Social media influence : Pharma benchmarks Klout-Kred-Tweetlevel

“To be influential is not to be popular”: Benchmark of Influence for Pharma accounts 

Last few months, different metrics capturing socialmedia influence have become more available. Klout , Kred , Tweetlevel Edelman, [3] measure through complex calculations, the influence of social media channels linked (or not) to socialmedia accounts. For the twitter channel, comparison could be interesting to see how these different metrics correlate for physicians and for pharma companies actives on Twitter.

Although some scoring indicators such as Kred and Tweetlevel includes several dimensions, I kept my primary focus on “Influence” (my long time fav topic) scoring and compare them with simple indicators such as #followers. Do complex calculations provide more value ? In this post, I present results for pharma twitter accounts.

Nice correlation was obtained for most active Twitter pharma accounts, Novartis is outlying (Klout 67; Kred 768). Pharma Twitter accounts where supplied by @pharmacjw (courtesy of cegedim CSD). I added two pharma execs accounts John Pugh (Boehringer) and Dennis Urbaniak (sanofi) to the bunch, just to see how individuals performed against companies including their own. For TL influence vs Klout the correlation is less obvious. This could be due to Klout score taking into account more than the Twitter channel where TL is currently limited to the Twitter channel.  Novartis is outlying here also (Klout 67; TL 61). Both scores highly correlate with the numbers of followers (size of the bubbles) and to the number of tweets. Interestingly, John Pugh and Dennis Urbaniak are aligned either on Klout score or on TL Influence with. Well, if these metrics are to be trusted, social media is  social after all as individuals rank equally next to official corporate account. But again, the question would be how many of their followers are patients and not #PR or #marketers.


8 thoughts on “Social media influence : Pharma benchmarks Klout-Kred-Tweetlevel

  1. Bonjour M. Jourquin ,

    Suite à la lecture de cet article fort intéressant, je me permets de vous donner mon avis et poser une question !

    Concernant TweetLevel je pense que cet outil est très intéressant et il l’est davantage lorsqu’il est couplé avec un autre outil de mesure d’influence, comme vous avez pu le faire. Il existe également un autre outil se nommant Twitalyzer, beaucoup plus poussé (mais malheureusement payant pour certaines commandes si ma mémoire est bonne). Le connaissez-vous ? Si oui qu’en pensez-vous ?

    Egalement, votre mise en relation des différents outils sous forme graphique est très pertinente, serait-il possible de savoir comment l’avez vous fait (un outil, logiciel etc en particulier ?) ?

    Bien cdmt.


    In English (if it is necessary) :
    Hello Mr. Jourquin

    After reading this very interesting article, let me give you my opinion and ask a question!

    On TweetLevel I think this tool is very interesting and it is even more when coupled with another measurement tool of influence, as you have done. There is also another tool naming Twitalyzer, much more extensive (but unfortunately paying for some commands if I remember correctly). Do you know him? If so what do you think?

    Also, your graphics linking data of various tools are highly relevant, is it possible to know how did you do it (a tool, software etc. in particular?)?


    • Solene,
      Thank you for your comment,
      Measuring Online Influence from various indicators help us to have a more robust vision of the metrics.
      I am still wondering if these metrics are truely able to differentiate influential socialmedia accounts from popular social media accounts.
      I will answer via @email for your more technical questions.

  2. I think your interrrogation about these tools is very relevant, differentiating influential accounts (which deal with the subjects that we want to study) in contrast to popular accounts.
    However, it is quite ambiguous on the web since the influential people are more and more ordinary people! Thus, popular accounts can quickly transofrmer into account influencing … isn’t it ?

    • In the past popular people could potentially becoming influent (celebrity marketing), today indeed ordinary people can become influential without being popular. However, metrics used to measure influence on Twitter use the number of followers as one of the main criteria. For tweetlevel metrics, Influence and popularity index are often almost equal…

      • As the creator of TweetLevel can I thank you for including this tool in your research.

        I would like to stress that all the four metrics are established in completely different ways. What is interesting is that the primary metric – influence, has only a very minor contribution from follower count. In fact the majority of the score comes from the ‘Is’ or Idea Starter metric, broadcast to engagement ratio, trust and several other factors – all of which are transparent and explained in the about us section.

        It is there mere fact that we do not confuse popularity with influence that we are able to identify people who are important that would normally be ignored because of their low follower count.

      • Hi Jonny, Thank you for this valuable explanation. Is the metrics not more an estimation of the digital social capital rather than “influence”?

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  4. Pingback: Social media influence : Pharma benchmarks Klout-Kred-Tweetlevel | Digital Health Journal

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