which equals 93.8. The simpler but slightly less accurate =((9.4+9.6+9.3)/3)*10 comes out similarly, at 94.4.
Which seems very good. E.g. “Full-Service Restaurants”, “Financial Advisors”, and “Online News and Opinion” all seem to hover around 70-80, while government services range a bit more widely from 60 to 90.
(Caveat that I didn’t realise that you were supposed to include labels on 1 and 10 for each of the questions until I checked the Wikipedia entry just now to calculate it, and I’m not sure how this would affect the results. The labels seem pretty weird to me, so I suspect it does affect it somehow.)
Thanks!