Comments on: Excellent Analytics Tip #16: Brand Evangelists Index

By: Avinash, son blogue et son livre: l’art de rendre heureuse la blogueuse-groupie que je suis | Le blogue de Carmen Gerea

Mon, 02 Nov 2009 01:42:52 +0000

[...]
Quelque part en mars j’ai commenté un article sur son blogue. Brièvement, il présentait la problématique suivante : suite à un événement, on demande aux participants leur appréciation sur la prestation du conférencier/formateur. Comment utiliser les donnes recueillies pour évaluer la personne et éventuellement la recommander pour des événements futurs? Il propose une méthode pour calculer un Brand Evangelists Index (BEI). Pour les curieux, vous pouvez lire le tout ici (en anglais).
[...]

By: Chris Claxton

Chris Claxton — Tue, 23 Jun 2009 03:35:42 +0000

Avinash,

Interesting post. Having a background in finance, I agree with a weighted average method. I like the conversations this blog creates…Thanks and keep coming!

Chris

By: Tomas Kapler

Tomas Kapler — Fri, 17 Apr 2009 14:56:07 +0000

I used this first time i need to measure quality of presenters 10 years ago, i think it is obvious that negative score is negative (-) and positive is positive (+).

After some time i have improved it far more – some people are positivistic, some are negativistic. If someone who ranks everything 100% gives you 90%, you are poor. If you recieve the same 90% from someone who ranks everything else bellow 50%, you are great.

So i have calculated their ranks for all questions and then calculate their overal index, which i use to recalculate the real value of every of their rank (weighting values in statistic terms)

Also this cannot be used as the only measurement of presenter quality – if a Microsoft guy would present Microsoft on the Linux conference, he would definitely rank very poorly, even if he would be awesome.

By: Koushik C

Koushik C — Fri, 20 Mar 2009 18:05:42 +0000

Hi Avinash,

Thanks. I would do something similar to Carmen, but adopt a Likert 5 point scale:

1 – Poor
2 – Below Avg
3 – Avg
4 – Above Avg
5 – Excellent

Adopting this, I would calculate the weighted score as a percentage of the max possible score of 18×5:

Johny: (0×1 + 0×2 + 6×3 + 12×4 + 0×5) / (18×5) = 73%

So, the results we land up are:

Score
Johnny 73%
Will 77%
Chris 97%
Guy 60%
Brian 76%
Apple 76%

As you can see, the inference is similar to your own. Hope this helps.

- Koushik

By: Monday March 2nd Roundup |

Monday March 2nd Roundup | — Wed, 11 Mar 2009 02:25:24 +0000

[...] Avinash Kaushik notes that sometimes the way we look at numbers can give inappropriate results, and suggests instead a brand evangelist index. Its an interesting way of using the natural biases we have towards numbers to create better understandings of why a number matters. [...]

By: Martin

Martin — Mon, 09 Mar 2009 21:59:01 +0000

Really great post Avinash, above all a rallying cry for Analysts to do more than just pass the numbers on.

It is interesting to read through the comments and see a focus on the mathematics and older models to make the argument that what we have works well already.

That focus is missing your rallying call to action, to set higher standards, but unsurprising as our job is to focus on the numbers and less beyond.

Carmen's methodology reflects the core accentuate both the positive and the negative.

The top box score does not do the latter and in my opinion a shortcoming of that methodology (your main message here).

Love the debate, thanks for moving the conversation forward.

Martin.