TV Audience and Tweets Flow: a great beauty or bigdata SLIP n.1 for marketing communication strategists (statistic)?

TV_Audience and Tweets: a big beauty or bigdata SLIP n.1 (statistic)?

After being awarded as the best foreign language movie (Italy) Academy Awards 20014, The Great Beauty, directed by Paolo Sorrentino, got an outstanding audience last week when it was broadcasted in Italy in TV prime time.

Comments and opinions about the movie apart (I would recommend to see it), providing trends and flows among social medias is getting more frequent every day. Few day ago, it has been posted by the Italian TV Network that transmitted the movie, a “statistic” (here) regarding the Tweet flows with the purpose to explain when twitters’ peaks happened as well as gathering the main influencers.

Accordingly to a third party analysis, twitters’ peaks happened at specific moments: 1) a meaningful sentence by Jep Gambardella, the protagonist, 2) when the Sabrina Ferilli (famous Italian actress) showed up in the movie with all her beauty and 3) at the end of the movie.

Very interesting. However, looking carefully at the charts (see figure above) I have noticed two things:

  1. Twitters’ peaks happen concurrently with a temporary decline of the TV audience (share). Thus, a correlation (negative) between peaks in Twitter and TV Share exists.
  2. The Twitters’ peaks and audiences’ downturns occur with a perfect timing: one each 30 minutes.

Since advertisements’ stops during TV shows, and radio broadcasts as well, are previously defined according to a specific TV time clock…

…well, I am wondering: Is there also a cause-effect relationship between advertisements’ stops during TV programs and the peaks registered in Twitter?

Who knows. An answer should be provided only analyzing data and real facts carefully. For example, why not putting chips in our home that register and transmit also when the refrigerator has been opened to bring something to eat or even when a WC has just been flushed? Other stimulating correlations might be found by gathering such kind of data.

Anyhow, finding correlations it’s quite easy. Just observe what happen. Finding causation relationships is definetely much more tricky (see also BigData S.L.I.P.S. n.1: statistic) since a deep knowledge of what is going to be analyzed is required and it is quite easy to fall into wrong assumptions. In this case, the beauty of human behaviours.

By the way, concerning the connection between Tweets and TV shows, last year Twitter and BBC America have established a partnership for advertising (see Mashable, Twitter Partners With BBC America to Promote Branded Videos).

Maybe it’s just a coincidence… or maybe Twitter and BBC have the information that when people go to the toilette is just for posting a tweet and not beacause of a TV break 😉

Feelink – Feel & Think approach for doing life!

IT, I, WE: A Framework For Assessing the Consumer Behavior

How the consumer behaviours should be inferred? Or, is the brand proposition consistent with the targeted culture? These is the issues to address for defining a marketing strategy.

Along my MBA experience, I had the both the opportunity to study some insights regarding the behavior of a Chinese customer and living a cultural experience in China within an exchange program (Sun Yat-sen University). So, how is possible to create a framework that measure the consistency (correlation) between the culture and the relative inferences about the decision making process of the consumer? That was what stimulate my curiosity during my permanence in China so much that was also the question I have chosen as a final essay for the exchange [2]:

IT, I and WE

Briefly, in order to evaluate the consistency between the culture and the inferred consumer behaviours the idea is to use the IT, I and WE paradigm initially developed by Daniel Ofman [1] within the Core Qualities where are mainly three areas that represent three different ways to see the world and the reality:

  • IT: IT is the world of science, truth and objective reality as well as of tasks and goals to achieve.
  • I: I is the inner world and is about arts and also self-understanding, self-consciousness and self-awareness.
  • WE: the “sense of WE”. Solidarity, inclusion and sense of being part of a group\community are the main values for such a WE personality.

Since the IT, I and WE model by Daniel Ofman has been applied also for managing diversities and conflicts among people (See Blue, Green and Red model by Diversity Icebreaker) [3], why not applying it also for asessing cultures and consumer behaviors? Let’s see how.


The model IT, I and WE in the methodology proposed has been implemented as follow:

  1. First, identify the main topics that in general can assess a culture.
  2. For each topic, given 6 points available, distribute the points among the three areas IT, I and WE.
  3.  Sum all the points obtained respectively for the IT, I and WE areas.
  4. Collects all the findings that describe the decision making process of the customer.
  5. As it has been done for the culture at point 2, assign per each characteristic of the consumer behaviors 6 point distributed among the area IT, I and WE.
  6.  Sum the scores obtained respectively for the IT, I and WE areas regarding the consumer behaviour.


IT, I, WE: A Framework for Assessing the Consumer Behaviour (Infographic)

The result obtained from the analysis of the Chinese consumer behaviors has shown:

  • A consistent preference to the WE area: 45% and 38% from the Cultural and consumer behavior respectively. The result suits the high context mark of the Chinese culture where trust is based on relationships rather that tasks and facts.
  • Divergences between IT and I areas. In fact, with the selected items, the Chinese Culture has shown a preference to the IT area (35%) rather than to I (20%), while the Chinese behaviors has shown a balance between them, 25% and 37% respectively for the IT and the I.

For further details see the references.


  1.  Ofman Daniel. (2004). Core Qualities: a Gateway to Human Resources. Cyan Communications.
  2. Gruer Ivan. (2013). ” IT, I, WE: a framework for the consumer behaviour“. (Slideshare).